In the rapidly evolving landscape of renewable energy integration, the challenge of balancing the grid with the intermittent nature of wind power has become a critical focus for energy operators. Li Dai, a researcher at the Changjiang Institute of Survey, Planning, Design and Research in Wuhan, China, has made significant strides in addressing this challenge with a novel approach to power dispatch.
Dai’s research, recently published in the journal Energies, introduces a security-constrained multi-stage robust dynamic economic dispatch model with storage (SMRDEDS). This model is designed to handle the multiple uncertainties of wind power outputs and N-1 contingencies, which are scenarios where any single component of the system fails. “The main challenge faced by operators is how to schedule flexible resources, such as traditional generation and storage, in the future to ensure the safe and stable operation of power grids under multiple uncertainties,” Dai explains. “Our model addresses these uncertainties by making sequential operation decisions as uncertainties are revealed gradually over time.”
The SMRDEDS model stands out by incorporating a combined two-stage Benders’ decomposition and relaxed approximation–robust dual dynamic programming (RA-RDDP) algorithm. This approach not only handles the computational challenges posed by large-scale post-contingency constraints but also enhances the solution efficiency of the traditional robust dual dynamic programming (RDDP) algorithm. “The RA-RDDP algorithm uses the inner relaxed approximation and outer approximation methods to approximate the upper and lower bounds of the future cost-to-go function,” Dai elaborates. “This overcomes the convergence issue of the traditional SDDP algorithm and solution efficiency of the RDDP algorithm.”
The implications of this research for the energy sector are profound. As wind power penetration rates continue to rise, the ability to manage grid stability and ensure economic operation becomes increasingly vital. Dai’s model provides a robust framework for dispatching power plants and storage systems, ensuring that the grid remains stable even in the face of unexpected fluctuations in wind power generation. This not only enhances the reliability of the power supply but also optimizes operational costs, making it a commercially attractive solution for energy providers.
The effectiveness of the SMRDEDS model has been validated through simulations on the IEEE-3 bus, IEEE-118 bus, and the German power system. The results demonstrate that the model significantly reduces computation time and operational costs compared to traditional methods. Moreover, it ensures N-1 security constraints with fewer reserves and reserve costs, making it a highly efficient and robust solution for real-world power system scheduling.
As the energy sector continues to pivot towards renewable sources, Dai’s research offers a promising strategy for integrating wind power into the grid. By addressing the uncertainties and contingencies that come with renewable energy, this model paves the way for more stable, efficient, and cost-effective power systems. The commercial impact of this research could be transformative, enabling energy providers to leverage wind power more effectively and reliably. The future of energy dispatch may well be shaped by models like SMRDEDS, ensuring that the transition to renewable energy is both smooth and economically viable.
