Optimal solution of combined economic and emission dispatch problem in microgrid using a new hybrid algorithm

A microgrid (MG) can be defined as a localized power generation and distribution network operating on a small scale, designed to minimize power loss during transmission and provide a consistent supply of electricity. It is crucial to integrate accessible renewable energy sources (RESs) in order to decrease the release of detrimental pollutants from the burning of fossil fuels. This paper proposes a hybrid whale optimization algorithm combined with simulated annealing (hWOASA) to tackle the combined economic and emission dispatch (CEED) problem in an MG incorporating wind and solar power generation. The CEED formulation effectively identifies the optimal scale of diverse generation sources to attain a balance between reducing fuel costs and emissions. The suggested hybrid algorithm integrates the advantages of two optimization algorithms to improve efficacy. This fact is substantiated by contrasting the performance of the proposed hWOASA algorithm with other established algorithms across various operational scenarios in the MG. The simulation results unequivocally demonstrate the potency of the suggested hybrid algorithm, which achieves a maximum improvement of 6.69% in the CEED operating cost. Additionally, statistical analysis is conducted to further demonstrate the effectiveness of the proposed hWOASA algorithm.