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/10.1088/1742-6596/1754/1/012035Additional details
Identifiers
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