基于信息-物理解耦的电力-蒸汽联产系统协同优化调度OA

To address the insufficient dispatch feasibility caused by the mismatch between cyber-layer optimization decisions and physical-layer nonlinear responses in a power-steam cogeneration system,a multi-time-scale coordinated optimal dispatch method based on cyber-physical decoupling is proposed.Firstly,a nonlinear mechanism model is established by considering the load rate-temperature coupled efficiency of the proton exchange membrane fuel cell,auxiliary power consumption,start-up hysteresis,thermal inertia of the cooling loop,and the dynamic coefficient of performance of the heat pump.This model is used to describe the response deviation of dispatch commands during physical execution.In the day-ahead stage,forecast data are used as the baseline,and candidate dispatch schemes are generated using conservative parameters and random intensity.The operation regret,energy self-sufficiency rate,and photovoltaic utilization rate are then evaluated using the mechanism model to select the day-ahead baseline dispatch scheme.In the intra-day stage,flexible interval tracking is used to correct real-time source-load fluctuations and physical response deviations in a rolling manner.The results show that ignoring the nonlinear dynamic characteristics of key equipment leads to high-frequency energy storage regulation,unplanned external energy purchase,and photovoltaic curtailment.Compared with the traditional model predictive control strategy,the proposed method reduces the battery aging cost,curtailment penalty,and total operating cost by 54.09%,21.82%,and 4.01%,respectively.In 200 random disturbance scenarios,the median total operating cost is reduced by 5.12%,and the median photovoltaic utilization rate remains at 93.38%.These results verify that considering physical-layer nonlinear responses is necessary for improving dispatch feasibility.