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Optimal scheduling of aggregated thermostatically controlled loads with renewable generation in the intraday electricity market

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  1. Ryan S. Montrose & John F. Gardner & Aykut C. Satici, 2021. "Centralized and Decentralized Optimal Control of Variable Speed Heat Pumps," Energies, MDPI, vol. 14(13), pages 1-18, July.
  2. Xiaolin Ayón & María Ángeles Moreno & Julio Usaola, 2017. "Aggregators’ Optimal Bidding Strategy in Sequential Day-Ahead and Intraday Electricity Spot Markets," Energies, MDPI, vol. 10(4), pages 1-20, April.
  3. Diaz-Londono, Cesar & Enescu, Diana & Ruiz, Fredy & Mazza, Andrea, 2020. "Experimental modeling and aggregation strategy for thermoelectric refrigeration units as flexible loads," Applied Energy, Elsevier, vol. 272(C).
  4. Vinicius Braga Ferreira da Costa & Gabriel Nasser Doyle de Doile & Gustavo Troiano & Bruno Henriques Dias & Benedito Donizeti Bonatto & Tiago Soares & Walmir de Freitas Filho, 2022. "Electricity Markets in the Context of Distributed Energy Resources and Demand Response Programs: Main Developments and Challenges Based on a Systematic Literature Review," Energies, MDPI, vol. 15(20), pages 1-43, October.
  5. Lee, Donghun & Kim, Kwanho, 2021. "PV power prediction in a peak zone using recurrent neural networks in the absence of future meteorological information," Renewable Energy, Elsevier, vol. 173(C), pages 1098-1110.
  6. Bomela, Walter & Zlotnik, Anatoly & Li, Jr-Shin, 2018. "A phase model approach for thermostatically controlled load demand response," Applied Energy, Elsevier, vol. 228(C), pages 667-680.
  7. Winstead, Christopher & Bhandari, Mahabir & Nutaro, James & Kuruganti, Teja, 2020. "Peak load reduction and load shaping in HVAC and refrigeration systems in commercial buildings by using a novel lightweight dynamic priority-based control strategy," Applied Energy, Elsevier, vol. 277(C).
  8. Zhang, Chenghua & Wu, Jianzhong & Zhou, Yue & Cheng, Meng & Long, Chao, 2018. "Peer-to-Peer energy trading in a Microgrid," Applied Energy, Elsevier, vol. 220(C), pages 1-12.
  9. Chen, Xi & Liu, Boxuan & Qiu, Jing & Shen, Wei & Reedman, Luke & Dong, Zhao Yang, 2021. "A new trading mechanism for prosumers based on flexible reliability preferences in active distribution network," Applied Energy, Elsevier, vol. 283(C).
  10. Vuelvas, José & Ruiz, Fredy & Gruosso, Giambattista, 2018. "Limiting gaming opportunities on incentive-based demand response programs," Applied Energy, Elsevier, vol. 225(C), pages 668-681.
  11. Okur, Özge & Heijnen, Petra & Lukszo, Zofia, 2021. "Aggregator’s business models in residential and service sectors: A review of operational and financial aspects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
  12. Zhong, Shengyuan & Wang, Xiaoyuan & Zhao, Jun & Li, Wenjia & Li, Hao & Wang, Yongzhen & Deng, Shuai & Zhu, Jiebei, 2021. "Deep reinforcement learning framework for dynamic pricing demand response of regenerative electric heating," Applied Energy, Elsevier, vol. 288(C).
  13. Iria, José & Soares, Filipe & Matos, Manuel, 2018. "Optimal supply and demand bidding strategy for an aggregator of small prosumers," Applied Energy, Elsevier, vol. 213(C), pages 658-669.
  14. Dong, Jingya & Song, Chunhe & Liu, Shuo & Yin, Huanhuan & Zheng, Hao & Li, Yuanjian, 2022. "Decentralized peer-to-peer energy trading strategy in energy blockchain environment: A game-theoretic approach," Applied Energy, Elsevier, vol. 325(C).
  15. Song, Yuguang & Xia, Mingchao & Chen, Qifang & Chen, Fangjian, 2023. "A data-model fusion dispatch strategy for the building energy flexibility based on the digital twin," Applied Energy, Elsevier, vol. 332(C).
  16. Wei, Congying & Xu, Jian & Liao, Siyang & Sun, Yuanzhang & Jiang, Yibo & Ke, Deping & Zhang, Zhen & Wang, Jing, 2018. "A bi-level scheduling model for virtual power plants with aggregated thermostatically controlled loads and renewable energy," Applied Energy, Elsevier, vol. 224(C), pages 659-670.
  17. Song, Yuguang & Chen, Fangjian & Xia, Mingchao & Chen, Qifang, 2022. "The interactive dispatch strategy for thermostatically controlled loads based on the source–load collaborative evolution," Applied Energy, Elsevier, vol. 309(C).
