Optimal allocation method of energy storage in PV station based on probabilistic power flow

doi:10.19799/j.cnki.2095-4239.2021.0151

Abstract

Abstract:

Large-scale photovoltaic (PV) stations will adversely affect the stability of the power system, while energy storage is considered to be one of the effective means to eliminate these effects. In this paper, the influence of PV plants on the power system and the function of the energy storage system (ESS) are analyzed from the perspective of power flow. First, the probability distribution model of power system components, storage model, Latin hypercube sampling (LHS) method, and Gram-Schmidt orthogonal sequence method are introduced in this paper. Second, this paper establishes the multiple objective optimization models that consider the energy storage system costs, the probability of a branch remaining active beyond the limit, and network loss. The genetic algorithm is used to find the best solution to the objective function (GA). Finally, the simulation is run on the IEEE 24 bus test system, including the effects of different PV capacities and access positions, as well as the effect of ESS. In this simulation, the optimal energy storage configuration for various PV capacities is obtained.

Key words: PV power generation, energy storage system, optimal configuration, probabilistic power flow, genetic algorithm

CLC Number:

TM 910.1

Delong ZHANG, Saif MUBAARAK, Siyu JIANG, Longze WANG, Jinxin LIU, Yongcong CHEN, Meicheng LI. Optimal allocation method of energy storage in PV station based on probabilistic power flow[J]. Energy Storage Science and Technology, 2021, 10(6): 2244-2251.

Figures/Tables 8

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