Analytics

Detailed specification of analytics functions, their benefits, and application.

Introduction

Analytics peruses only one goal: Guide technicians and building users to improve operational performance of buildings and energy systems, while the benefits of improved operational performance are multilateral:

  • Higher comfort, 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.

How to read the docs?

Each analysis function documentation starts with a short description. Specifications for the application of the analysis are ordered in tabs

Summary

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.

Example

In general you can expect a short case study on how the analysis function was applied during development or a test bench.

Results

Results of analytics functions are structured to deliver simple to navigate insights and fast to apply measures on how to improve operational performance.

Therefor, 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 timeserieses.

These categories are explained below. While the warning level, interpretation, and recommendation are specified for all analysis functions equally, KPIs and timeserieses 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 recommended.

Interpretation

The interpretation delivers a summary over the observed performance and state of the condition analyzed. In general it describes either a symptom of a suboptimal operation or condition could be found or not.

In the engineering vocabulary of Fault Detection and Diagnosis (FDD), the interpretation represents the Fault Detection.

Recommendation

Recommendations is a list of 0 (for sufficient operational performance) to n measurements on how to correct the reason for the detected symptom for suboptimal operation. Either by providing recommendations on how to correct the source of the symptom itself or on how to narrow down its cause.

KPIs and timeserieses

KPIs and timeserieses offer insights and transparency. They enable reporting and manual investigation of the operational behavior the component or system analyzed. KPIs and timeserieses are highly individual for each function and are explained in the respective specification of each analysis function in Results.

Components

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.

Application

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 limit the amount of analysis to the required ones without risking blind spots in the continuous monitoring.

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.

Summary
Example
Results
Components
Application
Summary

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 control loop is oscillating

  • Process value of control loop is not or to a negligible degree oscillating

  • Condition checks on times of components operation

Example

For this example we analyzed the temperature control loop of a supply air volume flow, which provides fresh air and heating to a large sales room. Figure 1 shows a plot of the process value of the control loop, the outlet temperature. The plot shows a 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 more into 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, signal color yellow, and derived recommendation on how to adjust controller parameters for a smoother operation.

Results

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

Either the operational rule checks of the analysis were tested positive or not

Recommendations

Available

Info

Yes

Recommendations on how to smooth the control loop oscillation. No recommendation, if oscillation is negligible

Components

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

Application

Recommended 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

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.

Summary
Example
Results
Components
Application
Summary

Value

  • Lower operating costs

  • Higher energy efficiency

  • Peak energy consumption reduction

  • Longer equipment and component life times

  • 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

Example

The Operating Cycle Analysis was applied to a real test bench, the heat pump of the E.ON Energy Research Center, RWTH Aachen University. 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 6 hours on a winter day.

Figure 1: Operating message and cycle behavior of heat pump

Short shut-down times between periods of duty indicate excessive start and stop processes of the heat pump, leading not only to energy losses and electricity consumption peaks but also to increased wear and tear of the heat pumps compressor.

The automated interpretation confirms our visual analysis of the time series shown in the figure, summed up by the qualitative warning level "red". The recommendations provide further instruction on how to isolate and fix the cause for the increased number of start and stop processes. Further, the result offers an advanced set of KPIs, providing additional insights into the cycle behavior of the heat pump.

Results

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 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

Either the operational rule checks of the analysis were tested positive or not

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

Operating times KPIs provide information on the total time of operation of the analysed component during the analysed time span.

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

%

Start

The Start KPI is the count of starts of the analysed component during the analysed time span.

KPI Identifier

Description

Value Range

Unit

starts

Count of starts

0 to inf

count

Closed operating cycle

A closed operating cycle is defined as period of time between a start nin_iof the component an the next start ni+1n_{i+1}. The KPI closed operating cycles represents the number of cycles observed during the analysed time span used to determine the operating cycle KPIs (cycle times, duty times, switch-off times).

