Hierarchical optimization scheduling for electric vehicles with PV-power storage charging stations

doi:10.3969/j.issn.2097-0706.2023.09.002

Abstract

Abstract:

Since electric vehicles are environmentally friendly and rechargeable， they can be taken as batteries under certain circumstances and participate in the operation of microgrids. As a result，PV-power storage integrated systems are important for the development of Energy Internet. But EV loads are highly volatile. The random EV loads with the attributes varying with time will impact the stable operation of microgrids. To address the dimension disaster and low effectiveness of the problem solving that accrues when large-scale EVs are connected to the power grid， a hierarchical optimization scheduling strategy is proposed. Based on the models for different units in the microgrid and different constraints， the dynamic electricity price model for EVs is established. To achieve the lowest operation cost of the microgrid， the highest profit from discharging and charging EVs and the minimal network loss， the optimization scheduling strategy for electric vehicles with PV-power storage charging stations is put forward， and the optimization objects on different layers are solved by adaptive particle swarm optimization. Finally， the simulation results show that the availability of electric vehicles contributes to peak load regulation， and the strategy can accommodate vehicle owners' needs while significantly lowering the operation cost of microgrid and charging cost of EVs.

Key words: electric vehicle, energy storage, microgrid, dynamic electricity price model, PV-power storage charging station, optimize scheduling, peak load regulation, Energy Internet

CLC Number:

TK019：TM72

HU Chao, PENG Wenhe, FANG Zhijian. Hierarchical optimization scheduling for electric vehicles with PV-power storage charging stations[J]. Integrated Intelligent Energy, 2023, 45(9): 11-17.

Figures/Tables 12

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Table 1

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成本	EV有序充放电	EV无序充电
EV充放电成本	55.884 2	724.650 3
微网优化成本	2 982.7	4 404.5