Optimizing trading decisions of wind power plants with hybrid energy storage systems using backwards approximate dynamic programming
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DOI: 10.1016/j.ijpe.2021.108155
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Cited by:
- Finnah, Benedikt & Gönsch, Jochen & Ziel, Florian, 2022. "Integrated day-ahead and intraday self-schedule bidding for energy storage systems using approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 301(2), pages 726-746.
- Kim, Seokwoo & Choi, Dong Gu, 2024. "A sample robust optimal bidding model for a virtual power plant," European Journal of Operational Research, Elsevier, vol. 316(3), pages 1101-1113.
- Benedikt Finnah, 2022. "Optimal bidding functions for renewable energies in sequential electricity markets," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(1), pages 1-27, March.
- Sgarbossa, Fabio & Arena, Simone & Tang, Ou & Peron, Mirco, 2023. "Renewable hydrogen supply chains: A planning matrix and an agenda for future research," International Journal of Production Economics, Elsevier, vol. 255(C).
- Karakoyun, Ece Cigdem & Avci, Harun & Kocaman, Ayse Selin & Nadar, Emre, 2023. "Deviations from commitments: Markov decision process formulations for the role of energy storage," International Journal of Production Economics, Elsevier, vol. 255(C).
- Sgarbossa, Fabio & Arena, Simone & Tang, Ou & Peron, Mirco, 2022. "Reprint of: Renewable hydrogen supply chains: A planning matrix and an agenda for future research," International Journal of Production Economics, Elsevier, vol. 250(C).
- Zhu, Junpeng & Meng, Dexin & Dong, Xiaofeng & Fu, Zhixin & Yuan, Yue, 2023. "An integrated electricity - hydrogen market design for renewable-rich energy system considering mobile hydrogen storage," Renewable Energy, Elsevier, vol. 202(C), pages 961-972.
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Keywords
Renewable energy; Hydrogen storage; Hybrid energy storage system; Backwards approximate dynamic programming; Optimal computing budget allocation;All these keywords.
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