考虑不规则风速概率分布特性的配电系统可靠性评估
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摘要
威布尔分布模型无法准确描述不规则风速概率分布特性,将其应用于含风电的配电网可靠性评估会造成评估结果偏差较大。为了提高评估结果的准确性,本文首次将改进混合半云模型应用于考虑不规则风速概率分布特性的配电系统可靠性评估中。采用美国Monteview地区时间间隔5 min的风速数据建立不同的风速概率分布模型,并应用于求解不同风速扰动情况下配电系统可靠性指标。算例结果表明:改进混合半云模型鲁棒性更好,更适用于含风电接入的配电系统可靠性评估。
Weibull distribution model cannot accurately describe the probability distribution characteristics of irregular wind speed, which will result in the large deviation of the evaluation result if the model is applied in the reliability evaluation of distribution network with wind power. In order to improve the accuracy of the evaluation result, the improved mixed half-cloud model is applied in the reliability evaluation of distribution network considering the probability distribution of irregular wind speed in this paper. The probability distribution models of different wind speeds are established based on the 5-minute interval wind speed data in Monteview,USA and are used to solve the reliability index of distribution system under different wind speed disturbances. The results of the example show that the improved mixed half-cloud model has better robustness and is more suitable for the reliability evaluation of distribution network with wind power.
Weibull distribution model cannot accurately describe the probability distribution characteristics of irregular wind speed, which will result in the large deviation of the evaluation result if the model is applied in the reliability evaluation of distribution network with wind power. In order to improve the accuracy of the evaluation result, the improved mixed half-cloud model is applied in the reliability evaluation of distribution network considering the probability distribution of irregular wind speed in this paper. The probability distribution models of different wind speeds are established based on the 5-minute interval wind speed data in Monteview,USA and are used to solve the reliability index of distribution system under different wind speed disturbances. The results of the example show that the improved mixed half-cloud model has better robustness and is more suitable for the reliability evaluation of distribution network with wind power.
引文
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[2]R.Doherty,M.O’Malley.A new approach to quantify reserve demand in systems with significant installed wind capacity[J].IEEE Trans.Power System,2005,20(2),587-595.
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[4]Libao Shi,Chen Wang,Liangzhong Yao.Optimal Power Flow Solution Incorporating Wind Power[J].Systems Journal,IEEE,2012,6(2),233-241.
[5]Fang Yao,Zhao Yang Dong,Ke Meng.Quantum-Inspired Particle Swarm Optimization for Power System Operations Considering Wind Power Uncertainty and Carbon Tax in Australia[J].Industrial Informatics,IEEE Transactions on,2012,8(4),880-888.
[6]Queiroz Oliveira O.D.,Araujo A.M.,Ramos Medeiros.APreliminary Approach of the Technical Feasibility of Offshore Wind Projects along the Brazilian Coast[J].Latin America Transactions,IEEE(Revista IEEE America Latina),2013,11(2),706-712.
[7]Zhilong Qin,Wenyuan Li,Xiaofu Xiong.Generation System Reliability Evaluation Incorporating Correlations of Wind Speeds With Different Distributions[J].Power Systems,IEEE Transactions on,2013,28(1),551-558.
[8]陈绍南,陈碧云,韦化,等.不规则风速概率分布的混合半云建模方法[J].中国电机工程学报,2015,35(6),1314-1321.
[9]陈绍南,陈碧云,韦化,等.改进混合半云模型在不规则风速概率分布拟合中的应用[J].电力自动化设备,2017,37(4),60-66.
[10]胡叶舟.大型风电场对发输电系统可靠性影响评估研究[D].保定:华北电力大学,2011.
[11]何禹清,彭建春,孙芊.考虑风电能量随机性的配电网可靠性快速评估[J].中国电机工程学报,2010,30(13):16-22.
[12]梁惠施,程林,刘思革.基于蒙特卡罗模拟的含微网配电网可靠性评估[J].电网技术,2011,35(10):76-81.
[13]袁兆祥,孔祥玉,赵帅.分布式电源接入配电系统可靠性分析方法[J].电力系统及其自动化学报,2013,25(4):112-116.
[14]孙若笛,谢开贵.计及风速-负荷相关性的配电网可靠性评估Monte Carlo模拟法[J].电力系统保护与控制,2012,40(18):12-18.
[2]R.Doherty,M.O’Malley.A new approach to quantify reserve demand in systems with significant installed wind capacity[J].IEEE Trans.Power System,2005,20(2),587-595.
[3]何禹清,彭建春,孙芊.考虑风电能量随机性的配电网可靠性快速评估[J].中国电机工程学报,2010,30(13):16-22.
[4]Libao Shi,Chen Wang,Liangzhong Yao.Optimal Power Flow Solution Incorporating Wind Power[J].Systems Journal,IEEE,2012,6(2),233-241.
[5]Fang Yao,Zhao Yang Dong,Ke Meng.Quantum-Inspired Particle Swarm Optimization for Power System Operations Considering Wind Power Uncertainty and Carbon Tax in Australia[J].Industrial Informatics,IEEE Transactions on,2012,8(4),880-888.
[6]Queiroz Oliveira O.D.,Araujo A.M.,Ramos Medeiros.APreliminary Approach of the Technical Feasibility of Offshore Wind Projects along the Brazilian Coast[J].Latin America Transactions,IEEE(Revista IEEE America Latina),2013,11(2),706-712.
[7]Zhilong Qin,Wenyuan Li,Xiaofu Xiong.Generation System Reliability Evaluation Incorporating Correlations of Wind Speeds With Different Distributions[J].Power Systems,IEEE Transactions on,2013,28(1),551-558.
[8]陈绍南,陈碧云,韦化,等.不规则风速概率分布的混合半云建模方法[J].中国电机工程学报,2015,35(6),1314-1321.
[9]陈绍南,陈碧云,韦化,等.改进混合半云模型在不规则风速概率分布拟合中的应用[J].电力自动化设备,2017,37(4),60-66.
[10]胡叶舟.大型风电场对发输电系统可靠性影响评估研究[D].保定:华北电力大学,2011.
[11]何禹清,彭建春,孙芊.考虑风电能量随机性的配电网可靠性快速评估[J].中国电机工程学报,2010,30(13):16-22.
[12]梁惠施,程林,刘思革.基于蒙特卡罗模拟的含微网配电网可靠性评估[J].电网技术,2011,35(10):76-81.
[13]袁兆祥,孔祥玉,赵帅.分布式电源接入配电系统可靠性分析方法[J].电力系统及其自动化学报,2013,25(4):112-116.
[14]孙若笛,谢开贵.计及风速-负荷相关性的配电网可靠性评估Monte Carlo模拟法[J].电力系统保护与控制,2012,40(18):12-18.