KPI Identifier

Description

Value Range

Unit

closed operating cycles

Count of closed operating cycles

0 to inf

count

Cycle times

Cycle time KPIs evaluate the cycle times of the closed cycles observed during the analysed time span. The mean, time-weighted average, minimum, and maximum cycle period are determined. In case there were no closed operating cycles observed during the analysed time span, none of the KPI variables are returned on API call.

KPI Identifier

Description

Value Range

Unit

cycle times.median

Median of cycle periods

0 to inf

h

cycle times.mean

Time-weighted average of cycle periods

0 to inf

h

cycle times.maximum

Longest cycle period

0 to inf

h

cycle times.minimum

Shortest cycle period

0 to inf

h

Duty times

Duty time KPIs evaluate the duty times of the closed cycles observed during the analysed time span. Duty time is defined as the time of component operation in a closed cycle. The mean, time-weighted average, minimum, and maximum duty period are determined. In case there were no closed operating cycles observed during the analysed time span, none of the KPI variables are returned on API call.

KPI Identifier

Description

Value Range

Unit

duty times.median

Median of duty periods

0 to inf

h

duty times.mean

Time-weighted average of duty periods

0 to inf

h

duty times.maximum

Longest duty period

0 to inf

h

duty times.minimum

Shortest duty period

0 to inf

h

Switch-off times

Switch-off time KPIs evaluate the shutdown times of the closed cycles observed during the analysed time span. Switch-off time is defined as the time of component shutdown in a closed cycle. The mean, time-weighted average, minimum, and maximum switch-off period are determined. In case there were no closed operating cycles observed during the analysed time span, none of the KPI variables are returned on API call.

KPI Identifier

Description

Value Range

Unit

switch-off times.median

Median of switch-off periods

0 to inf

h

switch-off times.mean

Time-weighted average of switch-off periods

0 to inf

h

switch-off times.maximum

Longest switch-off period

0 to inf

h

switch-off times.minimum

Shortest switch-off period

0 to inf

h

Components

boiler

Pin

Required

Mapping info

operating message

yes

Pin

Required

Mapping info

operating message

yes

fan

Pin

Required

Mapping info

operating message

yes

heat pump

Pin

Required

Mapping info

operating message

yes

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

Application

Recommended 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 measures temperatures or temperature setpoints of the system under consideration. Additionally the temperature spread of the system is determined. A reduced load mode offers the possibility of operational cost and energy reductions.

Summary
Example
Results
Components
Application
Summary

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

Example

This example shows the results of a Reduced Load Analysis performed on a heating circuit. Figure 1 shows the measured temperature. One can see a strong increase in temperature around 4 am and a reduction of temperature around 5 pm.

Figure 1: Measured temperature over a one day period

KPI

Value

Unit

reduced load operation

1

binary

temperature level shift

-9.31

°C

Results

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 of 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

0 = no reduced load identified

1 = reduced load identified

0 or 1

binary

Statistics of temperature level shift

KPI Identifier

Description

Value Range

Unit

temperature level shift

Difference between temperature levels during full load operation and reduced load operation

negative values = reduced temperature level for heating load reduction

positive values = raised temperature level for cooling load reduction

-inf to inf

°C

Timeserieses

KPI Identifier

Description

Value Range

Unit

reduced load operating message.timeseries

Timeseries of reduced operating mode

0 = no load reduction

1 = load reduction

0 or 1

binary

Components

boiler

Pin

Required

Mapping info

outlet temperature

no

Mapping of either outlet temperature or outlet temperature setpoint (preferred) is mandatory. If both pins are mapped, outlet temperature setpoint is used

outlet temperature setpoint

no

Mapping of either outlet temperature or outlet temperature setpoint (preferred) is mandatory. If both pins are mapped, outlet temperature setpoint is used

room

Pin

Required

Mapping info

temperature setpoint

no

Mapping of either temperature setpoint (preferred) or temperature is mandatory. If both pins are mapped, temperature setpoint is used

temperature

no

Mapping of either temperature setpoint (preferred) or temperature is mandatory. If both pins are mapped, temperature setpoint is used

Pin

Required

Mapping info

outlet temperature

no

Mapping of either outlet temperature or outlet temperature setpoint (preferred) is mandatory. If both pins are mapped, outlet temperature setpoint is used

outlet temperature setpoint

no

Mapping of either outlet temperature or outlet temperature setpoint (preferred) is mandatory. If both pins are mapped, outlet temperature setpoint is used

Application

Recommended 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 13776: 2007-09. In case of poor air quality, measures for improvement are recommended. Human performance is significantly influenced by air quality. In addition, the algorithms identifies calibration errors by physical plausibility checks.

