42 citations to 10.1016/j.energy.2017.04.032 (Crossref Cited-By Service)
  1. Dougal McQueen, Alan Wood, “Quantifying benefits of wind power diversity in New Zealand”, IET Renewable Power Generation, 13, no. 8, 2019, 1338  crossref
  2. Weiwu Ma, Song Fang, Gang Liu, Ruoyu Zhou, “Modeling of district load forecasting for distributed energy system”, Applied Energy, 204, 2017, 181  crossref
  3. 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  crossref
  4. 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  crossref
  5. Aliona Dreglea, Aoife Foley, Ulf Häger, Denis Sidorov, Nikita Tomin, Solving Urban Infrastructure Problems Using Smart City Technologies, 2021, 475  crossref
  6. Narjes Abbasabadi, Mehdi Ashayeri, “Urban energy use modeling methods and tools: A review and an outlook”, Building and Environment, 161, 2019, 106270  crossref
  7. 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  crossref
  8. 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  crossref
  9. 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  crossref
  10. 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  crossref
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