A configuration of energy storage capacity based on multi-objective optimization for gas turbine and wave energy grid-connected power system

Wave energy is a promising renewable energy source, however, its inherent intermittency and fluctuation characteristics introduce challenges for stable power generation and reliable operation. This paper investigates the optimal capacity configuration of a battery-supercapacitor hybrid energy storage system for the gas turbine and wave energy grid-connected power generation system. A multi-objective optimization framework is developed considering voltage fluctuation, life-cycle cost, and loss of power supply probability. The proposed framework integrates a dynamic simulation model, a multi-objective evolutionary optimization algorithm, and a multi-criteria decision-making method to determine the optimal energy storage configuration. In the proposed system, the micro gas turbine provides dispatchable power support for long-duration power imbalance, while the battery-supercapacitor hybrid energy storage system compensates rapid power fluctuations through the complementary characteristics of batteries and supercapacitors. The results demonstrate that the proposed method effectively balances power quality, economic performance, and reliability. Compared with the initial configuration, the optimized hybrid energy storage system reduces the energy storage investment cost by 39.2% while maintaining a low loss of power supply probability of 0.52%, indicating improved economic efficiency and power supply reliability. The proposed optimization framework provides an effective approach for capacity planning of hybrid energy storage systems in wave energy-based hybrid power systems.