A Bi-level Programming of Multi Scenario Distributed Generation Considering Flexible Supply and Demand

The grid-connection of high penetration renewable energy makes a higher request on the flexibility of power grid. During the planning stage of renewable energy system taking collaborative optimization of multiple flexible resources into consideration can effectively improve the system flexibility. For this reason, based on the analysis on flexible regulating ability, considering flexibility a bi-level planning model of distributed generation in distribution network was proposed. Taking economic goals and flexible goals as optimization objectives, a multi scenario coordinated optimization planning model was constructed. Considering the defect of low solution efficiency due to too large scenery scene set, on the basis of affinity propagation (abbr. AP) clustering algorithm an AP-Kmedoids-based bi-level scene reduction technology was put forward, and the reduced scene was verified. Finally, by use of the mixed solution strategy of integer adaptive particle swarm optimization (abbr. APSO) and chaos particle swarm optimization (abbr. CPSO) the simulation of the proposed bi-level programming model was implemented. Simulation results show that the proposed programming method is effective in improving economy and flexible regulation ability.