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Agent-based modelling of consumer energy choices

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Cited by:

  1. Rémi Delage & Toshihiko Nakata, 2022. "Multivariate Empirical Mode Decomposition and Recurrence Quantification for the Multiscale, Spatiotemporal Analysis of Electricity Demand—A Case Study of Japan," Energies, MDPI, vol. 15(17), pages 1-17, August.
  2. Zhangqi, Zhong & Zhuli, Chen & Lingyun, He, 2022. "Technological innovation, industrial structural change and carbon emission transferring via trade-------An agent-based modeling approach," Technovation, Elsevier, vol. 110(C).
  3. Leila Niamir & Gregor Kiesewetter & Fabian Wagner & Wolfgang Schöpp & Tatiana Filatova & Alexey Voinov & Hans Bressers, 2020. "Assessing the macroeconomic impacts of individual behavioral changes on carbon emissions," Climatic Change, Springer, vol. 158(2), pages 141-160, January.
  4. Junjun Zheng & Mingmiao Yang & Gang Ma & Qian Xu & Yujie He, 2020. "Multi-Agents-Based Modeling and Simulation for Carbon Permits Trading in China: A Regional Development Perspective," IJERPH, MDPI, vol. 17(1), pages 1-20, January.
  5. Baxter Williams & Daniel Bishop & Patricio Gallardo & J. Geoffrey Chase, 2023. "Demand Side Management in Industrial, Commercial, and Residential Sectors: A Review of Constraints and Considerations," Energies, MDPI, vol. 16(13), pages 1-28, July.
  6. Fouladvand, Javanshir, 2022. "Behavioural attributes towards collective energy security in thermal energy communities: Environmental-friendly behaviour matters," Energy, Elsevier, vol. 261(PB).
  7. Nuñez-Jimenez, Alejandro & Mehta, Prakhar & Griego, Danielle, 2023. "Let it grow: How community solar policy can increase PV adoption in cities," Energy Policy, Elsevier, vol. 175(C).
  8. Zhangqi Zhong & Lingyun He, 2022. "Macro-Regional Economic Structural Change Driven by Micro-founded Technological Innovation Diffusion: An Agent-Based Computational Economic Modeling Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 471-525, February.
  9. Fabian Scheller & Frauke Wiese & Jann Michael Weinand & Dominik Franjo Dominkovi'c & Russell McKenna, 2021. "An expert survey to assess the current status and future challenges of energy system analysis," Papers 2106.15518, arXiv.org.
  10. Amir Ali Safaei Pirooz & Mohammad J. Sanjari & Young-Jin Kim & Stuart Moore & Richard Turner & Wayne W. Weaver & Dipti Srinivasan & Josep M. Guerrero & Mohammad Shahidehpour, 2023. "Adaptation of High Spatio-Temporal Resolution Weather/Load Forecast in Real-World Distributed Energy-System Operation," Energies, MDPI, vol. 16(8), pages 1-16, April.
  11. Lai, Xiaodong & Liu, Jixian & Shi, Qian & Georgiev, Georgi & Wu, Guangdong, 2017. "Driving forces for low carbon technology innovation in the building industry: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 299-315.
  12. Chappin, Emile J.L. & Schleich, Joachim & Guetlein, Marie-Charlotte & Faure, Corinne & Bouwmans, Ivo, 2022. "Linking of a multi-country discrete choice experiment and an agent-based model to simulate the diffusion of smart thermostats," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
  13. Pavlović, Boban & Ivezić, Dejan & Živković, Marija, 2022. "Transition pathways of household heating in Serbia: Analysis based on an agent-based model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
  14. Auke Hoekstra & Maarten Steinbuch & Geert Verbong, 2017. "Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation," Complexity, Hindawi, vol. 2017, pages 1-23, December.
  15. Fodstad, Marte & Crespo del Granado, Pedro & Hellemo, Lars & Knudsen, Brage Rugstad & Pisciella, Paolo & Silvast, Antti & Bordin, Chiara & Schmidt, Sarah & Straus, Julian, 2022. "Next frontiers in energy system modelling: A review on challenges and the state of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
  16. Ding, Hao & Zhou, Dequn & Zhou, P., 2020. "Optimal policy supports for renewable energy technology development: A dynamic programming model," Energy Economics, Elsevier, vol. 92(C).
  17. Vafadarnikjoo, Amin & Chalvatzis, Konstantinos & Botelho, Tiago & Bamford, David, 2023. "A stratified decision-making model for long-term planning: Application in flood risk management in Scotland," Omega, Elsevier, vol. 116(C).
  18. John E. T. Bistline & Geoffrey Blanford & John Grant & Eladio Knipping & David L. McCollum & Uarporn Nopmongcol & Heidi Scarth & Tejas Shah & Greg Yarwood, 2022. "Economy-wide evaluation of CO2 and air quality impacts of electrification in the United States," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
  19. Zhang, Tianyu & Dong, Peiwu & Zeng, Yongchao & Ju, Yanbing, 2022. "Analyzing the diffusion of competitive smart wearable devices: An agent-based multi-dimensional relative agreement model," Journal of Business Research, Elsevier, vol. 139(C), pages 90-105.
  20. Florian Knobloch & Hector Pollitt & Unnada Chewpreecha & Vassilis Daioglou & Jean-Francois Mercure, 2017. "Simulating the deep decarbonisation of residential heating for limiting global warming to 1.5C," Papers 1710.11019, arXiv.org, revised May 2018.
