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27150 Robust peak-shaving for a neighborhood with electric vehicles
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Gerards, M.E.T. and Hurink, J.L. (2016) Robust peak-shaving for a neighborhood with electric vehicles. Energies, 9 (8). 594. ISSN 1996-1073 *** ISI Impact 2,077 ***

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Demand Side Management (DSM) is a popular approach for grid-aware peak-shaving. The most commonly used DSM methods either have no look ahead feature and risk deploying flexibility too early, or they plan ahead using predictions, which are in general not very reliable. To counter this, a DSM approach is presented that does not rely on detailed power predictions, but only uses a few easy to predict characteristics. By using these characteristics alone, near optimal results can be achieved for electric vehicle (EV) charging, and a bound on the maximal relative deviation is given. This result is extended to an algorithm that controls a group of EVs such that a transformer peak is avoided, while simultaneously keeping the individual house profiles as flat as possible to avoid cable overloading and for improved power quality. This approach is evaluated using different data sets to compare the results with the state-of-the-art research. The evaluation shows that the presented approach is capable of peak-shaving at the transformer level, while keeping the voltages well within legal bounds, keeping the cable load low and obtaining low losses. Further advantages of the methodology are a low communication overhead, low computational requirements and ease of implementation.

Item Type:Article
Research Group:EWI-CAES: Computer Architecture for Embedded Systems, EWI-DMMP: Discrete Mathematics and Mathematical Programming
Research Program:CTIT-General
Research Project:DREAM: Dynamic Real-time Control Of Energy Streams In Buildings, E-BALANCE: Balancing energy production and consumption in energy efficient smart neighbourhoods
Uncontrolled Keywords:Adaptive scheduling, Demand side management, Electric vehicles, Optimal scheduling, Smart grids
ID Code:27150
Deposited On:17 August 2016
ISI Impact Factor:2,077
More Information:statistics

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