Analytics
Specification of analytics functions, their benefits, and application.
Overview¶
Analytics pursues only one goal: Guiding technicians and building users to improve the operational performance of buildings and energy systems, while the benefits of improved operational performance are multilateral:
- Higher comfort, means higher well-being and therefore performance of people in buildings.
- Higher energy efficiency providing comfort and energy services.
- Lower effort maintaining and servicing complex technical facilities.
This page offers specifications on the available analysis functions. Each specification starts with an introduction to the analysis, followed by tabs providing deeper insights and application notes. Browse the tabs for insights in the analysis specifications.
This tab summarizes the value offered by the analysis function, the component types the analysis is recommended for, and the conditions checked by the analysis.
In general, you can expect a short case-study on how the analysis function was applied during development or a test bench.
Results of analytics functions are structured to deliver simple-to-navigate insights and fast-to-apply measures on how to improve operational performance.
Therefore, each result regardless of the analytics function includes
- One qualitative warning level, aka. traffic light color,
- One interpretation,
- Zero to n recommendations,
- Zero to n KPIs, and
- Zero to n timeseries.
These categories are explained below. While the warning level, interpretation, and recommendation are specified for all analysis functions equally, KPIs and time series differ between each analysis function.
Warning level
The warning level represents the urgency of looking into the analyzed condition and taking action to improve it. It can have one of these traffic light states, but not every analysis makes use of the full spectrum:
Red: Suboptimal performance identified. It can be expected that either improving the identified condition will have a strong effect on the performance or the effort to realize the optimization is moderate compared to its benefit.
Yellow: Suboptimal performance identified. The effort to optimize might consume its benefit. To reduce the effort, implement the measure with the maintenance work that is required anyway. Observation of the analyzed condition is recommended.
Green: Performance is satisfactory. No action is recommended.
Interpretation
The interpretation delivers a summary of the observed performance and state of the condition analyzed. It describes either a symptom of a suboptimal operation or a condition that could be identified.
Recommendation
Recommendations are summarized in a list of zero (for sufficient operational performance) to n measurements on how to improve the operational performance. The recommendations either help by providing information on how to correct the source of the symptom itself or on how to narrow down to its root cause.
KPIs and time series
KPIs and time series offer insights and transparency. They enable reporting and manual investigation of the operational behavior of the component or system analyzed. KPIs and time series are highly individual for each function and are explained in the respective specification of each analysis function in Results.
The Components tab contains the API identifier and information of
- The components the analysis function is available for,
- The pins of the components which need to be mapped, and
- The attributes of the component required.
The Application tab provides information on the application of the analysis function.
- Recommended time span: Most of the analysis functions have a sweet spot for the amount of historical data required to derive accurate results.
- Recommended repetition: Components of building energy systems are subject to seasonal effects and wear out. Follow the recommended repetition to ensure the analysis is performed as often as necessary, without risking blind spots during the continuous monitoring of the system.
Analysis functions¶
See below for the individual analysis function specification.
Alarm State Analysis¶
The Alarm State Analysis assesses the occurrences and duration of alarm messages of a component. It is particularly useful for notifying the user when alarm messages have been overseen, as it summarizes the alarm messages over a given time period. Additionally, the Alarm State Analysis considers the most recent alarm message to determine whether the error has been resolved. While this analysis can be used for all alarm messages, it is most suited to critical alarm messages.
Value
- Avoids alarm messages being overlooked
- Identifies faulty components
- Can reduce component wear-and-tear
- Can increase energy efficiency
Recommended for components
Any component or subsystem which could have an alarm or error message such as:
- Fans
- Heat pumps
- Thermal control loops
Checked conditions
- Last state of alarm message
- Relative duration of alarm message
- Total duration of alarm messages
- Total occurrences of alarm message
The Alarm State Analysis was performed on a component for February 2020. The error message is active at the beginning of the time period and then about twice a week after that.

Figure 1: Component error message for the month of February 2020
The analysis returns a red warning message to indicate that the error message over the time period is suboptimal. This is because the error message is active for a significant percentage of the total time.
KPI | Value | Unit |
---|---|---|
alarm message.last observation | inactive | binary |
alarm message.relative | 25.4 | % |
alarm message.duration | 164 | h |
alarm message.count | 12 | count |
Signal colors
Signal color | Available | Info |
---|---|---|
red | Yes | The occurrences or alarm message duration is very high. |
yellow | Yes | The occurrences or alarm message duration are acceptable. |
green | Yes | The occurrences and alarm message duration are insignificant. |
Interpretations
Available | Info |
---|---|
Yes | Interpretations summarize the result of the analysis |
Recommendations
Available | Info |
---|---|
Yes | Check the component for physical damage and consider changing the component setting. |
KPIs
Summary of alarm messages
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
alarm message.last observation | Last available alarm message. | Active, Inactive | binary |
alarm message.relative | Time of active alarm message as a percentage of total time. | 0 to 100 | % |
alarm message.duration | Total time of active alarm message. | 0 to inf | h |
alarm message.count | Occurrences of the alarm message. | 0 to inf | count |
Pin | Required | Mapping info |
---|---|---|
Alarm message | Yes | - |
Pin | Required | Mapping info |
---|---|---|
Alarm message | Yes | - |
Pin | Required | Mapping info |
---|---|---|
Alarm message | Yes | - |
Pin | Required | Mapping info |
---|---|---|
Alarm message | Yes | - |
Pin | Required | Mapping info |
---|---|---|
Alarm message | Yes | - |
Recommended Time Span
1 month
Recommended Repetition
Every month
- After changes of operational modes, e.g., transfers to heating mode
- After changes in the control system
- After maintenance of replacements
Control Loop Oscillation Analysis¶
The Control Loop Oscillation Analysis checks the process value of a control loop for oscillation. Oscillating process values are an indicator for suboptimal parameterization or structural dimensioning of the control loop.
Value
- Increase lifetime of valve, dampers, and adjacent components
- Avoid spontaneous failures
- Reduce energy consumption
- Reduce noise pollution
Recommended for components
Any liquid media supply system, such as:
- Thermal control loop with 2-way valve and pump
Checked conditions
- Process value of the control loop is oscillating
- Process value of the control loop is not or to a negligible degree oscillating
- Condition checks on times of components operation
For this example, we analyzed the temperature control loop of a supply air volume flow, which provides fresh air and heating to a large salesroom. Figure 1 shows a plot of the process value of the control loop, the outlet temperature. The plot shows an oscillation of the outlet temperature during periods of operation.

Figure 1: Oscillating processes value during operation
Figure 2 is a zoom of figure 1 to analyze the oscillation in more detail. The trajectory of the process value is common for control loops oscillating at medium frequency.

Figure 2: Oscillating process value during operation in detail
The Control Loop Analysis evaluated this oscillation as significant and assigned it the signal color yellow. Recommendations are made on how to adjust controller parameters for a smoother operation.
Signal colors
Signal color | Available | Info |
---|---|---|
red | No | Red as a signal for a low cost measure with high impact on the building operation will not be provided. |
yellow | Yes | An oscillating control loop is a symptom for suboptimal control parameters or component design. Investing the extra effort to identify the root cause and fixing it is strongly recommended. |
green | Yes | No or only slight, in respect to usual tolerances in buildings, negligible oscillation. |
Interpretations
Available | Info |
---|---|
Yes | Interpretations summarize the result of the analysis |
Recommendations
Available | Info |
---|---|
Yes | Recommendations on how to smooth the control loop oscillation. No recommendation, if oscillation is negligible |
Pin | Required | Mapping info |
---|---|---|
Operating message | No | strongly recommended Default: Always on |
Outlet temperature | Yes | The outlet temperature is the process value of a thermal control loop. |
Recommend Time Span
1 day to 1 week
Recommended Repetition
Weekly
- After changes of operational modes, e.g., transfers to heating mode
- After changes in the control system
- After maintenance or replacements
Dew Point Alert Analysis¶
Building automation systems often have dew point alert messages which identify the possibility of unwanted condensation taking place in rooms. If the dew point alert message is active for any amount of time during the period of analysis, a recommendation is made to the user since rooms condensation in rooms can be damaging. Furthermore, if the temperature and relative humidity of the room are known, the DewPointAlertAnalysis calculates the risk of condensation and takes these into account in the evaluation. The DewPointAlertAnalysis is recommended for any room with an existing dew point alert signal or with temperature and relative humidity sensors.
Value
- Avoids damage to rooms due to condensation
Recommended for components
- Rooms
Checked conditions
- Duration of dew point alert signal
- Duration in which the room temperature is between 2 °C and 4 °C above the dew point temperature
- Duration in which the room temperature is within 2 °C of the dew point temperature
The Dew Point Alert Analysis was performed on a room for a week in February 2020. For this particular room, a dew point alert message is available but no temperature and relative humidity data. As is shown in figure 1, the dew point alert signal is only active for a very short amount of time during the week.

Figure 1: Dew point alert for one week in February 2020
The analysis returns a red warning message to indicate that the dew point alert was active during a portion of the time period. This suggests that the condensation may have formed in the room. Note that only "dew point alert" KPIs are generated since no temperature and humidity data are available in this example.
KPI | Value | Unit |
---|---|---|
dew point alert message.relative | 1.69 | % |
dew point alert message.duration | 2.83 | h |
Signal colors
Signal color | Available | Info |
---|---|---|
red | Yes | Dew point alert message is active for some time or the temperature and humidity show a high chance of condensation. |
yellow | Yes | There is a moderate chance of condensation taking place in the room. |
green | Yes | Dew point alert message is not active during analysis period. No risk of condensation. |
Interpretations
Available | Info |
---|---|
Yes | Interpretations summarize the result of the analysis |
Recommendations
Available | Info |
---|---|
Yes | Check the room for condensation and mold. |
KPIs
The KPIs which are generated by this analysis depend on the information available in the analysis. The "dew point alert message" KPIs are generated if a dew point alert message is available. The condensation risk KPIs are generated using room temperature and relative humidity.
The condensation risk is evaluated as moderate if the room temperature is between 2 K and 4 K above the dew point temperature. A high condensation risk is when the room temperature is within 2 K of the dew point temperature.
Dew point alert
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
dew point alert message.relative | Time of active dew point alert message as a percentage of total time. | 0 to 100 | % |
dew point alert message.duration | Total time of active dew point alert message. | 0 to inf | h |
condensation risk moderate.relative | Time of moderate condensation risk as a percentage of total time. | 0 to 100 | % |
condensation risk moderate.duration | Total time of moderate condensation risk. | 0 to inf | h |
condensation risk high.relative | Time of high condensation risk as a percentage of total time. | 0 to 100 | % |
condensation risk high.duration | Total time of high condensation risk. | 0 to inf | h |
Pin | Required | Mapping info |
---|---|---|
Dew point alert message | No | The dew point alert message can be used as the only pin or in combination with temperature and humidity. |
Temperature | No | If the temperature is mapped, humidity must also be mapped. Can be used in combination with the dew point alert message. |
Humidity | No | If humidity is mapped, the temperature must also be mapped. Can be used in combination with the dew point alert message. |
Recommend Time Span
1 week to 1 month
Recommended Repetition
Every month
- After changes of operational modes, e.g., transfers to heating mode
- After changes in the control system
- After maintenance and replacement
Energy Conversion Analysis¶
The Energy Conversion Analysis evaluates the quality of the energy conversion of a component, based on efficiency indicators. It is useful to detect inefficient operational states. Furthermore, information is provided regarding which part of the plant is responsible for the malfunction and what could be done to resolve the problem.
Value
- Reduced operational costs
- Detection of broken components
Recommended for components
- Combined heat and power
Checked conditions
- Efficiency of component
- Power to heat ratio (for component combined heat and power)
The Energy Conversion Analysis was applied to a real combined heat and power plant and the pins operating message, generator power, heat flow, and fuel power were mapped. Figure 1 shows the time series recorded for an exemplary period of 7 days. The grey shaded periods correspond to the operation of the plant.

