• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

ELECTRIC POWER CONSTRUCTION ›› 2015, Vol. 36 ›› Issue (7): 114-119.doi: 10.3969/j.issn.1000-7229.2015.07.016

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Hierarchical Decentralized Optimal Charging Algorithm for Electric Vehicles Aggregation

LI Zhengshuo, GUO Qinglai, SUN Hongbin, XIN Shujun   

  1. State Key Lab of Control and Simulation of Power Systems and Generation Equipments, Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
  • Online:2015-07-01
  • Supported by:

    Project Supported by National Basic Research Program of China (973 Program)(2013CB228202), the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(51321005)and the National Natural Science Foundation of China(51361135703).

Abstract:

Electric vehicles (EVs) are very likely to be dispatched by the power grid in the form of aggregation in the future, e.g., the EVs in a large charging station being regarded and dispatched as one aggregation. After receiving the dispatch order from the power grid, an aggregator of EV aggregation should optimize each EV’s charging power to realize the dispatch order with regard to the aggregation, which is defined as a tracking problem. The tracking problem is a large-scale optimization problem which is hard to solve in a centralized manner. A hierarchical decentralized optimal algorithm was proposed to solve that problem. In the proposed algorithm, the aggregator sent coordination messages to EVs, while each EV solved a local small-scale optimization problem in a distributed manner and returned messages to the aggregator until the iteration process finished. To further enhance the computational efficiency, the sub-problem regarding the aggregator and each EV was deeply studied and its algorithm was improved. The numerical experiment results show that the proposed method has fast calculation speed, and is especially suitable for the large-scale tracking problem inside an EV aggregator.

Key words: electric vehicle, decentralized optimization, aggregation aggregator, tracking problem

CLC Number: