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Using behavioural economic theory in modelling of demand response

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Cited by:

  1. Lin, Jin & Dong, Jun & Liu, Dongran & Zhang, Yaoyu & Ma, Tongtao, 2022. "From peak shedding to low-carbon transitions: Customer psychological factors in demand response," Energy, Elsevier, vol. 238(PA).
  2. Ran, Cuiling & Zhang, Yanzi & Yin, Ying, 2021. "Demand response to improve the shared electric vehicle planning: Managerial insights, sustainable benefits," Applied Energy, Elsevier, vol. 292(C).
  3. Gupta, S. & Maulik, A. & Das, D. & Singh, A., 2022. "Coordinated stochastic optimal energy management of grid-connected microgrids considering demand response, plug-in hybrid electric vehicles, and smart transformers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
  4. Gilson Dranka, Géremi & Ferreira, Paula & Vaz, A. Ismael F., 2022. "Co-benefits between energy efficiency and demand-response on renewable-based energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
  5. Mina Masoomi & Mostafa Panahi & Reza Samadi, 2022. "Demand side management for electricity in Iran: cost and emission analysis using LEAP modeling framework," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(4), pages 5667-5693, April.
  6. Matthew Gough & Sérgio F. Santos & Mohammed Javadi & Rui Castro & João P. S. Catalão, 2020. "Prosumer Flexibility: A Comprehensive State-of-the-Art Review and Scientometric Analysis," Energies, MDPI, vol. 13(11), pages 1-32, May.
  7. Yang, Tianyu & Guo, Qinglai & Xu, Luo & Sun, Hongbin, 2021. "Dynamic pricing for integrated energy-traffic systems from a cyber-physical-human perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 136(C).
  8. Lynch, Muireann Á. & Nolan, Sheila & Devine, Mel T. & O’Malley, Mark, 2019. "The impacts of demand response participation in capacity markets," Applied Energy, Elsevier, vol. 250(C), pages 444-451.
  9. Heinrich, Carsten & Ziras, Charalampos & Syrri, Angeliki L.A. & Bindner, Henrik W., 2020. "EcoGrid 2.0: A large-scale field trial of a local flexibility market," Applied Energy, Elsevier, vol. 261(C).
  10. Adrian Tantau & András Puskás-Tompos & Costel Stanciu & Laurentiu Fratila & Catalin Curmei, 2021. "Key Factors Which Contribute to the Participation of Consumers in Demand Response Programs and Enable the Proliferation of Renewable Energy Sources," Energies, MDPI, vol. 14(24), pages 1-22, December.
  11. Meng, Yan & Fan, Shuai & Shen, Yu & Xiao, Jucheng & He, Guangyu & Li, Zuyi, 2023. "Transmission and distribution network-constrained large-scale demand response based on locational customer directrix load for accommodating renewable energy," Applied Energy, Elsevier, vol. 350(C).
  12. Lin, Jin & Dong, Jun & Dou, Xihao & Liu, Yao & Yang, Peiwen & Ma, Tongtao, 2022. "Psychological insights for incentive-based demand response incorporating battery energy storage systems: A two-loop Stackelberg game approach," Energy, Elsevier, vol. 239(PC).
  13. Todd, Annika & Cappers, Peter & Spurlock, C. Anna & Jin, Ling, 2019. "Spillover as a cause of bias in baseline evaluation methods for demand response programs," Applied Energy, Elsevier, vol. 250(C), pages 344-357.
  14. Bing Wang & Qiran Cai & Zhenming Sun, 2020. "Determinants of Willingness to Participate in Urban Incentive-Based Energy Demand-Side Response: An Empirical Micro-Data Analysis," Sustainability, MDPI, vol. 12(19), pages 1-18, September.
  15. Wang, Bohong & Guo, Qinglai & Yu, Yang, 2022. "Mechanism design for data sharing: An electricity retail perspective," Applied Energy, Elsevier, vol. 314(C).
  16. Lim, Keumju & Lee, Jongsu & Lee, Hyunjoo, 2021. "Implementing automated residential demand response in South Korea: Consumer preferences and market potential," Utilities Policy, Elsevier, vol. 70(C).