Figure 1: Period of one week for which the energy conversion is not acceptable
A very low generator power compared to the heat flow and the fuel power indicates a failure of the generator component. The automated interpretation confirms our visual analysis of the time series shown in the figure, summed up by the qualitative warning level “red”. It also provides recommendations to address the problem.
KPI | Value | Unit |
---|---|---|
generator power.mean | 9.4 | kW |
heat flow.mean | 640.9 | kW |
fuel power.mean | 1940.3 | kW |
power to heat ratio | 1.47 | % |
fuel utilization factor | 33.5 | % |
thermal efficiency | 33.0 | % |
electric efficiency | 0.485 | % |
Signal colors
Signal color | Available | Info |
---|---|---|
red | Yes | The quality of the energy conversion is not acceptable. |
yellow | Yes | The quality of the energy conversion is suboptimal. |
green | Yes | The quality of the energy conversion is good. |
Interpretations
Available | Info |
---|---|
Yes | Interpretations summarize the result of the analysis |
Recommendations
Available | Info |
---|---|
Yes | Recommendations to improve energy conversion. No recommendation, in case of good energy conversion. |
KPIs
Energy Performance KPIs
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
generator power.mean | Average generator power | 0 to inf | kW |
fuel power.mean | Average fuel power | 0 to inf | kW |
power to heat ratio | Cumulated electrical energy divided by the cumulated heat energy | 0 to inf | % |
fuel utilization factor | Total efficiency of the plant (i.e., total heat and power divided by total energy provided by the fuel energy). | 0 to 100 | % |
thermal efficiency | Cumulated heat energy divided by the total fuel energy. | 0 to 100 | % |
electrical efficiency | Cumulated electrical energy divided by the total fuel energy. | 0 to 100 | % |
Pin | Required | Mapping info |
---|---|---|
Operating message | No | - |
Generator power | Yes | - |
Heat flow | Yes | - |
Rate of fuel consumption | No | - |
Attribute | Required | Mapping info |
---|---|---|
Fuel price | No | Default: 0.06 €/kWh Gas |
Electricity price | No | Default: 0.18€/kWh |
Heat price | No | Default: 0.065 €/kWh |
Generator nominal power | No | - |
Nominal heat production | No | - |
Recommended Time Span
1 day to 1 week
Recommended Repetition
Every month
Fan Speed Analysis¶
The Fan Speed Analysis evaluates whether a fan is controlled, based on its fan speed. This helps to identify problems with fan control and ensures that fans are implemented more energy efficiently.
Value
- Detect AHU fans that are not controlled
- Reduce costs through better fan speed control
Recommended for components
- Fan
Checked conditions
- Stationary fan speed
In this example, we look at a Fan Speed Analysis of the historic 7-day fan speed. While the Operating Message (grey in the plot below) shows the times when the fan was operated, the fan speed (blue in the plot below) corresponds to the speed or load setting of the fan.

Figure 1: Speed and operating message of a 7 day fan speed analysis
From the analysis results, we can see that the fan was operated for 6 hours out of the 168 hours of the week or 3.57 % of the week. Additionally, we get statistics of the fan speed, e.g., the fan was operated at an average of 40 % load.
This corresponds to a static fan speed setting that is currently not controlled. To improve energy efficiency and thermal comfort you can consider different control strategies outlined in the recommendations.
KPI - Statistics
KPI | Value | Unit |
---|---|---|
operating time | 6 | h |
operating time.relative | 3.57 | % |
speed.maximum | 40 | % |
speed.minimum | 40 | % |
speed.mean | 40 | % |
speed.median | 40 | % |
Signal colors
Signal color | Available | Info |
---|---|---|
red | No | - |
yellow | Yes | Fan speed is not controlled |
green | Yes | Fan speed is controlled |
Interpretations
Available | Info |
---|---|
Yes | Information about the fan speed |
Recommendations
Available | Info |
---|---|
Yes | Recommendations to look into the different control options for this fan to save energy. |
KPIs
Statistics
statistics for "speed" will be calculated for all measured values that are not 0 %
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
operating time | Total time of operation | 0 to inf | h |
operating time.relative | Time of operation in relation to analysis period | 0 to 100 | % |
speed.maximum | Largest observation recorded for fan speed during analysis period | 0 to 100 | % |
speed.minimum | Smallest observation recorded for fan speed during analysis period | 0 to 100 | % |
speed.mean | Time-weighted average of fan speed | 0 to 100 | % |
speed.median | Time-weighted median of fan speed | 0 to 100 | % |
Pin | Required | Mapping info |
---|---|---|
Operating message | No | - |
Speed | Yes | Use this pin to connect the datapoint that reflects fan speed settings from 0 - 100 % load |
Recommended Time Span
1 week
Recommended Repetition
Every month
Filter Servicing Analysis¶
The Filter Servicing Analysis predicts when a filter is due to be serviced or replaced, based on filter contamination or the pressure difference over the filter. This ensures that filters always function optimally and are maintained or replaced as required.
Value
- Ensures filter is serviced when required
- Improves energy efficiency
Recommended for components
- Filter
Checked conditions
- Filter contamination
- Expected time till filter service or replacement
In this example, the filter contamination of an exhaust air filter of an air handling unit was analyzed over a period of four months. As can be seen in figure 1, filter contamination gradually increases over the analyzed period.

Figure 1: Filter contamination over a four month period
The signal analysis returns a green signal color since there is a significant amount of time before the filter is fully contaminated.
KPI | Value | Unit |
---|---|---|
days until filter service | 35 | d |
expected date of filter service | 2020-05-20 | date |
filter contamination | 79.3 | % |
Signal colors
Signal color | Available | Info |
---|---|---|
red | Yes | The filter is fully contaminated and should be serviced soon. |
yellow | Yes | The filter is almost contaminated, a filter service should scheduled. |
green | Yes | The filter is in a good condition and does not need to be serviced. |
Interpretations
Available | Info |
---|---|
Yes | Information regarding the filter condition and whether the filter needs to be serviced. |
Recommendations
Available | Info |
---|---|
Yes | Make necessary arrangements for the filter to be serviced. No recommendation if the filter does not need servicing within two weeks and the filter contamination is below 95%. |
KPIs
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
days until filter service | Number of days until filter expected filter service. | 0 to inf | d |
expected date of filter service | Date on which filter is expected to require a service (format: YYYY-MM-DD) | - | date |
filter contamination | Relative extent to which filter is contaminated. | 0 to 100 | % |
Pin | Required | Mapping info |
---|---|---|
Filter contamination | No | Either filter contamination (preferred) or pressure difference must be mapped. If both pins are mapped, filter contamination is used. |
Pressure difference | No | Either filter contamination (preferred) or pressure difference must be mapped. If both pins are mapped, filter contamination is used. |
Attribute | Required | Mapping info |
---|---|---|
Filter class | No | Default: F9 |
Initial pressure difference | No | Default: initial pressure difference of filter class (50 Pa for filter class F9). |
Final pressure difference | No | Default: final pressure difference of filter class (300 Pa for filter class F9). Setting this attribute is highly recommended. |
Recommended Time Span
1 month to 6 months
Recommended Repetition
Twice a month
Humidity Conditioning Analysis¶
The Humidity Conditioning Analysis compares the outside air humidity with the actual supply air humidity of the Air Handling Unit (AHU).
This analysis does not take into account air recirculation and humidity recovery modes. Make sure that the system is operated without such operational modes.
Value
- Detect operating conditions of AHUs that are not appropriate to the outside air conditions
- Avoids unnecessary changes in humidity, which cost a lot of energy
- Verifies sufficient supply air humidity
Recommended for components
- Air handling units with humidity conditioning
Checked conditions
- Compare actual operating hours with humidification, dehumidification, and no operation with the corresponding expected hours
This example shows a week of analysis for a summer scenario in July. The AHU is operating throughout the week. Relative humidity conditions are displayed in red and orange, green and blue are temperature conditions and brown and purple are the water load conditions.

Figure 1: Analysis of humidity, temperature and water load conditions over a whole week
The analysis uses two positions, intake (outside conditions) and outlet (supply conditions) to calculate water loads. A difference in these water loads corresponds to the pink line at the bottom. The operating hours will now be divided into three categories. Hours of humidification, hours of dehumidification, and hours of neither humidification nor dehumidification. These values are then compared to the expected hours in these categories derived from outside conditions. The total hours of correct operation (according to the expectation) are then evaluated for a recommendation.
KPI | Value | Unit |
---|---|---|
operating time | 168 | h |
operating time.relative | 100 | % |
humidification detected | 135 | h |
dehumidification detected | 18 | h |
humidification necessary | 0 | h |
dehumidification necessary | 49 | h |
humidification missing | 0 | h |
dehumidification missing | 49 | h |
humidification unnecessary | 135 | h |
dehumidification unnecessary | 18 | h |
total hours savings possible.relative | 91.1 | % |
total hours increase air quality.relative | 92.3 | % |
Signal colors
Signal color | Available | Info |
---|---|---|
red | No | - |
yellow | Yes | - |
green | Yes | The AHU operates in accordance to the expected operating conditions. |
Interpretations
Available | Info |
---|---|
Yes | Either the expected operating conditions are met by the operation of the AHU or the operating conditions do not fit. |
Recommendations
Available | Info |
---|---|
Yes | Recommendations regarding which operating mode (humidification, dehumidification) should be looked into to change the operating modes of the AHU. |
KPIs
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
operating time | Total time of operation | 0 to inf | h |
operating time.relative | Total time component was operated compared to analysis period | 0 to 100 | % |
Operating Conditions
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
humidification detected | The amount of time the component operates in humidification mode according to inflow/outflow analysis | 0 to inf | h |
dehumidification detected | The amount of time the component operates in dehumidification mode according to inflow/outflow analysis | 0 to inf | h |
humidification necessary | The amount of time the component should operate in humidification mode according to outside air conditions | 0 to inf | h |
dehumidification necessary | The amount of time the component should operate in dehumidification mode according to outside air conditions | 0 to inf | h |
humidification missing | The amount of time the component did not operate in humidification mode but should | 0 to inf | h |
dehumidification missing | The amount of time the component did not operate in dehumidification mode but should | 0 to inf | h |
humidification unnecessary | The amount of time the component operated in humidification mode but should not | 0 to inf | h |
dehumidification unnecessary | The amount of time the component operated in dehumidification mode but should not | 0 to inf | h |
total hours savings possible.relative | Percentage of time (de)humidification can be switched off according to outside air conditions relative to operating time | 0 to 100 | % |
total hours increase air quality.relative | Percentage of time (de)humidification should be switched on according to outside air conditions relative to operating time | 0 to 100 | % |
Pin | Required | Mapping info |
---|---|---|
Supply air temperature | Yes | conditioned air at supply-side exit of AHU |
Supply air relative humidity | Yes | conditioned air at supply-side exit of AHU |
Outside air temperature | Yes | intake air conditions |
Outside air relative humidity | Yes | intake air conditions |
Operating message | No | Mapping of operating message is strongly recommended. Default: Always operating |
Recommended Time Span
1 week
Recommended Repetition
Every month
- After changes of operational modes
- After changes in the control system
Operating Cycle Analysis¶
The Operating Cycle Analysis identifies excessive start and stop processes which lead to energy losses, energy consumption peaks due to higher energy consumption on plant start, and higher wear-and-tear of the component compared to a constant operation. Further, a frequently alternating operation of a component, e.g., a heat pump, has negative effects on adjacent components, which are enforced to alternate as well. Further, the algorithm takes low cycle rates as an indication of a possible under-supply of the adjacent systems.
Value
- Lower operating costs
- Higher energy efficiency
- Peak energy consumption reduction
- Longer equipment and component lifetimes
- Smoother system integration
Recommended for components
Energy conversion plants and components with high start-up energy consumption or wear, such as
- Heat pump
- Combined heat and power
- Boiler
- Fan
Checked conditions
- Short cycling of component operation, evaluated component-specific
- Long cycling of component operation, evaluated component-specific
- Expected cycling of component operation, evaluated component-specific
- Condition checks on times of components operation
The Operating Cycle Analysis was applied to a heat pump. Thus, a heat pump component model was instanced and the respective datapoint mapped to the pin operating message. Figure 1 shows the time series recorded for an exemplary period of 1 week in winter.

