Research on Dynamic Optimization Scheduling of Electric Gas Interconnection System Based on Model Predictive Control
In the current context where electricity,natural gas and people's lives are closely intertwined,the research on the scheduling and operation of the Integrated Energy System(IPGES)for electricity gas interconnection has extremely important value and significance.At present,the operation strategies of power gas interconnected systems are mostly based on day ahead profile design,and load forecasting errors often lead to suboptimal day ahead scheduling.In response to this situation,model predictive control has shown excellent performance in dealing with uncertainty problems due to its advantages of real—time and robustness.This study optimizes the day ahead scheduling on a long time scale,and real—time online optimal scheduling is carried out based on the model predictive control method.In intraday scheduling,Kalman filtering is used for short—term load forecasting,and a rolling optimization and real—time feedback correction model is established based on the latest prediction information for multi time scale scheduling.Finally,a case study was conducted to verify that this method has better economic efficiency and supply—demand matching in the dynamic optimization scheduling of power and natural gas interconnected systems,and can effectively cope with load fluctuations.
electricity gas interconnection systemmodel predictive controldynamic optimizationkalman filtering
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