NDLI: A practical real-time OPF method using new triangular approximate model of wind electric generators

Content Provider	IEEE Xplore Digital Library
Author	Venkatesh, B. Yu Peng
Copyright Year	2013
Description	Author affiliation: Electr. & Comput. Eng., Ryerson Univ., Toronto, ON, Canada (Venkatesh, B.) \|\| Ryerson Univ., Toronto, ON, Canada (Yu Peng)
Abstract	Near-term output forecast of wind electric generators (WEG) has uncertainties. Optimal power flow (OPF) schedules that consider forecasted output of WEGs carry risk due to these uncertainties. This risk can be quantified as expected energy not served (EENS). Traditional methods such as Monte Carlo simulation (MCS) with OPF can capture the stochastic nature of WEG output while considering ac transmission system constraints to simultaneously minimize risks from EENS and total operating costs, analyze influence of wind variability on total costs, correlate reserves and wind variability, etc. However, the MCS technique is extremely time consuming and computationally burdensome. This paper proposes a new triangular approximate distribution (TAD) model that very closely represents the normal probabilistic distribution function of forecasted wind speed to capture stochastic information of WEG output forecast and quantify EENS. This TAD model is used to formulate the proposed OPF method considering ac transmission systems to: 1) simultaneously minimize risk due to EENS and total operating costs and 2) analyze the impact of wind variability on system parameters such as EENS, operating costs, location marginal prices, and reserve costs. Tests on IEEE test systems reveal that the proposed method is accurate, fast, and suitable for real-time use.
Sponsorship	IEEE Power Energy Soc.
Starting Page	1
Ending Page	1
File Size	25874
Page Count	1
File Format	PDF
ISBN	9781479913039
ISSN	19449925
DOI	10.1109/PESMG.2013.6672957
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-21
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wind forecasting Computational modeling Real-time systems Predictive models Generators Educational institutions Uncertainty
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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