Risk-Averse Pre-Extreme Weather Events Self-Scheduling of a Wind Power Plant: A Hybrid Possibilistic-Scenario Model
سال انتشار: 1397
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 187
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شناسه ملی سند علمی:
JR_IECO-1-1_002
تاریخ نمایه سازی: 20 تیر 1401
چکیده مقاله:
This paper develops a new possibilistic-scenario model for a wind power plant to determine its optimal self-scheduling (SS) in the presence of high-impact low-probability events uncertainty. Nowadays, in the context of the power system, examining the effects of extreme weather events in the category of high-impact low-probability (HILP) events has become one of the most important issues for researchers all around the world. There are so many reports of HILP events which acknowledge that these incidents can directly affect the power plants and cause them to fail. Generally, the self-scheduling of generating units in the pre-extreme weather conditions would be different from normal conditions. In such manners, this paper tries to address the self-scheduling problem of a wind power plant in pre-extreme weather conditions. For this purpose, there are numerous uncertainty sources in the SS problem that could affect the final results which include electricity prices, wind power production and contingency-based lack of production in the face of HILP events. In this regard, this paper proposes an efficient hybrid probabilistic-possibilistic assessment tool for dealing with these uncertainties. Additionally, CVaR evaluation was used as the intrinsic risk management tool of both probabilistic and possibilistic parameters in the SS problem.
کلیدواژه ها:
Electricity market ، High-impact low-probability (HILP) events ، risk management ، Self-Scheduling ، Wind power plant
نویسندگان
Hooman Khaloie
Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
Amir Abdollahi
Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
Masoud Rashidinejad
Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran