In the rapidly evolving energy landscape, the integration of electric vehicles (EVs) and demand response (DR) technologies is revolutionizing how power grids operate. Jincheng Tang, a researcher at the School of Electric and Information Engineering, Yunnan Minzu University, has developed a groundbreaking model that could significantly enhance the efficiency and stability of virtual power plants (VPPs). This innovative approach, published in the journal Energies, addresses the challenges posed by the increasing number of EVs and the intermittent nature of renewable energy sources.
Tang’s research introduces a two-stage dual-level dispatch optimization model for multiple VPPs, incorporating EVs and DR technologies. The model is based on a Stackelberg game, a strategic interaction where one player (the leader) makes a decision first, and the other players (the followers) respond optimally. In this context, the distribution network operator (DNO) acts as the leader, aiming to maximize profits, while the VPPs act as followers, seeking to minimize their operational costs.
The model operates in two stages: day-ahead and intraday. In the day-ahead stage, a two-layer optimization scheduling model is established. The EV layer optimizes its actions for maximum comprehensive user satisfaction, while the VPP layer focuses on minimizing operating costs and interaction power. This dual-layer approach ensures that the scheduling arrangements for each distributed energy resource are both economical and efficient.
In the intraday stage, a Stackelberg game model is constructed, where the DNO and VPPs engage in a strategic game based on electricity prices and energy consumption strategies. “The intraday stage is crucial because it allows for real-time adjustments, ensuring that the power grid remains stable and efficient,” Tang explains. “By optimizing the interaction between the DNO and VPPs, we can achieve a win-win situation for all stakeholders.”
The simulation results are impressive. The model effectively reduces user costs, increasing the comprehensive satisfaction of EV users by 20.7% and reducing VPP operating costs by 13.37%. This dual-level optimization strategy not only enhances the economic efficiency of VPPs but also ensures the stable operation of the power system.
The implications of this research are far-reaching. As the number of EVs continues to grow, so does the need for efficient and stable power grid management. Tang’s model provides a robust framework for integrating EVs into the power system, ensuring that the benefits of renewable energy and DR technologies are fully realized. “This model can be a game-changer for the energy sector,” Tang says. “It offers a practical solution to the challenges posed by the increasing integration of EVs and renewable energy sources, paving the way for a more sustainable and efficient power grid.”
The research, published in Energies, highlights the potential for significant commercial impacts. By optimizing the scheduling of distributed energy resources and reducing operational costs, VPPs can become more competitive in the energy market. This could lead to increased investment in renewable energy projects and the development of more advanced DR technologies.
As the energy sector continues to evolve, Tang’s research offers a glimpse into the future of power grid management. By leveraging the strategic interactions between DNOs and VPPs, this model could shape the development of more efficient and sustainable energy systems. The integration of EVs and DR technologies, guided by this innovative approach, could revolutionize the way we generate, distribute, and consume energy.
