近年来，随着分布式电源与电力需求侧响应的快速发展，与其相关的配电网规划问题的重要性也日益增大。建立基于分布式电源及需求侧响应的配电网综合资源规划的数学模型，考虑了风电出力的随机性，并采用混合智能算法进行求解，旨在求得系统可靠性和经济性最高的配电网规划方案。在选取优化的目标函数时，同时考虑了多个方面的影响因素，包括电力系统网损费用、分布式电源的投资费用和运行费用、考虑需求侧响应的可中断负荷补偿费用、分布式电源引入后节约的购电费用、优化后产生的环境效益等；采用基于支持向量机和粒子群算法的混合智能算法对分布式电源进行规划。最后，以我国某地区实际配电网作为算例进行计算，验证所提算法对系统可靠性和经济性方面的改善作用。

With the fast development of distributed generation (DG) and demand response (DR), the issue of distribution network planning becomes increasingly important. The mathematical model of integrated resource planning for distribution network considering DG and DR is established. The stochasticity of wind power is considered, and a hybrid intelligent algorithm is used to solve the problem, aiming to obtain the distribution network planning scheme with the highest system reliability and economy. When choosing the optimal objective function, many factors are considered at the same time, including the network loss cost of power system, the investment cost and operating cost of DG, the interruptible load compensation cost considering DR, the saving of electricity purchase after introduction of DG, the environmental benefits after optimization, etc. The hybrid intelligent algorithm based on support vector machine and particle swarm optimization algorithm are adopted for the DG planning. Finally, an actual distribution network in China is taken as an example to verify the improvement effect of the proposed algorithm on system reliability and economy.