Abstract:The grid-connection of the distributed generation introduces unpredictable elements into the planning of the distribution network. To enhance the rationality of the distribution network planning, a planning strategy is proposed with the uncertain scenarios of source-storage win-photovoltaic-load uncertainty scenarios taken into account . A wind-light-load time series model is established using Latin hypercube sampling. To address the issues of low efficiency and poor accuracy in scene reduction, a three-layer reduction method of AP-TD-K-medoids is proposed based on the K-medoids algorithm. The establishment of a multi-objective programming model with economic benefits, voltage deviation, permeability as well as wind and light absorption taken as indicators. An improved multi-objective particle swarm optimization algorithm is proposed. In addition, the update of niche sharing technology is introduced on the basis of adaptive weights. The non-inferior solution set of Pareto archives is utilized for to planning scheme evaluation by combining the information entropy ordinal preference method with the grey relational degree method. Simulation is carried out on an IEEE33 bus distribution system, and the results indicate that both the model and the proposed algorithm are sound and effective.
标题：源–荷不确定场景下分布式电源与储能联合规划策略
英文标题：Joint Planning Strategy of Distributed Generation and Energy Storage Under Source-load Uncertainty Scenario