  21. Jianhua Zhang & Xiaolong Liu & Dimitris Ballas, 2023. "Spatial and relational peer effects on environmental behavioral imitation," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 25(4), pages 575-599, October.
  22. Nabernegg, Stefan & Bednar-Friedl, Birgit & Muñoz, Pablo & Titz, Michaela & Vogel, Johanna, 2019. "National Policies for Global Emission Reductions: Effectiveness of Carbon Emission Reductions in International Supply Chains," Ecological Economics, Elsevier, vol. 158(C), pages 146-157.
  23. Jiang, Jingjing & Ye, Bin & Liu, Junguo, 2019. "Research on the peak of CO2 emissions in the developing world: Current progress and future prospect," Applied Energy, Elsevier, vol. 235(C), pages 186-203.
  24. Brodnicke, Linda & Gabrielli, Paolo & Sansavini, Giovanni, 2023. "Impact of policies on residential multi-energy systems for consumers and prosumers," Applied Energy, Elsevier, vol. 344(C).
  25. Friedrich Krebs, 2017. "An Empirically Grounded Model of Green Electricity Adoption in Germany: Calibration, Validation and Insights into Patterns of Diffusion," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(2), pages 1-10.
  26. Heike I. Brugger & Adam Douglas Henry, 2019. "Equity of Incentives: Agent-Based Explorations of How Social Networks Influence the Efficacy of Programs to Promote Solar Adoption," Complexity, Hindawi, vol. 2019, pages 1-15, February.
  27. Lixin Zhou & Jie Lin & Yanfeng Li & Zhenyu Zhang, 2020. "Innovation Diffusion of Mobile Applications in Social Networks: A Multi-Agent System," Sustainability, MDPI, vol. 12(7), pages 1-17, April.
  28. Mittal, Anuj & Krejci, Caroline C. & Dorneich, Michael C., 2019. "An agent-based approach to designing residential renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 1008-1020.
  29. Moncada, J.A. & Verstegen, J.A. & Posada, J.A. & Junginger, M. & Lukszo, Z. & Faaij, A. & Weijnen, M., 2018. "Exploring policy options to spur the expansion of ethanol production and consumption in Brazil: An agent-based modeling approach," Energy Policy, Elsevier, vol. 123(C), pages 619-641.
  30. Knobloch, Florian & Pollitt, Hector & Chewpreecha, Unnada & Lewney, Richard & Huijbregts, Mark A.J. & Mercure, Jean-Francois, 2021. "FTT:Heat — A simulation model for technological change in the European residential heating sector," Energy Policy, Elsevier, vol. 153(C).
  31. Moon-Hyun Kim & Tae-Hyoung Tommy Gim, 2021. "Spatial Characteristics of the Diffusion of Residential Solar Photovoltaics in Urban Areas: A Case of Seoul, South Korea," IJERPH, MDPI, vol. 18(2), pages 1-16, January.
  32. Inês F. G. Reis & Ivo Gonçalves & Marta A. R. Lopes & Carlos Henggeler Antunes, 2021. "Assessing the Influence of Different Goals in Energy Communities’ Self-Sufficiency—An Optimized Multiagent Approach," Energies, MDPI, vol. 14(4), pages 1-32, February.
  33. Anna Borawska & Mariusz Borawski & Małgorzata Łatuszyńska, 2022. "Effectiveness of Electricity-Saving Communication Campaigns: Neurophysiological Approach," Energies, MDPI, vol. 15(4), pages 1-19, February.
  34. Georg Holtz & Christian Schnülle & Malcolm Yadack & Jonas Friege & Thorben Jensen & Pablo Thier & Peter Viebahn & Émile J. L. Chappin, 2020. "Using Agent-Based Models to Generate Transformation Knowledge for the German Energiewende—Potentials and Challenges Derived from Four Case Studies," Energies, MDPI, vol. 13(22), pages 1-26, November.
  35. Boza, Pal & Evgeniou, Theodoros, 2021. "Artificial intelligence to support the integration of variable renewable energy sources to the power system," Applied Energy, Elsevier, vol. 290(C).
  36. Jun Liu & Yu Qian & Yuanjun Yang & Zhidan Yang, 2022. "Can Artificial Intelligence Improve the Energy Efficiency of Manufacturing Companies? Evidence from China," IJERPH, MDPI, vol. 19(4), pages 1-18, February.
  37. Thompson, James R. & Frezza, Damon & Necioglu, Burhan & Cohen, Michael L. & Hoffman, Kenneth & Rosfjord, Kristine, 2019. "Interdependent Critical Infrastructure Model (ICIM): An agent-based model of power and water infrastructure," International Journal of Critical Infrastructure Protection, Elsevier, vol. 24(C), pages 144-165.
  38. Magnus Moglia & Aneta Podkalicka & James McGregor, 2018. "An Agent-Based Model of Residential Energy Efficiency Adoption," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 21(3), pages 1-3.
  39. Niamir, Leila & Filatova, Tatiana & Voinov, Alexey & Bressers, Hans, 2018. "Transition to low-carbon economy: Assessing cumulative impacts of individual behavioral changes," Energy Policy, Elsevier, vol. 118(C), pages 325-345.
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