电力系统自动化2018，Vol.42Issue(5)：86-93,8.DOI:10.7500/AEPS20170920009
基于加速时序蒙特卡洛法的风电场置信容量评估
Evaluation of Credit Capacity for Wind Farms Based on Accelerated Sequential Monte Carlo Method
摘要
Abstract
Along with the increase of wind power integrated to the power grid,how to quickly and accurately evaluate the capacity credit of wind farms to be built should be taken into consideration in the power system planning.Based on the concept of effective load carrying capacity(ELCC),this paper evaluates the capacity credit of wind farms on the load side according to the principle that the reliability of the power system should remain unchanged before and after the integration of newly built wind farms.When calculating the reliability index,an accelerated sequential Monte Carlo sampling(ASMCS) method is proposed aiming at the problems that the analytic methods can not take the sequential characteristics of load curve and the traditional simulation methods consume too much time.On this basis,the ASMCS method is combined with linear interpolation method when computing capacity credit of wind power in power systems with high reliability,to avoid the negative influence of numerical oscillation on the iteration process of secant method when calculating the reliability indices by the simulation method.Finally,the actual data of generators,load curve and wind power of Gansu Province and Qinghai Province in China are employed to design an example to verify the correctness and validity of the proposed method.关键词
有效载荷容量/置信容量/时序蒙特卡洛法/重要性采样/线性插值法Key words
effective load carrying capacity(ELCC)/capacity credit/sequential Monte Carlo method/importance sampling/linear interpolation method引用本文复制引用
蔡霁霖,徐青山,王旭东..基于加速时序蒙特卡洛法的风电场置信容量评估[J].电力系统自动化,2018,42(5):86-93,8.基金项目
国家电网公司科技项目(SGTJDK00DWJS1500100) （SGTJDK00DWJS1500100）
国家自然科学基金资助项目(51377021) （51377021）
江苏省产学研前瞻性联合研究项目(BY2016076-12).This work is supported by State Grid Corporation of China(No.SGTJDK00DWJS1500100)and National Natural Science Foundation of China(No.51377021),and Jiangsu Provincial Innovation Fund for Industry-university-research Cooperation of China(No.BY2016076-12). （BY2016076-12）
