Optimal Active Power Dispatch Using Grey Wolf Optimization for Economic and Environmental Solutions

In the field of electricity production, the producer must ensure both low production costs and satisfactory quality of the electricity supplied. Matching supply and demand is a difficult task since any shortage of supply violates the contract between the supplier and the buyer. Any increase in production is damaging to the power company's financial income because the electricity produced cannot be stored. Some academics have been interested in reducing the additional costs associated with producing electrical energy that far exceeds the energy necessary, as well as the loss of revenue in the event of a production deficit. This article investigates a multi-source electrical network, which includes wind turbines and solar cells in addition to gas turbines, in order to lower both fuel costs and CO2 emissions from gas turbines. This is accomplished using the gray wolf algorithm optimization (GWO), a nature-inspired method. The gray wolf algorithm optimization (GWO), which is inspired by nature, is used to do this. Finally, GWO's findings are compared to those of the ALO, MVO, and WOA algorithms.