多源不确定性下分布式能源系统鲁棒优化调度方法综述OA

With the rapid penetration of distributed renewable generation,energy storage and heterogeneous loads,the scheduling of distributed energy systems(DESs)exhibits complex operational characteristics featured by deep coupling of multi-energy flows,multi-timescale dynamic coordination,and multi-agent interactions.Multi-source uncertainties propagate and disturb across energy carriers and time horizons,reducing system safety margins and increasing the difficulty of maintaining feasible system operation.As a result,DES scheduling is driven to evolve from deterministic cost-oriented optimization toward risk-aware and feasibility-guaranteed robust decision-making.Firstly,this paper summarizes the scheduling modeling framework for DESs.Combined with the propagation characteristics of uncertain disturbances in multi-energy conversion chains and network constraints,the main sources of uncertainties as well as their cross-carrier and cross-time-horizon propagation features are systematically analyzed.Secondly,modeling paradigms including scenario sets,uncertainty sets and distributional ambiguity sets are summ-arized,and their different impacts on scheduling feasibility and risk control are compared.Special emphasis is placed on the model formulation,solution methodologies and applicable scenarios of robust optimization,multi-stage adaptive robust optimization and distributionally robust optimization for DES scheduling.Key issues including non-anticipativity,full-scenario feasibility,conservativeness control and out-of-sample risk management are elaborated,together with their application boundaries concerning safety,economy and data dependence in DESs.Finally,future research directions for robust scheduling of DESs under uncertainties are discussed.