Comprehensive analysis of wind-solar-salt cavern energy storage system operations: A case study on Tai’an salt cavern

• Neural networks enhance energy dispatch by accurately predicting wind and solar output. • Monthly scheduling maxes storage potential, boosting profits via strategic trading. • High internal pressure ensures stable, long-term hydrogen energy storage in salt caverns. • Optimized scheduling cuts carbon, mitigates waste in combined systems. Integrated multi-energy systems optimize energy allocation and scheduling to achieve diversified, synergistic energy use, representing a vital approach for energy transition, green development, and climate change mitigation. This study emphasizes the critical role of energy storage technologies in renewable energy grid integration, illustrated by a case study of salt caverns in Shandong Province. An integrated energy planning model combining wind, solar, hydrogen, and salt cavern storage was developed. Neural networks forecast wind and solar power generation. An optimized indicator framework and objective functions were established and solved using particle swarm optimization and the CPLEX solver, enabling multilevel optimization and multi-timescale energy dispatch analysis. Results show an average monthly emission reduction of 20–30 kilotons and economic benefits exceeding 1 million USD. Finally, FLAC3D simulations on a simplified Tai’an salt cavern model investigated long-term creep and deformation under optimized dispatch conditions. Short-term internal pressure fluctuations caused by optimization have minimal impact on cavern plastic deformation, while a minimum operational pressure near 8 MPa supports long-term cavern stability. These findings provide empirical evidence for the safe long-term operation of salt cavern hydrogen storage, laying a theoretical foundation for integrated energy system planning and advancing understanding of geological hydrogen storage safety.