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Number of items: 13.

Zhao, Yongning, Xu, Xiandong, Qadrdan, Meysam and Wu, Jianzhong 2021. Optimal operation of compressor units in gas networks to provide flexibility to power systems. Applied Energy 290 , 116740. 10.1016/j.apenergy.2021.116740

Lu, Peng, Ye, Lin, Zhong, Wuzhi, Qu, Ying, Zhai, Bingxu, Tang, Yong and Zhao, Yongning 2020. A novel spatio-temporal wind power forecasting framework based on multi-output support vector machine and optimization strategy. Journal of Cleaner Production 254 , 119993. 10.1016/j.jclepro.2020.119993

Zhao, Yongning, Qadrdan, Meysam and Jenkins, Nick 2020. A modelling framework for characterising the impacts of uncertainty on energy systems. Presented at: The 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), The Hague, The Netherlands, 25-28 October 2020.

Ye, Lin, Zhang, Cihang, Lu, Peng, Tang, Yong, Zhong, Wu Zhi, Sun, Bohao, Qu, Ying, Sun, Bohao, Zhao, Yongning, Zhai, Bing Xu, Lan, Hai Bo, Sun, Huadong, Li, Zhi and He, Boyu 2019. Hierarchical model predictive control strategy based on dynamic active power dispatch for wind power cluster integration. IEEE Transactions on Power Systems 34 (6) , pp. 4617-4629. 10.1109/TPWRS.2019.2914277

Zhao, Yongning, Ye, Lin, Wang, Zheng, Wu, Linlin, Zhai, Bingxu, Lan, Haibo and Yang, Shihui 2019. Spatio-temporal Markov chain model for very-short-term wind power forecasting. Journal of Engineering 2019 (18) , pp. 5018-5022. 10.1049/joe.2018.9294

Ye, Lin, Zhang, Cihang, Xue, Hui, Li, Jiachen, Lu, Peng and Zhao, Yongning 2019. Study of assessment on capability of wind power accommodation in regional power grids. Renewable Energy 133 , pp. 647-662. 10.1016/j.renene.2018.10.042

Ye, Lin, Zhang, Yali, Zhang, Cihang, Lu, Peng, Zhao, Yongning and He, Boyu 2019. Combined Gaussian Mixture Model and cumulants for probabilistic power flow calculation of integrated wind power network. Computers and Electrical Engineering 74 , pp. 117-129. 10.1016/j.compeleceng.2019.01.010

Lu, Peng, Ye, Lin, Sun, Bohao, Zhang, Cihang, Zhao, Yongning and Teng, Jingzhu 2018. A new hybrid prediction method of ultra-short-term wind power forecasting based on EEMD-PE and LSSVM optimized by the GSA. Energies 11 (4) , -. 10.3390/en11040697

Zhao, Yongning, Ye, Lin, Pinson, Pierre, Tang, Yong and Lu, Peng 2018. Correlation-constrained and sparsity-controlled vector autoregressive model for spatio-temporal wind power forecasting. IEEE Transactions on Power Systems 33 (5) , pp. 5029-5040. 10.1109/TPWRS.2018.2794450

Zhao, Yongning, Ye, Lin, Wang, Weisheng, Sun, Huadong, Ju, Yuntao and Tang, Yong 2018. Data-driven correction approach to refine power curve of wind farm under wind curtailment. IEEE Transactions on Sustainable Energy 9 (1) , pp. 95-105. 10.1109/TSTE.2017.2717021

Ye, Lin, Zhao, Yongning, Zeng, Cheng and Zhang, Cihang 2017. Short-term wind power prediction based on spatial model. Renewable Energy 101 , pp. 1067-1074. 10.1016/j.renene.2016.09.069

Zhao, Yongning, Ye, Lin, Li, Zhi, Song, Xuri, Lang, Yansheng and Su, Jian 2016. A novel bidirectional mechanism based on time series model for wind power forecasting. Applied Energy 177 , pp. 793-803. 10.1016/j.apenergy.2016.03.096

Li, Zhi, Ye, Lin, Zhao, Yongning, Song, Xuri, Teng, Jingzhu and Jin, Jingxin 2016. Short-term wind power prediction based on extreme learning machine with error correction. Protection and Control of Modern Power Systems 1 , 1. 10.1186/s41601-016-0016-y

This list was generated on Sat Jun 12 04:09:19 2021 BST.