Summary
Example
Results
Components
Application
Summary

Value

  • Higher occupant comfort, health and performance

Recommended for components

  • Rooms

  • Occupied indoor areas

Checked conditions

  • Indoor CO2 concentration evaluation based on DIN EN 13776: 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

Example

The setpoint deviation analysis was applied to a real test bench, a heating system at the E.ON Energy Research Center, RWTH Aachen University. Thus, a room component model was instanced and the respective datapoints mapped to this component.

Figure 1: CO2 concentration trajectory for an average office day

In this scenario, figure 1 shows the timeseries recorded for an exemplary period of 12 hours on a working day in August. The CO2 concentration in the air remained between what is considered "good" and "medium" for most of the day. However, for about 7 percent of the period, air quality was poor, with a maximum CO2 concentration of 1463 ppm, so that a complete evaluation on that day indicates poor air quality. The results provide an advanced set of KPIs that provide quantitative insights into the air quality of the rooms and support the human reasoning for analysis. A number of suggestions for possible countermeasures are given, and further investigation of the root cause of air quality problems is possible through the aedifion front-end data visualization.

Results

Signal colors

Signal color

Available

Info

red

Yes

CO2 concentrations critical for human health

yellow

Yes

CO2 concentrations reducing human comfort, decisiveness, and performance or wrongly calibrated CO2 sensors

green

Yes

CO2 concentrations sufficient for high comfort

Interpretations

Available

Info

Yes

Either the operational rule checks of the analysis were tested positive or not

Recommendations

Available

Info

Yes

Recommendations to improve fresh air supply, if necessary or 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 EU regulation 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 to the carbon dioxide concentrations over the analysed 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

Components

room

Pin

Required

Mapping info

co2

yes

operating message

no

Mapping of either presence (preferred) or operating message is strongly recommended. If both pins are mapped, pressence is used

Default: Always presence

presence

no

Mapping of either presence (preferred) or operating message is strongly recommended. If both pins are mapped, pressence is used

Default: Always presence

Application

Recommended Time Span

1 days 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 amount 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 allows to respect holidays and exceptional day schedules.

Summary
Example
Results
Components
Application
Summary

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

Example

This example shows a schedule analysis for a component "fan" connected to a supply fan operating message of a 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 anticipated schedule.

Figure 1: Operating times of component and reference schedule

The following KPIs show that a reduction of ~9% of the total operating time is possible. With the help of the plot we can also see, that the times were we can reduce the operating time are distributed over the workdays of the week.

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

Results

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

Either the operational rule checks of the analysis were tested positive or not

Recommendations

Available

Info

Yes

Recommendations to improve scheduled operation of the component. No recommendation, in case of sufficient measurement quality

KPIs

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 therefor 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

