Performance and Trade-Off Analysis of Hybrid Energy Systems Under Energy Trilemma

Abstract

The increasing demand for reliable, affordable, and environmentally sustainable energy presents a significant challenge for energy-intensive applications requiring continuous power supply. Hybrid energy systems, which integrate conventional generation with renewable energy technologies and energy storage, offer a practical pathway for addressing this energy trilemma. This study developed an integrated framework for evaluating hybrid energy systems under varying operating and design conditions by combining techno-economic optimization, life-cycle assessment (LCA), and multi-criteria decision analysis (MCDA). Key decision variables included renewable energy penetration, battery storage capacity, and load demand characteristics. Dynamic system models were developed in Simulink and Python and applied to multiple operating scenarios representing variations in renewable resource availability, storage utilization, and energy demand. The optimization results demonstrated a clear trade-off between economic and environmental performance. Pareto-optimal solutions achieved levelized costs of energy (LCOE) ranging from $0.1626/kWh to $0.1645/kWh while lifecycle CO2 emissions varied between 4.03 × 106 and 4.08 × 106 kg CO2. The narrow cost range indicated that substantial emission reductions could be achieved with only marginal increases in energy cost. System reliability remained consistently high across all optimized solutions, ranging from 99.00% to 99.04%, indicating that reliability constraints were satisfied throughout the design space. Results further showed that photovoltaic capacity consistently converged to its maximum value of 2000 kW, highlighting the importance of renewable penetration in reducing emissions and fuel consumption. Battery storage was identified as the primary factor influencing the cost-emission trade-off, although increasing storage capacity beyond certain levels yielded diminishing economic benefits. Multi-criteria evaluation using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) identified the most balanced configuration with a score of 0.7313, demonstrating an effective compromise between reliability, renewable penetration, cost, and emissions. The findings highlighted the value of integrated modeling and optimization approaches for supporting hybrid energy system design and provide practical guidance for achieving cost-effective, reliable, and low-carbon energy solutions in energy-intensive applications.