Multi-Objective Optimization of Combined Heat and Power Economic Emission Dispatch in Multi-Energy Systems

This paper presents a multi-objective energy management framework for residential multi-energy systems (MES) integrating photovoltaic (PV), wind, combined heat and power (CHP), battery energy storage system (BESS), thermal energy storage (TES), electric vehicle (EV), and grid resources. The research addresses the gap in coordinated economic–environmental optimization of highly coupled residential energy assets under renewable uncertainty and time-of-use pricing. A 24-h mathematical model minimizes energy expenditure and greenhouse-gas (GHG) emissions subject to electrical and thermal balance, generation, grid, storage, and EV operational constraints. NSGA-II and SPEA2 are implemented in Python/PyMOO and evaluated under three progressively complex scenarios. The proposed framework contributes an integrated scheduling architecture and scenario-based assessment of algorithmic performance. NSGA-II achieves −2.5592 ₦/day and 0.00040 kg/day in Scenario I, and −2.68698 ₦/day and 0.000296 kg/day in Scenario II, outperforming SPEA2 on both reported objectives. In Scenario III, NSGA-II attains 75.93173 ₦/day, while SPEA2 achieves 141,584.79 kg/day emissions. Convergence results show rapid initial NSGA-II improvement followed by stabilization, whereas SPEA2 exhibits progressive, archive-based refinement of the final non-dominated solution set.