Components

boiler

Pin

Required

Mapping info

operating message

yes

Attribute

Required

Mapping info

custom_day_schedules

no

custom_holiday

no

preconditioning

no

regional_key

no

schedule

yes

schedule_timezone

no

Strongly recommended

Default: UTC

shutdown_flexibility

no

Pin

Required

Mapping info

operating message

yes

Attribute

Required

Mapping info

custom_day_schedules

no

custom_holiday

no

preconditioning

no

regional_key

no

schedule

yes

schedule_timezone

no

Strongly recommended

Default: UTC

shutdown_flexibility

no

fan

Pin

Required

Mapping info

operating message

yes

Attribute

Required

Mapping info

custom_day_schedules

no

custom_holiday

no

preconditioning

no

regional_key

no

schedule

yes

schedule_timezone

no

Strongly recommended

Default: UTC

shutdown_flexibility

no

heat pump

Pin

Required

Mapping info

operating message

yes

Attribute

Required

Mapping info

custom_day_schedules

no

custom_holiday

no

preconditioning

no

regional_key

no

schedule

yes

schedule_timezone

no

Strongly recommended

Default: UTC

shutdown_flexibility

no

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

custom_day_schedules

no

custom_holiday

no

preconditioning

no

regional_key

no

schedule

yes

schedule_timezone

no

Strongly recommended

Default: UTC

shutdown_flexibility

no

room

Pin

Required

Mapping info

operating message

yes

Attribute

Required

Mapping info

custom_day_schedules

no

custom_holiday

no

preconditioning

no

regional_key

no

schedule

yes

schedule_timezone

no

Strongly recommended

Default: UTC

shutdown_flexibility

no

Application

Recommended 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

Setpoint Deviation Analysis

The Setpoint Deviation Analysis identifies insufficient setpoint attainment by comparing the actual value of a controlled system to its setpoint value. Insufficient setpoint attainment is a symptom which can be traced back to plenty of different causes. E.g., insufficient supply of a controlled system with the required temperature level, suboptimal controller software and parameters, or a blocked valve. The Setpoint Deviation Analysis supports narrowing down the root cause of insufficient setpoint attainment and is specially recommended in complex energy systems.

Summary
Example
Results
Components
Application
Summary

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

  • Process value value overshooting its setpoint, evaluated component specific

  • Process value value undershooting its setpoint, evaluated component specific

  • Process value value sufficiently achieving its setpoint, evaluated component specific

  • Condition checks on times of components operation

Example

The setpoint deviation analysis was applied to a real test bench, a heating system at the E.ON Energy Research Center, RWTH Aachen University. Thus, a thermal control loop component model was instanced and the respective datapoints mapped to this component.

Figure 1: Example of a process value (actual value) undershooting its setpoint

In this scenario, figure 1 shows the time series recorded for an exemplary period of 36 hours on a November workday. The temperature setpoint and the actual measured value started to drift apart around 12 am on the 19th. Since then, the control loop did not comply with the setpoint temperatures although the control loop was operating.

The automated interpretation confirms our visual analysis of the time series shown in the figure, summed up by the qualitative warning level "red". The recommendations provide further instruction on how to isolate and fix the cause for the inadequate setpoint compliance. Further, the result offers an advanced set of KPIs, providing additional insights into the control loop behaviour. They support human reasoning for a case-by-case analysis.

For example, the drop in temperatures is peculiar and could point to a technical defect or malfunction, such as a blocked valve. Another cause might be a sudden drop in the temperatures supplied to the distribution system, such as an heat-pump or boiler issue. Further investigation of the root cause is possible via data visualization on the aedifion front-end.

Results

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

Either the operational rule checks of the analysis were tested positive or not

Recommendations

Available

Info

Yes

Recommendations on how to investigate the root cause of a setpoint deviation. No recommendation, if setpoint compliance is sufficient

KPIs

Incidence of setpoint deviation

Duration of the setpoint deviations, bundled by threshold value ranges.

KPI Identifier

Description

Value Range

Unit

setpoint deviation.lower threshold

Component specific lower threshold for evaluation of the extent of the setpoint deviation

0 to inf

unit of setpoint

setpoint deviation.upper threshold

Component specific upper threshold for evaluation of the extent of the setpoint deviation

0 to inf

unit of setpoint

setpoint deviation.above lower threshold and below upper threshold

Duration with absolute value of setpoint deviation between lower and upper threshold

0 to inf

h

setpoint deviation.above lower threshold and below upper threshold.relative

Duration with absolute value of setpoint deviation between lower and upper threshold relative to total time of analysis

0 to 100

%

setpoint deviation.above upper threshold

Duration with absolute value of setpoint higher than upper threshold

0 to inf

h

setpoint deviation.above upper threshold.relative

Duration with absolute value of setpoint higher than upper threshold relative to total time of analysis

0 to 100

%

setpoint deviation.below lower threshold

Duration with absolute value of setpoint smaller than lower threshold

0 to inf

h

setpoint deviation.below lower threshold.relative

Duration with absolute value of setpoint smaller than lower threshold relative to total time of analysis

0 to 100

%

Operating time

Operating time KPIs provide information on the total time of operation of the analysed component during the analysed 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

%

Statistics of setpoint deviation

General information KPIs to give further insight into the setpoint compliance over the analysed time frame.