  18. Diaz, Cesar & Ruiz, Fredy & Patino, Diego, 2017. "Modeling and control of water booster pressure systems as flexible loads for demand response," Applied Energy, Elsevier, vol. 204(C), pages 106-116.
  19. Bahrami, Shahab & Amini, M. Hadi, 2018. "A decentralized trading algorithm for an electricity market with generation uncertainty," Applied Energy, Elsevier, vol. 218(C), pages 520-532.
  20. Wang, Haixin & Yang, Junyou & Chen, Zhe & Li, Gen & Liang, Jun & Ma, Yiming & Dong, Henan & Ji, Huichao & Feng, Jiawei, 2020. "Optimal dispatch based on prediction of distributed electric heating storages in combined electricity and heat networks," Applied Energy, Elsevier, vol. 267(C).
  21. Xia, Mingchao & Song, Yuguang & Chen, Qifang, 2019. "Hierarchical control of thermostatically controlled loads oriented smart buildings," Applied Energy, Elsevier, vol. 254(C).
  22. Kai Ma & Chenliang Yuan & Jie Yang & Zhixin Liu & Xinping Guan, 2017. "Switched Control Strategies of Aggregated Commercial HVAC Systems for Demand Response in Smart Grids," Energies, MDPI, vol. 10(7), pages 1-18, July.
  23. Li, Yang & Feng, Bo & Li, Guoqing & Qi, Junjian & Zhao, Dongbo & Mu, Yunfei, 2018. "Optimal distributed generation planning in active distribution networks considering integration of energy storage," Applied Energy, Elsevier, vol. 210(C), pages 1073-1081.
  24. Wang, Xiaoyu & Jia, Hongjie & Jin, Xiaolong & Mu, Yunfei & Wei, Wei & Yu, Xiaodan & Liang, Shuo, 2024. "Bi-level optimal operations for grid operator and low-carbon building prosumers with peer-to-peer energy sharing," Applied Energy, Elsevier, vol. 359(C).
  25. Wenhao Zhuo & Andrey V. Savkin & Ke Meng, 2019. "Decentralized Optimal Control of a Microgrid with Solar PV, BESS and Thermostatically Controlled Loads," Energies, MDPI, vol. 12(11), pages 1-15, June.
  26. Moreno, Blanca & Díaz, Guzmán, 2019. "The impact of virtual power plant technology composition on wholesale electricity prices: A comparative study of some European Union electricity markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 99(C), pages 100-108.
  27. Adhikari, Rajendra & Pipattanasomporn, M. & Rahman, S., 2018. "An algorithm for optimal management of aggregated HVAC power demand using smart thermostats," Applied Energy, Elsevier, vol. 217(C), pages 166-177.
  28. Luciana Marques & Wadaed Uturbey & Miguel Heleno, 2021. "An Integer Non-Cooperative Game Approach for the Transactive Control of Thermal Appliances in Energy Communities," Energies, MDPI, vol. 14(21), pages 1-22, October.
  29. Donghun Lee & Kwanho Kim, 2019. "Recurrent Neural Network-Based Hourly Prediction of Photovoltaic Power Output Using Meteorological Information," Energies, MDPI, vol. 12(2), pages 1-22, January.
  30. Pied, Marie & Anjos, Miguel F. & Malhamé, Roland P., 2020. "A flexibility product for electric water heater aggregators on electricity markets," Applied Energy, Elsevier, vol. 280(C).
  31. Jie Yang & Tongyu Liu & Huaibao Wang & Zhenhua Tian & Shihao Liu, 2019. "Optimizing the Regulation of Aggregated Thermostatically Controlled Loads by Jointly Considering Consumer Comfort and Tracking Error," Energies, MDPI, vol. 12(9), pages 1-17, May.
  32. Ibrahim Ali Kachalla & Christian Ghiaus, 2024. "Electric Water Boiler Energy Prediction: State-of-the-Art Review of Influencing Factors, Techniques, and Future Directions," Energies, MDPI, vol. 17(2), pages 1-32, January.
  33. Iria, José & Soares, Filipe & Matos, Manuel, 2019. "Optimal bidding strategy for an aggregator of prosumers in energy and secondary reserve markets," Applied Energy, Elsevier, vol. 238(C), pages 1361-1372.
  34. Wei, Congying & Xu, Jian & Liao, Siyang & Sun, Yuanzhang & Jiang, Yibo & Zhang, Zhen, 2018. "Coordination optimization of multiple thermostatically controlled load groups in distribution network with renewable energy," Applied Energy, Elsevier, vol. 231(C), pages 456-467.
  35. Kong, Xiangyu & Kong, Deqian & Yao, Jingtao & Bai, Linquan & Xiao, Jie, 2020. "Online pricing of demand response based on long short-term memory and reinforcement learning," Applied Energy, Elsevier, vol. 271(C).
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