基于最优引导策略的分布式电源优化配置

Distributed Generation Planning Based on the Optimized Guidance Strategy

针对分布式电源(distributed generation,DG)在配电网中的优化配置问题,考虑投资综合成本衡量方案的经济性、用系统网损衡量方案的环保性、用电压偏差衡量方案的电压稳定性,建立了分布式电源多目标优化配置模型。运用改进的多目标粒子群算法对分布式电源配置模型进行求解,引入最优极值引导策略对多目标粒子群算法的全局最优值选取进行改进,将非支配排序和精英保留策略嵌入算法中,有效地提高了算法的全局寻优性能,使算法能够快速有效地收敛到Pareto最优前沿。并以IEEE33节点配电网标准测试系统为例,对分布式电源的安装位置和容量进行优化,将所得到的结果与NSGA-II算法进行比较,结果表明算法具有更好的全局收敛效率和寻优能力。

According to the planning problem of distributed generation （DG） in the distribution network, a multi-objec- tive optimization allocation model of DG is established by considering of schemes economic evaluated by comprehen- sive investment cost, the environmental protection of schemes evaluated by system loss, and the voltage stability of schemes evaluated by the voltage deviation. The distributed generation optimal allocation model is solved by using of the multi-objective particle swarm algorithm, the optimized guidance strategy is adopted to improve the selection of global optimization values for the multi-objective particle swarm algorithm, and the global optimization performance is effectively improved by introducing the non-dominated sorting and elitist strategy into algorithm, which make algo- rithm quickly converge to the Pareto optimal front. Taking testing system of IEEE33 node distribution network as an ex- ample, after optimizing the distributed generation installa- tion position and capacity, the proposed algorithm has better global convergence and searching capability compared to the results obtained with the NSGA-II algorithm.