Three-Stage Analysis of the Maximum Accommodation Capacity of a Distribution System with High Photovoltaic Penetration

Jiaqi Gu, Fei Mei, Jixiang Lu, Jinjun Lu, Jingcheng Chen, Xinmin Zhang and Limin Li
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Jiaqi Gu: College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
Fei Mei: College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
Jixiang Lu: State Key Laboratory of Smart Grid Protection and Control, NARI Group Corporation, Nanjing 211000, China
Jinjun Lu: State Key Laboratory of Smart Grid Protection and Control, NARI Group Corporation, Nanjing 211000, China
Jingcheng Chen: State Grid Tianjin Electric Power Company, Tianjin 300010, China
Xinmin Zhang: State Grid Tianjin Electric Power Company, Tianjin 300010, China
Limin Li: Tianjin Huadian Beichen Distributed Energy Co., Ltd., Tianjin 300400, China

Energies, 2020, vol. 13, issue 17, 1-18

Abstract: The safety and stability of a distribution network will be affected by high photovoltaic (PV) penetration. Therefore, it is of great significance to evaluate the PV accommodation capacity of a distribution network and to select an appropriate PV accommodation scheme. This paper assesses the PV accommodation capacity of a distribution network with an improved algorithm and optimizes the accommodation scheme with a comprehensive index. First, the PSO (particle swarm optimization)–Monte Carlo algorithm is used to evaluate the maximum accommodation capacity of a distribution network with PV integration. Second, a year-round voltage timing simulation is performed to analyze the node voltage that exceeds the limit under the planned PV capacity, which is higher than the previously evaluated maximum accommodation capacity. Finally, the staged control strategy of the PV inverter and energy storage is carried out to select the scheme for the sizing and siting of energy storage. The simulation tests use a 10 kV standard distribution network as an example for PV evaluation and PV accommodation scheme selection to verify the feasibility and effectiveness of the proposed model.

Keywords: PV power accommodation; PSO–Monte Carlo algorithm; the staged control strategy of PV inverter and energy storage; the sizing and siting of energy storage (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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