Composite power system risk evaluation considering the accurate model of renewable power output

被引:5
作者
Zhang, Kanjun [1 ]
Zhou, Hubing [1 ]
Li, Hengxuan [1 ]
Tang, Aihong [2 ]
Li, Chen [2 ]
机构
[1] State Grid Hubei Elect Power Co Ltd, Elect Power Res Inst, Wuhan 430077, Peoples R China
[2] Wuhan Univ Technol, Sch Automat, Wuhan 430070, Peoples R China
关键词
Risk evaluation; Composite system; Renewable energy; Accurate model; Sequential cross-entropy; MONTE-CARLO-SIMULATION; SPEED PROBABILITY-DISTRIBUTION; RELIABILITY EVALUATION; ADEQUACY ASSESSMENT; PARALLEL;
D O I
10.1016/j.egyr.2023.04.232
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The fluctuation of renewable energy will threaten the reliable operation of the composite transmission and generation power system, so the risk level of the composite system with renewable energy attached must be studied. However, the accuracy of the renewable energy model has typically been overlooked in current risk assessment approaches. Therefore, this study provides an accurate hybrid wind/solar power output model that takes the wind farm's seasonal and spatial characteristics, as well as the correlation between wind and solar PV power into account. For the first, build the seasonal Weibull model of the wind speed and correct the speed captured by each wind turbine considering different spatial characteristics of the wind farm. Secondly, build the probability distribution function of the solar power based on the kernel density estimation method. In the next, construct the joint probability distribution function considering the correlation between wind and solar PV power based on copula theory. Then, using the suggested accurate renewable energy model, the sequential Cross-entropy (SCE) technique is utilized to evaluate the risk indices of the composite system with renewable energy. To validate the models and technique, the modified IEEE-RTS79 is studied. The findings indicate that the accuracy of the renewable energy model influences the risk assessment outcomes. (C) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CCBY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:1861 / 1874
页数:14
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