# 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

• 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 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.

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

# ​thermal control loop​

 Pin Required Mapping info operating message no Strongly recommendedDefault: Always on outlet temperature yes The outlet temperature is the process value of a thermal control loop
Application

# 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.

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 $n_i$of the component an the next start $n_{i+1}$. 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 ​

# ​combined heat and power​

 Pin Required Mapping info operating message yes ​

# ​fan​

 Pin Required Mapping info operating message yes ​

## ​heat pump​

 Pin Required Mapping info operating message yes ​

## ​thermal control loop​

 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 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

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.

 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 detected0 = no reduced load identified1 = 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 operationnegative values = reduced temperature level for heating load reductionpositive 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 mode0 = no load reduction1 = 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

# ​thermal control loop​

 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 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.

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 usedDefault: Always presence presence no Mapping of either presence (preferred) or operating message is strongly recommended. If both pins are mapped, pressence is usedDefault: 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.

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 recommendedDefault: UTC shutdown_flexibility no ​

# ​combined heat and power​

 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 recommendedDefault: 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 recommendedDefault: 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 recommendedDefault: UTC shutdown_flexibility no ​

# ​thermal control loop​

 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 recommendedDefault: 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 recommendedDefault: UTC shutdown_flexibility no ​
Application

# 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.

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 recommendedDefault: Always operating outlet temperature yes ​ outlet temperature setpoint yes ​

# ​combined heat and power​

 Pin Required Mapping info operating message no Mapping strongly recommendedDefault: 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 recommendedDefault: Always operating

# ​room​

 Pin Required Mapping info operating message no Mapping strongly recommendedDefault: Always operating temperature yes ​ temperature setpoint yes ​

# ​thermal control loop​

 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 usedDefault: 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 usedDefault: Always operating
Application

# 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.

 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

# ​thermal control loop​

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 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

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.

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.

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.:

 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 recommendedDefault: Always on outlet temperature yes ​

# ​combined heat and power​

 Pin Required Mapping info inlet temperature yes ​ operating message no Strongly recommendedDefault: 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 recommendedDefault: Always operating

# ​thermal control loop​

 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 usedDefault: 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 usedDefault: Always on inlet temperature recirculation yes ​
Application

# 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.

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 recommendedDefault: Always operating volume flow yes ​
 Attribute Required Mapping info volume_flow_unit no Default: l/s

# ​combined heat and power​

 Pin Required Mapping info inlet temperature yes ​ outlet temperature yes ​ operating message no Mapping strongly recommendedDefault: Always operating volume flow yes ​
 Attribute Required Mapping info volume_flow_unit no Default: l/s

# ​heat meter​

 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 recommendedDefault: 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