In a significant advancement for the energy sector, researchers have developed a groundbreaking three-level distributed scheduling model aimed at enhancing the participation of distributed energy resources (DERs) in demand response initiatives. This innovative model, crafted by Qifeng Huang from the Marketing Service Center at the State Grid Jiangsu Electric Power Co., Ltd. in Nanjing, China, leverages the principles of conditional value-at-risk (CVaR) to address the complexities of integrating DERs into the electricity market.
As the energy landscape evolves, characterized by a growing diversity of trading entities and models, the need for effective coordination between distribution network operators (DNO), DER aggregators, and individual DERs has never been more crucial. Huang emphasizes the importance of this model, stating, “By employing the analytical target cascading method, we can create a consensus between different levels, which not only enhances decision-making power but also boosts the economic viability of DER participation in demand response.”
The model operates by establishing a demand response framework that allows for the sharing of incentive and compensation prices across its three levels. This approach amplifies the influence of DER aggregators on pricing strategies, thus fostering a more collaborative environment that encourages greater participation from DERs. The restructuring of the photovoltaic output model using CVaR theory is particularly noteworthy, enabling stakeholders to effectively measure and manage the risks associated with the inherent uncertainties of renewable energy sources.
The implications of this research are profound. With the increasing integration of DERs into the power grid, DNOs face mounting pressures to maintain stability and reliability. The proposed model not only alleviates some of this burden but also empowers DERs to optimize their scheduling based on actual output and risk preferences. Huang points out, “This model not only increases the bargaining power of DER aggregators and DERs but also enhances their enthusiasm for participating in demand response. It allows them to set prices that reflect their real-time capabilities, which is a game-changer for the sector.”
The validation of the model through numerical analysis using the IEEE 33-node distribution network showcases its practical applicability, suggesting that it can be a pivotal tool in the ongoing transition to a more decentralized and resilient energy grid. As the energy sector continues to adapt to the dual challenges of increasing demand and the need for sustainable practices, innovations like Huang’s model could play a crucial role in shaping future developments.
While the current research focuses primarily on electricity scheduling, there is potential for future studies to incorporate additional factors, such as carbon emissions and regional policies related to renewable energy. This could further enhance the model’s applicability and effectiveness in addressing the multifaceted challenges of modern energy systems.
The findings of this research were published in the journal ‘Inventions’, which translates to ‘Inventions’ in English, highlighting the innovative nature of the work. As the energy landscape continues to evolve, the insights derived from this study could pave the way for more effective and economically viable demand response strategies, ultimately benefiting both consumers and the industry at large. For more information about Qifeng Huang’s work, you can visit the Marketing Service Center, State Grid Jiangsu Electric Power Co., Ltd..
