混合粒子群优化算法的新能源电网规划研究

以合理规划新能源电网，降低电网电能损耗，提升新能源消纳能力，设计了混合粒子群优化算法的新能源电网规划方法。以最小电能损耗与最大新能源消纳为目标函数，潮流功率、容量、线路输电能力、风能与太阳能出力为约束条件，建立新能源电网规划模型；通过结合自然选择机理与粒子群算法，设计混合粒子算法，在混合粒子群算法内引入混沌扰动与变异策略，避免惰性粒子陷入局部最优，优化混合粒子群算法，利用优化混合粒子群算法求解规划模型，获取最佳规划方案。实验表明，该方法可有效获取最佳规划方案，降低电能损耗，提升新能源消纳能力，提升电网断面利用率；规划后的电网日累计发电量显著提升、碳排放量显著下降。

Research on new energy grid planning based on hybrid particle swarm optimization algorithm

In order to reasonably plan the new energy grid,reduce the power loss of the grid,and improve the new energy consumption capacity,a new energy grid planning method based on hybrid particle swarm optimization algorithm is designed.Taking the minimum power loss and maximum new energy consumption as the objective function,and the power flow,capacity,line transmission capacity,wind energy and solar energy output as the constraints,a new energy grid planning model is established.By combining natural selection mechanism and particle swarm optimization algorithm,a hybrid particle algorithm is designed.Chaotic perturbation and mutation strategies are introduced into the hybrid particle swarm optimization algorithm to avoid inert particles falling into local optimization.The hybrid particle swarm optimization algorithm is optimized.The optimal hybrid particle swarm optimization algorithm is used to solve the planning model and obtain the optimal planning scheme.The experimental results show that the method can effectively obtain the best planning scheme,reduce power consumption,improve the new energy consumption capacity,and improve the grid cross-section utilization.After the planning,the accumulated daily power generation of the grid has significantly increased and carbon emissions have significantly decreased.