General procedure for long-term energy-environmental planning for transportation sector of developing countries with limited data based on LEAP (long-range energy alternative planning) and EnergyPLAN

Energy-environmental planning for transportation sector requires extensive data for energy carriers types, production, and consumption as well as vehicle technologies. However, in developing countries, where private transportation sector is growing at an enormous rate and energy-environmental planning is needed the most, the required relevant data are usually limited or unavailable. The objective of this study is to develop a general procedure for long-term energy-environmental planning for transportation sector in developing countries to manage GC (gasoline consumption) for LDVs (light duty vehicle), based on historical data for POP (population) and GDP (gross domestic product). The general procedure is applied to Iran, as a developing country, and several scenarios are examined. For planning purposes up to 2025, based on historical data, the Grey model is used for the needed POP and GDP forecasts, and four ANNs (artificial neural network) are designed and used for forecasts of VP (vehicle population), TV (traffic volume), VKT (average private vehicles kilometers traveled/capita), and GC up to 2025. The scenarios examined include (a) S-BAU (business as usual), (b) S-GDP (GDP growth), (c) S-PUB (public transportation improvement), and (d) S-EV (utilization of electric vehicle). Energy models LEAP (long-range energy alternative planning) and EnergyPLAN are employed for annual and hourly analyses, respectively. The results show that S-PUB is the most effective scenario for reduction in GC, environmental emissions, and resource depletion.