MG-OPT：基于帕累托的智能多目标优化框架与含氢整合的混合可再生能源系统中的交易型能源

Abstract This paper presents Microgrid Optimization (MG-OPT), an intelligent multi-objective framework for Zero-Net Emissions Hybrid Renewable Energy Systems utilizing Mixed-Integer Linear Programming and Pareto-based optimization. MG-OPT uniquely integrates photovoltaic, wind, and fuel cell sources with hydrogen storage , optimizing across four competing objectives: minimizing costs and emissions while maximizing renewable utilization and profit through transactive energy mechanisms. Simulation results across three scenarios demonstrate remarkable performance: the baseline configuration (30 kW) achieves 95 % emissions reduction with $31 daily profit; the EV-integrated system (40 kW) maintains 75 % emissions reduction with $28 daily profit; and the advanced configuration (50 kW) accomplishes complete decarbonization while generating $45 daily profit—all compared to conventional grid-only systems. Economic analysis reveals substantial long-term viability with net positive revenue ranging from $30,331 to $45,446 over six years. While hydrogen integration requires a higher initial investment, it enables complete emission elimination in advanced configurations while enhancing system flexibility and economic returns. This research provides decision-makers with optimal trade-off solutions bridging theoretical optimization and practical implementation requirements for sustainable energy systems.