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Keywords

energy storage configuration; multi‑park liaison; energy consumption; multi‑objective optimization.

Abstract

Reasonable distributed energy storage configuration plays a crucial role in the energy consumption process of the park. How to consider the connection between multiple parks and the constraints between economic costs and energy consumption benefits is a difficult problem to solve when configuring energy storage batteries. In addition, modern distribution networks are mostly closed‑loop and open‑loop operation, and the dynamic connection between multiple parks is also an important technical means to promote energy consumption. This paper proposes a multi‑park energy storage multi‑objective optimal configuration model considering network reconfiguration. First of all, the model mathematically represents the constraint relationship between configuration economy and energy consumption benefit, considers various investment and operation constraints, and introduces virtual power to represent the connection state between various parks; The model improves the energy consumption level from the system level through the dynamic reconstruction of the network. Secondly, based on the second‑order cone relaxation and polyhedral linearization method, the original mixed‑integer nonlinear non‑convex model, which is difficult to solve directly, is transformed into a mixed‑integer linear programming model. Finally, the proposed method is applied to the improved IEEE 33 bus system to construct a multi‑objective Pareto curve. The results show that the dynamic connection between multiple parks is helpful to improve each other's energy consumption level, and the proposed method can provide the optimal solution of multi‑objective energy storage configuration for engineering practice.

DOI

10.19781/j.issn.1673-9140.2023.03.006

First Page

54

Last Page

64

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