Flexible and robust security-constrained unit commitment in the presence of wind power generation uncertainty
- سال انتشار: 1403
- محل انتشار: مجله آنالیز غیر خطی و کاربردها، دوره: 15، شماره: 11
- کد COI اختصاصی: JR_IJNAA-15-11_004
- زبان مقاله: انگلیسی
- تعداد مشاهده: 178
نویسندگان
Department of Electrical Engineering, Tehran Branch, Technical and Vocational University, Tehran, Iran
Department of Electrical Engineering, Shahid Bahonar University, Kerman, Iran
Morteza Jadidoleslam Zeidabadi
Faculty of Electrical Engineering, Sirjan University of Technology, Sirjan, Iran
Electrical and Computer Department, Kermanshah Brannch, Technical and Vocational University, Kermanshah, Iran
چکیده
Unreliable resources in conventional power systems have created new challenges for the users of these systems. These sources of production, including wind and solar sources, with a significant share in the power generation of many power systems, cause problems in the safe and stable operation of power systems due to uncertainty. Therefore, it is very important to provide a method or model for safe and stable operation of power systems. The main innovation of this paper is to present a new SCUC model to maximize the flexibility of the system along with reducing the operating cost in the form of a security-constrained multi-level robust optimization problem in the presence of wind uncertainty sources. Also, a set of demand response programs and rapid response hybrid cycle units are used as sources of flexibility. Accordingly, the tolerable range of uncertainty and system slope reservation is developed with a low-cost combination and with the commitment to flexible covering resources. The desired optimization problem has been solved with the help of the NCCG algorithm and the MILP method. The efficiency and reliability of this proposed model have been simulated and evaluated in IEEE ۶-bus and ۱۱۸-bus standard power systems, and the simulation results confirm the technical and economic efficiency of this model.کلیدواژه ها
SCUC, Wind Power Generation, Flexibility, robustness, Multilevel Optimization, Demand responseاطلاعات بیشتر در مورد COI
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