KPI Identifier

Description

Value Range

Unit

setpoint deviation.maximum

Largest setpoint deviation

-inf to inf

unit of setpoint

setpoint deviation.mean

Average setpoint deviation

-inf to inf

unit of setpoint

setpoint deviation.median

Median setpoint deviation

-inf to inf

unit of setpoint

Components

boiler

Pin

Required

Mapping info

operating message

no

Mapping strongly recommended

Default: Always operating

outlet temperature

yes

outlet temperature setpoint

yes

Pin

Required

Mapping info

operating message

no

Mapping strongly recommended

Default: Always operating

outlet temperature

yes

outlet temperature setpoint

yes

heat pump

Pin

Required

Mapping info

condenser outlet temperature

no

Required, if condenser shall be analysed

condenser outlet temperature setpoint

no

Required, if condenser shall be analysed

evaporator outlet temperature

no

Required, if evaporator shall be analysed

evaporator outlet temperature setpoint

no

Required, if evaporator shall be analysed

operating message

no

Mapping strongly recommended

Default: Always operating

room

Pin

Required

Mapping info

operating message

no

Mapping strongly recommended

Default: Always operating

temperature

yes

temperature setpoint

yes

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

Application

Recommended 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

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.

Summary
Example
Results
Components
Application
Summary

Value

  • Reduce energy cost

  • Increase lifespan of pumps in heating and cooling circuits

Recommended for components

Any liquid media supply system, such as

  • thermal control loop with 2-way valve and pump

Checked conditions

  • Pump is shutdown, if two-way valve is closed

  • Pump is still operation although the two-way valve is closed

  • Condition checks on times of components operation

Example

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

%

Results

Signal colors

Signal color

Available

Info

red

Yes

Significant pump operation times although two-way valve was closed 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

Either the operational rule checks of the analysis were tested positive or not

Recommendations

Available

Info

Yes

Recommendations to improve synchronized operation of components. No recommendation, in case of sufficient measurement quality

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

Components

Apply only for 2-way valve systems

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

pump 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

valve position

no

Mapping of either valve position (preferred) or valve position setpoint is mandatory. If both pins are mapped, 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, valve position is used

Application

Recommended 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 systems operation. While a small temperature spread indicates the potential for volume flow and therefor pump power consumption reduction, a huge spread indicates thermal under supply of the downstream systems and consumers.

Summary
Example
Results
Components
Application
Summary

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 too high volume flows, evaluated component specific

  • Temperature spread is too large and risk sufficient energy supply, evaluated component specific

  • Temperature spread is as expected, evaluated component specific

  • Condition checks on times of components operation

Example

The temperature spread analysis was applied to a heating circuit instanciated as a thermal control loop.

Figure 1: Outlet temperature and return temperature of the thermal control loop

A analysis for one week in the beginning of September 2018 is shown in figure 1. A small temperature spread is detected through the KPI "temperature spread.average" of 1.56 K.

KPI

Value

Unit

temperature spread.average

1.56

Kelvin

temperature spread.minimum

-0.716

Kelvin

temperature spread.maximum

22.8

Kelvin

Results

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

Either the operational rule checks of the analysis were tested positive or not

Recommendations

Available

Info

Yes

Recommendations on how to adjust volume flows for a 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. E.g.:

temperature spread.minimum will be evaporator temperature spread.minimum

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

Components

boiler

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

heat pump

Pin

Required

Mapping info

condenser inlet temperature

no

Required, if condenser shall be analysed

condenser outlet temperature

no

Required, if condenser shall be analysed

evaporator inlet temperature

no

Required, if evaporator shall be analysed

evaporator outlet temperature

no

Required, if evaporator shall be analysed

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 strongly recommended. 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, pump operating message is used

Default: Always on

inlet temperature recirculation

yes

Application

Recommended 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

Virtual Heat Meter

The Virtual Heat Meter determines the heat flux and energy delivered in heating/cooling piping networks such as thermal control loops or energy conversion plants. The determination is based on the temperature difference and volume flow over measurement point. It substitutes physical heat meters and enables energy flux tracing.

