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Data-driven scenario generation of renewable energy production based on controllable generative adversarial networks with interpretability

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Cited by:

  1. Elinor Ginzburg-Ganz & Eden Dina Horodi & Omar Shadafny & Uri Savir & Ram Machlev & Yoash Levron, 2025. "Statistical Foundations of Generative AI for Optimal Control Problems in Power Systems: Comprehensive Review and Future Directions," Energies, MDPI, vol. 18(10), pages 1-54, May.
  2. Mousavi, Rashin & Mousavi, Arash & Mousavi, Yashar & Tavasoli, Mahsa & Arab, Aliasghar & Kucukdemiral, Ibrahim Beklan & Alfi, Alireza & Fekih, Afef, 2025. "Revolutionizing solar energy resources: The central role of generative AI in elevating system sustainability and efficiency," Applied Energy, Elsevier, vol. 382(C).
  3. Wang, Chunling & Liu, Chunming & Zhou, Xiulin & Zhang, Gaoyuan, 2024. "Flexibility-based expansion planning of active distribution networks considering optimal operation of multi-community integrated energy systems," Energy, Elsevier, vol. 307(C).
  4. Zhang, Hanyu & Zandehshahvar, Reza & Tanneau, Mathieu & Van Hentenryck, Pascal, 2025. "Weather-informed probabilistic forecasting and scenario generation in power systems," Applied Energy, Elsevier, vol. 384(C).
  5. 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).
  6. Ma, Zherui & Wang, Jiangjiang & Feng, Yingsong & Wang, Ruikun & Zhao, Zhenghui & Chen, Hongwei, 2023. "Hydrogen yield prediction for supercritical water gasification based on generative adversarial network data augmentation," Applied Energy, Elsevier, vol. 336(C).
  7. Chen, Zhiqiang & Li, Jianbin & Cheng, Long & Liu, Xiufeng, 2023. "Federated-WDCGAN: A federated smart meter data sharing framework for privacy preservation," Applied Energy, Elsevier, vol. 334(C).
  8. Ye, Lin & Peng, Yishu & Li, Yilin & Li, Zhuo, 2024. "A novel informer-time-series generative adversarial networks for day-ahead scenario generation of wind power," Applied Energy, Elsevier, vol. 364(C).
  9. Chen, Xianqing & Dong, Wei & Yang, Lingfang & Yang, Qiang, 2023. "Scenario-based robust capacity planning of regional integrated energy systems considering carbon emissions," Renewable Energy, Elsevier, vol. 207(C), pages 359-375.
  10. Liu, Xin & Yu, Jingjia & Gong, Lin & Liu, Minxia & Xiang, Xi, 2024. "A GCN-based adaptive generative adversarial network model for short-term wind speed scenario prediction," Energy, Elsevier, vol. 294(C).
  11. Ama Ranawaka & Damminda Alahakoon & Yuan Sun & Kushan Hewapathirana, 2024. "Leveraging the Synergy of Digital Twins and Artificial Intelligence for Sustainable Power Grids: A Scoping Review," Energies, MDPI, vol. 17(21), pages 1-52, October.
  12. Lingxue Lin & Zuowei You & Fengjiao Li & Jun Liu & Chengwei Yang, 2025. "A Two-Stage Hidden Markov Model for Medium- to Long-Term Multiple Wind Farm Power Scenario Generation," Energies, MDPI, vol. 18(8), pages 1-15, April.
  13. Ali Keyvandarian & Ahmed Saif, 2024. "An Adaptive Distributionally Robust Optimization Approach for Optimal Sizing of Hybrid Renewable Energy Systems," Journal of Optimization Theory and Applications, Springer, vol. 203(2), pages 2055-2082, November.
  14. Yishan Shi & Ruipeng Guo & Yuchen Tang & Yi Lin & Zhanxin Yang, 2023. "Integrated Transmission Network Planning by Considering Wind Power’s Uncertainty and Disasters," Energies, MDPI, vol. 16(14), pages 1-25, July.
  15. Hu, Jianqiang & Fan, Yueyun & Lai, Meiyi & Yu, Jie, 2025. "Demand response of PEV networks by dynamic distributed pinning control scheme," Energy, Elsevier, vol. 317(C).
