Uncertain Environmental Economic Dispatch of Power Grid with Solar PV Based on a Multi-objective Cross Entropy Algorithm

The penetration of renewable energies into power systems is a trend in this field. However, the randomness and uncertainty of these intermittent energy sources is also a thorny problem. Robust optimization method is introduced to solve this kind of problems in this paper. Firstly, the dynamic environmental economic load dispatch model (DEED) with solar photovoltaic is established, and then the adjustable robust optimization method is introduced to transform the initial DEED model into a robust optimization model with uncertain parameters. In order to balance the robustness of the system and the economy of the scheme, a robust cost method with improved uncertain boundary is used for decision-making. Then, a multi-objective cross entropy algorithm, namely MMOCE is used to solve the DEED problem defined by the final model. MMOCE algorithm adopts a congestion calculation technology and an external archive mechanism, and the introduction of adaptive parameter operator and cross operator further improves the performance of the algorithm. Based on the robust decision method, the MMOCE is used to solve the model, and a reasonable and reliable multi-objective solution considering the robustness and economy of the system is obtained.