@inproceedings{eba3d276992d4a39b90f67f8c05a9fd7,
title = "Spinning reserve optimization with wind power output and electric vehicles considering the operator's risk preference",
abstract = "This paper presents a spinning reserve optimization model in the energy internet with gas turbines and electric vehicles to deal with wind power uncertainty. The operator's risk preference on system security and wind power consumption is taken into account in the model based on the chance constraints. The costs of expected demand loss and wind power spillage not covered by spinning reserves are incorporated in the objective function. In order to improve computational efficiency, a method is proposed to linearize the formulation of EENS and EWS. The impacts on system security, wind power consumption, and spinning reserve scheduling under different risk preferences are systematically investigated on the IEEE reliable test system RTS79. The operation characteristics of gas turbines and electric vehicles are summarized and the optimal risk-preference-related confidence levels are found.",
keywords = "electric vehicles, energy internet, risk preference, spinning reserve",
author = "Tao Qian and Xiuli Wang and Wentao Zhang and Jianxue Wang and Baorong Zhou and Siyu Lu",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017 ; Conference date: 27-11-2017 Through 28-11-2017",
year = "2017",
month = jun,
day = "28",
doi = "10.1109/EI2.2017.8245495",
language = "英语",
series = "2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--6",
booktitle = "2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017 - Proceedings",
}