  16. He, Jiaming & Tan, Qinliang & Lv, Hanyu, 2025. "Data-driven climate resilience assessment for distributed energy systems using diffusion transformer and polynomial expansions," Applied Energy, Elsevier, vol. 380(C).
  17. Li, Zilu & Peng, Xiangang & Cui, Wenbo & Xu, Yilin & Liu, Jianan & Yuan, Haoliang & Lai, Chun Sing & Lai, Loi Lei, 2024. "A novel scenario generation method of renewable energy using improved VAEGAN with controllable interpretable features," Applied Energy, Elsevier, vol. 363(C).
  18. Li, Ding & Zhang, Yufei & Yang, Zheng & Jin, Yaohui & Xu, Yanyan, 2024. "Sensing anomaly of photovoltaic systems with sequential conditional variational autoencoder," Applied Energy, Elsevier, vol. 353(PA).
  19. Daniel Fernández Valderrama & Juan Ignacio Guerrero Alonso & Carlos León de Mora & Michela Robba, 2024. "Scenario Generation Based on Ant Colony Optimization for Modelling Stochastic Variables in Power Systems," Energies, MDPI, vol. 17(21), pages 1-14, October.
  20. Chen, Xianqing & Yang, Lingfang & Dong, Wei & Yang, Qiang, 2024. "Net-zero carbon emission oriented Bi-level optimal capacity planning of integrated energy system considering carbon capture and hydrogen facilities," Renewable Energy, Elsevier, vol. 237(PB).
  21. Wang, Yuwei & Song, Minghao & Jia, Mengyao & Shi, Lin & Li, Bingkang, 2023. "TimeGAN based distributionally robust optimization for biomass-photovoltaic-hydrogen scheduling under source-load-market uncertainties," Energy, Elsevier, vol. 284(C).
  22. Yilin Xie & Ying Xu, 2022. "Transmission Expansion Planning Considering Wind Power and Load Uncertainties," Energies, MDPI, vol. 15(19), pages 1-18, September.
  23. 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).
  24. Liuqing Gu & Jian Xu & Deping Ke & Youhan Deng & Xiaojun Hua & Yi Yu, 2024. "Short-Term Output Scenario Generation of Renewable Energy Using Transformer–Wasserstein Generative Adversarial Nets-Gradient Penalty," Sustainability, MDPI, vol. 16(24), pages 1-20, December.
  25. Kim, Jeongdong & Qi, Meng & Park, Jinwoo & Moon, Il, 2023. "Revealing the impact of renewable uncertainty on grid-assisted power-to-X: A data-driven reliability-based design optimization approach," Applied Energy, Elsevier, vol. 339(C).
  26. Liu, Jingxuan & Zang, Haixiang & Zhang, Fengchun & Cheng, Lilin & Ding, Tao & Wei, Zhinong & Sun, Guoqiang, 2023. "A hybrid meteorological data simulation framework based on time-series generative adversarial network for global daily solar radiation estimation," Renewable Energy, Elsevier, vol. 219(P1).
  27. 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).
  28. Zhao, Wei & Shao, Zhen & Yang, Shanlin & Lu, Xinhui, 2025. "A novel conditional diffusion model for joint source-load scenario generation considering both diversity and controllability," Applied Energy, Elsevier, vol. 377(PC).
  29. Huang, Nantian & Zhao, Xuanyuan & Guo, Yu & Cai, Guowei & Wang, Rijun, 2023. "Distribution network expansion planning considering a distributed hydrogen-thermal storage system based on photovoltaic development of the Whole County of China," Energy, Elsevier, vol. 278(C).
  30. Gao, Fang & Xu, Zidong & Yin, Linfei, 2024. "Bayesian deep neural networks for spatio-temporal probabilistic optimal power flow with multi-source renewable energy," Applied Energy, Elsevier, vol. 353(PA).
  31. Zhang, Xiangyu & Glaws, Andrew & Cortiella, Alexandre & Emami, Patrick & King, Ryan N., 2025. "Deep generative models in energy system applications: Review, challenges, and future directions," Applied Energy, Elsevier, vol. 380(C).
  32. Chen, Xianqing & Dong, Wei & Yang, Qiang, 2022. "Robust optimal capacity planning of grid-connected microgrid considering energy management under multi-dimensional uncertainties," Applied Energy, Elsevier, vol. 323(C).
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