Figure 1: Operating message and cycle behavior of heat pump
Short shut-down times are observed between periods of duty indicating excessive start and stop processes of the heat pump. This not only leads to energy losses and electricity consumption peaks, but also increased wear-and-tear of the heat pump's compressor.
The attributes "Coefficient of performance", "Nominal heat production" and "Electricity price" are set to 4, 1000kW, and 0.18€/kWh. This enables Economic KPIs with the accuracy level "High". The calculations show daily start-up costs of 66 €/d and costs of one start to be 2.75 € (start-up cost).
The automated interpretation confirms our visual analysis of the time series shown in the figure, summed up by the qualitative warning level "yellow". The recommendations provide further instruction on how to isolate and fix the cause for the increased number of start and stop processes. Furthermore, the result offers an advanced set of KPIs, providing additional insights into the cycle behavior of the heat pump.
KPI | Value | Unit |
---|---|---|
operating time | 84 | h |
operating time.relative | 50 | h |
starts | 168 | count |
closd operaing cyces | 167 | count |
cycle times.median | 1 | h |
cycle times.mean | 1 | h |
cycle times.maximum | 1 | h |
cycle times.minimum | 1 | h |
duty times.median | 0.5 | h |
duty times.mean | 0.5 | h |
duty times.maximum | 0.5 | h |
duty times.minimum | 0.5 | h |
switch-off times.median | 0.5 | h |
switch-off times.mean | 0.5 | h |
switch-off times.maximum | 0.5 | h |
switch-off times.minimum | 0.5 | h |
start-up costs.daily | 66 | €/d |
start-up costs.weekly | 462 | €/week |
start-up costs | 2.75 | € |
Signal colors
Signal color | Available | Info |
---|---|---|
red | No | The analysis identifies the symptom and recommends measures to investigate the root cause of short cycling respectively long cycling. Red as a signal for a low-cost measure with a high impact on the building operation will not be provided. |
yellow | Yes | Unwanted cycling rates are a strong symptom for suboptimal control and system performance. Investing the extra effort to identify the root cause and fixing it is strongly recommended. |
green | Yes | Sufficient cycle rates in respect to usual operation in buildings |
Interpretations
Available | Info |
---|---|
Yes | Interpretations summarize the result of the analysis |
Recommendations
Available | Info |
---|---|
Yes | Recommendations on how to investigate the root cause of an unwanted cycle rate. No recommendation, if cycle rate is sufficient |
KPIs
Operating Time and Operating Cycles
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
operating time | Total time of operation | 0 to inf | h |
operating time.relative | Total time of operation divided by total time span | 0 to 100 | % |
starts | Count of starts | 0 to inf | count |
closed operating cycles | Count of closed operating cycles. Cycles are counted form start(\(n_i\)) to start(\(n_{i+1}\)) and both starts are within the analysed period | 0 to inf | count |
cycle times.median | Median of cycle periods. Not returned in case no closed cycle was observed | 0 to inf | h |
cycle times.mean | Time-weighted average of cycle periods. Not returned in case no closed cycle was observed | 0 to inf | h |
cycle times.maximum | Longest cycle period. Not returned in case no closed cycle was observed | 0 to inf | h |
cycle times.minimum | Shortest cycle period. Not returned in case no closed cycle was observed | 0 to inf | h |
duty times.median | Median of duty periods. Not returned in case no closed cycle was observed | 0 to inf | h |
duty times.mean | Time-weighted average of duty periods. Not returned in case no closed cycle was observed | 0 to inf | h |
duty times.maximum | Longest duty period. Not returned in case no closed cycle was observed | 0 to inf | h |
duty times.minimum | Shortest duty period. Not returned in case no closed cycle was observed | 0 to inf | h |
switch-off times.median | Median of switch-off periods. Not returned in case no closed cycle was observed | 0 to inf | h |
switch-off times.mean | Time-weighted average of switch-off periods. Not returned in case no closed cycle was observed | 0 to inf | h |
switch-off times.maximum | Longest switch-off period. Not returned in case no closed cycle was observed | 0 to inf | h |
switch-off times.minimum | Shortest switch-off period. Not returned in case no closed cycle was observed | 0 to inf | h |
Economic KPIs
Economic KPIs estimate the economic optimization potentials of the observed operational state. The KPIs indicate the total startup costs based on KPI "starts" and the costs of one cycle of the investigated component.
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
start-up costs.daily | Identified daily costs of start-ups. It is provided as the average daily value. | 0 to inf | €/day |
start-up costs.weekly | Identified weekly costs of start-ups. It is provided as the average weekly value. This KPI is only provided, if the analyzed time span is at least one week long. | 0 to inf | €/week |
start-up costs | Estimation of the cost of one start-up including the shutdown of the device. | 0 to inf | € |
The Economic KPIs are provided for the components:
- Boiler
- Combined heat and power
- Heat Pump
Their availability and accuracy depend on the component's mapping. The analysis function always determines the highest possible accuracy.
Accuracy Levels:
The following tables summarize the pins and attributes required to achieve various accuracy levels for the economic KPIs.
High
Components | Pins | Attributes |
---|---|---|
Combined heat and power | - | Start-up costs Generator nominal power |
Boiler | - | Start-up costs Nominal heat production |
Heat pump | - | Coefficient of performance Electricity price Nominal heat production |
Medium
Components | Pins | Attributes |
---|---|---|
Boiler | - | Nominal heat production |
Heat pump | - | Nominal heat production |
Combined heat and power | - | Generator nominal power |
If the available attributes and mapped pins are not sufficient enough to reach a "Medium" accuracy for the economic KPIs, no economic KPIs are calculated.
Pin | Required | Mapping info |
---|---|---|
Operating message | Yes | - |
Attribute | Required | Mapping info | Unit |
---|---|---|---|
Nominal heat production | No | Necessary for Economic KPIs, all accuracy levels. Used to scale "Start-up costs". Default: None | kW |
Startup costs | No | Necessary for Economic KPIs, accuracy level "High". Scaled with "Nominal heat production": Default: 0.01 €/kW | €/kW |
Pin | Required | Mapping info |
---|---|---|
Operating message | Yes | - |
Attribute | Required | Mapping info | Unit |
---|---|---|---|
Generator nominal power | No | Necessary for Economic KPIs, all accuracy levels. Used to scale "Start-up costs". Default: None | kW |
Startup costs | No | Necessary for economic KPIs, accuracy level "High". Scaled with "Generator nominal power": Default: 0.02 €/kW | €/kW |
Pin | Required | Mapping info |
---|---|---|
Operating message | Yes | - |
Pin | Required | Mapping info |
---|---|---|
Operating message | Yes | - |
Attribute | Required | Mapping info | Unit |
---|---|---|---|
Coefficient of performance | No | Necessary for Economic KPIs, accuracy level "High". Default: 4 | |
Nominal heat production | No | Necessary for Economic KPIs, all accuracy levels. Used to scale "Start-up costs". Default: None | kW |
Startup costs | No | Necessary for Economic KPIs, accuracy level "High". Scaled with "Generator nominal power": Default: 0.18 €/kW | €/kW |
Pin | Required | Mapping info |
---|---|---|
Operating message | No | Mapping of either operating message (preferred) or pump operating message is mandatory. If both pins are mapped, operating message is used |
Pump operating message | No | Mapping of either operating message (preferred) or pump operating message is mandatory. If both pins are mapped, operating message is used |
Recommend Time Span
1 day to 1 week
Recommended Repetition
Every month
- Cycle rates have a strong seasonal effect
- Frequent repetition allows to identify operational bad points
- After changes of operational modes, e.g., transfers to heating mode
- After changes in the control system
- After maintenance or replacements
Reduced Load Analysis¶
The Reduced Load Analysis identifies the presence of a reduced load mode based on temperature setpoints of the system under consideration. The temperature spread of the system is determined. A reduced load mode offers the possibility of operational cost and energy reductions. Additionally, a comparison with a user-defined schedule reveals times when the component could be in a reduced load operating mode.
Value
- Lower operating costs
- Lower energy consumption
Recommended for components
Heat and cold distribution systems, energy conversion plants, and indoor areas, such as
- Heating loops
- Cooling loops
- Boilers
- Office rooms
- Schooling rooms
Checked conditions
- Existence of a load reduction period, e.g., night-time temperature reduction for heating
- Condition checks on times of components operation
- Estimation of times when the load can be reduced according to a user-defined schedules
This example shows the results of a Reduced Load Analysis performed on a heating circuit.

Figure 1: Temperature setpoint of the heating circuit
Schedule
Day | Time |
---|---|
Mon | 05:00 - 18:00 |
Tue | 05:00 - 18:00 |
Wed | 05:00 - 18:00 |
Thu | 05:00 - 18:00 |
Fri | 05:00 - 18:00 |
Sat | 07:00 - 14:00 |
Sun | 07:00 - 14:00 |
KPI | Value | Unit |
---|---|---|
reduced load operation | Yes | binary |
temperature level shift | 10 | °C |
operating time | 62.4 | h |
operating time.normal load.reducible | 1.77 | h |
operating time.normal load.reducible.relative | 2.84 | % |
operating time.normal load.scheduled | 60.6 | h |
Signal colors
Signal color | Available | Info |
---|---|---|
red | Yes | No load reduction identified (applied for thermal control loop) |
yellow | Yes | No load reduction identified (applied for any other component than thermal control loop) |
green | Yes | Load reduction identified |
Interpretations
Available | Info |
---|---|
Yes | Either the operational rule checks if the analysis were tested positive or not |
Recommendations
Available | Info |
---|---|
Yes | Implementation hints for load reduction. No recommendation, in case of sufficient measurement quality. |
KPIs
Identification of reduced load mode
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
reduced load operation | Whether a reduced load mode was detected No = no reduced load identified Yes = reduced load identified | Yes, No | binary |
Statistics of temperature level shift
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
temperature level shift | Difference between setpoint temperature levels at the time of load reduction negative values = reduced temperature level for heating load reduction positive values = raised temperature level for cooling load reduction | -inf to inf | °C |
Schedule operating times
KPIs of this category analyse if the load reduction is in accordance to a schedule and if there are further savings by adjusting/implementing a load reduction schedule.
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
operating time | Total time of operation | 0 to inf | h |
operating time.normal load.reducible | Total time component was operated under normal load outside the reviewed schedule and therefore could be saved | 0 to inf | h |
operating time.normal load.reducible.relative | Percentage of reducible operating time under normal load relative to the total operating time | 0 to 100 | % |
operating time.normal load.scheduled | Total time of operation under normal load that is scheduled | 0 to inf | h |
Time series
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
normal load.timeseries | Timeseries of reduced operating mode 0 = reduced load operation 1 = normal operation | 0 or 1 | binary |
Pin | Required | Mapping info |
---|---|---|
Outlet temperature setpoint | Yes | - |
Attribute | Required | Mapping info |
---|---|---|
Custom day schedules | No | - |
Custom holiday | No | - |
Pre-conditioning period | No | - |
Regional key | No | - |
Schedule | No | times for operation at normal load |
Schedule timezone | No | strongly recommended Default: UTC |
Shutdown flexibility | No | - |
Pin | Required | Mapping info |
---|---|---|
Temperature setpoint | Yes | - |
Attribute | Required | Mapping info |
---|---|---|
Custom day schedules | No | - |
Custom holiday | No | - |
Pre-conditioning period | No | - |
Regional key | No | - |
Schedule | No | times for operation at normal load |
Schedule timezone | No | strongly recommended Default: UTC |
Shutdown flexibility | No | - |
Pin | Required | Mapping info |
---|---|---|
Outlet temperature setpoint | Yes | - |
Attribute | Required | Mapping info |
---|---|---|
Custom day schedules | No | - |
Custom holiday | No | - |
Pre-conditioning period | No | - |
Regional key | No | - |
Schedule | No | times for operation at normal load |
Schedule Timezone | No | strongly recommended Default: UTC |
Shutdown Flexibility | No | - |
Recommend Time Span
1 day to 1 week
Recommended Repetition
Every 3 months
- After changes of operational modes, e.g., transfers to heating mode
- After changes in the control system
- After maintenance or replacements
Room Air Quality Analysis¶
The Room Air Quality Analysis checks and interprets the compliance of carbon dioxide concentration in the air to the recommendations of DIN EN 13779: 2007-09. In the case of poor air quality, measures for improvement are recommended. Human performance is significantly influenced by air quality. Furthermore, the algorithm identifies calibration errors by physical plausibility checks.
Value
- Higher occupant comfort, health and performance
Recommended for components
- Room
Checked conditions
- Indoor CO2 concentration evaluation based on DIN EN 13779: 2007-09
- Identification of higher room ventilation needs
- Sensor calibration check by plausibility of minimal measured concentration levels
- Condition checks on times of components operation
The room air quality analysis was applied to an office room with a CO2 sensor and a schedule from 8:00 to 18:00.

