Considering the complex spatio-temporal distribution characteristics of the distribution network net load
a multi-objective energy storage system optimal configuration model for the energy storage system is proposed. Firstly
based on the spatiotemporal stochastic distribution characteristics of net load
a spatio-temporal prediction model for uncoordinated electric vehicle charging load is constructed. Secondly
an optimization model for energy storage configuration is established
considering key factors such as the daily comprehensive cost of energy storage systems
the net load fluctuation rate
and network losses. The model is solved by integrating a multiobjective whale optimization algorithm with the Gurobi solver. A case analysis is conducted on an improved IEEE33-node distribution network. The results indicate that by incorporating the spatiotemporal characteristics of distribution network net loads into the energy storage optimization configuration
the fluctuations of net loads can be significantly smoothed
verifying the feasibility and effectiveness of the proposed configuration model.
LATA P, VADHERA S.Reliability improvement of radial distribution system by optimal placement and sizing of energy storage system using TLBO[J]. Journal of energy storage, 2020, 30: 101492.
MIRJALILI S, LEWIS A.The whale optimization algorithm[J]. Advances in engineering software, 2016, 95: 51-67.
JANGIR P, JANGIR N.Non-dominated sorting whale optimization algorithm (NSWOA): a multi-objective optimization algorithm for solving engineering design problems[J]. Global journal of research in engineering. 2017.