Research on low-carbon optimization strategy of virtual power plant based on demand response

With rising renewable energy and electricity demand, virtual power plants (VPPs) play a crucial role in balancing supply and demand, improving efficiency, and reducing emissions. This article conducts in-depth research on low-carbon optimization scheduling strategies for virtual power plants. Firstly, a virtual power plant model considering demand response was established, including two types of loads: transferable load and reducible load, and modeled using price based and incentive based demand response strategies, respectively. Secondly, a model considering customer energy satisfaction was established to evaluate customer satisfaction from two aspects: electricity consumption behavior and electricity cost. Finally, a virtual power plant optimization model was constructed with the goal of minimizing operating costs and considering constraints on power balance and customer satisfaction. Simulation results demonstrate a 35.7% cost reduction, a 71.6% increase in renewable energy utilization, and a customer satisfaction level of 0.79.