考虑主动管理模式的多目标分布式电源规划

在考虑主动管理模式条件下,建立了多目标双层分布式电源规划模型.其中,上层规划以分布式电源年投资运行成本和网损最小为目标,下层规划以分布式电源出力切除量最小为目标,考虑风电光伏等间歇式能源出力的随机性及负荷的不确定性,利用基于拉丁超立方抽样的蒙特卡洛模拟方法对风速、光照强度和负荷进行抽样,利用非支配排序遗传算法对上层规划模型进行求解,采用原对偶内点法对下层规划模型进行求解,以得到问题的Pareto最优解集,从而避免了传统加权求解方法中权重确定的主观性.同时,通过对33节点配电网算例的仿真和分析,验证了所建模型的合理性和算法的有效性.

Multi-Objective Distributed Generation Planning Considering Active Management

Considering the active management, a multi-objective distributed generation planning model was proposed, the upper level planning objective of which was to minimize both the investment and operating cost of distributed generation and the power loss, while the lower level planning objective of which was to minimize the curtailment value of distributed generation. It took into account the randomness of intermittent generation, such as wind turbine generation and photovoltaic power generation, as well as the uncertainty of loads. The Latin hypercube sampling-based Monte Carlo simulation was used to sample the wind speed, the illumination intensity and the load. The upper planning model was solved by the non-dominated sorting genetic algorithm while the lower planning model was solved by the prime-dual interior point method. Finally, the Pareto-optimal solutions were obtained, which could avoid the subjective impact of the traditional weighted methods on determining the weights. The feasibility of the model and the effectiveness of the algorithm were proved by the simulation and analysis of a 33-bus distribution system.