RESEARCH ON ECONOMIC STOCHASTIC MODEL PREDICTION CONTROL METHOD OF WIND-SOLAR-HYDROGEN COUPLING SYSTEM
An optimization method based on economic stochastic model prediction control is proposed to address the impact of uncertainty on both sides of the source and load of the wind-solar-hydrogen coupling system.Firstly,according to the characteristics of the equipment in the wind-solar-hydrogen coupling system,a state-space model considering the start-stop state of the equipment is established.Then,the scenario generation technology is used to process wind and solar output,as well as electrical load prediction data to generate a scenario set that describes the system uncertainty.Finally,based on the generated scenarios,a mixed-integer linear programming problem is formulated under the designed economic stochastic model predictive control framework,and then the system is economically optimized and controlled.A scenario generation mechanism based on nonparametric prediction is proposed,which provides a scenario set that accurately describes the system's uncertainty for the economic stochastic model prediction control method.Simulation results demonstrate the effectiveness of the proposed method in addressing uncertainty in the wind-solar-hydrogen coupling system,achieving a 5.89%reduction in operating costs compared to conventional stochastic model predictive control method,and a 13.25%reduction compared to conventional model predictive control method.
wind powerPVhydrogennonparametric predictionuncertaintystochastic model predictive controlscenario generation
NETL
NSTL
万方数据
