基于削峰填谷的微电网并网运行的优化调度

摘要

Renewable energies such as photovoltaic and wind play an dominate role in the micro-grid generation system, but these energies have randomness and fluctuation, and they cannot follow manual scheduling, thus the scheduling model can not be applied in the micro-grid directly. By referring to the scheduling principles and considering the features of micro-grid, the objective functions of minimum generation cost and minimum pollution emissions were established. For the existing load difference between the peak and the valley, the system controlled the charging and discharging time of battery and the power and time of grid interaction to realize load shifting. As the optimal scheduling of micro-grid was a multi-objective, nonlinear and multi-constraint model, the hybrid particle swarm algorithm was proposed. And for the local convergence and slow convergence rate of the particle swarm algorithm, the random search which could obtain certain value was adopted to replace the particle which lost evolutionary and the process of selecting hybrid. The simulation results prove that the model of micro-grid optimal dispatch is correct and feasible, and of hybrid particle swarm optimization algorithm (HPSO) is converged.%基于微电网中的光伏和风力等可再生能源发电占主导地位，而其具有很强的随机性和波动性，不遵循人工调度，而传统电网的调度模型不能直接应用到微电网等问题，借鉴大电网的调度经验，针对微电网本身特点，建立最小发电成本和最少污染物排放的2个目标函数。针对大电网存在较大的峰谷负荷差等问题，通过控制蓄电池充放电时段和功率、大电网交互功率和时段，以实现大电网的削峰填谷的目的。针对微电网优化调度是一个多目标、非线性、多约束条件的模型，提出杂交粒子群算法对模型进行求解，针对粒子群算法中可能存在的局部收敛和收敛速度慢等问题，随机搜索取值代替失去进化的粒子和选择杂交过程。仿真结果验证了微电网优化调度模型的正确性和有效性，以及杂交粒子群算法的收敛性。