Analysis of energy storage capacity optimization of distribution network based on quadratic planning algorithm under large scale DG access

Author:

Song Xinfu1,Li Changling1,Yi Geng1,Zhong Rui1,Wang Wei2

Affiliation:

1. 1 Economic Research Institute, State Grid Xinjiang Electric Power Company , Urumqi , Xinjiang , , China .

2. 2 College of Intelligent Equipment , Shandong University of Science and Technology , Tai’an , Shandong , , China .

Abstract

Abstract The intermittent, random and uncontrollable characteristics of renewable energy generation bring many challenges to the actual operation of distribution grid (DG) energy storage. This paper firstly establishes a whole life cycle model applicable to the distribution grid energy storage system, which fully considers the various types of costs of VSC converter stations. Secondly, for comprehensive reactive power optimization, a sequential quadratic programming algorithm is used, and inequality constraints are added to the objective function in the form of penalty functions to optimize the state of on-load transformers and capacitors. Finally, the effectiveness of its distribution grid energy storage configuration optimization is verified by applying the distribution grid energy storage optimization based on the quadratic programming algorithm to electric vehicle charging piles. The results show that after two stages of optimization, the configuration capacity of distribution grid energy storage is increased by 53.14Kw/h compared with that before optimization, which is a substantial increase. The average annual cost of battery 0’ access decreases by 0.275, and battery 2’ access decreases by 0.581. This shows that the energy storage capacity optimization strategy based on the sequential quadratic programming algorithm proposed in this paper can improve the efficiency of energy storage utilization. It provides the basis for the user to select the energy storage capacity.

Publisher

Walter de Gruyter GmbH

Subject

Applied Mathematics,Engineering (miscellaneous),Modeling and Simulation,General Computer Science

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