含分布式电源配电网的扩展规划研究

Distribution network expansion planning including distributed generation

分布式电源并网运行的输出功率具有明显的随机性,很大程度上影响着配电网规划的资金投入及规划方案。考虑分布式电源出力的不确定性,采用期望值规划模型,以年总投资费用最小为优化目标进行配电网扩展规划。求解过程中运用了混合编码方式的自适应遗传算法,加快了迭代进度,避免陷入局部最优。算例通过与传统配电网扩展规划的分析比较,并验证了该方法的有效性。

Distributed power grid to run the output power has a obvious stochastic, which significantly influenced the distribution network planning on capital investment planning and final solution. Considering the uncertain output of DG, this paper adopts an expectations programming model to minimize the total investment cost for the optimization goal of distribution network expansion planning. In the solving process, combined-coded adaptive GA is used to speed up the iterations progress, to avoid falling into local optimum. Compared with the traditional distribution network expansion planning in the example, the model and method introduced in this paper show more effectiveness.