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Modeling and simulation of consumer response to dynamic pricing with enabled technologies

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  1. Li, Lanlan & Gong, Chengzhu & Wang, Deyun & Zhu, Kejun, 2013. "Multi-agent simulation of the time-of-use pricing policy in an urban natural gas pipeline network: A case study of Zhengzhou," Energy, Elsevier, vol. 52(C), pages 37-43.
  2. Feuerriegel, Stefan & Neumann, Dirk, 2014. "Measuring the financial impact of demand response for electricity retailers," Energy Policy, Elsevier, vol. 65(C), pages 359-368.
  3. Doostizadeh, Meysam & Ghasemi, Hassan, 2012. "A day-ahead electricity pricing model based on smart metering and demand-side management," Energy, Elsevier, vol. 46(1), pages 221-230.
  4. Boßmann, Tobias & Eser, Eike Johannes, 2016. "Model-based assessment of demand-response measures—A comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1637-1656.
  5. Hungerford, Zoe & Bruce, Anna & MacGill, Iain, 2019. "The value of flexible load in power systems with high renewable energy penetration," Energy, Elsevier, vol. 188(C).
  6. Alahäivälä, Antti & Heß, Tobias & Cao, Sunliang & Lehtonen, Matti, 2015. "Analyzing the optimal coordination of a residential micro-CHP system with a power sink," Applied Energy, Elsevier, vol. 149(C), pages 326-337.
  7. Blanca Moreno & María T García-à lvarez, 2017. "Analyzing the impact of fossil fuel import reliance on electricity prices: The case of the Iberian Electricity Market," Energy & Environment, , vol. 28(7), pages 687-705, November.
  8. Vardakas, John S. & Zorba, Nizar & Verikoukis, Christos V., 2015. "Performance evaluation of power demand scheduling scenarios in a smart grid environment," Applied Energy, Elsevier, vol. 142(C), pages 164-178.
  9. Upton, J. & Murphy, M. & Shalloo, L. & Groot Koerkamp, P.W.G. & De Boer, I.J.M., 2015. "Assessing the impact of changes in the electricity price structure on dairy farm energy costs," Applied Energy, Elsevier, vol. 137(C), pages 1-8.
  10. Behboodi, Sahand & Chassin, David P. & Crawford, Curran & Djilali, Ned, 2016. "Renewable resources portfolio optimization in the presence of demand response," Applied Energy, Elsevier, vol. 162(C), pages 139-148.
  11. Mohammad Rozali, Nor Erniza & Wan Alwi, Sharifah Rafidah & Manan, Zainuddin Abdul & Klemeš, Jiří Jaromír, 2015. "Peak-off-peak load shifting for hybrid power systems based on Power Pinch Analysis," Energy, Elsevier, vol. 90(P1), pages 128-136.
  12. Rajeev, T. & Ashok, S., 2015. "Dynamic load-shifting program based on a cloud computing framework to support the integration of renewable energy sources," Applied Energy, Elsevier, vol. 146(C), pages 141-149.
  13. He, Senyu & Yin, Jianhua & Zhang, Bin & Wang, Zhaohua, 2018. "How to upgrade an enterprise’s low-carbon technologies under a carbon tax: The trade-off between tax and upgrade fee," Applied Energy, Elsevier, vol. 227(C), pages 564-573.
  14. Huang, Shiyang & Hu, Guiping, 2018. "Biomass supply contract pricing and environmental policy analysis: A simulation approach," Energy, Elsevier, vol. 145(C), pages 557-566.
  15. Gu, Chenghong & Yan, Xiaohe & Yan, Zhang & Li, Furong, 2017. "Dynamic pricing for responsive demand to increase distribution network efficiency," Applied Energy, Elsevier, vol. 205(C), pages 236-243.
  16. Gong, Chengzhu & Tang, Kai & Zhu, Kejun & Hailu, Atakelty, 2016. "An optimal time-of-use pricing for urban gas: A study with a multi-agent evolutionary game-theoretic perspective," Applied Energy, Elsevier, vol. 163(C), pages 283-294.
  17. Harris, A.R. & Rogers, Michelle Marinich & Miller, Carol J. & McElmurry, Shawn P. & Wang, Caisheng, 2015. "Residential emissions reductions through variable timing of electricity consumption," Applied Energy, Elsevier, vol. 158(C), pages 484-489.
  18. Osaru Agbonaye & Patrick Keatley & Ye Huang & Motasem Bani Mustafa & Neil Hewitt, 2020. "Design, Valuation and Comparison of Demand Response Strategies for Congestion Management," Energies, MDPI, vol. 13(22), pages 1-29, November.
  19. Wang, Ge & Zhang, Qi & Li, Hailong & McLellan, Benjamin C. & Chen, Siyuan & Li, Yan & Tian, Yulu, 2017. "Study on the promotion impact of demand response on distributed PV penetration by using non-cooperative game theoretical analysis," Applied Energy, Elsevier, vol. 185(P2), pages 1869-1878.
  20. Woo, C.K. & Sreedharan, P. & Hargreaves, J. & Kahrl, F. & Wang, J. & Horowitz, I., 2014. "A review of electricity product differentiation," Applied Energy, Elsevier, vol. 114(C), pages 262-272.
  21. Woo, C.K. & Li, R. & Shiu, A. & Horowitz, I., 2013. "Residential winter kWh responsiveness under optional time-varying pricing in British Columbia," Applied Energy, Elsevier, vol. 108(C), pages 288-297.
  22. Feuerriegel, Stefan & Neumann, Dirk, 2016. "Integration scenarios of Demand Response into electricity markets: Load shifting, financial savings and policy implications," Energy Policy, Elsevier, vol. 96(C), pages 231-240.
  23. Moreno, Blanca & García-Álvarez, María Teresa & Ramos, Carmen & Fernández-Vázquez, Esteban, 2014. "A General Maximum Entropy Econometric approach to model industrial electricity prices in Spain: A challenge for the competitiveness," Applied Energy, Elsevier, vol. 135(C), pages 815-824.
  24. Vardakas, John S. & Zorba, Nizar & Verikoukis, Christos V., 2016. "Power demand control scenarios for smart grid applications with finite number of appliances," Applied Energy, Elsevier, vol. 162(C), pages 83-98.
  25. Hugo Algarvio & Fernando Lopes, 2023. "Bilateral Contracting and Price-Based Demand Response in Multi-Agent Electricity Markets: A Study on Time-of-Use Tariffs," Energies, MDPI, vol. 16(2), pages 1-17, January.
  26. Liu, Xiuli & Moreno, Blanca & García, Ana Salomé, 2016. "A grey neural network and input-output combined forecasting model. Primary energy consumption forecasts in Spanish economic sectors," Energy, Elsevier, vol. 115(P1), pages 1042-1054.
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