Research on Optimization Configuration of Distributed Power Sources Based on Multi-Scenario Analysis
In order to make the grid connection planning of distributed power sources more reasonable,the uncertainty issues of intermittent distributed power generation output and load forecasting are included in the solution process.Firstly,multi scenario analysis is introduced to transform the source load uncertainty problem into a deterministic problem.The Latin hyperpower square sampling method is used to generate the initial planning scenario,and the density peak clustering idea and elbow method are used to improve the K-means clustering algorithm and reduce the scenario.Secondly,a distributed power grid optimization configuration model is constructed with the objective function of minimizing the annual comprehensive cost.Finally,in response to the slow convergence speed and susceptibility to local optima in particle swarm optimization,an adaptive inertia weight factor was adopted,and the particle swarm algorithm was improved by combining genetic mutation ideas.The effectiveness of the established model and proposed method was verified through IEEE 33 node standard simulation examples.
distributed power generationuncertaintymulti-scenario analysisimproved particle swarm optimization algorithmK-means clustering algorithm
万方数据
维普
