Two-Layer Optimization Model for the Siting and Sizing of Energy Storage Systems in Distribution Networks

• Main Authors: Tao Sun, Linjun Zeng, Feng Zheng, Ping Zhang, Xinyao Xiang, Yiqiang Chen
• Format: Article
• Language: English
• Published: MDPI AG 2020-05-01
• Series: Processes
• Subjects: optimal sizing and siting; energy storage system; multi-objective optimization; fuzzy entropy weight; vague set
• Online Access: https://www.mdpi.com/2227-9717/8/5/559

One of the most important issues that must be taken into consideration during the planning of energy storage systems (ESSs) is improving distribution network economy, reliability, and stability. This paper presents a two-layer optimization model to determine the optimal siting and sizing of ESSs in the distribution network and their best compromise between the real power loss, voltage stability margin, and the application cost of ESSs. Thereinto, an improved bat algorithm based on non-dominated sorting (NSIBA), as an outer layer optimization model, is employed to obtain the Pareto optimal solution set to offer a group of feasible plans for an internal optimization model. According to these feasible plans, the method of fuzzy entropy weight of vague set, as an internal optimization model, is applied to obtain the synthetic priority of Pareto solutions for planning the optimal siting and sizing of ESSs. By this means, the adopted fuzzy entropy weight method is used to obtain the objective function’s weights and vague set method to choose the solution of planning ESSs’ optimal siting and sizing. The proposed method is tested on a real 26-bus distribution system, and the results prove that the proposed method exhibits higher capability and efficiency in finding optimum solutions.