Summary
Example
Results
Components
Application
Summary

Value

Quantifies heat fluxes and heat for

  • Trace energy fluxes

  • Enable other analytics functions

  • Enables comparison to hardware heat meters

Recommended for components

Heat and cold conversion or distribution systems, such as

  • Thermal control loops

  • Heat pumps

  • Boilers

  • Heat meters

Checked conditions

  • Determines heat flux from temperature difference and volume flow for several components

  • Condition checks on times of components operation

Example

The Virtual Heat Meter was tested in the field, on a boilder at the E.ON Energy Research Center, RWTH Aachen University. Thus, a boiler was instanced and the respective datapoints pinned to it. Figure 1 shows the inlet- and outlet timeseries recorded for an exemplary period, along with the heat flow calculated. The volume flow during the observed period was constant.

Figure 1: Heat flow determined by the virtual heat meter
Results

Signal colors

Signal color

Available

Info

red

No

yellow

No

green

Yes

Heat flux is determined

Interpretations

Available

Info

No

This analysis function provides only KPIs and timeserieses

Recommendations

Available

Info

No

This analysis function provides only KPIs and timeserieses

KPIs

Statistics of heat flux

Providing insights into value range of the heat flux.

Negative values indicate cooling, while positive indicate heating.

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 flux.maximum will be evaporator heat flux.maximum

KPI Identifier

Description

Value Range

Unit

heat flux.maximum

Largest heat flux

-inf to inf

kW

heat flux.minimum

Smallest heat flux

-inf to inf

kW

heat flux.mean

Average heat flux

-inf to inf

kW

heat flux.median

Median heat flux

-inf to inf

kW

heat

Aggregated heat transferred

-inf to inf

kWh

Timeserieses

KPI Identifier

Description

Value Range

Unit

heat flux.timeseries

Timeseries of transferred heat

-inf to inf

kW

heat flux.cumulated

Timeseries of cumulated transferred heat

-inf to inf

kWh

Components

boiler

Pin

Required

Mapping info

inlet temperature

yes

outlet temperature

yes

operating message

no

Mapping strongly recommended

Default: Always operating

volume flow

yes

Attribute

Required

Mapping info

volume_flow_unit

no

Default: l/s

Pin

Required

Mapping info

inlet temperature

yes

outlet temperature

yes

operating message

no

Mapping strongly recommended

Default: Always operating

volume flow

yes

Attribute

Required

Mapping info

volume_flow_unit

no

Default: l/s

Pin

Required

Mapping info

inlet temperature

yes

outlet temperature

yes

volume flow

yes

Attribute

Required

Mapping info

volume_flow_unit

no

Default: l/s

heat pump

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 analysed

condenser outlet temperature

no

Required, if condenser shall be analysed

condenser volume flow

no

Required, if condenser shall be analysed

evaporator inlet temperature

no

Required, if evaporator shall be analysed

evaporator outlet temperature

no

Required, if evaporator shall be analysed

evaporator volume flow

no

Required, if evaporator shall be analysed

operating message

no

Mapping strongly recommended

Default: Always operating

Attribute

Required

Mapping info

volume_flow_unit

no

Default: l/s

Attributes

volume_flow_unit:

The unit used in this datapoint needs to be specified in order for the analysis to yield correct result. If unspecified, the default unit assumed for this measurement is litersPerSecond. Acceptable inputs for this attribute include:

  • cubicMetersPerSecond

  • cubicMetersPerMinute

  • cubicMetersPerHour