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Implementing automated residential demand response in South Korea: Consumer preferences and market potential
Affiliation:1. Department of Environment, ESAC-Polytechnic Institute of Coimbra, 3045-601 Coimbra, Portugal;2. INESC Coimbra, Rua Antero de Quental 199, 3000-033 Coimbra, Portugal;3. Department of Electrical and Computer Engineering, University of Coimbra, 3030-290 Coimbra, Portugal;4. Environmental Change Institute, University of Oxford, South Parks Road, Oxford OX1 3QY, UK;5. Centre for Social Studies, University of Coimbra, 3000-995 Coimbra, Portugal;6. Department of Mechanical Engineering, University of Aveiro, Campus de Santiago, 3810-193 Aveiro, Portugal;1. DeGroote School of Business, McMaster University, Canada;2. Department of Economics, McMaster University, Canada;1. Technology Management Economics and Policy Program, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-742, South Korea;2. Center for Transportation Research, Cockrell School of Engineering College of Engineering, The University of Texas at Austin, 1 University Station C1761, Austin, TX 78712, United States;1. Department of Electronics and Communication Engineering, Universiti Tenaga Nasional, Jalan IKRAM-UNITEN, 43000, Kajang, Selangor, Malaysia;2. Department of Computer and Software Engineering, University of Al-Mustansiriyah, 10001, Baghdad, Iraq;3. Institute of Networked & Embedded Systems/Lakeside Labs, Alpen-Adria-Universität Klagenfurt, 9020, Klagenfurt, Austria
Abstract:In recent years, electricity demand response (DR) has attracted attention as the most cost-effective way to balance the electricity grid. This study analyzes the preferences of South Korean energy consumers on residential DR and calculated the potential capacity of peak reduction in summer. The estimation demonstrates that consumers have heterogeneous preferences for automated residential DR programs and highly value reducing their monthly electricity bills. A scenario analysis shows that approximately 60.0% of metropolitan consumers in South Korea would participate in a residential DR program, and the corresponding reduction in the peak load is forecasted to be approximately 1.74 GW.
Keywords:Residential demand response  Consumer preference  Discrete choice experiment
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