基于模型预测控制的多源自动发电控制系统及运行优化

Multi-source Automatic Power Generation Control System andOperation Optimization based on Model Predictive Control

根据火电站、风电场和光伏电站的动态响应特性,搭建了基于模型预测控制的多源自动发电控制系统模型,并利用粒子群优化算法优化区域内系统的动态响应调节性能。案例分析表明,与优化前相比,多源自动发电控制系统模型能提高系统的动态响应能力,减少区域控制总偏差,减少区域“弃风”、“弃光”,让风光新能源充分发挥调节潜力。

According to the dynamic response characteristics of thermal power stations,wind farms,and photovoltaic power stations,a multi-source automatic power generation control model is constructed based on model predictive control.Then,the particle swarm optimization is used to optimize the dynamic response regulation performance of the system in the region.Case study shows that the multi-source automatic power generation control model can improve the dynamic response performance of the system,reduce the total regional control deviation and the abandoned wind and light,and fully utilize the regulatory potential of the renewable energies such as wind power and photovoltaic power.