Scenario-based forecast for the electricity demand in Qatar and the role of energy efficiency improvements
| Autor: | Massimiliano Caporin, Tommaso Di Fonzo, Ahmed A.A. Khalifa |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
020209 energy
Population electricity consumption electricity efficiency scenario-based forecast 02 engineering and technology 010501 environmental sciences Management Monitoring Policy and Law Electricity consumption 01 natural sciences Energy policy Q47 scenario-based forecast Market segmentation Hardware_GENERAL 0202 electrical engineering electronic engineering information engineering Economics Population growth Electricity market education C53 C32 0105 earth and related environmental sciences education.field_of_study electricity consumption Scenario based Electricity efficiency business.industry Scenario-based forecast Environmental economics O13 General Energy Electricity electricity efficiency business Efficient energy use |
| Popis: | We model the electricity consumption in the market segment that compose the Qatari electricity market. We link electricity consumption to GDP growth and Population Growth. Building on the estimated model, we develop long-range forecasts of electricity consumption from 2017 to 2030 over different scenarios for the economic drivers. In addition, we proxy for electricity efficiency improvements by reducing the long-run elasticity of electricity consumption to GDP and Population. We show that electricity efficiency has a crucial role in controlling the future development of electricity consumption. Energy policies should consider this aspect and support both electricity efficiency improvement programs, as well as a price reform. This paper was made possible by NPRP grant # [ NPRP9-232-5-026 ] from the Qatar National Research Fund (a member of Qatar Foundation, Qatar). The statements made herein are solely the responsibility of the authors. In addition, we thank the Conservation and Energy Efficiency Department at KAHRAMAA, the Qatar General Electricity and Water Corporation, for their cooperation and providing us with a detailed dataset that was fundamental for the estimation and forecasting process. Scopus |
| Databáze: | OpenAIRE |
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