Forecasting long-term energy demand and reductions in GHG emissions

Abstract

This work projects the long-term energy demand and assesses the effects of using renewable-energy technologies on greenhouse gas (GHG) emissions in the Marun Basin, Iran. Energy projections are made with the Low Emissions Analysis Platform (LEAP) model. Demographic and macro-economic data, per capita energy use in the urban and agricultural sectors in the Marun Basin, were gathered and input to the LEAP model to simulate the energy system in the period 2016–2040. This work’s results show that under the Business As Usual (BAU) scenario the electricity demand trend in the domestic sector would increase from 1783 MWh in 2016 to 2341 MWh by 2040. The fossil fuels consumed by the urban sector would increase from 738 million barrel of oil equivalents (BOE) in 2016 to 968 million BOE in 2040. The CO₂ emissions under the BAU scenario would increase from 27.33 million tons in 2016 to 35.87 million tons in 2040. A scenario was created to provide electricity service by means of residential solar panels (RSPs) to rural areas currently not connected to the national power grid. The LEAP model’s results show CO₂ emissions would be reduced by 17%, and 20% of the domestic diesel use would be replaced by electricity generated with solar panels.