摘要
模拟生成风光联合输出功率时间序列对电力系统的规划、调度和控制具有重要意义。综合考虑风电和光伏输出功率日特性、天气特性及波动性,提出4种基于Markov链和Copula理论的模拟生成风光联合输出功率时间序列方法:第1种方法利用改进Markov链分别生成风电和光伏输出功率时间序列,再将二者叠加得到风光联合输出功率时间序列;第2种方法将风/光输出功率历史序列按时间对应相加作为历史数据,运用改进Markov链直接生成风光联合输出功率时间序列的方法;为了降低传统方法抽样随机性,第3种方法运用改进Markov链和Copula理论的结合来生成风光联合输出功率时间序列;为寻求更好的方法,第4种方法运用熵权法进行组合模拟来生成风光联合输出功率时间序列。工程实例表明,所提出的4种方法均正确有效,其中的组合生成法效果更好。
For the planning,scheduling and control of power grid,it is significant to generate joint wind and photovoltaic(PV)power output time series by simulation method.Considering daily characteristics,whether characteristics and fluctuation properties of wind and PV power output,four simulation methods based on Markov chain and Copula theory to generate wind and PV power output time series were proposed.For the first method,the improved Markov Chain was utilized to generate two time series for wind power and PV power respectively and the two time series were superposed to obtain the joint wind and PV power output time series.As for the second method,the historical sequence of wind and PV power output were correspondingly added and the results were regarded as the historical data,then the improved Markov chain was utilized to directly generate the joint wind and PV power output time series.In the third method,to reduce the randomness due to the traditional sampling method,utilizing the combination of Markov chain with Copula theory,the joint wind and PV power output time series were generated.As for the fourth method,to seek a better method,the entropy weight method was used to carry out the combination simulation to generate the time series for wind and PV power output.Results of engineering practice show that all four proposed methods are correct and effective,and the fourth method,i.e.,the combination generation method is more effective.
作者
肖白
吕丹琪
张舒捷
张节潭
刘金山
XIAO Bai;Lü Danqi;ZHANG Shujie;ZHANG Jietan;LIU Jinshan(College of Electrical Engineering,Northeast Electric Power University,Jilin 132000,Jilin Province,China;State Grid Qinghai Electric Power Company,Xining 810008,Qinghai Province,China)
出处
《现代电力》
北大核心
2020年第3期245-254,共10页
Modern Electric Power
基金
国家重点研发计划项目(2017YFB0902200)
吉林省产业创新专项基金项目(2019C058-7)
吉林省教育厅科技项目(JJKH20180442KJ)
国家电网公司科技项目(5228001700CW)。