Figure 1: CO2 concentration and presence
In this scenario, figure 1 shows the time series recorded for a week in July. Air quality is good for at least 60 percent of the office hours. Especially right before lunchtime and in the afternoon, there is room for improvement. If this office is used with 100 people and an average salary of 41 €/hour, better air quality could increase productivity such that we could save approximately 1140 € per week.
KPI | Value | Unit |
---|---|---|
co2.maximum | 1232 | ppm |
co2.minimum | 399 | ppm |
co2.mean | 672.9 | ppm |
co2.median | 643 | h |
co2 duration.IDA1.relative | 60.7 | % |
co2 duration.IDA1 | 42.5 | h |
co2 duration.IDA2.relative | 28.8 | % |
co2 duration.IDA2 | 20.2 | h |
co2 duration.IDA3.relative | 10.4 | % |
co2 duration.IDA3 | 7.31 | h |
co2 duration.IDA4.relative | 0 | % |
co2 duration.IDA4 | 0 | h |
room air quality salary savings.daily | 162.9 | €/d |
room air quality salary savings.weekly | 1140.3 | €/d |
room air quality productivity gains.relative | 0.397 | €/d |
Signal colors
Signal color | Available | Info |
---|---|---|
red | Yes | CO2 concentrations critical for human health |
yellow | Yes | CO2 concentrations can reduce human comfort, decisiveness, and performance or wrongly calibrated CO2 sensors |
green | Yes | CO2 concentrations sufficient for high comfort |
Interpretations
Available | Info |
---|---|
Yes | Interpretations summarize the result of the analysis |
Recommendations
Available | Info |
---|---|
Yes | Recommendations to improve fresh air supply, if necessary or to re-calibrate the sensor, if physically implausible measures are observed. No recommendation, in case of sufficient air quality |
KPIs
Air Quality Classification
How long was the air quality in the room (based on carbon dioxide concentrations) considered “good”, “medium”, “moderate” or “poor”? Assessments are based on DIN EN 13779 classifications of Indoor Air Quality (IDA) classes 1 (“good”) to 4 (“poor”).
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
co2 duration.IDA1.relative | Duration with “good“ indoor air quality | 0 to 100 | % |
co2 duration.IDA2.relative | Duration with “medium “ indoor air quality | 0 to 100 | % |
co2 duration.IDA3.relative | Duration with “moderate “ indoor air quality | 0 to 100 | % |
co2 duration.IDA4.relative | Duration with “poor “ indoor air quality | 0 to 100 | % |
co2 duration.IDA1 | Duration with “good“ indoor air quality | 0 to inf | h |
co2 duration.IDA2 | Duration with “medium “ indoor air quality | 0 to inf | h |
co2 duration.IDA3 | Duration with “moderate “ indoor air quality | 0 to inf | h |
co2 duration.IDA4 | Duration with “poor “ indoor air quality | 0 to inf | h |
Statistics of CO2 Concentration
Providing deeper insights into the carbon dioxide concentrations over the analyzed period.
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
co2.maximum | Largest CO2 concentrations | 0 to inf | ppm |
co2.minimum | Smallest CO2 concentrations | 0 to inf | ppm |
co2.mean | Average CO2 concentrations | 0 to inf | ppm |
co2.median | Median CO2 concentrations | 0 to inf | ppm |
Economic KPIs
Economic KPIs estimate the economic optimization potentials of the observed operational state. The KPIs indicate the possible productivity gains and the resulting salary savings for adjusting the CO2 content of the room air below 1000 ppm.
The Economic KPIs are provided for the components:
- Room
Their availability and accuracy depend on the component's mapping. The analysis function always determines the highest possible accuracy.
Accuracy Levels:
High
Components | Pins | Attributes |
---|---|---|
Room | Presence or Operting message CO2 | Complementary: Room type (used in combination with Presence or Operating message to estimate room usage). |
Medium
Components | Pins | Attributes |
---|---|---|
Room | CO2 | Schedule Complementary: Custom day schedule Schedule timezone Custom holiday Regional key Room type (used in combination with schedule attributes to estimate room usage). |
Low
Components | Pins | Attributes |
---|---|---|
Room | CO2 Assumption of 24/7 usage | Complementary: Room type (used to estimate room usage). |
All Accuracy Levels
Components | Pins | Attributes |
---|---|---|
Room | - | Average salary Maximum occupation of the room |
Salary savings KPIs
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
room air quality salary savings.daily | Identified salary savings potential from employee productivity losses due to CO2 content in the room air above 1000 ppm. The savings are provided as average daily savings potential. | 0 to inf | €/d |
room air quality salary savings.weekly | Identified salary savings potential from employee productivity losses due to CO2 content in the room air above 1000 ppm. The savings are provided as average weekly savings potential if the analyzed period is at least one week long. | 0 to inf | €/week |
Productivity gains KPI
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
room air quality productivity gains.relative | Identified percentual productivity gains for reducing the CO2 content in the room air to values below 1000 ppm. | 0 to 100 | % |
Pin | Required | Mapping info | Unit |
---|---|---|---|
CO2 | Yes | Necessary for Economic KPIs, all accuracy levels. | ppm |
Operating message | No | Used for Economic KPIs, accuracy level "High". It is used subordinate to pin "presence". Default: Always presence | binary |
Presence | No | Used for Economic KPIs, accuracy level "High". It is preferred over pin "operating message". Default: Always presence | binary |
Attribute | Required | Mapping info | Unit |
---|---|---|---|
Average salary | No | Necessary for Salary KPIs of Economic KPIs, all accuracy levels. | €/person |
Occupation max | No | Necessary for Salary KPIs of Economic KPIs, all accuracy levels. | - |
Room type | No | Available values: - 24/7 full occupancy - classroom - single person office multi persons office - store - restaurant - conference room - kindergarten Default: 24/7 full occupancy | - |
Schedule timezone | No | Default: UTC | - |
Custom day schedules | No | Default: {} | - |
Regional key | No | Default: None | - |
Schedule | No | Default: None | - |
Recommend Time Span
1 day to 1 week
- Utilize on days with room occupation
Recommended Repetition
Every month
- After changes of room occupation or usage
- After changes of operational modes, e.g., transfers to heating mode
- After changes in the control system of the ventilation systems
- After maintenance or replacements in ventilation systems
Schedule Analysis¶
The Schedule Analysis is used to compare the actual occurred switch on/switch off times of the component with a schedule/timetable stored inside analytics. This analysis aims at identifying the number of hours the component is active outside of the scheduled times. In addition to a one-time check, the analysis is suitable for permanent checks, e.g., to identify manual overwriting of the operating schedule. The analysis considers holidays and customized schedules.
Value
- Lower operating times of HVAC components
- Lower energy consumption
- Lower maintenance costs due to less component operating time
Recommended for components
Any HVAC component or room whose usage follows a recurrent schedule, such as:
- Fans
- Thermal control loops
- Office rooms
- Sales rooms
Checked conditions
- Component operation outside a user-defined schedule
- Component operation during a user-defined schedule
- Condition checks on times of components operation
This example shows a schedule analysis for a component "fan" connected to a supply fan operating message of an HVAC machine. The switch on/off times of the machine are shown as a blue line in figure 1, blue regions in the background correspond to the expected schedule.

