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Published February 1, 2021 | Version v1
Journal article

Optimal Operation Strategy of Energy Storage System in PV-integrated EV Charging Station Based on improved NSGA-II

  • 1. Electric Power Research Institute, State Grid Shanghai Municipal Electric Power Company, Shanghai, 200437 (China)
  • 2. Shanghai University of Electric Power, Shanghai, 200090 (China)
  • 3. EPTC(BEIJING) Electric Power Research Institute, Beijing, 100000 (China)

Description

In order to realize the economic operation of PV-integrated EV charging station and reduce the additional construction and transformation brought by the charging station to the power grid, an optimal operation strategy of energy storage system in PV-integrated EV charging station based on the improved NSGA-II is proposed. Firstly, with the power of the energy storage system and the capacity of the transformer as constraints, the optimization operation model of energy storage is built with the minimum variance of side loads of the power grid and the minimum purchase cost from the power grid as objective functions. Then, aiming at the low efficiency of the traditional NSGA-II gene recombination operator, the improved NSGA-II based on the adaptive recombination operator is proposed to solve the model, and the optimal operation strategy is obtained from the final Pareto solution set by using fuzzy clustering method. Finally, the effectiveness of the proposed algorithm is verified by example simulation, indicating that the improved NSGA-II can further improve the operation economy of charging stations and the load level of the power grid. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/1742-6596/1754/1/012035

Additional details

Publishing Information

Journal Title
Journal of Physics. Conference Series (Online)
Journal Volume
1754
Journal Issue
1
Journal Page Range
[10 p.]
ISSN
1742-6596

Conference

Title
3. International Symposium on Power Electronics and Control Engineering
Acronym
ISPECE 2020
Dates
27-29 Nov 2020
Place
Chongqing (China)

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
54032821
Subject category
S25: ENERGY STORAGE; S42: ENGINEERING;
Resource subtype / Literary indicator
Conference
Descriptors DEI
ALGORITHMS; COMPUTERIZED SIMULATION; ENERGY STORAGE; ENERGY STORAGE SYSTEMS; FUZZY LOGIC; GENE RECOMBINATION; OPERATION; OPTIMIZATION; RECOMBINATION
Descriptors DEC
ENERGY SYSTEMS; MATHEMATICAL LOGIC; SIMULATION; STORAGE