Power Flow Optimization Strategy of Distribution Network with Source and Load Storage Considering Period Clustering

The large-scale grid connection of new energy will affect the optimization power flow. In order to solve this problem, paper proposes a flow strategy model distribution network with non-fixed weighting factors source, load and storage. objective function is lowest cost, smallest voltage deviation loss, many constraints, such as constraint, climbing constraint storage operation are also considered. Firstly, equivalent curve obtained by superimposing output wind solar turbines initial load, best k value elbow rule. k-means algorithm used cluster in different periods, then fuzzy comprehensive evaluation method determine factor each period. Then, particle swarm multi-objective model, optimal values unit period obtained. Finally, IEEE33 an example verify effectiveness proposed through two cases: fixed proportion factor, factor. can improve economy reliability networks.