Assessment of Conservation Voltage Reduction in Distribution Networks with Voltage Regulating Distribution Transformers

• Published in: Energies (Basel) Vol. 16; no. 7; p. 3155
• Main Authors: Igiligi, Anthony, Vielhauer, Armin, Ehrenwirth, Mathias, Hurm, Christian, Summ, Thorsten, Trinkl, Christoph, Navarro Gevers, Daniel
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.04.2023
• Subjects: Alternative energy sources; Analysis; Automation; conservation voltage reduction; Consumers; Electric transformers; Electricity; Energy consumption; Infrastructure; Load; peak power; Performance management; Power supply; Supply and demand; tap change; voltage regulating distribution transformers; United States; Germany
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en16073155

The application of voltage reduction in medium and low voltage grids to reduce peak power demand or energy consumption has been implemented since the 1980s using several approaches. Conservation Voltage Reduction (CVR), as one such approach, uses a voltage control device to reduce or increase the voltage setpoint on a busbar, thereby reducing or increasing the amount of active and reactive power supply in the network. Voltage regulation for CVR is always implemented according to established network planning standards in each country. Research in this field has proven that a CVR factor (CVRf) of 0.7–1.5 for peak demand reduction can be achieved. This is an evaluation metric of CVR. The aim of this research is to determine and validate CVRf for peak demand reduction by comparing actual results obtained during regular tap changes with other randomly distributed periods outside tap change operations, using a set of measurement data. It is important to understand CVR deployment capability by evaluating CVR potentials from historical random tap operations before a robust network-wide deployment is introduced. This research provides such guidance. It also provides a novel approach to determining tap changes from voltage measurements using a time-based algorithm. A CVRf ranging from 0.95 to 1.61 was estimated using a measurement dataset from a test field. The result of the entire evaluation shows that the CVRf are smaller during peak PV production and greater during peak demand periods. Further evaluation using statistical hypotheses testing and a control chart was used to validate the evaluation.