基于加速时序蒙特卡洛法的风电场置信容量评估

随着风电资源接入电网规模的增大,如何快速准确地评估待建风电场的置信容量是电力系统规划时需要考虑的问题。文中基于有效载荷容量这一概念,根据新能源接入前后系统可靠性不变的原则,从负荷侧评价了风电资源的置信容量。在计算可靠性指标时,针对当前解析法无法考虑负荷曲线时序性而时序仿真法计算时间较长的问题,提出了一种可靠性指标的加速时序蒙特卡洛计算方法。在此基础上,在计算可靠性较高的系统风电置信容量时,将该方法和线性插值法相结合,避免了采用仿真法计算可靠性指标时的数值波动对弦截法迭代过程造成的不利影响。最后,利用甘青地区电网实际机组、负荷和风电出力数据设计了算例,并验证了算法的正确性。

Evaluation of Credit Capacity for Wind Farms Based on Accelerated Sequential Monte Carlo Method

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.