Modelling weather effects for impact analysis of residential time-of-use electricity pricing
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DOI: 10.1016/j.enpol.2017.03.015
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Cited by:
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- Blaschke, Maximilian J., 2022. "Dynamic pricing of electricity: Enabling demand response in domestic households," Energy Policy, Elsevier, vol. 164(C).
- Goulden, Murray & Spence, Alexa & Wardman, Jamie & Leygue, Caroline, 2018. "Differentiating ‘the user’ in DSR: Developing demand side response in advanced economies," Energy Policy, Elsevier, vol. 122(C), pages 176-185.
- Kaneko, Nanae & Fujimoto, Yu & Kabe, Satoshi & Hayashida, Motonari & Hayashi, Yasuhiro, 2020. "Sparse modeling approach for identifying the dominant factors affecting situation-dependent hourly electricity demand," Applied Energy, Elsevier, vol. 265(C).
- Mosquera-López, Stephanía & Uribe, Jorge M. & Manotas-Duque, Diego F., 2018. "Effect of stopping hydroelectric power generation on the dynamics of electricity prices: An event study approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 456-467.
- Kaneko, Nanae & Fujimoto, Yu & Hayashi, Yasuhiro, 2022. "Sensitivity analysis of factors relevant to extreme imbalance between procurement plans and actual demand: Case study of the Japanese electricity market," Applied Energy, Elsevier, vol. 313(C).
- Cui, Weiwei & Li, Lin, 2018. "A game-theoretic approach to optimize the Time-of-Use pricing considering customer behaviors," International Journal of Production Economics, Elsevier, vol. 201(C), pages 75-88.
- Lanlan Li & Xinpei Song & Jingjing Li & Ke Li & Jianling Jiao, 2023. "The impacts of temperature on residential electricity consumption in Anhui, China: does the electricity price matter?," Climatic Change, Springer, vol. 176(3), pages 1-26, March.
- Su, Yongxin & Zhou, Yao & Tan, Mao, 2020. "An interval optimization strategy of household multi-energy system considering tolerance degree and integrated demand response," Applied Energy, Elsevier, vol. 260(C).
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Keywords
Time-of-use pricing; Effect of weather on residential electricity demand; Regression models;All these keywords.
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