Techno-economic analysis of optimally hybrid photovoltaic-wind systems to meet the energy demand of a residential building in six different areas of Iran

This study aims to determine the electrical energy demands of a typical residential building and identify the most efficient and cost-effective renewable and off-grid hybrid photovoltaic-wind system (HPWS) for four different climates in Iran. To determine its energy requirements throughout the year, a residential building consisting of 36 units on 9 floors with a total substructure area of 2518.2 m² was considered in six areas: Bandar Abbas, Shiraz, Tehran, Tabriz, Yazd, and Zabol. The energy requirements contain the electrical loads of a variable refrigerant flow (VRF) system, internal equipment, and lighting, all modeled in DesignBuilder (DB) software in accordance with the standards set by Iran’s national building regulations. For validation purposes, Carrier HAP software is utilized. The outcomes are categorized across seven different energy-economic scenarios, with a detailed examination of the annual energy performance of the system with the lowest Net Present Cost (NPC) and Levelized Cost of Energy (COE). The results indicate that only in Zabol and Bandar Abbas can wind turbines (WTs) meet the annual energy demands. Additionally, due to the high solar radiation potential in the areas and the relatively high cost of WTs compared to solar photovoltaic modules (SPVMs), the use of PV array systems in all areas emerges as the most cost-effective option. Furthermore, because Bandar Abbas has the highest electrical energy consumption and Tabriz and Shiraz have the lowest and highest solar radiation potential, respectively, the lowest NPC and COE are associated with Shiraz (1,508,967,000 IRR and 13 IRR/kWh), while the highest is related to Tabriz (15,843,960,000 IRR and 132 IRR/kWh) and followed by Bandar Abbas (14,023,400,000 IRR and 87 IRR/kWh) based on the economic analysis. The implementation of this research significantly contributes to reducing environmental pollution, and its findings can be utilized for similar regions around the world.