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Development of a novel time-of-use tariff algorithm for residential prosumer price-based demand side management

Citations

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Cited by:

  1. Pereira, Diogo Santos & Marques, António Cardoso, 2020. "How should price-responsive electricity tariffs evolve? An analysis of the German net demand case," Utilities Policy, Elsevier, vol. 66(C).
  2. Vladimir Z. Gjorgievski & Nikolas G. Chatzigeorgiou & Venizelos Venizelou & Georgios C. Christoforidis & George E. Georghiou & Grigoris K. Papagiannis, 2020. "Evaluation of Load Matching Indicators in Residential PV Systems-the Case of Cyprus," Energies, MDPI, vol. 13(8), pages 1-18, April.
  3. Michał Gliński & Carsten Bojesen & Witold Rybiński & Sebastian Bykuć, 2019. "Modelling of the Biomass mCHP Unit for Power Peak Shaving in the Local Electrical Grid," Energies, MDPI, vol. 12(3), pages 1-14, January.
  4. Sulaima, Mohamad Fani & Dahlan, Nofri Yenita & Yasin, Zuhaila Mat & Rosli, Marlinda Mohd & Omar, Zulkiflee & Hassan, Mohammad Yusri, 2019. "A review of electricity pricing in peninsular Malaysia: Empirical investigation about the appropriateness of Enhanced Time of Use (ETOU) electricity tariff," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 348-367.
  5. Ouyang, Tiancheng & Qin, Peijia & Xie, Shutao & Tan, Xianlin & Pan, Mingming, 2023. "Flexible dispatch strategy of purchasing-selling electricity for coal-fired power plant based on compressed air energy storage," Energy, Elsevier, vol. 267(C).
  6. Zhang, Miao & Kang, Jiaxi & Tang, Ruixin & Xu, Fangyuan & Fan, Yiliang & Tang, Xiongming & Zhang, Haotian, 2020. "Sharing car park system for parking units of multiple EVs in a power market," Energy, Elsevier, vol. 212(C).
  7. Wanlei Xue & Xin Zhao & Yan Li & Ying Mu & Haisheng Tan & Yixin Jia & Xuejie Wang & Huiru Zhao & Yihang Zhao, 2023. "Research on the Optimal Design of Seasonal Time-of-Use Tariff Based on the Price Elasticity of Electricity Demand," Energies, MDPI, vol. 16(4), pages 1-17, February.
  8. Hua, Weiqi & Jiang, Jing & Sun, Hongjian & Tonello, Andrea M. & Qadrdan, Meysam & Wu, Jianzhong, 2022. "Data-driven prosumer-centric energy scheduling using convolutional neural networks," Applied Energy, Elsevier, vol. 308(C).
  9. Andruszkiewicz, Jerzy & Lorenc, Józef & Weychan, Agnieszka, 2020. "Seasonal variability of price elasticity of demand of households using zonal tariffs and its impact on hourly load of the power system," Energy, Elsevier, vol. 196(C).
  10. Venizelos Venizelou & Apostolos C. Tsolakis & Demetres Evagorou & Christos Patsonakis & Ioannis Koskinas & Phivos Therapontos & Lampros Zyglakis & Dimosthenis Ioannidis & George Makrides & Dimitrios T, 2023. "DSO-Aggregator Demand Response Cooperation Framework towards Reliable, Fair and Secure Flexibility Dispatch," Energies, MDPI, vol. 16(6), pages 1-21, March.
  11. Hussain, I. & Ali, S.M. & Khan, B. & Ullah, Z. & Mehmood, C.A. & Jawad, M. & Farid, U. & Haider, A., 2019. "Stochastic Wind Energy Management Model within smart grid framework: A joint Bi-directional Service Level Agreement (SLA) between smart grid and Wind Energy District Prosumers," Renewable Energy, Elsevier, vol. 134(C), pages 1017-1033.
  12. Solanke, Tirupati U. & Khatua, Pradeep K. & Ramachandaramurthy, Vigna K. & Yong, Jia Ying & Tan, Kang Miao, 2021. "Control and management of a multilevel electric vehicles infrastructure integrated with distributed resources: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
  13. Zhaoming Yang & Qi Xiang & Yuxuan He & Shiliang Peng & Michael Havbro Faber & Enrico Zio & Lili Zuo & Huai Su & Jinjun Zhang, 2023. "Resilience of Natural Gas Pipeline System: A Review and Outlook," Energies, MDPI, vol. 16(17), pages 1-19, August.
