基于混合智能粒子群算法的广义电源主动配电网优化配置

研究广义电源接入主动配电网的优化配置问题。提出一种电压偏差指标。建立综合考虑投资经济效益、电压偏差及污染气体排放指标的多目标优化配置模型。提出一种混合智能粒子群算法，在优化过程中引入快速非支配排序策略、精英保留策略和拥挤距离计算策略以改善其全局搜索能力。对IEEE-33节点、PG&E-69节点配电系统进行计算，分析在不同负荷水平下各指标的变化情况，研究负荷变化时广义电源的最佳配置。研究表明，广义电源的接入与合理配置能够有效提高投资运行效益和系统电压稳定性，同时说明该方法能够保证配置方案的多样性和多目标优化过程的寻优性。

Optimal allocation of generalized power sources in active distribution network based on hybrid intelligent particle swarm optimization algorithm

Optimal allocation of generalized power sources in active distribution network is researched. A simple index of voltage stability is put forward. Considering the investment and operation benefit, the stability of voltage and the pollution emissions of generalized power sources in active distribution network, a multi-objective optimization planning model is established. A hybrid intelligent particle swarm optimization algorithm is proposed to solve the optimal model. In order to improve the global search ability, the strategies of fast non-dominated sorting, elitism and crowding distance are adopted in this algorithm. Finally, the model and algorithm by different load level of IEEE-33 node and PG&E-69 node are tested to find the best configuration of GP. The computed result shows that with the generalized power reasonable access to the active distribution network, the investment benefit and the voltage stability of the system are improved, and the proposed algorithm has better global search capability.