Lagrangian Relaxation Based on Improved Proximal Bundle Method for Short-Term Hydrothermal Scheduling

Short-term hydrothermal scheduling (STHS) can improve water use efficiency, reduce carbon emissions, and increase economic benefits by optimizing the commitment dispatch of hydro thermal generating units together. However, limited large system scale complex hydraulic electrical constraints, STHS poses great challenges in modeling for operators. This paper presents an improved proximal bundle method (IPBM) within framework Lagrangian relaxation STHS, which incorporates expert (ES) technique into (PBM). In IPBM, initial values Lagrange multipliers are firstly determined using linear combination optimal solutions ES. Then, each time PBM declares a null step iterations, solution space is inferred from ES, orthogonal design performed to derive new updates multipliers. A case study large-scale China implemented demonstrate effectiveness proposed method. Results different cases indicate that IPBM superior standard global search ability computational providing alternative STHS.