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Modeling technological change in energy systems – From optimization to agent-based modeling

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Cited by:

  1. Koppelaar, Rembrandt H.E.M. & Keirstead, James & Shah, Nilay & Woods, Jeremy, 2016. "A review of policy analysis purpose and capabilities of electricity system models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1531-1544.
  2. Baños, R. & Manzano-Agugliaro, F. & Montoya, F.G. & Gil, C. & Alcayde, A. & Gómez, J., 2011. "Optimization methods applied to renewable and sustainable energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(4), pages 1753-1766, May.
  3. Reis, Inês F.G. & Gonçalves, Ivo & Lopes, Marta A.R. & Antunes, Carlos Henggeler, 2022. "Towards inclusive community-based energy markets: A multiagent framework," Applied Energy, Elsevier, vol. 307(C).
  4. Zhou, Xiong & Huang, Guohe & Zhu, Hua & Chen, Jiapei & Xu, Jinliang, 2015. "Chance-constrained two-stage fractional optimization for planning regional energy systems in British Columbia, Canada," Applied Energy, Elsevier, vol. 154(C), pages 663-677.
  5. Tao, Zhenmin & Moncada, Jorge Andres & Delarue, Erik, 2023. "Exploring the impact of boundedly rational power plant investment decision-making by applying prospect theory," Utilities Policy, Elsevier, vol. 82(C).
  6. Bhardwaj, Chandan & Axsen, Jonn & McCollum, David, 2022. "Which “second-best” climate policies are best? Simulating cost-effective policy mixes for passenger vehicles," Resource and Energy Economics, Elsevier, vol. 70(C).
  7. Hurmekoski, Elias & Hetemäki, Lauri, 2013. "Studying the future of the forest sector: Review and implications for long-term outlook studies," Forest Policy and Economics, Elsevier, vol. 34(C), pages 17-29.
  8. Gabbasa, Mohamed & Sopian, Kamaruzzaman & Yaakob, Zahira & Faraji Zonooz, M.Reza & Fudholi, Ahmad & Asim, Nilofar, 2013. "Review of the energy supply status for sustainable development in the Organization of Islamic Conference," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 18-28.
  9. Yousefi, Shaghayegh & Moghaddam, Mohsen Parsa & Majd, Vahid Johari, 2011. "Optimal real time pricing in an agent-based retail market using a comprehensive demand response model," Energy, Elsevier, vol. 36(9), pages 5716-5727.
  10. Ciarli, Tommaso & Savona, Maria, 2019. "Modelling the Evolution of Economic Structure and Climate Change: A Review," Ecological Economics, Elsevier, vol. 158(C), pages 51-64.
  11. Bale, Catherine S.E. & Varga, Liz & Foxon, Timothy J., 2015. "Energy and complexity: New ways forward," Applied Energy, Elsevier, vol. 138(C), pages 150-159.
  12. Mardan, Nawzad & Klahr, Roger, 2012. "Combining optimisation and simulation in an energy systems analysis of a Swedish iron foundry," Energy, Elsevier, vol. 44(1), pages 410-419.
  13. Nolting, Lars & Praktiknjo, Aaron, 2022. "The complexity dilemma – Insights from security of electricity supply assessments," Energy, Elsevier, vol. 241(C).
  14. Graeme S. Hawker & Keith R. W. Bell, 2020. "Making energy system models useful: Good practice in the modelling of multiple vectors," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 9(1), January.
  15. 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.
  16. Haghnevis, Moeed & Askin, Ronald G. & Armbruster, Dieter, 2016. "An agent-based modeling optimization approach for understanding behavior of engineered complex adaptive systems," Socio-Economic Planning Sciences, Elsevier, vol. 56(C), pages 67-87.
  17. Anna Garcia-Teruel & Yvonne Scholz & Wolfgang Weimer-Jehle & Sigrid Prehofer & Karl-Kiên Cao & Frieder Borggrefe, 2022. "Teaching Power-Sector Models Social and Political Awareness," Energies, MDPI, vol. 15(9), pages 1-24, April.
  18. Peter Lopion & Peter Markewitz & Detlef Stolten & Martin Robinius, 2019. "Cost Uncertainties in Energy System Optimization Models: A Quadratic Programming Approach for Avoiding Penny Switching Effects," Energies, MDPI, vol. 12(20), pages 1-12, October.
  19. Gong, Chengzhu & Yu, Shiwei & Zhu, Kejun & Hailu, Atakelty, 2016. "Evaluating the influence of increasing block tariffs in residential gas sector using agent-based computational economics," Energy Policy, Elsevier, vol. 92(C), pages 334-347.
  20. Li, Pei-Hao & Barazza, Elsa & Strachan, Neil, 2022. "The influences of non-optimal investments on the scale-up of smart local energy systems in the UK electricity market," Energy Policy, Elsevier, vol. 170(C).
  21. Kuznetsova, Elizaveta & Li, Yan-Fu & Ruiz, Carlos & Zio, Enrico & Ault, Graham & Bell, Keith, 2013. "Reinforcement learning for microgrid energy management," Energy, Elsevier, vol. 59(C), pages 133-146.
