In the vast expanses of China’s deserts and Gobi regions, a new energy revolution is taking shape. Large-scale wind and solar farms are being constructed, forming the backbone of the country’s new-type power systems. However, integrating these intermittent energy sources with traditional thermal power and energy storage systems presents significant challenges. A recent study published in the *Journal of Shanghai Jiao Tong University* (Shanghai Jiaotong Daxue xuebao) offers a novel solution to these challenges, with potentially far-reaching implications for the energy sector.
The research, led by Yinguo Yang from the Electric Power Dispatching and Control Center of Guangdong Power Grid Co., Ltd., and a team from Tsinghua University, focuses on the coordinated day-ahead scheduling and real-time dispatch of wind-thermal-storage energy bases. The team’s innovative approach addresses the limited flexibility of these systems, a constraint imposed by the need to balance construction costs and carbon emissions.
“Our method determines the startup and shutdown plans of thermal units and their adjustable output ranges based on a rough prediction of wind power,” explains Yang. This day-ahead planning is followed by a real-time stage, where dispatch strategies are generated using a quantile-based rule. This approach eliminates the need for high-precision forecasts, a significant advantage given the inherent variability of wind and solar power.
The team’s method has been validated through case studies, demonstrating its effectiveness in wind-thermal-storage systems. Notably, it outperforms rolling optimization methods when the three-step prediction error exceeds 10%. This is a crucial finding, as it highlights the robustness of the method in real-world scenarios where predictions can often be inaccurate.
The commercial implications of this research are substantial. By improving the operational scheduling of large-scale new energy bases, the method can enhance the reliability and efficiency of power systems. This, in turn, can drive down costs and reduce carbon emissions, making renewable energy more competitive and attractive to investors.
Moreover, the research underscores the importance of accurate day-ahead or intraday short-term forecasts. As Yang notes, “The performance of operational scheduling can be improved by enhancing the accuracy of these forecasts.” This insight could spur advancements in forecasting technologies, further boosting the efficiency of renewable energy systems.
The study’s findings are a significant step forward in the integration of renewable energy sources into power systems. As the world grapples with the challenges of climate change and the need for sustainable energy, such innovations are more important than ever. The method proposed by Yang and his team offers a promising path forward, one that could shape the future of the energy sector and contribute to a more sustainable world.
In the words of the researchers, their method “provides valuable reference for the operation of large-scale new energy bases.” Indeed, it is a beacon of innovation in the quest for cleaner, more efficient, and more reliable energy systems.