Carbon-aware virtual power plant operation with DER integration and energy–carbon trading using cheetah optimization algorithm

Résumé fourni par la source

The increasing integration of distributed energy resources (DERs), including photovoltaic systems, wind turbines, battery energy storage systems, and electric vehicles, is accelerating the transition toward intelligent, low-carbon, and market-oriented power systems. In this context, virtual power plants (VPPs) have emerged as an effective solution for coordinating distributed resources and enabling flexible energy management. This study proposes a carbon-aware multi-objective optimisation framework for coordinated energy and carbon trading within VPPs using the cheetah optimisation algorithm (COA). The proposed framework enables real-time interaction among prosumers, consumers, and the utility grid while simultaneously considering operational cost reduction, carbon-emission mitigation, and efficient DER scheduling. A scalarized multi-objective formulation is developed to balance economic and environmental objectives under dynamic operating conditions. The proposed COA-based framework is validated on an IEEE-15 bus distribution system comprising multiple VPPs with integrated DERs, battery storage, and electric vehicles. The simulation results show that the proposed method can effectively improve the utilization rate of renewable energy, reduce the dependence on the grid, promote the coordinated dispatch of distributed resources and support low-carbon energy trading operations. A comparative analysis with existing optimization approaches confirms the robustness, adaptability and computational effectiveness of the proposed methodology for modern carbon-aware VPP management. The proposed framework provides a scalable and flexible foundation for future transactive energy systems with advanced market mechanisms and intelligent distributed coordination.