Energy Comparison Value
The Energy Comparison Value ( ECV ) is a quantity with which an energy loss reduction can be demonstrated with high accuracy by comparing load intervals. The ECV is based on the principle of comparing the energy of small successive load intervals in combination with a controllable or bridgeable system. The process requires a device with which efficiency-increasing systems or system parts can be bridged by means of a bypass switch.
Individual consumers, production systems or even entire buildings can be recorded.
definition
The ECV is based on the direct comparison of successive intervals in which the energy consumption is determined with and without the influence of the energy efficiency-increasing system components. The system can be completely isolated or, as shown in the graphic, only bridged.
The method corresponds to the principle of energy comparisons, as can be found in the ISO17741 standard and also in other publications on energy efficiency determinations (see list of literature). The main difference is that the option of a switching device (bypass switch) enables the effect to be switched on and off in a coordinated manner over short periods of time. In this way, on the one hand, the principle of baselining and reporting is retained and, on the other hand, long-term effects e.g. B. eliminated by seasonal influences.
Modeling the measurement process
The measurement method compares the mean energies of two time interval series (measurement series) with a simultaneously assumed conservation tendency. In the ECV measurement method, it is assumed that the maintenance tendency of a series of measurements is large with short interval durations and that it becomes correspondingly smaller and decreases with increasing interval durations. Here it is initially assumed for the modeling that the energy density is even identical in two consecutive intervals. The interval duration for determining the ECV is only a few minutes (typically << 60 min.) And is usually defined with an interval duration of five minutes; variations of this are basically possible. Each interval contains a number of power measured values or a corresponding energy value, which corresponds to a 5-minute interval with constant average power. Through the successive measurement intervals and their comparison based on the energy density E ( https://de.wikipedia.org/wiki/Energiedichte ), which are derived from the recorded performance measurement data for each interval
result, two time series Ea and Eb result, which are identical according to the assumption - this applies if the interval duration is chosen to be sufficiently long or correspondingly short. It therefore applies to stationary operation, without bypass switching operations, for the interval energies and thus also . Furthermore, an energy efficiency device is to be switched on for the duration of the second interval . This changes the energy density of the series , one obtains . This applies to
and ,
where is a factor that directly indicates energy savings or increased consumption. There is an energy saving with , with the system is neutral and with an additional consumption is displayed.
Calculation of the ECV
The ECV shows the additional consumption before the implementation of energy efficiency measures. He uses this as a basis for calculating the ECV value. It is therefore inversely defined as the percentage additional consumption:
in percent [%] or also in percent [%].
The comparison base value for the ECV is the defined energy consumption after the energy efficiency measure has taken place.
development
The ECV was developed by Livarsa GmbH , which has also secured the trademark rights to the abbreviation and name. Together with the bypass switching principle, energy efficiency devices that are centralized or installed at network nodes can be examined using measurements and their effects can be determined. In general, the reliable detection and quantification of low energy savings in systems installed centrally or at a network node is usually a metrological challenge. The fluctuations and inaccuracies in the course of energy consumption are often above the range of savings of a central energy efficiency facility. In contrast to clearly defined energy efficiency measures, such as replacing incandescent lamps with LED lighting, in which the savings can be determined through type-related lower consumption, this is usually not possible with central systems. In addition, the expected savings are in the lower single-digit percentage range.
Properties and example
After defining and modeling the measurement method , two time series are created from the load profiles. In the case of an inactive energy efficiency device, two time series with identical average power (physics) or identical energy consumption result . If you draw the energy densities of the individual intervals in a coordinate system in such a way that each point in the diagram shows the energy density , a point cloud is created from the value pairs around the straight line through the origin with a gradient of one.
The illustration of the point cloud shows an example of a series of measured values consisting of 25,599 value pairs at 5-minute intervals and from a 12-month measurement record from a manufacturing company. The value pairs of the point cloud show that the energy densities of successive intervals are not identical and therefore require closer examination. This can be carried out by means of a regression analysis or linear regression in order to determine the slope of the model line and to be able to compare it with the expected slope of one. In the example of the 12-month recording there is a slope of with a coefficient of determination of . If the slope of the regression line deviates from one and runs through the origin, the energy densities of the intervals b have a mean deviation compared to the energy densities of the intervals a. This shows the difference in the average energy consumption between active and inactive energy efficiency devices.
The figures show a real 12-hour measurement with 5-minute intervals a) load curve of the intervals b) regression analysis. As can be seen in the example of the real 12-hour measurement, the regression line has a lower slope, this reaches a value of and thus indicates an energy consumption that has been reduced by around 4.2%. This results in an ECV of 4.4%, the coefficient of determination is here
credentials
- ↑ Measurement procedure to prove the increase in energy efficiency in a central energy efficiency facility! LIVERSA, 2020, accessed July 8, 2020 .
- ↑ PH Profos: Basics of measurement technology : with 46 tables, pg. 56, ISBN 3-486-24148-6
See also
- Efficiency : only considers the ratio of energy yield (output) to supplied energy (input) and is not considered in this type of analysis.
- Energy efficiency
- Directive 2006/32 / EC on energy end-use efficiency and energy services
- Linear regression
literature
- O. Akinsooto, D. de Canha, and JHC Pretorius: Energy savings reporting and uncertainty in measurement amp; veri fi cation . In 2014 Australasian Universities Power Engineering Conference (AUPEC), 2014, p. 1-5 .
- ASHRAE: ASHRAE Guideline 14: Measurement of Energy and Demand Savings . American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc., ASHRAE Customer Service, 1791 Tullie Circle, NE, Atlanta, GA 30329-2305, 2002.
- Standard ISO 17741: 2016 General technical rules for measurement, calculation and verification of energy savings of projects (ISO 17741: 2016)
- J. Jiricka and D. Mezera: Electric power savers - operating measurements of practical installations . In 2015 16th International Scienti fi c Conference on Electric Power Engineering (EPE), May 2015, p. 331-334 .
- JK Kissock and C. Eger: Measuring industrial energy savings . Applied Energy, 85 (5), 2008, ISSN 0306-2619 , pp. 347-361 ( sciencedirect.com ).
- PH Profos: Basics of measurement technology: with 46 tables . 5th, revised. Edition. Oldenbourg, Munich, Vienna, 1997, ISBN 3-486-24148-6 .