新能源电力系统不确定优化调度方法研究现状及展望

Research Status and Prospect of Uncertain Optimal Dispatch Methods for Renewable Energy Power Systems

风电场和光伏电站出力的不确定性给电力系统优化调度带来很大技术挑战。文中主要介绍了考虑新能源不确定性的电力系统优化调度方法的研究现状及后续研究方向展望。首先,重点论述了各种不确定优化调度(UOD)方法,包括随机优化方法、鲁棒优化方法、随机鲁棒优化结合方法和基于人工智能技术的方法。其中,随机优化方法包括场景法、机会约束规划法和近似动态规划法;鲁棒优化方法包括传统鲁棒优化法和分布鲁棒优化法;随机鲁棒优化结合方法包括采样鲁棒优化法和分布鲁棒机会约束规划法。然后,介绍了每一种方法的优化模型形式、模型的转化和求解原理及其优缺点。最后,对UOD的后续重点研究方向进行展望,包括兼顾多个目标的UOD问题及多目标不确定优化方法、输配系统UOD问题及分布式不确定优化方法、考虑稳定性约束的UOD问题及含常微分方程约束的不确定优化方法、考虑管道传输动态的综合能源系统UOD问题及含偏微分方程约束的不确定优化方法。

The uncertainty of the power output of wind farms and photovoltaic power plants brings significant technical challenges to the optimal dispatch of power systems.This paper mainly introduces the research status and future research direction prospect of the optimal dispatch methods for power systems considering the uncertainty of renewable energy.Firstly,various uncertain optimal dispatch(UOD)methods are discussed including stochastic optimization(SO)methods,robust optimization(RO)methods,combined SO and RO methods and artificial intelligence technology-based methods.SO methods include scenario-based method,chance-constrained programming method and approximate dynamic programming method.RO methods include traditional RO method and distributionally RO method.Combined SO and RO methods include sample RO method and distributionally robust chance-constrained programming method.Secondly,the form of the optimization model,the principles of model transformation and solution,as well as the advantages and disadvantages for each method are introduced.Finally,the future research directions of UOD are prospected,including the UOD problem with multiple objectives and the multi-objective uncertain optimization method,the UOD problem of transmission and distribution systems and the distributed uncertain optimization method,the UOD problem considering the stability constraints and the uncertain optimization method with ordinary differential equation constraints,and the UOD problem of integrated energy systems considering the pipeline transmission dynamics and the uncertain optimization method with partial differential equation constraints.