基于贝叶斯离散优化的电力调度网络发令多任务优先级解耦方法

Multi-task Priority Decoupling Method for Issuing Instructions in Power Dispatching Network Based on Bayesian Discrete Optimization

电网输电线路的负荷率和利用率的不断加重,为电力系统运行调度增加了难度。为了合理规划调度任务,保证电网运行安全,研究基于贝叶斯离散优化的电力调度网络发令多任务优先级解耦方法。建立电力调度模型,设定调度优化目标和约束条件;基于贝叶斯离散优化预测电力负荷,为任务优先级判定提供依据;通过分块解耦动态仿真电力系统,将复杂外部系统转换为简单等值系统;通过电力调度多任务优先级解耦,划分优先级,接收操作令,完成电力调度的解耦。经实验论证分析,所提模型得到的解耦前后的仿真曲线较为吻合,仿真结果可以真实准确地反映电力系统的动态行为,对过载线路有功功率的调节效果明显,越限问题得到了很大程度的改善。

The increasing load rate and utilization rate of power transmission lines increase the difficulty of power system operation and dispatching.In order to rationally plan dispatching tasks and ensure the safety of power network operation,a multi-task priority decoupling method based on Bayesian discrete optimization is studied.Power dispatching model is established,dispatching optimization objectives and constraints are set.The power load is predicted based on Bayesian discrete optimization to provide basis for task priority judgment.The complex external system is transformed into a simple equivalent system by the dynamic simulation of power system with block decoupling.By decoupling multi-task priority of power dispatching,dividing priority and receiving operation order,the decoupling of power dispatching is completed.The simulation curves before and after decoupling of the proposed model are consistent with the experimental analysis,and the simulation results can reflect the dynamic behavior of the power system truly and accurately,and the adjustment effect of the active power of the overload line is obvious,and the overlimit problem has been greatly improved.