Heliyon (Oct 2023)
Energy modeling to compensate for the seasonal lack of electrical and thermal energy depending on the different climates of Iran
Abstract
Renewable energy sources are in focus for environment-friendly power generation when compared to non-renewable sources. Modeling an energy system of a statistical population can shed light on the possibilities and potential of using renewable resources. In this study, energy modeling of 4 provinces of Iran with different climates is done for 2020 and 2032. The lack of energy caused by seasonal climatic impacts is compensated for by using renewable energy systems. The modeling of three different scenarios is considered to indicate different policies in each energy system strategy. The energy system's past data is gathered and analyzed to predict future data, and then the 2032 energy system is modeled using EnergyPLAN. The results show that there will be a shortage of electrical energy in summers in hot & humid and hot & dry climates, while the energy shortage for cold and temperate & humid climates is the heating demand in winters. Three scenarios of business as usual (BAU), using maximum possible renewable energy (S1), and changing the structure of the energy supply system (S2) are considered with their specification. The results indicate that by using S1, 61.42 TWh of primary energy sources (PES), and by using S2, 136.7 TWh of PES consumption is reduced. Also, for the same scenarios, 29.98 Mt less CO2 is emitted for all climates. The climatic analysis illustrates that using solar in hot & humid and hot & dry, wind and geothermal in cold, and hydropower in hot & humid and temperate & humid climates produce the most amount of renewable potential which not only compensates the lack of seasonal energy but also replace 8% of the total energy needed, previously supplied by fossil fuels. Totally for the 4 provinces, 3250 MW of hydropower, 5625 MW of solar, 650 MW of wind, and 100 MW of geothermal energy are considered while other provinces with the same climate could benefit too based on their geographical specification.
