Economic and Low-Carbon-Oriented Distribution Network Planning Considering the Uncertainties of Photovoltaic Generation and Load Demand to Achieve Their Reliability

Weifeng Xu, Bing Yu, Qing Song, Liguo Weng, Man Luo and Fan Zhang ()
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Weifeng Xu: State Grid Hangzhou Xiaoshan Power Supply Company, Hangzhou 311200, China
Bing Yu: State Grid Hangzhou Xiaoshan Power Supply Company, Hangzhou 311200, China
Qing Song: State Grid Hangzhou Xiaoshan Power Supply Company, Hangzhou 311200, China
Liguo Weng: State Grid Hangzhou Xiaoshan Power Supply Company, Hangzhou 311200, China
Man Luo: State Grid Hangzhou Xiaoshan Power Supply Company, Hangzhou 311200, China
Fan Zhang: College of Automation, Hangzhou Dianzi University, Hangzhou 310018, China

Energies, 2022, vol. 15, issue 24, 1-15

Abstract: The integration of renewable resources with distribution networks (DNs) is an effective way to reduce carbon emissions in energy systems. In this paper, an economic and low-carbon-oriented optimal planning solution for the integration of photovoltaic generation (PV) and an energy storage system (ESS) in DNs is proposed. A convolutional neural network (CNN)-based prediction model is adopted to characterize the uncertainties of PV and load demand in advance. Then, taking the lowest total economic cost, the largest carbon emission reduction, and the highest system power supply reliability as the optimization objectives, the optimal distribution network planning model is constructed. The improved multi-objective particle swarm optimization (MOPSO) algorithm is used to solve the optimization model, and the effectiveness of the proposed solution is confirmed through a comparative case study on the IEEE-33 bus system. Simulation results show that the proposed solution can better maintain the balance between economic cost and carbon emissions in DNs.

Keywords: carbon emission; photovoltaic generation; energy storage system; distribution network planning; uncertainty modeling (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: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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