  14. Han, Yang & Lam, Jacqueline C.K. & Li, Victor O.K. & Newbery, David & Guo, Peiyang & Chan, Kelvin, 2024. "A deep learning approach for fairness-based time of use tariff design," Energy Policy, Elsevier, vol. 192(C).
  15. Ahir, Rajesh K. & Chakraborty, Basab, 2021. "A meta-analytic approach for determining the success factors for energy conservation," Energy, Elsevier, vol. 230(C).
  16. Julio A. de Bitencourt & Daniel P. Bernardon & Henrique S. Eichkoff & Vinicius J. Garcia & Daiana W. Silva & Lucas M. Chiara & Renan L. B. Gomes & Sebastian A. Butto & Solange M. K. Barbosa & Alejandr, 2023. "An Alternative Regulation of Compensation Mechanisms for Electric Energy Transgressions of Service Quality Limits in Dispersed and Seasonal Areas," Energies, MDPI, vol. 16(15), pages 1-26, July.
  17. Jicheng Liu & Fangqiu Xu & Shuaishuai Lin & Hua Cai & Suli Yan, 2018. "A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization," Energies, MDPI, vol. 11(12), pages 1-22, November.
  18. Yang, So Young & Woo, JongRoul & Lee, Wonjong, 2024. "Assessing optimized time-of-use pricing for electric vehicle charging in deep vehicle-grid integration system," Energy Economics, Elsevier, vol. 138(C).
  19. Aliakbari Sani, Sajad & Bahn, Olivier & Delage, Erick, 2022. "Affine decision rule approximation to address demand response uncertainty in smart Grids’ capacity planning," European Journal of Operational Research, Elsevier, vol. 303(1), pages 438-455.
  20. Yamamoto, Yoshihiro, 2021. "A bidirectional payment system for mitigating the supply–demand imbalance among prosumers based on the core of coalitional game theory under the enhanced use of renewable energy," Energy Economics, Elsevier, vol. 96(C).
  21. Kaur, Amrit Pal & Singh, Mukesh, 2023. "Time-of-Use tariff rates estimation for optimal demand-side management using electric vehicles," Energy, Elsevier, vol. 273(C).
  22. Venizelou, Venizelos & Makrides, George & Efthymiou, Venizelos & Georghiou, George E., 2020. "Methodology for deploying cost-optimum price-based demand side management for residential prosumers," Renewable Energy, Elsevier, vol. 153(C), pages 228-240.
  23. Hortay, Olivér & Kökény, László, 2020. "A villamosenergia-fogyasztás elhalasztásával kapcsolatos lakossági attitűd felmérése Magyarországon [A survey of popular attitudes to deferment of electricity consumption in Hungary]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 657-687.
  24. Sasaki, Kento & Aki, Hirohisa & Ikegami, Takashi, 2022. "Application of model predictive control to grid flexibility provision by distributed energy resources in residential dwellings under uncertainty," Energy, Elsevier, vol. 239(PB).
  25. Althaher, Sereen Z. & Alnaser, Sahban W. & Long, Chao & Zhou, Yue, 2024. "Introducing storage operators for coordinating residential batteries in distribution networks under time-of-use tariffs and adaptive power limits," Applied Energy, Elsevier, vol. 371(C).
  26. Cesar Diaz-Londono & José Vuelvas & Giambattista Gruosso & Carlos Adrian Correa-Florez, 2022. "Remuneration Sensitivity Analysis in Prosumer and Aggregator Strategies by Controlling Electric Vehicle Chargers," Energies, MDPI, vol. 15(19), pages 1-24, September.
  27. Kim, Hakpyeong & Choi, Heeju & Kang, Hyuna & An, Jongbaek & Yeom, Seungkeun & Hong, Taehoon, 2021. "A systematic review of the smart energy conservation system: From smart homes to sustainable smart cities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
  28. Förster, Robert & Harding, Sebastian & Buhl, Hans Ulrich, 2024. "Unleashing the economic and ecological potential of energy flexibility: Attractiveness of real-time electricity tariffs in energy crises," Energy Policy, Elsevier, vol. 185(C).
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