Integration of conventional and renewable energy resources using artificial bee colony based combined emission and economic dispatch

Reliable and cost-effective electricity generation has been a significant problem for many years. Economic dispatch (ED) techniques have been widely used for efficient power production at minimal cost. However, conventional ED techniques have been studied considering only traditional power plants. With the depletion of fossil fuels and rising environmental concerns, many countries are shifting toward maximizing the share of renewable energy resources in their energy mix. The dispatch strategies should consider both conventional and renewable energy systems to align with this transition. Therefore, in this study, the ED of a system comprising 13 photovoltaic (PV) plants and 10 thermal generators is optimized using the binary artificial bee colony technique within a combined economic and emission dispatch (CEED) framework. Only selected expenditures, fuel and emission charges for thermal units, and the per-unit expense of PV power are considered. Moreover, both full solar radiation and reduced radiation conditions, simulating cloudy weather, are included in the CEED framework. The results demonstrate that the proposed algorithm gives satisfactory outputs, capping the PV share to 25% to maintain grid stability and leverage renewable energy benefits. Furthermore, the proposed algorithm is compared with particle swarm optimization (PSO) within the CEED framework. The comparative analysis depicts that the proposed algorithm reports less computational time than PSO.