Voltage Zoning Regulation Method of Distribution Network with High Proportion of Photovoltaic Considering Energy Storage Configuration

Fangfang Zheng, Xiaofang Meng (), Tiefeng Xu, Yongchang Sun and Nannan Zhang
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Fangfang Zheng: College of Information and Electric Engineering, Shenyang Agricultural University, Shenyang 110866, China
Xiaofang Meng: College of Information and Electric Engineering, Shenyang Agricultural University, Shenyang 110866, China
Tiefeng Xu: College of Information and Electric Engineering, Shenyang Agricultural University, Shenyang 110866, China
Yongchang Sun: Economic and Technological Development Zone Heating Limited Company, Dalian 116600, China
Nannan Zhang: College of Information and Electric Engineering, Shenyang Agricultural University, Shenyang 110866, China

Sustainability, 2023, vol. 15, issue 13, 1-19

Abstract: Photovoltaics have uncertain characteristics. If a high proportion of photovoltaics are connected to the distribution network, the voltage will exceed the limit. In order to solve this problem, a voltage regulation method of a distribution network considering energy storage partition configuration is proposed. Taking the minimum total voltage deviation, the minimum total cost, the minimum total power loss, and the minimum energy storage device installation ratio as the objective function, and considering various conditions, such as voltage deviation constraint and energy storage constraint, a mathematical model of voltage regulation is established. Firstly, a high proportion of photovoltaics are connected to the distribution network, and the voltage deviation curve is obtained. The optimal k value is determined by the elbow rule. The voltage deviation curve of each node is clustered by the k-means algorithm so as to determine the energy storage device partition. The energy storage device is connected to various clustering centers, and then the weighting factor of each objective function is determined by the fuzzy comprehensive evaluation method. For comparison and analysis, ( k + 1) schemes are determined through the partition configuration of ( k + 1) energy storage devices. Then, the model is solved by particle swarm optimization, and the unit output result and the minimum objective function value are obtained. Finally, an example of IEEE33 is used to verify the effectiveness of the proposed model.

Keywords: high proportion photovoltaic; voltage regulation; k-means clustering; energy storage partition; particle swarm optimization algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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