In the face of escalating climate challenges, the energy sector is grappling with unprecedented hurdles, particularly the dual threat of extreme drought and unreliable renewable energy forecasts. A groundbreaking study led by CHEN Cong, published in ‘Renmin Zhujiang’ (translated to ‘Yangtze River People’), offers a beacon of hope. The research, focusing on the intricate dance of hydropower, wind, and solar energy, promises to revolutionize how we manage and predict energy outputs during extreme weather events.
The study, which delves into the complexities of hydro-wind-solar systems, introduces a novel method for assessing the flexibility regulation capability of hydropower systems. This is particularly crucial in scenarios where renewable energy forecasts are off the mark, and hydropower generation is suddenly curtailed due to drought. “The auto-regressive moving average model (ARMA), standardized runoff index (SRI), and run theory were employed to construct inflow scenarios under extreme drought conditions,” CHEN Cong explains. This approach allows for a more accurate prediction of water inflow, which is vital for hydropower generation.
But the innovation doesn’t stop there. The research also employs kernel density estimation and Copula theory to create scenarios for wind-solar systems under extreme forecast errors. This dual-pronged approach ensures that the mid-term complementary scheduling model for hydro-wind-solar systems is both robust and adaptable. The model, which aims to minimize total operational costs, is transformed into a mixed-integer linear programming (MILP) model. This makes it more practical for real-world applications, where linear programming is often the go-to method for optimization problems.
The case study, conducted on a hydro-wind-solar integrated base in Southwest China, demonstrated the method’s effectiveness. It showed that the proposed method could quantitatively evaluate the flexibility regulation capacity of cascade hydropower systems. This is a game-changer for the energy sector, especially in regions prone to extreme drought and unreliable renewable energy forecasts.
The research also proposes operational strategies, including critical water level control and tolerance coefficient for hydropower energy storage loss. These strategies provide a theoretical framework for ensuring the secure and stable operation of hydro-wind-solar integrated bases under extreme conditions. “This research is not just about predicting the future; it’s about preparing for it,” CHEN Cong states. “By understanding and mitigating the risks associated with extreme weather events, we can ensure a more stable and reliable energy supply.”
The implications of this research are far-reaching. As the world transitions to renewable energy, the ability to predict and manage energy outputs during extreme weather events will be crucial. This study provides a roadmap for achieving this, paving the way for a more resilient and sustainable energy future. The findings, published in ‘Renmin Zhujiang’, offer a compelling case for integrating hydropower, wind, and solar energy systems. This could significantly enhance the energy sector’s ability to weather the storms of climate change, both literally and figuratively.
