Integrated Optimization of Energy Storage Systems in a Multi-Energy Hub with Waste Heat Recovery from Modular Multilevel Converter

This paper presents a novel reliability-constrained optimization framework for the design and sizing of a Multi-Energy Hub (MEH) that integrates Combined Heat and Power (CHP), Electrical Energy Storage Systems (ESS), Thermal Storage Systems (TSS), renewable energy sources, and uniquely waste heat recovery from a Modular Multilevel Converter (MMC). The proposed energy hub model simultaneously meets the electricity and thermal demands of an industrial consumer under real tariff conditions and climate data from Phoenix, Arizona. The key innovation lies in modeling the thermal losses of the MMC as a valuable source of heat recovery, which reduces boiler fuel consumption and operational expenditures (OPEX). The optimization framework employs a Genetic Algorithm (GA) to minimize the total cost, encompassing capital expenditure (CAPEX) and OPEX, while enforcing constraints on energy balance, storage limitations, system capacity, and permissible energy shortage. Two scenarios one with MMC heat recovery and the other without are evaluated for both summer and winter conditions. The results show that incorporating MMC heat recovery reduces total cost by up to 2.3%, mainly due to reduced gas consumption in the boiler. Furthermore, a reliability-based constraint ensures that at least 95% of the energy demand is met, minimizing Energy Not Supplied (ENS) and enhancing system resilience. The proposed method provides a scalable and flexible design tool for next-generation industrial energy systems, particularly in hot climates with highly variable energy demand. Integrating waste heat from power electronics into hybrid energy systems introduces a novel dimension in thermal-electric synergy.