| Title |
Modelling and optimisation of long-term forecasting of electricity demand in oil-rich area, South Iran |
| ID_Doc |
75384 |
| Authors |
Pourarshad, M; Noorollahi, Y; Atabi, F; Panahi, M |
| Title |
Modelling and optimisation of long-term forecasting of electricity demand in oil-rich area, South Iran |
| Year |
2021 |
| Published |
|
| DOI |
10.1080/01430750.2021.1915381 |
| Abstract |
The present study was conducted to predict the electricity status based on scenario design and energy modelling using optimization approach by 2050 in Khuzestan, Iran. Two scenarios were proposed, one investigating the current trend called the BAU (Business as Usual) and the other SMD (Sustainable Management and Development scenario). According to the BAU scenario, electricity consumption will reach from 29.08 to 73.79 TWh during 2017-2050, reducing renewable energy sources from 30.3 to 18.9%. In addition to being more dependent on fossil fuels and increasing greenhouse gas emissions, power plant capacity will not be responsive to the peak of electricity consumption. However, this situation will be improved in the SMD scenario using consumption management strategies, increased efficiency, and resource development. Reducing electricity demand and generation by 2.5 and 28.2%, respectively, will reduce environmental externalities by 658.8 million and saves 173 MTCO2e. The SMD scenario's benefit would be equal to 6,376.8 million compared to the BAU considering all socio-economic and environmental indicators. The results show that relying on fossils to generate electricity will cost more in long-term. The SMD scenario with the participation and development of renewables with greater dispersion reduces transmission losses and optimizes electricity generation to minimize environmental hazards. |
| Author Keywords |
Energy planning; scenario-based forecasting; optimisation and modelling; electricity demand; sustainable development of Khuzestan |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Emerging Sources Citation Index (ESCI) |
| EID |
WOS:000644210900001 |
| WoS Category |
Energy & Fuels |
| Research Area |
Energy & Fuels |
| PDF |
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