Multi-energy complementary system two-stage optimization scheduling method and system considering source-storage-load cooperation

摘要

#$%^&*AU2020100983A420200716.pdf#####ABSTRACT The present disclosure provides a multi-energy complementary system two-stage optimization scheduling method and system considering source-storage-load cooperation. First-stage optimization: acquiring load data, obtaining optimal load data via optimization 5 through a genetic algorithm by taking economic optimization as an objective and user comfort degree as a constraint, and taking optimized loads as inputs of second-stage optimization. Second-stage optimization: taking a minimum operation cost as an objective to optimize output and an energy storage state of an appliance based on stochastic dynamic programming, and outputting the operation cost to the first-stage optimization. The 10 first-stage optimization and the second-stage optimization are subjected to loop iteration to obtain an optimal load curve and an optimal system operation strategy so as to realize source-load optimal matching. The present disclosure finally obtains the optimal load curves and the system operation strategy through loop iteration of two-layer optimization, and effectively unifies demand response, energy storage and stochastic optimization into 15 one optimization framework, so as to effectively solve the source-load stochastic problem, realize source-load optimal matching and further improve the economy of the system.Drawings Photovoltaic1-E -. Wind power *Electricitygridl - - ---------------- E-------P LFffffli I, ~ 4m Power Epp E p I Cooling generationunit- - - E Heating pump I storage Season conversion Q CL~ Waste heat va ve IOl IAbsorption O recovery Abo ion system I Heating I storage I E-S Heating QH , H:nd exchanger _ - - -Fuel Electricity Cooling Heating FIG. 1 First-stage: demand response layer Objective: economic optimization Load curve Operation cost Second-stage: operation optimization layer Objective: minimum operation cost FIG. 2 1