Figure 1: Operating times of component and reference schedule
A reduction of ~9% of the total operating time is possible, as can be seen in the table of KPIs below. With the help of the plot we can also see, that the times where we can reduce the operating time are distributed over the workdays of the week. Furthermore, the mapping of the component enables the determination of economic KPIs with a "low" accuracy level. Assuming a nominal power consumption of 3 kW and the electricity price to be 0.18 €/kWh, the energy costs outside the scheduled operating times are calculated. This results in weekly energy costs of 3.75 € which fall outside of the schedule.
KPI | Value | Unit |
---|---|---|
operating time | 74 | h |
operating time.reducible | 6.94 | h |
operating time.reducible.relative | 9.38 | % |
operating time.scheduled | 67.1 | h |
savings.daily | 1.53 | €/d |
energy consumption costs.outside schedule.daily | 0.54 | €/day |
energy consumption costs.outside schedule.weekly | 3.75 | €/week |
Signal colors
Signal color | Available | Info |
---|---|---|
red | Yes | Significant operation times outside of the parameterized schedule identified |
yellow | Yes | Partial operation times outside of the parameterized schedule identified |
green | Yes | Sufficient operation according to the parameterized schedule |
Interpretations
Available | Info |
---|---|
Yes | Interpretations summarize the result of the analysis |
Recommendations
Available | Info |
---|---|
Yes | Recommendations to improve the scheduled operation of the component. No recommendation, in case of sufficient measurement quality |
KPIs
Operating Time and Schedule
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
operating time | Total time of operation | 0 to inf | h |
operating time.reducible | Total time component was operated outside the reviewed schedule and therefore could be saved | 0 to inf | h |
operating time.reducible.relative | Percentage of reducible time relative to the total operating time | 0 to 100 | % |
operating time.scheduled | Total time of operation during schedule | 0 to inf | h |
Economic KPIs
Economic KPIs estimate the economic optimization potentials of the observed operational state. The KPIs indicate the energy costs outside of scheduled operating or usage times of the investigated component.
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
energy consumption costs.outside schedule.daily | Identified energy consumption costs outside of scheduled operating time. The costs are provided as average daily costs. | 0 to inf | €/day |
energy consumption costs.outside schedule.weekly | Identified energy consumption costs outside of scheduled operating time. The costs are provided as average weekly costs. This KPI is provided if the analyzed time span is at least one week long. | 0 to inf | €/week |
The Economic KPIs are provided for the components:
- Boiler
- Combined heat and power
- Fan
- Heat pump
Their availability and accuracy depend on the component's mapping. The analysis function always determines the highest possible accuracy.
Accuracy Levels:
The following tables summarize the pins and attributes required to achieve various accuracy levels for the economic KPIs.
High
Components | Pins | Attributes |
---|---|---|
Boiler | Rate of fuel consumption | Fuel price |
Combined heat and power | Rate of fuel consumption | Fuel price |
Fan | Electrical power | Electricity price |
Heat pump | Electrical power | Electricity price |
Medium
Components | Pins | Attributes |
---|---|---|
Boiler | Heat flow | Efficiency Fuel price |
Combined heat and power | Generator power Heat flow | Fuel price Fuel utilization factor |
Fan | Speed | Electricity price Nominal power consumption |
Heat pump | Heat flow | Coefficient of performance Electricity price |
Low
Components | Pins | Attributes |
---|---|---|
Fan | - | Electricity price Nominal power consumption |
Heat pump | - | Coefficient of performance Electricity price Nominal heat production |
Boiler | - | Efficiency Fuel price Nominal heat production |
Combined heat and power | - | Fuel price Fuel utilization factor Generator nominal power Nominal heat production |
If the available attributes and mapped pins are not sufficient enough to reach a "Low" accuracy for the economic KPIs, see "operating time.reducible.relative for a rough estimation.
Pin | Required | Mapping info | Unit |
---|---|---|---|
Rate of fuel consumption | No | Necessary for economic KPIs, accuracy level "High". | kW |
Heat flow | No | Necessary for economic KPIs, accuracy level "Medium". | kW |
Operating message | Yes | - | - |
Attribute | Required | Mapping info | Unit |
---|---|---|---|
Custom day schedules | No | - | - |
Custom holiday | No | - | - |
Efficiency | No | Necessary for economic KPIs, accuracy levels "Medium" and "Low". Default: 0.915 | - |
Fuel price | No | Necessary for economic KPIs, all accuracy levels. Default: 0.06 €/kWh | €/kWh |
Nominal heat production | No | Necessary for economic KPIs, accuracy level "Low". Default: None | kW |
Pre-conditioning period | No | - | min |
Regional key | No | - | - |
Schedule | Yes | - | - |
Schedule timezone | No | strongly recommended Default: UTC | - |
Shutdown flexibility | No | - | min |
Pin | Required | Mapping info | Unit |
---|---|---|---|
Fuel power | No | Necessary fo economic KPIs, accuracy level "High" | kW |
Generator power | No | Necessary for economic KPIs, accuracy level "Medium" | kW |
Heat flow | No | Necessary for economic KPIs, accuracy level "Medium" | kW |
Operating message | Yes | - | - |
Attribute | Required | Mapping info | Unit |
---|---|---|---|
Custom day schedules | No | - | - |
Custom holiday | No | - | - |
Fuel price | No | Necessary for economic KPIs, all accuracy levels. Default: 0.06 €/kWh | €/kWh |
Fuel utilization factor | No | Necessary for economic KPIs, accuracy levels "Medium" and "Low". Default: 0.87 | - |
Generator nominal power | No | Necessary for economic KPIs, accuracy level "Low". Default: None | kW |
Nominal heat production | No | Necessary for economic KPIs, accuracy level "Low". Default: None | kW |
Pre-conditioning period | No | - | min |
Regionalkey | No | - | - |
Schedule | Yes | - | - |
Schedule timezone | No | strongly recommended Default: UTC | - |
Shutdown flexibility | No | - | min |
Pin | Required | Mapping info | Unit |
---|---|---|---|
Electrical power | No | Necessary for economic KPIs, accuracy level "High" | kW |
Speed | No | Necessary for economic KPIs, accuracy level "Medium" | % |
Operating message | Yes | - |
Attribute | Required | Mapping info | Unit |
---|---|---|---|
Custom day schedules | No | - | - |
Custom holiday | No | - | - |
Electricity price | No | Necessary for Economic KPIs, all accuracy levels. Default: 0.18 €/kWh | €/kWh |
Nominal power consumption | No | Necessary for Economic KPIs, accuracy levels "Medium" and "Low". Default: None | kW |
Pre-conditioning period | No | - | min |
Regional key | No | - | - |
Schedule | Yes | - | - |
Schedule timezone | No | strongly recommended Default: UTC | - |
Shutdown flexibility | No | - | min |
Pin | Required | Mapping info | Unit |
---|---|---|---|
Condenser heat flow | No | Necessary for economic KPIs, accuracy level "Medium". | kW |
Electrical power | No | Necessary for economic KPIs, accuracy level "High". | kW |
Operating message | Yes | - | - |
Attribute | Required | Mapping info | Unit |
---|---|---|---|
Custom day schedules | No | - | - |
Custom holiday | No | - | - |
Electricity price | No | Necessary for economic KPIs, all accuracy levels. Default: 0.18 €/kWh | €/kWh |
Nominal heat production | No | Necessary for economic KPIs, accuracy level "Low". Default: None | kW |
Pre-conditioning period | No | - | min |
Regional key | No | - | - |
Schedule | Yes | - | - |
Schedule timezone | No | strongly recommended Default: UTC | - |
Shutdown flexibility | No | - | min |
Pin | Required | Mapping info |
---|---|---|
Operating message | No | Mapping of either operating message (preferred) or pump operating message is mandatory. If both pins are mapped, operating message is used |
Pump operating message | No | Mapping of either operating message (preferred) or pump operating message is mandatory. If both pins are mapped, operating message is used |
Attribute | Required | Mapping info | Unit |
---|---|---|---|
Custom day schedules | No | - | - |
Custom holiday | No | - | - |
Pre-conditioning period | No | - | min |
Regional key | No | - | - |
Schedule | Yes | - | - |
Schedule timezone | No | strongly recommended Default: UTC | - |
Shutdown flexibility | No | - | min |
Applying a schedule analysis on rooms is recommended to check for a scheduled room control operation. Utilize the reduced load analysis if a scheduled load reduction of heating or cooling utilities shall be analyzed.
Pin | Required | Mapping info |
---|---|---|
Operating message | Yes | - |
Attribute | Required | Mapping info | Unit |
---|---|---|---|
Custom day schedules | No | - | - |
Custom holiday | No | - | - |
Pre-conditioning period | No | - | min |
Regional key | No | - | - |
Schedule | Yes | - | - |
Schedule timezone | No | strongly recommended Default: UTC | - |
Shutdown flexibility | No | - | min |
Recommend Time Span
1 week
Recommended Repetition
Every week
- After adjustment of usage times of the analyzed component
- After changes of operational modes, e.g., transfers to heating mode
- After changes in the control system
- After maintenance or replacements
Sensor Outage Analysis¶
The Sensor Outage Analysis uses the time series data of the sensor to detect irregularities of observations. This implies manual overwriting of the sensor values, constant observations for expected volatile trajectories of the data points' observations, and also value plausibility checks by types of sensors.
Value
- Confirm normal operation of sensors
- Identify faulty measurement setups inside your building automation system
- Detection of permanently manual overwritten sensors causing permanent manipulation of control loop
Recommended for components
Any component with sensors measuring physical quantities.
Checked conditions
- Measurements of a sensor lie within a reasonable range
- Detects constant observation for sensors which expect volatile trajectories
For this example we are looking at a temperature sensor for the room air temperature, that is connected to a component "room". The KPIs are generated according to the mapped pins. For this setup we mapped a datapoint to pin pin "temperature", thus the result contains the three KPIs listed below.
The room temperature is measured by the sensor with values above the plausibility limit of 40 °C. The KPI "pin.temperature.above high limit = 1" indicates that the measured values do not lie within a reasonable range for room temperatures.
If any of the KPIs have the boolean value of 1, a faulty sensor is detected and the signal color red is returned to alarm. A detected fault can be caused by various reasons ranging from manually overwritten sensors over a faulty sensor to a wrong configured measurement system.

Figure 1: Room air temperature over a two day period
KPI | Value | Unit |
---|---|---|
pin.temperature.below low limit | No | binary |
pin.temperature.above high limit | Yes | binary |
pin.temperature.faulty | No | binary |
Signal colors
Signal color | Available | Info |
---|---|---|
red | Yes | One or more Sensors have to be checked |
yellow | No | - |
green | Yes | No faulty sensors detected |
Interpretations
Available | Info |
---|---|
Yes | Detection of faulty sensors or plausible observations |
Recommendations
Available | Info |
---|---|
Yes | Recommendations to correct the reason for the sensor fault |
KPIs
PIN_NAME refers to the actual pin on the component that the KPI belongs to.
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
pin.{PIN NAME}.datatype | Indicator of Pin datatype | analog, digital | - |
pin.{PIN NAME}.below low limit | Time Series values of pin "PIN_NAME" below low limit 0 = observations in plausible range 1 = observations below lowest plausible value detected | Yes, No | binary |
pin.{PIN NAME}.above high limit | Time Series values of pin "PIN_NAME" above high limit 0 = observations in plausible range 1 = observations above highest plausible value detected | Yes, No | binary |
Sensor Fault
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
pin.{PIN NAME}.faulty | Sensor of pin "PIN_NAME" below low limit | Yes, No | binary |
Additional KPIs for Digital Pins
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
pin.{PIN NAME}.contains not allowed values | Indicator if time series on pin contains only values of 0 or 1 | Yes, No | binary |
Pin | Required | Mapping info |
---|---|---|
Inlet temperature | No | low limit = 1 high limit = 100 |
Outlet temperature | No | low limit = 1 high limit = 100 |
Pin | Required | Mapping info |
---|---|---|
Speed | No | low limit = 0 high limit = 100 |
Pin | Required | Mapping info |
---|---|---|
Inlet temperature | No | low limit = 1 high limit = 100 |
Outlet temperature | No | low limit = 1 high limit = 100 |
Pin | Required | Mapping info |
---|---|---|
Inlet temperature | No | low limit = 1 high limit = 100 |
Outlet temperature | No | low limit = 1 high limit = 100 |
Pin | Required | Mapping info |
---|---|---|
Condenser inlet temperature | No | low limit = -50 high limit = 100 |
Condenser outlet temperature | No | low limit = -50 high limit = 100 |
Evaporator inlet temperature | No | low limit = -50 high limit = 100 |
Evaporator outlet temperature | No | low limit = -50 high limit = 100 |
Pin | Required | Mapping info |
---|---|---|
Temperature | No | low limit = 5 high limit = 40 |
Humidity | No | low limit = 0 high limit = 100 |
CO2 | No | low limit = 300 |
Pin | Required | Mapping info |
---|---|---|
Inlet temperature | No | low limit = -50 high limit = 100 |
Outlet temperature | No | low limit = -50 high limit = 100 |
Inlet temperature recirculation | No | low limit = -50 high limit = 100 |
Valve position | No | low limit = 0 high limit = 100 |
Pin | Required | Mapping info |
---|---|---|
Temperature | No | low limit = -50 high limit = 50 |
Reference temperature | No | low limit = -50 high limit = 50 |
Relative humidity | No | low limit = 0 high limit = 100 |
Reference humidity | No | low limit = 0 high limit = 100 |
Pin | Required | Mapping info |
---|---|---|
Supply air temperature | No | low limit = -20 high limit = 50 |
Outside air temperature | No | low limit = -50 high limit = 50 |
Supply relative humidity | No | low limit = 0 high limit = 100 |
Outside relative humidity | No | low limit = 0 high limit = 100 |
Pin | Required | Mapping info |
---|---|---|
Pressure difference | No | low limit = 0 |
Recommend Time Span
1 week - several weeks
Recommended Repetition
Every week
- A sensor fault can occur at any moment
Setpoint Deviation Analysis¶
The Setpoint Deviation Analysis identifies setpoints that are not met by their process values. The difference between the setpoint and the actual value is also known as the setpoint deviation. A high setpoint deviation is a symptom that can be traced back to many different causes. E.g., the insufficient supply of a controlled system with the required temperature level, suboptimal controller software, and parameters, or a blocked valve. The Setpoint Deviation Analysis incorporates features that help to narrow down the root cause of a high setpoint deviation, such as setpoint deviations caused by upstream components.
Value
Setpoint deviation is a strong symptom for faulty control loop operation, e.g., caused by
- Technical defects in the control loop supply,
- Control loop malfunctions, and
- Faulty control loop parameter settings.
Benefits of improving insufficient setpoint value attainment are
- Higher occupant comfort, health, and performance
- Lower operating costs
- Higher energy efficiency
Recommended for components
Control loops, such as
- Heating systems
- Ventilation systems
- Air-conditioning systems
Checked conditions
- Setpoint deviation
- Setpoint value is has been manually overridden
- Upstream components do not have the required temperature levels to meet the setpoint
In this example, a thermal control loop is assessed for a week (see Figure 1). Throughout the week, there is a high setpoint deviation, indicating that there is a problem with the thermal control loop.

