- Dougal McQueen, Alan Wood, “Quantifying benefits of wind power diversity in New Zealand”, IET Renewable Power Generation, 13, no. 8, 2019, 1338
- Weiwu Ma, Song Fang, Gang Liu, Ruoyu Zhou, “Modeling of district load forecasting for distributed energy system”, Applied Energy, 204, 2017, 181
- Zhen‐Long Li, Jing Xia, An Liu, Peng Li, “States prediction for solar power and wind speed using BBA‐SVM”, IET Renewable Power Generation, 13, no. 7, 2019, 1115
- Fang Liu, Ranran Li, Aliona Dreglea, “Wind Speed and Power Ultra Short-Term Robust Forecasting Based on Takagi–Sugeno Fuzzy Model”, Energies, 12, no. 18, 2019, 3551
- Aliona Dreglea, Aoife Foley, Ulf Häger, Denis Sidorov, Nikita Tomin, Solving Urban Infrastructure Problems Using Smart City Technologies, 2021, 475
- Narjes Abbasabadi, Mehdi Ashayeri, “Urban energy use modeling methods and tools: A review and an outlook”, Building and Environment, 161, 2019, 106270
- Jianxi Wang, Shida Zhang, Yonghui Sun, Xinye Du, Pengpeng Wu, Rabea Jamil Mahfoud, “Day-Ahead Optimal Dispatch for Active Distribution Network Considering Probability Model of Controllable Distributed Generation”, Front. Energy Res., 9, 2022, 814850
- Aleksandr Domyshev, Denis Sidorov, Daniil Panasetsky, Yonghui Sun, Ping Ju, Feng Wu, 2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2), 2018, 1
- Xu Qin, Yu Yong, “Fostering the efficiency of the natural resource market for a comprehensive, long-term energy transition”, Econ Change Restruct, 57, no. 3, 2024, 114
- Yang Shen, Deyi Li, Wenbo Wang, “Multi-Energy Load Prediction Method for Integrated Energy System Based on Fennec Fox Optimization Algorithm and Hybrid Kernel Extreme Learning Machine”, Entropy, 26, no. 8, 2024, 699