A bottom-up energy-economic-environmental-reliability optimization framework for hybrid renewable energy systems in near-zero energy buildings under dynamic load conditions

초록

Achieving carbon neutrality in the building sector requires optimal integration of renewable energy sources and storage systems that can match variable building demand while reducing grid imports during peak periods. Conventional sizing frameworks often rely on simplified load assumptions, which can lead to suboptimal performance of hybrid renewable energy systems (HRES) under realistic operating conditions. This study presents a bottom-up energy-economic-environmental-reliability framework for sizing HRES in a multizone office building under dynamic load conditions. The framework integrates a detailed TRNSYS-based building energy model, which captures heating and cooling demands, lighting and equipment loads, thermal comfort control, and dynamic occupancy patterns under dynamic outdoor and operating conditions, with a many-objective optimization procedure for HRES component sizing. The preferred optimal HRES configuration consists of a battery system with 3 cells in series and 8 in parallel, a photovoltaic array with 12 series and 10 parallel modules, two wind turbines, a 15-kW fuel cell, and a 21-kW electrolyzer, with a total investment cost of $0.194million.TheoptimizedsystemachievedannualCO2emissionsof8212kgCO2/yr,alossofpowersupplyprobabilityof10.5$381,900, with an annualized cost of $21,339,alevelizedcostofenergyof$0.178/kWh, and a profitability index of 1.91. Annual CO2 savings reached 33,554 kgCO2 and 42,960 kgCO2 when compared with electricity supplied by the global and South Korean grid mixes, respectively. These results demonstrate the importance of dynamic-load representation for accurate HRES sizing and practical low-carbon building integration. © 2026 Elsevier Ltd

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