کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5001301 1460868 2017 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Information gap decision theory approach to deal with wind power uncertainty in unit commitment
ترجمه فارسی عنوان
روش تئوری تصمیم گیری شکاف برای مقابله با عدم اطمینان انرژی باد در تعهد واحد
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی مهندسی انرژی و فناوری های برق
چکیده انگلیسی


- A robust model for unit commitment (UC) problem is proposed.
- Information gap decision theory (IGDT) is utilized to handle the wind power uncertainties.
- Risk averse (RA) and opportunity seeker (OS) strategies are developed via IGDT.
- The impact of demand flexibility on the operation costs is investigated.

The renewable energy sources (RES) integration in the electricity supply utilities can reduce the energy procurement costs as well as the environmental concerns. Wind power is the most popular form of RES which is vastly utilized worldwide. This paper proposes a robust model for unit commitment (UC) problem, minimizing the operating costs considering uncertainty of wind power generation. In order to handle the uncertainties arising from volatile nature of wind power, information gap decision theory (IGDT) is utilized, where risk averse (RA) and opportunity seeker (OS) strategies are developed. RA strategy gives a robust decision making tool for handling the severe uncertainty of wind power, whereas the OS strategy makes benefit of possible uncertainties by adjusting the decision variables in a right way. Besides, the impact of demand flexibility (or demand response) on the operation costs is also investigated. The proposed model is examined on the IEEE 118-bus test system, and its benefits over the existing stochastic programming technique is examined. The obtained results demonstrate the applicability of the proposed method to deal with the UC problem with uncertain wind power generation. It is also observed that demand flexibility has positive impacts in both RA and OS strategies.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Electric Power Systems Research - Volume 145, April 2017, Pages 137-148
نویسندگان
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