  22. C. Wilson & A. Grubler & N. Bauer & V. Krey & K. Riahi, 2013. "Future capacity growth of energy technologies: are scenarios consistent with historical evidence?," Climatic Change, Springer, vol. 118(2), pages 381-395, May.
  23. Chen, Huayi & Ma, Tieju, 2017. "Optimizing systematic technology adoption with heterogeneous agents," European Journal of Operational Research, Elsevier, vol. 257(1), pages 287-296.
  24. Moglianesi, Andrea & Keppo, Ilkka & Lerede, Daniele & Savoldi, Laura, 2023. "Role of technology learning in the decarbonization of the iron and steel sector: An energy system approach using a global-scale optimization model," Energy, Elsevier, vol. 274(C).
  25. Charlie Wilson:, 2010. "Growth dynamics of energy technologies: using historical patterns to validate low carbon scenarios," GRI Working Papers 32, Grantham Research Institute on Climate Change and the Environment.
  26. Dong, Cong & Huang, Guohe & Cai, Yanpeng & Li, Wei & Cheng, Guanhui, 2014. "Fuzzy interval programming for energy and environmental systems management under constraint-violation and energy-substitution effects: A case study for the City of Beijing," Energy Economics, Elsevier, vol. 46(C), pages 375-394.
  27. Matthias Kühnbach & Felix Guthoff & Anke Bekk & Ludger Eltrop, 2020. "Development of Scenarios for a Multi-Model System Analysis Based on the Example of a Cellular Energy System," Energies, MDPI, vol. 13(4), pages 1-23, February.
  28. Kim, Seunghyok & Koo, Jamin & Lee, Chang Jun & Yoon, En Sup, 2012. "Optimization of Korean energy planning for sustainability considering uncertainties in learning rates and external factors," Energy, Elsevier, vol. 44(1), pages 126-134.
  29. Ma, Tieju & Chen, Huayi, 2015. "Adoption of an emerging infrastructure with uncertain technological learning and spatial reconfiguration," European Journal of Operational Research, Elsevier, vol. 243(3), pages 995-1003.
  30. Chen, Huayi & Zhou, P., 2019. "Modeling systematic technology adoption: Can one calibrated representative agent represent heterogeneous agents?," Omega, Elsevier, vol. 89(C), pages 257-270.
  31. Lin, Q.G. & Huang, G.H., 2010. "An inexact two-stage stochastic energy systems planning model for managing greenhouse gas emission at a municipal level," Energy, Elsevier, vol. 35(5), pages 2270-2280.
  32. Mohammed, Y.S. & Mustafa, M.W. & Bashir, N., 2014. "Hybrid renewable energy systems for off-grid electric power: Review of substantial issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 527-539.
  33. Rossi, Paula & Kagatsume, Masaru, 2010. "Economic Impact of Japan's Food and Agricultural FDI on Worldwide Recipient Countries," Conference papers 332018, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
  34. Wilson, Charlie, 2010. "Growth dynamics of energy technologies: using historical patterns to validate low carbon scenarios," LSE Research Online Documents on Economics 37602, London School of Economics and Political Science, LSE Library.
  35. Cong, Rong-Gang & Wei, Yi-Ming, 2010. "Potential impact of (CET) carbon emissions trading on China’s power sector: A perspective from different allowance allocation options," Energy, Elsevier, vol. 35(9), pages 3921-3931.
  36. 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.
  37. Barazza, Elsa & Strachan, Neil, 2020. "The impact of heterogeneous market players with bounded-rationality on the electricity sector low-carbon transition," Energy Policy, Elsevier, vol. 138(C).
  38. Kraan, O. & Kramer, G.J. & Nikolic, I., 2018. "Investment in the future electricity system - An agent-based modelling approach," Energy, Elsevier, vol. 151(C), pages 569-580.
  39. Moradi, Mohammad H. & Razini, Saleh & Mahdi Hosseinian, S., 2016. "State of art of multiagent systems in power engineering: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 814-824.
  40. Poghosyan, Anush & Greetham, Danica Vukadinović & Haben, Stephen & Lee, Tamsin, 2015. "Long term individual load forecast under different electrical vehicles uptake scenarios," Applied Energy, Elsevier, vol. 157(C), pages 699-709.
  41. Chen, Huayi & Ma, Tieju, 2014. "Technology adoption with limited foresight and uncertain technological learning," European Journal of Operational Research, Elsevier, vol. 239(1), pages 266-275.
  42. Ding, Suiting & Zhang, Ming & Song, Yan, 2019. "Exploring China's carbon emissions peak for different carbon tax scenarios," Energy Policy, Elsevier, vol. 129(C), pages 1245-1252.
  43. Heo, Deung-Yong Yong, 2015. "Studies on electric power markets: preparing for the penetration of renewable resources," ISU General Staff Papers 201501010800005377, Iowa State University, Department of Economics.
  44. Liu, Zhen & Lieu, Jenny & Zhang, Xiliang, 2014. "The target decomposition model for renewable energy based on technological progress and environmental value," Energy Policy, Elsevier, vol. 68(C), pages 70-79.
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