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An Operation Model for Distribution Companies Using the Flexibility of Electric Vehicle Aggregators

handle: 10397/93386
An operation model for distribution companies (DISCOs) is proposed to reduce their operation costs by fully utilizing the flexibility of electric vehicle aggregators (EVAs). In the proposed model, linear decision rules approximation is adopted to achieve mathematical tractability, and distributionally robust optimization is applied to evaluate costs affected by uncertainties in renewable power outputs and EVA charging demands. Case studies are conducted under various settings. With the proposed model, using EVAs to mitigate uncertainties is achieved and is further classified into delaying uncertainties and eliminating uncertainties. As a result, average penalties for DISCO’s deviations from its planned energy portfolio are reduced. Besides, EVA charging demands are shifted to hours with lower energy prices to reduce energy costs of DISCO. Using EVAs to mitigate uncertainties and shifting EVA charging demands are properly coordinated under the proposed model. Moreover, power losses in EVA charging and discharging are utilized to reduce the scale of uncertainties, which decreases average penalties for energy deviations of DISCO.
- Hong Kong Polytechnic University China (People's Republic of)
- Hong Kong Polytechnic University (香港理工大學) Hong Kong
- Illinois Institute of Technology United States
- Hong Kong Polytechnic University (香港理工大學) China (People's Republic of)
- Illinois Institute of Technology United States
Renewable energy, 330, Uncertainty, 004, Electric vehicle aggregator, Distributionally robust optimization, Distribution company
Renewable energy, 330, Uncertainty, 004, Electric vehicle aggregator, Distributionally robust optimization, Distribution company
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