Abstract
The integration of renewable energy sources, such as wind and solar power, into the grid is essential for achieving carbon peaking and neutrality goals. However, the inherent variability and unpredictability of these energy sources pose significant challenges to power system stability. Advanced energy storage systems (ESS) are critical for mitigating these challenges, with gravity energy storage systems (GESS) emerging as a promising solution due to their scalability, economic viability, and environmental benefits. This paper proposes a multi-objective economic capacity optimization model for GESS within a novel power system framework, considering the impacts on power network stability, environmental factors, and economic performance. The model is solved using an enhanced Grasshopper Optimization Algorithm (W-GOA) incorporating a whale spiral motion strategy to improve convergence and solution accuracy. Simulations on the IEEE 30-node system demonstrate that GESS reduces peak-to-valley load differences by 36.1% and curtailment rates by 42.3% (wind) and 18.7% (PV), with a 15% lower levelized cost than CAES. The results indicate that GESS effectively mitigates peak load pressures, stabilizes the grid, and provides a cost-effective solution for integrating high shares of renewable energy. This study highlights the potential of GESS as a key component in future low-carbon power systems, offering both technical and economic advantages over traditional energy storage technologies.