IDEAS home Printed from https://ideas.repec.org/r/eee/energy/v213y2020ics0360544220318727.html
   My bibliography  Save this item

Day-ahead optimal bidding and scheduling strategies for DER aggregator considering responsive uncertainty under real-time pricing

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. 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.
  2. Tao, Peng & Xu, Fei & Dong, Zengbo & Zhang, Chao & Peng, Xuefeng & Zhao, Junpeng & Li, Kangping & Wang, Fei, 2022. "Graph convolutional network-based aggregated demand response baseline load estimation," Energy, Elsevier, vol. 251(C).
  3. Chen, J.J. & Qi, B.X. & Rong, Z.K. & Peng, K. & Zhao, Y.L. & Zhang, X.H., 2021. "Multi-energy coordinated microgrid scheduling with integrated demand response for flexibility improvement," Energy, Elsevier, vol. 217(C).
  4. Iria, José & Scott, Paul & Attarha, Ahmad & Gordon, Dan & Franklin, Evan, 2022. "MV-LV network-secure bidding optimisation of an aggregator of prosumers in real-time energy and reserve markets," Energy, Elsevier, vol. 242(C).
  5. Li, Songrui & Zhang, Lihui & Nie, Lei & Wang, Jianing, 2022. "Trading strategy and benefit optimization of load aggregators in integrated energy systems considering integrated demand response: A hierarchical Stackelberg game," Energy, Elsevier, vol. 249(C).
  6. Wang, Yubin & Zheng, Yanchong & Yang, Qiang, 2023. "Day-ahead bidding strategy of regional integrated energy systems considering multiple uncertainties in electricity markets," Applied Energy, Elsevier, vol. 348(C).
  7. Seong-Hyeon Cha & Sun-Hyeok Kwak & Woong Ko, 2023. "A Robust Optimization Model of Aggregated Resources Considering Serving Ratio for Providing Reserve Power in the Joint Electricity Market," Energies, MDPI, vol. 16(20), pages 1-27, October.
  8. Carmine Cancro & Camelia Delcea & Salvatore Fabozzi & Gabriella Ferruzzi & Giorgio Graditi & Valeria Palladino & Maria Valenti, 2022. "A Profitability Analysis for an Aggregator in the Ancillary Services Market: An Italian Case Study," Energies, MDPI, vol. 15(9), pages 1-26, April.
  9. Wang, Zibo & Dong, Lei & Shi, Mengjie & Qiao, Ji & Jia, Hongjie & Mu, Yunfei & Pu, Tianjiao, 2023. "Market power modeling and restraint of aggregated prosumers in peer-to-peer energy trading: A game-theoretic approach," Applied Energy, Elsevier, vol. 348(C).
  10. Khojasteh, Meysam & Faria, Pedro & Lezama, Fernando & Vale, Zita, 2022. "Optimal strategy of electricity and natural gas aggregators in the energy and balance markets," Energy, Elsevier, vol. 257(C).
  11. Zhang, Yin & Qian, Tong & Tang, Wenhu, 2022. "Buildings-to-distribution-network integration considering power transformer loading capability and distribution network reconfiguration," Energy, Elsevier, vol. 244(PB).
  12. Wu, Hongbin & Wang, Jingjie & Lu, Junhua & Ding, Ming & Wang, Lei & Hu, Bin & Sun, Ming & Qi, Xianjun, 2022. "Bilevel load-agent-based distributed coordination decision strategy for aggregators," Energy, Elsevier, vol. 240(C).
  13. Mohammad Mehdi Davari & Hossein Ameli & Mohammad Taghi Ameli & Goran Strbac, 2022. "Impact of Local Emergency Demand Response Programs on the Operation of Electricity and Gas Systems," Energies, MDPI, vol. 15(6), pages 1-20, March.
  14. 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).
  15. Wang, Yubin & Zheng, Yanchong & Yang, Qiang, 2023. "Nash bargaining based collaborative energy management for regional integrated energy systems in uncertain electricity markets," Energy, Elsevier, vol. 269(C).
  16. Nykyri, Mikko & Kärkkäinen, Tommi J. & Levikari, Saku & Honkapuro, Samuli & Annala, Salla & Silventoinen, Pertti, 2022. "Blockchain-based balance settlement ledger for energy communities in open electricity markets," Energy, Elsevier, vol. 253(C).
  17. Wang, Yubin & Zheng, Yanchong & Yang, Qiang, 2023. "Optimal energy management of integrated energy systems for strategic participation in competitive electricity markets," Energy, Elsevier, vol. 278(PA).
  18. Zhang, Li & Gao, Yan & Zhu, Hongbo & Tao, Li, 2022. "Bi-level stochastic real-time pricing model in multi-energy generation system: A reinforcement learning approach," Energy, Elsevier, vol. 239(PA).
  19. Han, Rushuai & Hu, Qinran & Cui, Hantao & Chen, Tao & Quan, Xiangjun & Wu, Zaijun, 2022. "An optimal bidding and scheduling method for load service entities considering demand response uncertainty," Applied Energy, Elsevier, vol. 328(C).
  20. Wang, Fei & Lu, Xiaoxing & Chang, Xiqiang & Cao, Xin & Yan, Siqing & Li, Kangping & Duić, Neven & Shafie-khah, Miadreza & Catalão, João P.S., 2022. "Household profile identification for behavioral demand response: A semi-supervised learning approach using smart meter data," Energy, Elsevier, vol. 238(PB).
  21. Chang, Weiguang & Dong, Wei & Yang, Qiang, 2023. "Day-ahead bidding strategy of cloud energy storage serving multiple heterogeneous microgrids in the electricity market," Applied Energy, Elsevier, vol. 336(C).
  22. Sachin Kahawala & Daswin De Silva & Seppo Sierla & Damminda Alahakoon & Rashmika Nawaratne & Evgeny Osipov & Andrew Jennings & Valeriy Vyatkin, 2021. "Robust Multi-Step Predictor for Electricity Markets with Real-Time Pricing," Energies, MDPI, vol. 14(14), pages 1-20, July.
  23. Li, Qirui & Yang, Zhifang & Yu, Juan & Li, Wenyuan, 2023. "Impacts of previous revenues on bidding strategies in electricity market: A quantitative analysis," Applied Energy, Elsevier, vol. 345(C).
  24. Guo, Hongye & Chen, Qixin & Shahidehpour, Mohammad & Xia, Qing & Kang, Chongqing, 2022. "Bidding behaviors of GENCOs under bounded rationality with renewable energy," Energy, Elsevier, vol. 250(C).
  25. Lankeshwara, Gayan & Sharma, Rahul & Yan, Ruifeng & Saha, Tapan K., 2022. "Control algorithms to mitigate the effect of uncertainties in residential demand management," Applied Energy, Elsevier, vol. 306(PA).
  26. Chen, Xiaodong & Ge, Xinxin & Sun, Rongfu & Wang, Fei & Mi, Zengqiang, 2024. "A SVM based demand response capacity prediction model considering internal factors under composite program," Energy, Elsevier, vol. 300(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.