High Proportion of Distributed PV Reliability Planning Method Based on Big Data

Author:

Fang Hualiang1,Shang Lei1,Dong Xuzhu1ORCID,Tian Ye2

Affiliation:

1. School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China

2. Electric Power Research Institute, State Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, China

Abstract

The higher proportion of distributed photovoltaic and lower fossil energy integrated into the power network brings huge challenges in power supply reliability and planning. The distributed photovoltaic planning method based on big data is proposed. According to the impact of stochastic photovoltaics and loads on reliability planning, the probability model of distributed photovoltaic and load is analyzed, and the dynamic capacity–load ratios are presented based on big data. The multi-scenario generation and reduction algorithm of stochastic distributed photovoltaic and load planning is studied, and a source–load scenario matching model is proposed based on big data. According to the big data scenario of source–load, the reliability indexes and dynamic capacity–load ratio may be obtained. Finally, the IEEE 33-bus system is used as an example, and the results show that distributed photovoltaic planning methods based on big data can improve photovoltaic utilization and power supply reliability.

Funder

State Grid Corporation of China Headquarters Management of Science and Technology Project

China Scholarship Council

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction

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