Robust and opportunistic scheduling of district integrated natural gas and power system with high wind power penetration considering demand flexibility and compressed air energy storage

被引:48
作者
Li, Yuchun [1 ]
Wang, Jinkuan [1 ]
Han, Yinghua [2 ]
Zhao, Qiang [3 ]
Fang, Xiaohan [1 ]
Cao, Zhiao [1 ]
机构
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Peoples R China
[2] Northeastern Univ Qinhuangdao, Sch Comp & Commun Engn, Qinhuangdao 066004, Hebei, Peoples R China
[3] Northeastern Univ Qinhuangdao, Sch Control Engn, Qinhuangdao 066004, Hebei, Peoples R China
关键词
DIGPS; IGDT; Robust optimization; Opportunity seeker strategy; Wind energy; CAES; DISTRIBUTION NETWORKS; RESPONSE PROGRAM; UNIT COMMITMENT; OPTIMIZATION; HUB; MODEL; GENERATION; MANAGEMENT; OPERATION; FLOW;
D O I
10.1016/j.jclepro.2020.120456
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Coordinating integrated energy system and clean energy sources, particularly wind energy, is deemed as a desirable means to alleviate the energy and environmental crisis. However, the nature of uncertainty and intermittency of wind energy is imperative to be considered for the stable operation of the system. The gas-fired generation units with fast start-up and high ramp-rate can deepen the coupling of multiple energy sources and increase system flexibility to deal with uncertainties. This paper proposes a novel day-ahead scheduling for the district integrated natural gas and power system (DIGPS) at the presence of severe uncertainty caused by high wind power penetration. A linear and flexible energy flow equation is presented to build the energy conversion and coupling of the proposed DIGPS. Moreover, information gap decision theory (IGDT) is employed to better depict the inherent uncertainty of wind power output. Two different decisions including risk averse and opportunity seeker strategies are formulated to implement the co-optimization operation of the DIGPS. Also, compressed air energy storage (CAES) and demand response program (DRP) are introduced to reduce system operation costs and the impact of wind power uncertainty. An illustrative example and a modified IEEE 33-bus distribution system are tested to demonstrate the performance of the proposed model. Numerical testing results show that the total cost has reduced 3.63% with considering DRP. Besides, compared with stochastic programming and error-based interval forecasting method, the proposed IGDT approach can obtain cost reductions of 3% and 14%, respectively. The calculation time has been reduced by 91% in comparison with stochastic programming. (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页数:19
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