Figure 1: Example of a process value (actual value) undershooting its setpoint
Recommendations are given to check the thermal control loop to find possible causes of the high setpoint deviation.
KPI | Value | Unit |
---|---|---|
operating time | 164.7 | h |
operating time.relative | 98.0 | % |
setpoint deviation tolerance | 1.5 | °C |
outlet temperature setpoint deviation.duration.greater than threshold | 164.7 | h |
outlet temperature setpoint deviation.duration.greater than threshold.relative | 100.0 | % |
outlet temperature.actual value above setpoint.maximum | 0.0 | °C |
outlet temperature.actual value above setpoint.mean | 0.0 | °C |
outlet temperature.actual value below setpoint.maximum | 44.0 | °C |
outlet temperature.actual value below setpoint.mean | 29.6 | °C |
Signal colors
Signal color | Available | Info |
---|---|---|
red | No | The analysis identifies the symptom and recommends measures to investigate the root cause of the setpoint deviation. Red as a signal for a low cost measure with high impact on the building operation will not be provided. |
yellow | Yes | Setpoint deviation is a strong symptom for suboptimal control and system performance. Investing the extra effort to identify the root cause and fixing it is strongly recommended. |
green | Yes | Sufficient setpoint compliance in respect to usual tolerances in buildings |
Interpretations
Available | Info |
---|---|
Yes | Interpretations summarize the result of the analysis |
Recommendations
Available | Info |
---|---|
Yes | Recommendations on how to investigate the root cause of a setpoint deviation. No recommendation, if setpoint compliance is sufficient |
KPIs
{setpoint} refers to the setpoint type, e.g., temperature. The available setpoint types are:
- co2
- outlet temperature
- temperature
- condenser/evaporator outlet temperature (for heat pumps)
Operating Time
Operating time KPIs provide information on the total time of operation of the analyzed component during the analyzed time frame.
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
operating time | Total operating time | 0 to inf | h |
operating time.relative | Relative operating time | 0 to 100 | % |
Incidence of Setpoint Deviation
Duration and statistics of the setpoint deviations, for deviations greater than the setpoint deviation tolerance.
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
setpoint deviation tolerance | The setpoint deviation which is considered acceptable | 0 to inf | unit of setpoint |
{setpoint} deviation.duration.greater than threshold | Total time for which the setpoint deviation is greater than the threshold for setpoint deviation. | 0 to inf | h |
{setpoint} deviation.duration.greater than threshold.relative | Total time for which the setpoint deviation is greater than the threshold for setpoint deviation, relative to total operating time. | 0 to 100 | % |
{setpoint}.actual value above setpoint.maximum | Largest setpoint deviation where process values is greater than setpoint. | 0 to inf | unit of setpoint |
{setpoint} .actual value above setpoint.mean | Average setpoint deviation where process values is greater than the setpoint. | 0 to inf | unit of setpoint |
{setpoint} .actual value below setpoint.maximum | Largest setpoint deviation where process values is smaller than setpoint. | 0 to inf | unit of setpoint |
{setpoint} .actual value below setpoint.mean | Average setpoint deviation where process values is smaller than setpoint. | 0 to inf | unit of setpoint |
Upstream component check
KPIs regarding the upstream components.
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
{setpoint}.duration.above inlet | Total time for which the outlet setpoint is above the inlets. | 0 to inf | unit of setpoint |
{setpoint}.duration.above inlet.relative | Total time for which the outlet setpoint is above the inlets, relative to total operating time. | 0 to inf | unit of setpoint |
{setpoint}.duration.below inlet | Total time for which the outlet setpoint is below the inlets. | 0 to inf | unit of setpoint |
{setpoint}.duration.below inlet.relative | Total time for which the outlet setpoint is below the inlets, relative to the total operating time. | 0 to inf | unit of setpoint |
Pin | Required | Mapping info |
---|---|---|
Operating message | No | Mapping strongly recommended Default: Always operating |
Outlet temperature | Yes | - |
Outlet temperature setpoint | Yes | - |
Attribute | Required | Mapping info | Unit |
---|---|---|---|
Temperature setpoint deviation tolerance | No | Default: 1.5°C |
Pin | Required | Mapping info |
---|---|---|
Operating message | No | Mapping strongly recommended Default: Always operating |
Outlet temperature | Yes | - |
Outlet temperature setpoint | Yes | - |
Attribute | Required | Mapping info | Unit |
---|---|---|---|
Temperature setpoint deviation tolerance | No | Default: 1.5°C |
Pin | Required | Mapping info |
---|---|---|
Condenser outlet temperature | No | Required, if condenser shall be analyzed |
Condenser outlet temperature setpoint | No | Required, if condenser shall be analyzed |
Evaporator outlet temperature | No | Required, if evaporator shall be analyzed |
Evaporator outlet temperature setpoint | No | Required, if evaporator shall be analyzed |
Operating message | No | Mapping strongly recommended Default: Always operating |
Attribute | Required | Mapping info | Unit |
---|---|---|---|
Condenser outlet temperature setpoint deviation tolerance | No | Default: 1.5°C | |
Evaporator outlet temperature setpoint deviation tolerance | No | Default: 1.5°C |
Pin | Required | Mapping info |
---|---|---|
Operating message | No | Mapping strongly recommended Default: Always operating |
Temperature | Yes | - |
Temperature setpoint | Yes | - |
Attribute | Required | Mapping info | Unit |
---|---|---|---|
CO2 setpoint deviation tolerance | No | Default: 150 ppm | |
Temperature setpoint deviation tolerance | No | Default: 2.5°C |
Pin | Required | Mapping info |
---|---|---|
Inlet temperature | Yes | - |
Operating message | No | Mapping of either operating message (preferred) or pump operating message is strongly recommended. If operating message and pump operating message are mapped, operating message will be used Default: Always operating |
Outlet temperature | Yes | - |
Pump operating message | No | Mapping of either operating message (preferred) or pump operating message is strongly recommended. If operating message and pump operating message are mapped, operating message will be used Default: Always operating |
Attribute | Required | Mapping info | Unit |
---|---|---|---|
Outlet temperature setpoint deviation tolerance | No | Default: 1.5°C |
Recommend Time Span
1 day to 1 week
Recommended Repetition
Every week
- After changes of operational modes, e.g., transfers to heating mode
- After changes in the control system
- After maintenance or replacements
Setpoint Plausibility Analysis¶
The Setpoint Plausibility Analysis identifies implausible setpoint values for common application of a component. This is achieved by identifying periods for which the setpoints falls outside of predefined limits.
Value
- Increase efficiency through better operation
- Improve occupant comfort
Recommended for components
- Rooms
Checked conditions
- Comparison between actual setpoint and typical setpoint for application
In this example, the temperature setpoint of a room changes from 21°C to 16°C (see Figure 1). Since 16°C is below the recommended temperature for rooms, the analysis is evaluated with the signal color "yellow".

Figure 1: Temperature setpoint of a room for the period of a week.
The reason for a lower limit of temperature setpoints within rooms is that thermal comfort is reduced and the likelihood of condensation and mold forming increases with low room temperatures. Recommendations are made to reset the setpoint to fall within typical setpoint limits for a room to improve operation and thermal comfort.
KPI | Value | Unit |
---|---|---|
operating time | 70.0 | h |
operating time.relative | 41.7 | % |
temperature setpoint.above upper setpoint limit.duration | 0.0 | h |
temperature setpoint.above upper setpoint limit.duration.relative | 0.0 | % |
temperature setpoint.below lower setpoint limit.duration | 50.0 | h |
temperature setpoint.below lower setpoint limit.duration.relative | 71.4 | % |
Signal colors
Signal color | Available | Info |
---|---|---|
red | No | - |
yellow | Yes | Setpoint is outside of the range of setpoints typical for this component for a significant amount of the time. |
green | Yes | Setpoint is within typical limits for this component. |
Interpretations
Available | Info |
---|---|
Yes | Either the operational rule checks of the analysis were tested positive or not. |
Recommendations
Available | Info |
---|---|
Yes | Recommendations to reset the setpoint so that it falls within the expected range for the component. |
KPIs
{setpoint} refers to the setpoint type. The available setpoint types are "co2" and "temperature".
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
operating time | Total operating time. | 0 to inf | h |
operating time.relative | Relative operating time. | 0 to 100 | % |
{setpoint}.above upper setpoint limit.duration | Total time for which the setpoint is above the upper setpoint limit. | 0 to inf | h |
{setpoint}.above upper setpoint limit.duration.relative | Total time for which the setpoint is above the upper setpoint limit, relative to the total operating time. | 0 to 100 | % |
{setpoint}.below lower setpoint limit.duration | Total time for which the setpoint is below the lower limit. | 0 to inf | h |
{setpoint}.below lower setpoint limit.duration.relative | Total time for which the setpoint is below the lower limit, relative to the total operating time. | 0 to 100 | % |
Pin | Required | Mapping info |
---|---|---|
CO2 setpoint | No | - |
Temperature setpoint | No | - |
Operating message | No | Mapping strongly recommended Default: Always operating |
Synchronized Operation Analysis¶
The Synchronized Operation Analysis detects whether the operation of the analyzed components is synchronized correctly. E.g., the pump of a thermal control loop is operating while the 2-way valve is closed or rather almost closed. If pumps continue to be operated with the valve closed, this leads to unnecessary power consumption and higher wear of the pump due to the additional running time. A valve opening of 10 % or less is considered as closed.
Value
- Reduce energy cost
- Increase lifespan of pumps in heating and cooling circuits
- Check the interaction between system and pump during switch operations of the system
Recommended for components
Any fluid supply system using, such as
- Thermal control loop with 2-way valve and pump
- Thermal control loop with a 3-way valve and pump#
- Boiler with pump
- Combined heat and power unit with pump
- Heat pump with evaporator/condenser feeding pumps
Checked conditions
- Pump is shutdown, if the two-way valve is closed
- Pump is still operating although the two-way valve is closed
- Condition checks on times of components operation
For this example, we use a heating circuit with a 2-way-valve.
Figure 1 shows the pump operating message and valve position of a thermal control loop. During the analysis period, the valve position lies between 0 and 20 %. With the KPI pump operating time.valve closed.relative we can estimate that the valve is nearly closed for ~40 % of the operating time.

Figure 1: Valve position and pump operating message
KPI | Value | Unit |
---|---|---|
pump operating time.valve closed.relative | 39.7 | % |
pump operating time.valve closed | 76.2 | h |
pump operating time.relative | 100 | % |
Signal colors
Signal color | Available | Info |
---|---|---|
red | Yes | Significant pump operation times although 2-way valve was identified as closed |
yellow | Yes | Partial operation times outside of the parameterized schedule identified |
green | Yes | Sufficient operation according to the parameterized schedule |
Interpretations
Available | Info |
---|---|
Yes | Interpretations summarize the result of the analysis |
Recommendations
Available | Info |
---|---|
Yes | Recommendations to improve the synchronized operation of components. No recommendation, if components are synchronized correctly. |
KPIs
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
pump operating time.valve closed.relative | Percentage of time the pump is active while the 2-way valve is nearly closed based on total operating time | 0 to 100 | % |
pump operating time.valve closed | The amount of time the pump is active while the 2-way valve is nearly closed | 0 to inf | h |
pump operating time.relative | Percentage of time the pump is active based on the whole analysis period | 0 to 100 | % |
pump operating time | Time the pump is active based on the whole analysis period | 0 to inf | h |
Attribute "Valve type" set to "2-way valve" or "3-way valve"
Pin | Required | Mapping info |
---|---|---|
Operating message | No | Mapping of either pump operating message (preferred) or operating message is mandatory. If both pins are mapped, the pump operating message is used. |
Pump operating message | No | Mapping of either pump operating message (preferred) or operating message is mandatory. If both pins are mapped, the pump operating message is used. |
Valve position | No | Mapping of either valve position (preferred) or valve position setpoint is mandatory. If both pins are mapped, the valve position is used. |
Valve position setpoint | No | Mapping of either valve position (preferred) or valve position setpoint is mandatory. If both pins are mapped, the valve position is used. |
Pin | Required | Mapping info |
---|---|---|
Operating message | Yes | General operating message for the CHP. |
Pump operating message | Yes | Operating message of the (cooling) pump. |
Pin | Required | Mapping info |
---|---|---|
Operating message | Yes | General operating message for the boiler unit. |
Pump operating message | Yes | Operating message of the feeding pump. |
Pin | Required | Mapping info |
---|---|---|
Operating message | Yes | General operating message of the heat pump. |
Condenser pump operating message | No | At least one pump operating message has to be connected. |
Evaporator pump operating message | No | At least one pump operating message has to be connected. |
Recommend Time Span
1 week
Recommended Repetition
Every 3 months
- After changes of operational modes, e.g., transfers to heating mode
- After changes in the control system
- After maintenance or replacements
Temperature Spread Analysis¶
The Temperature Spread Analysis assesses the temperature difference between a supply and return temperature sensor of a heat or cold distribution system during the system's operation. While a small temperature spread indicates the potential for volume flow and therefore pump power consumption reduction, a huge spread indicates thermal undersupply of the downstream systems and consumers.
Value
- Higher occupant comfort, health and performance
- Higher energy efficiency
- Lower operating costs
Recommended for components
Heat and cold distribution systems, such as
- Thermal control loop
Checked conditions
- Temperature spread is too small causing volume flows that are too high, evaluation is component-specific
- Temperature spread is too large and risk sufficient energy supply, evaluation is component-specific
- Temperature spread is as expected, evaluation is component-specific
- Condition checks on times of component's operation
The temperature spread analysis was applied to a heating circuit instantiated as a thermal control loop.