  17. Raman, Gururaghav & Zhao, Bo & Peng, Jimmy Chih-Hsien & Weidlich, Matthias, 2022. "Adaptive incentive-based demand response with distributed non-compliance assessment," Applied Energy, Elsevier, vol. 326(C).
  18. Ziras, Charalampos & Heinrich, Carsten & Pertl, Michael & Bindner, Henrik W., 2019. "Experimental flexibility identification of aggregated residential thermal loads using behind-the-meter data," Applied Energy, Elsevier, vol. 242(C), pages 1407-1421.
  19. Puskás-Tompos András, 2022. "DR and Aggregators status in CSE Europe," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 16(1), pages 1219-1236, August.
  20. Qi Huang & Aihua Jiang & Yu Zeng & Jianan Xu, 2022. "Community Flexible Load Dispatching Model Based on Herd Mentality," Energies, MDPI, vol. 15(13), pages 1-18, June.
  21. Adrian Tantau & András Puskás-Tompos & Laurentiu Fratila & Costel Stanciu, 2021. "Acceptance of Demand Response and Aggregators as a Solution to Optimize the Relation between Energy Producers and Consumers in order to Increase the Amount of Renewable Energy in the Grid," Energies, MDPI, vol. 14(12), pages 1-19, June.
  22. Wu, Xin & Yao, Lijuan & Pi, Tanxin & Liu, Yuhang & Li, Xiang & Gong, Gangjun, 2023. "Virtual-real interaction control of hybrid load system for low-carbon energy services," Applied Energy, Elsevier, vol. 330(PB).
  23. Puskás-Tompos András, 2020. "Energy Trading Perspectives in the Digital Era," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 14(1), pages 16-27, July.
  24. Prina, Matteo Giacomo & Manzolini, Giampaolo & Moser, David & Nastasi, Benedetto & Sparber, Wolfram, 2020. "Classification and challenges of bottom-up energy system models - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 129(C).
  25. Spandagos, Constantine & Yarime, Masaru & Baark, Erik & Ng, Tze Ling, 2020. "“Triple Target” policy framework to influence household energy behavior: Satisfy, strengthen, include," Applied Energy, Elsevier, vol. 269(C).
  26. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
  27. Ma, Kai & Zhang, Rencai & Yang, Jie & Song, Debao, 2023. "Collaborative optimization scheduling of integrated energy system considering user dissatisfaction," Energy, Elsevier, vol. 274(C).
  28. Gržanić, M. & Capuder, T. & Zhang, N. & Huang, W., 2022. "Prosumers as active market participants: A systematic review of evolution of opportunities, models and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
  29. Das, Laya & Garg, Dinesh & Srinivasan, Babji, 2020. "NeuralCompression: A machine learning approach to compress high frequency measurements in smart grid," Applied Energy, Elsevier, vol. 257(C).
  30. Zhang, Chao & Lasaulce, Samson & Wang, Li & Saludjian, Lucas & Poor, H. Vincent, 2022. "A refined consumer behavior model for energy systems: Application to the pricing and energy-efficiency problems," Applied Energy, Elsevier, vol. 308(C).
  31. Qiang Wang & Thomas Dogot & Guosheng Wu & Xianlei Huang & Changbin Yin, 2019. "Residents’ Willingness for Centralized Biogas Production in Hebei and Shandong Provinces," Sustainability, MDPI, vol. 11(24), pages 1-16, December.
  32. Xiu Cheng & Jiameng Yang & Yumei Jiang & Wenbin Liu & Yang Zhang, 2022. "Determinants of Proactive Low-Carbon Consumption Behaviors: Insights from Urban Residents in Eastern China," IJERPH, MDPI, vol. 19(10), pages 1-15, May.
  33. Satoshi Nakano & Ayu Washizu, 2020. "On the Acceptability of Electricity Demand Side Management by Time of Day," Energies, MDPI, vol. 13(14), pages 1-21, July.
  34. Felipe Moraes do Nascimento & Julio Cezar Mairesse Siluk & Fernando de Souza Savian & Taís Bisognin Garlet & José Renes Pinheiro & Carlos Ramos, 2020. "Factors for Measuring Photovoltaic Adoption from the Perspective of Operators," Sustainability, MDPI, vol. 12(8), pages 1-29, April.
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