基于多场景建模技术的低碳经济电源规划

Research on Generation Expansion Planning in Low-carbon Economy Environment based on Multi-scenario Technique

以往的电源规划模型多是以年最大负荷以及年用电量的预测值为基准,基于多场景建模技术建立了更加精细的低碳经济电源规划模型,为减少计算量,利用k-means算法对场景进行缩减。采用多种群遗传算法(multiple population genetic algorithm,MPGA)对所建模型进行优化求解,构建了一个传统电源规划模型以便和本文所建模型进行比较,通过算例分析验证了本文所建模型的优越性。

The conventional generation expansion planning models were mostly based on the forecast data of yearly peak load and annual power consumption. A sophisticated generation expansion planning model of low-carbon economy is established in this paper based on multi-scenario technique. To decrease the amount of calculation, the k-means clustering algorithm is used to reduce the scenario amounts.The multiple population genetic algorithm(MPGA) is applied to get the optimal solution of the established model. A comparison is made between the proposed model and the conventional generation expansion planning model. The superiority of the proposed model has been validated through case studies.