As renewable energy sources like wind and solar power become increasingly integral to the global energy landscape, the challenge of managing their intermittency and ramp events is more pressing than ever. A recent study led by Kunpeng Zhang from the Key Laboratory of Power Grid Intelligent Dispatch and Control at Shandong University proposes a groundbreaking two-stage multi-objective optimal dispatch strategy designed to optimize the power allocation of hybrid energy storage systems (HESS). This innovative approach not only enhances the reliability of renewable energy but also holds significant commercial implications for the energy sector.
Zhang’s research, published in the ‘International Journal of Electrical Power & Energy Systems’, addresses the pressing need for effective ramp stress mitigation—a phenomenon that can lead to instability in power systems. With the increasing penetration of renewable sources, the variability of energy generation can result in sudden demand-supply mismatches, which pose risks to grid stability. “Our method focuses on optimizing the interaction between various energy storage systems, including batteries and hydrogen storage, to ensure a more reliable energy supply,” Zhang explains.
The proposed strategy operates in two stages: a day-ahead dispatch model and an intraday dispatch model. The day-ahead model assesses generation plans and available storage capacities, identifying critical time slots when adjustable reserves may fall short. This foresight allows operators to prepare for potential shortfalls, thereby enhancing grid resilience. The intraday model dynamically adjusts parameters based on real-time data, ensuring that energy dispatch is not only efficient but also responsive to changing conditions.
One of the standout features of Zhang’s research is its use of a non-isometric scaling method to improve the distribution of Pareto optimal solutions within the non-dominated sorting genetic algorithm III (NSGA-III). This advanced computational approach enhances the decision-making process, making it easier for energy managers to navigate complex trade-offs between energy loss and system reliability. “By refining how we prioritize responses from different energy storage systems, we can significantly reduce energy loss and bolster the overall efficiency of renewable energy utilization,” Zhang notes.
The implications of this research extend beyond theoretical advancements. By improving the efficiency and reliability of hybrid power generation systems, energy companies can optimize their operations, reduce costs, and increase their competitiveness in a rapidly evolving market. As countries strive to meet ambitious carbon reduction targets, innovations like Zhang’s could play a crucial role in facilitating the transition to a more sustainable energy future.
This research not only highlights the importance of advanced optimization techniques in energy management but also sets the stage for future developments in the field. As the energy sector continues to grapple with the challenges posed by renewable integration, strategies like those proposed by Zhang could become essential tools for ensuring a stable and efficient energy supply. For more information, you can visit Key Laboratory of Power Grid Intelligent Dispatch and Control, Shandong University.
