4.7 Article

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

期刊

JOURNAL OF CLEANER PRODUCTION
卷 256, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2020.120456

关键词

DIGPS; IGDT; Robust optimization; Opportunity seeker strategy; Wind energy; CAES

资金

  1. National Key Research and Development Program of China [2016YFB0901900]
  2. Natural Science Foundation of Hebei Province of China [F2017501107]
  3. Open Research Fund from the State Key Laboratory of Rolling and Automation, Northeastern University [2017RALKFKT003]
  4. Ph.D. Foundation of Northeastern University at Qinhuangdao [XNB201803, XNK201603]

向作者/读者索取更多资源

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.

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