标题：Probability-Interval-Based Optimal Planning of Integrated Energy System With Uncertain Wind Power
作者：Li, Zhe; Wang, Chengfu; Li, Bowen; Wang, Jinyu; Zhao, Penghui; Zhu, Wenli; Yang, Ming; Ding, Ying
作者机构：[Li, Zhe; Wang, Chengfu; Li, Bowen; Zhu, Wenli; Yang, Ming] Shandong Univ, Sch Elect Engn, Minist Educ, Key Lab Power Syst Intelligent Dispatch & Cont 更多
会议名称：55th IEEE/IAS Industrial and Commercial Power Systems Technical Conference (ICPS)
会议日期：MAY 05-09, 2019
来源：IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
关键词：Wind power generation; Artificial neural networks; Cogeneration;; Planning; Pipelines; Power systems; Numerical models; Conditional; value-at-risk (CVaR); electricity storage system (ESS); integrated; energy system (IES); optimal planning; uncertain wind power
摘要：Owing to a higher energy supply efficiency and operational flexibility, integrated energy system (IES), including the power, heating, and gas systems, will be the primary form of energy supply in the future. However, with the increase of large-scale stochastic wind power integration, the IES planning will face a significant challenge as the traditional power system. Therefore, a probability-interval-based IES planning considering wind power integration is proposed in this article. First, a conditional value-at-risk (CVaR) based probability-interval method is developed to describe the uncertain wind power. Second, beside traditional facilities, electricity storage system is introduced to improve the flexibility of IES. Then, an expansion planning model for IES is established to minimize the total cost including investment, operation, CVaR cost, and unserved energy cost. Moreover, the piecewise linearization method is used to deal with the nonlinear integral terms of the proposed model to improve the solution efficiency. Finally, IEEE14-NGS14 and IEEE118-NGS40 systems are constructed and the planning model is solved by GAMS/CPLEX. The numerical results illustrate the correctness and effectiveness of the proposed method.