Optimization scheduling method for regional integrated energy systems considering source and load uncertainties
The Regional Integrated Energy System(RIES)represents a crucial technological strategy for future energy solu-tions,with an emphasis on regional integration as a key developmental direction.The substantial integration of renewable energy and the diversification of load types introduce multifaceted uncertainties that significantly impact the operation of the electrical grid.In response to these issues,this paper presents an optimized RIES model that incorporates multiple uncertainties,multi-energy coupling,and Integrated Demand Response(IDR).The proposed RIES optimization model encompasses renewable energy sources,coupling devices,energy storage units,and both electrical and thermal loads.This model undergoes a comparative analy-sis of the mathematical characteristics of source and load uncertainties.To address these uncertainties,Robust Optimization(RO)is applied to new energy source variability,while Stochastic Optimization(SO)was utilized for load uncertainty character-ization.The model was then empirically validated using actual RIES data.Research findings indicated that the application of RO and SO methods for modeling source and load uncertainties enhances robustness and economic efficiency.The RIES model,con-sidering these uncertainties,effectively reduces the disparity between peak and valley loads,decreases the pressure on equipment supply,and guarantees collaborative optimization of the system's operations,thereby improving both the reliability and economic viability of the system.
computer simulationoptimization modelintegrated energy systemsuncertaintymulti-energy coupling
万方数据
维普
