Personalized retail pricing design for smart metering consumers in electricity market
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DOI: 10.1016/j.apenergy.2023.121545
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- Wang, Jun & Xu, Jian & Wang, Jingjing & Ke, Deping & Yao, Liangzhong & Zhou, Yue & Liao, Siyang, 2024. "Two-stage distributionally robust offering and pricing strategy for a price-maker virtual power plant," Applied Energy, Elsevier, vol. 363(C).
- Morteza Neishaboori & Alireza Arshadi Khamseh & Abolfazl Mirzazadeh & Mostafa Esmaeeli & Hamed Davari Ardakani, 2024. "Stochastic optimal pricing for retail electricity considering demand response, renewable energy sources and environmental effects," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 23(5), pages 435-451, October.
- Michalakopoulos, Vasilis & Sarmas, Elissaios & Papias, Ioannis & Skaloumpakas, Panagiotis & Marinakis, Vangelis & Doukas, Haris, 2024. "A machine learning-based framework for clustering residential electricity load profiles to enhance demand response programs," Applied Energy, Elsevier, vol. 361(C).
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Keywords
Electricity retailer; Demand response; Smart meter; Clustering model; Bi-level optimization;All these keywords.
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