4.6 Article

Optimal scheduling of an EV aggregator for demand response considering triple level benefits of three-parties

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.ijepes.2020.106447

关键词

Aggregator; Demand response; Electric vehicle; Users' satisfaction; Load shifting; Vehicle to Vehicle

资金

  1. National Key R&D Program of China [2018YFE0122200]
  2. Major Science and Technology Achievements Conversion Project of Hebei Province of China [19012112Z]
  3. Science and Technology Project of State Grid Corporation of China (SGCC) [NY7116021, kjgw2018-014]
  4. Fundamental Research Funds for the Central Universities of China [2018QN077]
  5. FEDER funds through COMPETE 2020
  6. FCT [POCI-01-0145-FEDER-029803 (02/SAICT/2017)]
  7. FLEXIMAR-project (Novel marketplace for energy flexibility) from Business Finland Smart Energy Program, 2017-2021

向作者/读者索取更多资源

The electric vehicle, when managed by an aggregator, is a suitable candidate for participating in demand response in power system operation. An optimal scheduling algorithm is necessary to maximize the aggregator's benefit, considering the benefits of distribution system, aggregator, and EV users. This study defines the benefits of the three parties and tests the optimal scheduling system to analyze the impact of aggregator facilities, technology, and operation mode on the benefits.
The electric vehicle (EV), when aggregated by an agent (Aggregator), is a suitable candidate for participating in demand response in power system operation. As the interface between distribution network and EV users, as well as an independent party at the same time, an optimal scheduling algorithm is necessary with consideration of benefits of three parties, which in return will affect aggregators' sustainable development. The benefits of distribution system from demand response, aggregator and EV users are defined in this paper. EV users' benefit is described by their satisfaction on SOCs reached after a given period of time and overall costs/revenues for charging/discharging and policy award/penalty, while the benefit of distribution network for the integration of large amount EV loads through aggregator is evaluated by aggregator's load shifting capability through a pricebased demand response (DR) program under real time electricity price. The optimal scheduling of the aggregator is with an objective of maximizing its own benefit under constraints of EV users' minimum satisfaction and minimum load-shifting capability required by distribution network. The optimization scheduling is tested by a test system, and further analysis is given on the effect of aggregator's facility level and technology (Vehicle to Vehicle) and the operation mode of aggregator group on the benefits of three parties.

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