A Markovian wind farm generation model and its application to adequacy assessment

Shuwei Miao, Kaigui Xie, Hejun Yang, Heng-Ming Tai and Bo Hu

Renewable Energy, 2017, vol. 113, issue C, 1447-1461

Abstract: Wind profile, wake effect, and wind turbine outage create considerable impact on the energy production of a wind farm. This paper proposes a Markovian wind farm generation model that incorporates these factors. This model considers the wind farm as a generating unit with multiple generation states. The probability, frequency of occurrence, and transition rate of each state can be obtained using the collected wind profile data and wind turbine reliability parameters. The power output of each state is calculated using Jensen wake model and enumerated wind farm layouts. The proposed model is verified by a sequential Monte Carlo simulation approach using a test wind farm and recorded wind profile data from four different sites in North Dakota, USA. A state merging technique is developed to enable the application of the proposed model to adequacy assessment. The Roy Billiton Test System with a test wind farm is used to demonstrate the application of the proposed model and the procedure to adequacy assessment. Moreover, this paper investigates the influence of wake effect, peak load, seasonal wind pattern, wind turbine reliability parameters, and wind turbine type on system adequacy.

Keywords: Wind farm reliability; Markov; Wake effect; Adequacy assessment; Wind speed (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:113:y:2017:i:c:p:1447-1461

DOI: 10.1016/j.renene.2017.07.011

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