Figure 1: Outlet temperature and return temperature of the thermal control loop
Analysis for one week in May 2020 is shown in figure 1. A small temperature spread "temperature spread.mean" is calculated for this period of 5 °C. Thus a recommendation to reduce the volume flow of the heating circuit is returned to the user.
KPI | Value | Unit |
---|---|---|
operating time | 84.9 | h |
operating mode | heating | |
inlet temperature recirculation.mean | 40.4 | °C |
outlet temperature.mean | 45.4 | °C |
temperature spread.mean | 4.94 | °C |
temperature spread.median | 4.68 | °C |
temperature spread.minimum | -4.24 | °C |
temperature spread.maximum | 22.3 | °C |
Signal colors
Signal color | Available | Info |
---|---|---|
red | No | Red as a signal for a low cost measure with high impact on the building operation will not be provided. |
yellow | Yes | Temperature spreads usually can be optimized by volume flow adjustments. Savings allow for medium-term amortization |
green | Yes | Sufficient temperature spread in respect to usual tolerances in buildings |
Interpretations
Available | Info |
---|---|
Yes | Interpretations summarize the result of the analysis |
Recommendations
Available | Info |
---|---|
Yes | Recommendations on how to adjust volume flows for higher energy efficiency or better energy provision. No recommendation, if temperature spread is sufficient. |
KPIs
Heat pump:
The KPI identifiers are extended by the prefix condenser or evaporator to specify the side of the heat pump the temperature spread analysis is applied on.
Example evaporator: temperature spread.minimum will be evaporator temperature spread.minimum
General
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
operating time | Amount of time component is switched on | 0 to inf | h |
Statistics of temperature spread
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
temperature spread.maximum | Maximum of temperature spread | -inf to inf | °C |
temperature spread.mean | Mean of temperature spread | -inf to inf | °C |
temperature spread.median | Median of temperature spread | -inf to inf | °C |
temperature spread.minimum | Minimum of temperature spread | -inf to inf | °C |
Specific for thermal control loops
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
operating mode | Indication of heat transfer | heating, cooling, neutral | - |
inlet temperature recirculation.mean | Mean of inlet temperature recirculation | -inf to inf | °C |
outlet temperature.median | Median of outlet temperature | -inf to inf | °C |
Specific for heat pumps
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
operating mode | Indication of heat transfer | heating, cooling, neutral | - |
inlet temperature.mean | Mean of inlet temperature | -inf to inf | °C |
outlet temperature.median | Median of outlet temperature | -inf to inf | °C |
Pin | Required | Mapping info |
---|---|---|
Inlet temperature | Yes | - |
Operating message | No | strongly recommended Default: Always on |
Outlet temperature | Yes | - |
Pin | Required | Mapping info |
---|---|---|
Inlet temperature | Yes | - |
Operating message | No | strongly recommended Default: Always on |
Outlet temperature | Yes | - |
Pin | Required | Mapping info |
---|---|---|
Condenser inlet temperature | No | Required, if condenser shall be analyszed |
Condenser outlet temperature | No | Required, if condenser shall be analyzed |
Evaporator inlet temperature | No | Required, if evaporator shall be analyzed |
Evaporator outlet temperature | No | Required, if evaporator shall be analyzed |
Operating message | No | Mapping strongly recommended Default: Always operating |
Pin | Required | Mapping info |
---|---|---|
Operating message | No | Mapping of either pump operating message (preferred) or operating message is mandatory. If both pins are mapped, pump operating message is used Default: Always on |
Outlet temperature | Yes | - |
Pump operating message | No | Mapping of either pump operating message (preferred) or operating message is strongly recommended. If both pins are mapped, valve position is used Default: Always on |
Inlet temperature recirculation | Yes | - |
Recommend Time Span
1 day to 1 week
Recommended Repetition
Every month
- After changes of operational modes, e.g., transfers to heating mode
- After changes in the control system
- After maintenance or replacements
Thermal Comfort Analysis¶
The Thermal Comfort Analysis evaluates the comfort level of a room by determining the indicators PMV (Predicted Mean Vote) and PPD (Predicted Percentage of Dissatisfied). They are calculated from room air temperature, room air humidity, and expected level of clothing depending on the outdoor temperature. Influences on thermal comfort in rooms like thermal exchange by radiation and influences of drafts are simplified in the determination.
Value
- Check and evaluate the room comfort level
- Higher occupant comfort, health and performance
Recommended for components
- Rooms with usual conditioning like offices, schools, salesrooms
Checked conditions
- Sufficient thermal comfort
For this example, we look at a room for an analysis period of two days as shown in figure 1. In this time we can categorize the room comfort level according to the comfort level categories in the table below. The PMV level stays inside the neutral category for the entire 48 hour period.

Figure 1: Temperatures and humidity while presence over a two days period in march
KPI | Value | Unit |
---|---|---|
operating time | 48 | h |
operating time.relative | 100 | % |
predicted percentage of dissatisfied.mean | 11.3 | % |
predicted percentage of dissatisfied.median | 9.66 | % |
predicted percentage of dissatisfied.maximum | 41.1 | % |
predicted percentage of dissatisfied.minimum | 5.0 | % |
predicted mean vote.mean | -0.483 | n.a. |
predicted mean vote.median | -0.472 | n.a. |
predicted mean vote.maximum | 0.0831 | n.a. |
predicted mean vote.minimum | -1.32 | n.a. |
duration.predicted mean vote.hot | 0 | h |
duration.predicted mean vote.warm | 0 | h |
duration.predicted mean vote.warmish | 0 | h |
duration.predicted mean vote.neutral | 25 | h |
duration.predicted mean vote.coolish | 23 | h |
duration.predicted mean vote.cool | 0 | h |
duration.predicted mean vote.cold | 0 | h |
duration.category A.relative | 8.33 | % |
duration.category B.relative | 43.8 | % |
duration.category C.relative | 22.9 | % |
duration.no category.relative | 25.0 | % |
duration.predicted mean vote.neutral | 48 | h |
Signal colors
Signal color | Available | Info |
---|---|---|
red | Yes | Room comfort level is insufficient |
yellow | Yes | Room comfort level is sufficient |
green | Yes | Room comfort level is good |
Interpretations
Available | Info |
---|---|
Yes | Evaluation of the room comfort level for peak and average values |
Recommendations
Available | Info |
---|---|
Yes | Recommendations to improve the room comfort level |
KPIs
Temperatures
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
room.temperature.mean | Average room temperature during presence and analysis period | inf | °C |
room.relative humidity.mean | Average relative humidity for room during presence and analysis period | 0 to 100 | % |
outdoor temperature.mean | Average outdoor temperature during presence and analysis period | inf | °C |
Operating Time
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
operating time | Duration of presence, respectively active room control if presence is not measured | 0 to inf | h |
operating time.relative | Duration of presence, respectively active room control if presence is not measured, relative to analyzed time | 0 to 100 | % |
Predicted Mean Vote - PMV
Following the Climate Assessment Scale of DIN EN ISO 7730, 2006 with
PMV Value | Classification |
---|---|
pmv > 2.5 | hot |
1.5 < pmv <= 2.5 | warm |
0.5 < pmv <= 1.5 | warmish |
-0.5 <= pmv <= 0.5 | neutral |
-1.5 <= pmv < -0.5 | coolish |
-2.5 <= pmv < -1.5 | cool |
pmv < -2.5 | cold |
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
predicted mean vote.mean | Average of PMV for analysis period | -3 to 3 | - |
predicted mean vote.median | Median of PMV for analysis period | -3 to 3 | - |
predicted mean vote.maximum | Maximum PMV reached during analysis period | -3 to 3 | - |
predicted mean vote.minimum | Minimum PMV reached during analysis period | -3 to 3 | - |
duration.predicted mean vote.hot | Duration the PMV is classified as hot | 0 to inf | h |
duration.predicted mean vote.warm | Duration the PMV is classified as warm | 0 to inf | h |
duration.predicted mean vote.warmish | Duration the PMV is classified as warmish | 0 to inf | h |
duration.predicted mean vote.neutral | Duration the PMV is classified as neutral | 0 to inf | h |
duration.predicted mean vote.coolish | Duration the PMV is classified as coolish | 0 to inf | h |
duration.predicted mean vote.cool | Duration the PMV is classified as cool | 0 to inf | h |
duration.predicted mean vote.cold | Duration the PMV is classified as cold | 0 to inf | h |
Predicted Percentage of Dissatisfied - PPD
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
predicted percentage of dissatisfied.mean | Average of PPD for analysis period | 0 to 100 | % |
predicted percentage of dissatisfied.median | Median of PPD for analysis period | 0 to 100 | % |
predicted percentage of dissatisfied.maximum | Maximum PPD reached during analysis period | 0 to 100 | % |
predicted percentage of dissatisfied.minimum | Minimum PPD reached during analysis period | 0 to 100 | % |
Comfort Level Categories
According to norm DIN EN 15251, 2007
Category | PMV |
---|---|
A | -0,2 < PMV < +0,2 |
B | -0,5 < PMV < +0,5 |
C | -0,7 < PMV < +0,7 |
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
duration.category A.relative | Percentage of time the room comfort level corresponds to category A | 0 to 100 | % |
duration.category A | Duration that the room comfort level corresponds to category A | 0 to inf | h |
duration.category B.relative | Percentage of time the room comfort level corresponds to category B | 0 to 100 | % |
duration.category B | Duration that the room comfort level corresponds to category B | 0 to inf | h |
duration.category C.relative | Percentage of time the room comfort level corresponds to category C | 0 to 100 | % |
duration.category C | Duration that the room comfort level corresponds to category C | 0 to inf | h |
duration.no category.relative | Percentage of time the room comfort level corresponds to no category | 0 to 100 | % |
duration.no category | Duration that the room comfort level corresponds to no category | 0 to inf | h |
Time series
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
predicted mean vote.time series | Timeseries with the PMV value for each observation | -3 to 3 | - |
predicted percentage of dissatisfied.time series | Timeseries with the PPD value for each observation | 0 to 100 | % |
category.time series | Timeseries with a category classification for each observation | A, B, C, NOCAT | string |
Economic KPIs
Economic KPIs estimate the economic optimization potential of the observed operational state. The KPIs indicate the possible productivity gains and the resulting salary savings for adjusting the thermal state to the thermal comfort range. The thermal comfort range is defined by PMV category B (-0.5 < PMV < 0.5). Category B describes a normal level of expectation, according to DIN EN 15251:2012-12.
The Economic KPIs are provided for the components:
- Room
Their availability and accuracy depend on the component's mapping. The analysis function always determines the highest possible accuracy.
Accuracy Levels:
High
Components | Pins | Attributes |
---|---|---|
Room | Presence or Operating message Temperature Humidity Outside air temperature | Complementary: Room type (used in combination with "Presence" or "Operating message" to estimate room usage). |
Medium
Components | Pins | Attributes |
---|---|---|
Room | Temperature Humidity Outside air temperature | Schedule Complementary: Custom day schedule Schedule timezone Custom holiday Regional key Room type (used in combination with pins Schedule attributes to estimate room usage). |
Low
Components | Pins | Attributes |
---|---|---|
Room | Temperature Humidity Outside air temperature Assumption of 24/7 usage | Complementary: Room type (used to estimate room usage). |
All Accuracy Levels
Components | Pins | Attributes |
---|---|---|
Room | - | Average salary Occupation max |
Salary savings KPIs: Required additional mapping to all accuracy levels.
Components | Pins | Attributes |
---|---|---|
Room | - | Average salary Occupation max |
Salary savings KPIS
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
thermal comfort salary savings.daily | Identified salary savings potential from employee productivity losses for the thermal state outside of comfort limits (Category B). The savings are provided as average daily savings potential. | 0 to inf | €/day |
thermal comfort salary savings.weekly | Identified salary savings potential from employee productivity losses for the thermal state outside of comfort limits (Category B). The savings are provided as average weekly savings potential if the analyzed period is at least one week long. | 0 to inf | €/week |
Productivity Gains KPI
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
thermal comfort productivity gains.relative | Identified percentual productivity gains for adjusting the thermal state to the comfort range (Category B). | 0 to 100 | % |
Pin | Required | Mapping info | Unit |
---|---|---|---|
Temperature | Yes | - | °C |
Humidity | Yes | - | % |
Outside air temperature | Yes | - | °C |
Operating message | No | Mapping of either presence (preferred) or operating message is strongly recommended. If both pins are mapped, presence is used Default: Always presence | binary |
Presence | No | Mapping of either presence (preferred) or operating message is strongly recommended. If both pins are mapped, presence is used Default: Always presence | binary |
Attribute | Required | Mapping info | Unit |
---|---|---|---|
Average salary | No | Necessary for Salary savings KPIs of Economic KPIs, all accuracy levels. | €/person |
Occupation max | No | Necessary for Salary savings KPIs of Economic KPIs, all accuracy levels. | - |
Room type | No | Available values: - 24/7 full occupancy - classroom - single person office multi persons office - store - restaurant - conference room - kindergarten Default: 24/7 full occupancy | - |
Schedule timezone | No | Default: UTC | - |
Custom day schedules | No | Default: {} | - |
Regional key | No | Default: None | - |
Schedule | No | Default: None | - |
Recommend Time Span
1 week
Recommended Repetition
Every month
- After changes of presence schedules or room schedules
Virtual Heat Meter¶
The Virtual Heat Meter determines the heat flow and energy delivered in heating/cooling piping networks such as thermal control loops or energy conversion plants. The determination is either based on the temperature difference and volume flow, or the readings from a physical heat meter in the field. It substitutes physical heat meters and enables energy flow tracing.
Value
Quantifies heat flow and heat:
- Traces energy flow
- Enable other analytics functions
- Enables comparison to hardware heat meters
Recommended for components
Heat and cold conversion or distribution systems, such as
- Boilers
- Combined heat and power
- Heat meters
- Heat pumps
- Thermal control loops
Checked conditions
- Determines heat flow from temperature difference and volume flow for several components.
- Condition checks on times of components operation.
- Compares the measured heat with the virtual heat (calculated by analysis), if both are available.
The virtual heat meter analysis was tested on a combined heat and power plant for one week. Figure 1 shows the inlet/outlet temperatures, volume flow, and heat flow of the combined heat and power plant.

