Risk assessment of a power system containing wind power and photovoltaic based on improved Monte Carlo mixed sampling
DOI:DOI: 10.19783/j.cnki.pspc.211076
Key Words:risk assessment  Monte Carlo  mixed sampling  wind power and photovoltaic  power system
Author NameAffiliation
MA Yanfeng 1. Key Laboratory of Distributed Energy Storage and Microgrid of Hebei Province, North China Electric Power University, Baoding 071003, China
2. State Grid Hebei Electric Power Co., Ltd. Research Institute, Shijiazhuang 050021, China 
LUO Zerong 1. Key Laboratory of Distributed Energy Storage and Microgrid of Hebei Province, North China Electric Power University, Baoding 071003, China
2. State Grid Hebei Electric Power Co., Ltd. Research Institute, Shijiazhuang 050021, China 
ZHAO Shuqiang 1. Key Laboratory of Distributed Energy Storage and Microgrid of Hebei Province, North China Electric Power University, Baoding 071003, China
2. State Grid Hebei Electric Power Co., Ltd. Research Institute, Shijiazhuang 050021, China 
WANG Zijian 1. Key Laboratory of Distributed Energy Storage and Microgrid of Hebei Province, North China Electric Power University, Baoding 071003, China
2. State Grid Hebei Electric Power Co., Ltd. Research Institute, Shijiazhuang 050021, China 
XIE Jiarong 1. Key Laboratory of Distributed Energy Storage and Microgrid of Hebei Province, North China Electric Power University, Baoding 071003, China
2. State Grid Hebei Electric Power Co., Ltd. Research Institute, Shijiazhuang 050021, China 
ZENG Siming 1. Key Laboratory of Distributed Energy Storage and Microgrid of Hebei Province, North China Electric Power University, Baoding 071003, China
2. State Grid Hebei Electric Power Co., Ltd. Research Institute, Shijiazhuang 050021, China 
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Abstract:The access of wind power and photovoltaic with strong randomness and uncertainty makes the operation of a power system more complicated, and in particular it is necessary to comprehensively and efficiently evaluate the operational risk of a power system containing wind power and photovoltaic. First, there is low computational efficiency of the traditional Monte Carlo method in power system risk assessment. Thus a version based on improved Monte Carlo mixed sampling is proposed, one which is combined with the ideas of full probability, equal dispersion and adaptive importance sampling to offer a risk assessment method. Secondly, the system's load loss, voltage over-limit, branch over-limit, and steady-state frequency over-limit risks are calculated, and a three-tier evaluation index system is used to evaluate the operational risk of the system. Finally, the improved IEEE-RTS79 system and the actual system in a northwestern province are used as examples to verify the effectiveness and accuracy of the proposed method. And the system risks of wind power and photovoltaic in different access locations, access capacities and access ratios are analyzed. The results can provide reference information for power system operation and planning. This work is supported by the National Key Research & Development Program of China (No. 2017YFB0902200).
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