Time series generative adversarial network controller for long-term smart generation control of microgrids
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DOI: 10.1016/j.apenergy.2020.116069
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- Yin, Linfei & Wu, Yunzhi, 2022. "Mode-decomposition memory reinforcement network strategy for smart generation control in multi-area power systems containing renewable energy," Applied Energy, Elsevier, vol. 307(C).
- Yin, Linfei & Lin, Chen, 2024. "Matrix Wasserstein distance generative adversarial network with gradient penalty for fast low-carbon economic dispatch of novel power systems," Energy, Elsevier, vol. 298(C).
- Yin, Linfei & Zhang, Bin, 2023. "Relaxed deep generative adversarial networks for real-time economic smart generation dispatch and control of integrated energy systems," Applied Energy, Elsevier, vol. 330(PA).
- Wang, Yihan & Wen, Zongguo & Cao, Xin & Dinga, Christian Doh, 2022. "Is information and communications technology effective for industrial energy conservation and emission reduction? Evidence from three energy-intensive industries in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
- Turowski, M. & Heidrich, B. & Weingärtner, L. & Springer, L. & Phipps, K. & Schäfer, B. & Mikut, R. & Hagenmeyer, V., 2024. "Generating synthetic energy time series: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 206(C).
- Han, Kunlun & Yang, Kai & Yin, Linfei, 2022. "Lightweight actor-critic generative adversarial networks for real-time smart generation control of microgrids," Applied Energy, Elsevier, vol. 317(C).
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- Yin, Linfei & Zheng, Da, 2024. "Decomposition prediction fractional-order PID reinforcement learning for short-term smart generation control of integrated energy systems," Applied Energy, Elsevier, vol. 355(C).
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Keywords
Generative adversarial networks; Reinforcement learning; Economic dispatch; Smart generation control; Generation commands dispatch;All these keywords.
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