Multi-objective two-stage optimization scheduling algorithm for virtual power plants considering low carbon

Abstract

Abstract With the continuous growth of energy demand, the importance of developing and utilizing low-carbon energy is becoming increasingly prominent. In this context, virtual power plant technology has been proposed. It is a technology for integrating, coordinating and optimizing distributed energy resources, which has significant effects in improving energy utilization efficiency and reducing carbon emissions. This article proposed a virtual power plant scheduling method based on multi-objective two-stage optimization scheduling algorithm considering low carbon. This method first determines the production and consumption of various energy resources in the virtual power plant, including wind power, thermal power and hydropower. Then, with the goal of minimizing costs and reducing carbon emissions, multi-objective optimization algorithms are used to allocate and schedule energy resources in the virtual power plant. On this basis, a two-stage optimization strategy was introduced, combining long-term optimization and short-term scheduling to adapt to energy allocation and scheduling needs at different time scales. The experimental results indicate that this method can effectively improve the energy utilization efficiency and economy of virtual power plants, and reduce carbon emissions.