Figure 1: Temperatures, volume flow and heat flow of combined heat and power plant
The virtual heat is compared with the measured heat and based on the relatively small difference between the two heats, a green signal color is returned.
KPI | Value | Unit |
---|---|---|
measured heat | 43.4 | MWh |
measured heat flow.mean | 444.6 | kW |
measured heat flow.minimum | 0.1 | kW |
measured heat flow.maximum | 1113.1 | kW |
measured heat flow.median | 595.8 | kW |
virtual heat | 41.4 | MWh |
virtual heat flow.mean | 324.1 | kW |
virtual heat flow.minimum | -1213.2 | kW |
virtual heat flow.maximum | 1061.8 | kW |
virtual heat flow.median | 548.9 | kW |
heat difference | 2.01 | MWh |
heat difference.relative | 4.63 | % |
The analysis only returns recommendations and evaluations if both a measured heat/heat flow is available and a virtual heat is calculated. Otherwise only KPI results and time series are returned.
Signal colors
Signal color | Available | Info |
---|---|---|
red | No | - |
yellow | Yes | There is a significant difference between the virtual heat and the measured heat for this component or its sub-components. |
green | Yes | There is no significant difference between the virtual heat and the measured heat for this component and all of its sub-components. |
Interpretations
Available | Info |
---|---|
Yes | Either the operational rule checks of the analysis were tested positive or not |
Recommendations
Available | Info |
---|---|
Yes | Consider re-calibrating the heat meter |
KPIs
Statistics of heat flow
Negative values indicate cooling, while positive indicate heating.
Virtual and measured heat:
The "virtual heat" refers to heat calculated using temperatures and volume flows where "measured heat" refers to heats supplied by physical heat meters. The KPIs and time series are available for both cases and referred to as either measured or virtual heats e.g.:
measured heat flow is the heat flow measured by a heat meter
Units:
The units of the returned heat and heat flow are selected according to the magnitude of the result. Typical units are presented in the table below. Other possible units include MWh for heat and MW or W for heat flow.
Heat pump:
The KPI identifiers are extended by the prefix condenser or evaporator to specify the side of the heat pump the virtual heat meter is applied on. E.g.:
heat flow.maximum will be evaporator heat flow.maximum
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
heat flow.maximum | Largest heat flow | -inf to inf | kW |
heat flow.minimum | Smallest heat flow | -inf to inf | kW |
heat flow.mean | Average heat flow | -inf to inf | kW |
heat flow.median | Median heat flow | -inf to inf | kW |
heat | Aggregated heat transferred | -inf to inf | kWh |
heat difference | Difference between measured and virtual heat | -inf to inf | kWh |
heat difference.relative | Percentage difference between virtual and measured heat | 0 to 100 | % |
Time series
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
heat flow.time series | Timeseries of transferred heat | -inf to inf | kW |
heat flow.cumulated | Timeseries of cumulated transferred heat | -inf to inf | kWh |
Pin | Required | Mapping info |
---|---|---|
Inlet temperature | No | - |
Outlet temperature | No | - |
Volume flow | No | - |
Heat | No | - |
Heat flow | No | - |
Attribute | Required | Mapping info |
---|---|---|
Heat flow unit | No | Default: kW |
Heat unit | No | Default: kWh |
Volume flow unit | No | Default: litersPerSecond |
Pin | Required | Mapping info |
---|---|---|
Inlet temperature | No | - |
Outlet temperature | No | - |
Volume flow | No | - |
Volume flow | No | - |
Heat | No | - |
Heat flow | No | - |
Attribute | Required | Mapping info |
---|---|---|
Heat flow unit | No | Default: kW |
Heat unit | No | Default: kWh |
Volume flow unit | No | Default: litersPerSecond |
Pin | Required | Mapping info |
---|---|---|
Inlet temperature | No | - |
Outlet temperature | No | - |
Volume flow | No | - |
Heat | No | - |
Heat flow | No | - |
Attribute | Required | Mapping info |
---|---|---|
Heat flow unit | No | Default: kW |
Heat unit | No | Default: kWh |
Volume flow unit | No | Default: litersPerSecond |
The Virtual Heat Meter is determined on the condenser and evaporator side depending on the mapped datapoints.
Pin | Required | Mapping info |
---|---|---|
Condenser inlet temperature | No | Required, if condenser shall be analyzed |
Condenser outlet temperature | No | Required, if condenser shall be analyzed |
Condenser volume flow | No | Required, if condenser shall be analyzed |
Condenser heat flow | No | Required, if condenser shall be analyzed |
Condenser heat | No | Required, if condenser shall be analyzed |
Evaporator inlet temperature | No | Required, if evaporator shall be analyzed |
Evaporator outlet temperature | No | Required, if evaporator shall be analyzed |
Evaporator volume flow | No | Required, if evaporator shall be analyzed |
Evaporator heat flow | No | Required, if evaporator shall be analyzed |
Evaporator heat | No | Required, if evaporator shall be analyzed |
Attribute | Required | Mapping info |
---|---|---|
Heat flow unit | No | Default: kW |
Heat unit | No | Default: kWh |
Volume flow unit | No | Default: litersPerSecond |
Attributes
The units used for this analysis need to be specified for the analysis to yield correct results. If unspecified, the default unit is taken.
Heat flow unit
default: kW
Available units:
- W
- kW
- MW
- GW
Heat unit
default: kWh
Available units:
- Wh
- kWh
- MWh
- GWh
Volume flow unit:
Default: litersPerSecond
Available units:
- cubicMetersPerSecond
- cubicMetersPerMinute
- cubicMetersPerHour
- litersPerSecond
- litersPerMinute
- litersPerHour
Recommend Time Span
1 day to 1 month
Recommended Repetition
Every month
Weather Station Analysis¶
Two important sensors for HVAC system control are the outdoor air temperature sensor and the outdoor air humidity sensor. Many control decisions, e.g., what amount of heat/humidity is to be provided, and the switching between heating and cooling modes, are made based on the measured outdoor temperature and humidity. The sensors are prone to wear out over the lifetime of the building. Furthermore, the sensors are often influenced by solar radiation or heat emitted from components in its surrounding. Wrongly measured outside air temperature or humidity directly corresponds to a thermal over/undersupply of the building or incorrect indoor humidity, often leading to poor user comfort and increased energy consumption.
The Weather Station Analysis identifies installation errors and measurement offsets of the outdoor air temperature sensor and derives optimization measures for better outdoor air temperature measuring.
Value
- Higher operational performance due to reliable information about outside air conditions
- Higher occupant comfort, health, and performance
- Lower operating costs
- Better system coordination in systems with redundant sensors
Recommended for components
- Weather station
Checked conditions
- Offset between measured outdoor air temperature and weather service reference data
- Offset between measured outdoor air humidity and weather service reference data
- Outdoor air temperature sensor is mistakenly influenced by solar radiation
- Outdoor air temperature sensor is mistakenly influenced by its surrounding, e.g., exhaust gases
- Outdoor air temperature measures are compliant to weather service reference data
For this Weather Station Analysis we instantiated a "weather station" component and analyzed a week of weather data. The following plot shows the measured temperature of a sensor located at a building facade. During the reviewed period in the summer, the sensor is influenced in the afternoon.

Figure 1: Measured data outdoor air temperature and reference outdoor air temperature
In figure 1 you can see a significant difference between sensor and weather reference. This is also reflected in the value of the calculated KPIs. During the analysis period, all 7 days are recognized by the KPI as "radiation influenced days". Additionally, the offset at night is elevated and thus a larger "sensor offset squared error" is present.
KPI | Value | Unit |
---|---|---|
radiation influenced.relative | 100 | % |
radiation influenced days | 7 | count |
offset RMSE | 7.3 | Kelvin |
offset ME | 6.4 | Kelvin |
Signal colors
Signal color | Available | Info |
---|---|---|
red | Yes | Significant solar radiation influence and/or offset identified |
yellow | Yes | Partial solar radiation influence and/or moderate offset identified |
green | Yes | Sufficient accuracy of outdoor air temperature measurements |
Interpretations
Available | Info |
---|---|
Yes | Interpretations summarize the result of the analysis |
Recommendations
Available | Info |
---|---|
Yes | Recommendations to improve outdoor air temperature measurement, if necessary or re-calibrate the sensor, if physically implausible measures are observed. No recommendation, in case of sufficient measurement quality. |
KPIs
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
radiation influenced days.relative | Ratio of days with more than one hour of sun radiation influence to days analyzed | 0 to 100 | % |
radiation influenced days | Days with more than one hour of sun radiation influence | 0 to inf | days |
offset RMSE | Root mean square error of the offset between measured outdoor air temperature and the reference data set. | 0 to inf | Kelvin |
offset ME | Mean error of the offset between measured outdoor air temperature and the reference data set. | -inf to inf | Kelvin |
Sensor errors
KPI Identifier | Description | Value Range | Unit |
---|---|---|---|
Temperature RMSE | Root mean square error between the measured outdoor air temperature and the reference data set. | 0 to inf | Kelvin |
Temperature ME | Mean error between the measured outdoor air temperature and the reference data set. | -inf to inf | Kelvin |
Humidity RMSE | Root mean square error between the measured outdoor relative humidity and the reference data set. | 0 to 100 | % |
offset ME | Mean error of the offset between measured outdoor air temperature and the reference data set. | -inf to inf | Kelvin |
Pin | Required | Mapping info |
---|---|---|
Temperature | No | Mandatory for outside air temperature checkup |
Humidity | No | Mandatory for outside air humidity checkup |
Attribute | Required | Mapping info |
---|---|---|
Latitude | Yes | - |
Longitude | Yes | - |
Recommend Time Span
1 month
Recommended Repetition
Every month
- After changes of operational modes, e.g., transfers to heating mode
- After changes in the control system
- After maintenance or replacements
Information¶
The library of analytics functions is constantly expanding. If you are missing an analytics function, wish to implement your own functions, or want us to implement it for you, feel free to contact us.