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机构地区:[1]水资源与水电工程科学国家重点实验室(武汉大学),湖北省武汉市430072 [2]甘肃省电力公司风电技术中心,甘肃省兰州市730050
出 处:《电网技术》2014年第9期2416-2421,共6页Power System Technology
基 金:国家自然科学基金项目(51379159);高等学校博士学科点专项科研基金资助项目(20130141130001)~~
摘 要:提出了一种风电随机出力的时间序列模型,运用反变换方法将原始出力序列转换为平稳、正态序列,采用自回归移动平均模型对序列进行回归,再将模拟的正态序列转换回原始域,得到风电出力的模拟时间序列。运用该模型对风电出力序列进行模拟,结果同时满足风电出力的时间相关性、概率分布特性、时间分布特性以及波动特性,这说明该模型可用于风电出力不确定分析、电力系统随机优化以及风电储能系统优化运行等方面的研究。The uncertainty of wind power brings new challenge to power grid operation, and a stochastic wind power model, which captures both probability distribution and temporal correlation of the wind power generation, is the base for the research on large-scale wind farms. A time-series model of stochastic output of wind power is proposed, and the inverse transformation is utilized to transform the original wind power output into normal stationary series and the auto-regressive moving-average model is adopted for the regression of the normal stationary series, and then the simulated normal series are turned back into original domain to obtain simulated time series of wind power out. Using the proposed model, the wind power output series are simulated, and the simulation results can simultaneously satisfy the temporal correlation, probability distribution characteristics, time distribution characteristics and fluctuation characteristics of wind power output, thus the proposed model can be used in the analysis on uncertainty of wind power output and stochastic optimization of power grid as well as in the research on optimal operation of energy storage system for wind power.
关 键 词:风电出力 时间序列 时间相关性 概率分布 反变换
分 类 号:TM71[电气工程—电力系统及自动化]
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