Research on Power Planning Based on Robust Optimization Under Carbon Trading Condition

ObjectivesIt is important to improve the processing ability of uncertain parameters in power planning.MethodsA robust power planning model based on cardinality constrained uncertainty set under carbon trading condition was proposed. To reduce the degree of uncertainty, the uncertainty scenario set with cardinality constraints was constructed, and then the concept of “uncertainty budget” was introduced to redefine the best and worst scenarios. Based on duality theory, the robust model with max-min-max three-level programming structure was transformed into equivalent mixed-integer linear programming, which was solved by Baron solver in GAMS.ResultsThe cost of carbon trading can promote a lower proportion of thermal power generation and a higher proportion of renewable energy generation. When the uncertainty budget is larger, the objective function value is lower, and the decision-making style is more conservative.ConclusionsThe power planning strategy based on robust optimization under carbon trading conditions can improve the ability to handle uncertain parameters. The planning results are robust and feasible, providing decision support for decision-makers in situations of information uncertainty.