一种混合算法的风电多目标优化调度策略

Research on multi-objective optimal dispatch of wind power based on hybrid algorithm

针对风力发电等分布式电源对电力系统稳定性和安全性影响的问题,提出了一种含风电电力系统备用成本和运行风险平衡调度的新模型。首先,设定包含正负旋转备用成本、电力系统运行风险的目标函数,增加保证电力系统运行可靠性的约束条件。其次,采用场景生成技术对风力发电输出功率进行模拟,并在差分进化算法和花授粉算法的基础上提出具有时变模糊选择机制的混合多目标优化算法。最后,运用四机组风力发电系统进行仿真分析。仿真结果表明:该模型能够实现对花授粉算法最优解的再次精确寻优,能够实现Pareto最优解集中数据的多样性,提升Pareto前沿数据的搜索与挖掘能力,最终实现对多个冲突目标最大限度的优化,并获得满足约束条件的最优调度策略。

Aiming at the problem of the influence of distributed power sources such as wind power generation on the stability and safety of power systems,a new model of balanced dispatching with reserve costs and operational risks of wind power systems is pro-posed.First,set the objective function including positive and negative rotation reserve cost and power system operation risk,and in-crease the constraints to ensure the power system operation reliability.Secondly,the scene generation technology is used to simulate the output power of wind power generation,and a hybrid multi-objective optimization algorithm with time-varying fuzzy selection mechanism is proposed based on the differential evolution algorithm and the flower pollination algorithm.Finally,a four-unit wind power generation system is used for simulation analysis.The simulation results show that the model can realize the accurate optimiza-tion of the optimal solution of the flower pollination algorithm again,can realize the diversity of data in the Pareto optimal solution set,improve the search and mining capabilities of Pareto’s frontier data,and finally achieve multiple conflicting goals.Maximize the optiopti-mization and obtain the optimal scheduling strategy that meets the constraints.