Economic and environmental optimal operation of the micro energy network considering hybrid energy storage systems participation

• An offshore micro energy system is designed to improve access to new energy sources and hybrid energy storage solutions. • An Economic and environmental modeling for offshore micro energy system is proposed. • Modeling CO 2 capture is done by storage systems. • Multi-performance of storage systems is implemented by power-to-gas and gas to-power systems. • PSO based-chaotic local search is used for solving optimization approach. This study proposes the pressing challenge of achieving low-carbon operations in the oil and gas sector, particularly for offshore platforms, while simultaneously ensuring the reliability of energy supply. The focus is on developing and implementing an enhanced scheduling strategy specifically designed for Offshore Micro-Energy Systems. The strategy combines new energy sources with a hybrid energy storage system that features a floating power-to-gas and associated gas storage module. An economic optimization model has been created to enhance scheduling for low-carbon operations, taking into account carbon emissions, operational costs, and the operational status of the gas turbine generator. A hybrid algorithm combining chaotic local search and particle swarm optimization is utilized to address the optimization problem. The hybrid algorithm combines the global search strengths of particle swarm optimization with chaotic local search and resulting in improved local search efficiency and better convergence to optimal solutions. Additionally, results of case studies confirm that the proposed model effectively facilitates the integration of new energy sources and hybrid energy storage systems for minimizing operational cost and CO 2 emissions. The involvement of renewable energy sources and hybrid energy storage systems results in a reduction of operating costs and CO 2 emissions by 16.8 % and 55.3 %, respectively, when compared to without their participation.