A Wind Farm Reliability Model Considering Both Wind Variability and Turbine Forced Outages

Sulaeman, Samer; Benidris, Mohammed; Mitra, Joydeep; Singh, Chanan

doi:10.1109/tste.2016.2614245

Cited by 85 publications

(35 citation statements)

References 35 publications

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“…Generating capacity of the unit is in this case a random variable, which can achieve l si + 1 different values. Different techniques have been used to model wind generation and integrate them to evaluate the reliability of wind-integrated power systems [7][8][9][10].…”

Section: Methodology Of Determining the Reliability Indices For Powermentioning

confidence: 99%

“…In that case the RTS-79 capacity was enhanced by wind turbines of total capacity 852 MW what makes total system capacity 4257 MW. Probabilities in Table 3 were obtained [10] by the most commonly used approach of combining wind variability and turbine output power curve [8][9]. leads to underestimation of power system reliability.…”

Section: Impact Of Wind Turbines Reliability Model On Power System Rementioning

confidence: 99%

“…This calculation was done using own computer program GRA (Generation Reliability Assessment) described in [3]. LOLE, which is the expected number of hours during a given time period (year) in which a system is unable to meet its total demand [1,3,9], was chosen as reliability index. The results in case A seems to be the most accurate (real number of wind units and multi-stage wind unit reliability model), so we assuming case A as reference.…”

Section: Impact Of Wind Turbines Reliability Model On Power System Rementioning

confidence: 99%

“…The power system ability to cover the load in both cases: including and excluding the additional generating capacity of wind turbines are calculated for the same level of system reliability. The assumed LOLPs (Loss of peak Load Probability -another often used generation reliability index, defined as the probability of encountering event in which a system is unable to meet its peak demand during a given time period [1,3,[7][8][9][10]) level is equal to 0.015. The calculation of reliability for different peak load values, and for different wind generation shares were preformed.…”

Section: Impact Of Wind Generation Share On Power System Reliabilitymentioning

confidence: 99%

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Impact of wind turbines reliability models on the power generation system reliability

2019

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In this paper we describe the methodology of determining the reliability indices for power generating subsystem. We analyse then influence of the considered wind power plant reliability modelling on system reliability. The proposed reliability model of wind power plant is two-state model as compromise between calculation time and accuracy. We have found an empirical relationship between the power system reliability index LOLE (Loss of Load Expectation) and reserve capacity margin for a given wind share. This allowed us to estimate the required minimal reserve capacity margin for a given level of power system security and for a known structure of system installed capacity.

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Section: Methodology Of Determining the Reliability Indices For Powermentioning

confidence: 99%

Section: Impact Of Wind Turbines Reliability Model On Power System Rementioning

confidence: 99%

Section: Impact Of Wind Turbines Reliability Model On Power System Rementioning

confidence: 99%

Section: Impact Of Wind Generation Share On Power System Reliabilitymentioning

confidence: 99%

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Impact of wind turbines reliability models on the power generation system reliability

2019

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“…Until now, there are several approaches modelling wind power correlation. Reference [13] uses the cluster mean to represent average output of wind turbine generators (WTGs) from the same wind farm in a wind farm reliability model. This method only considers the correlation of WTGs' outputs in the same wind farm and could not be applied to a complex situation.…”

Section: Introductionmentioning

confidence: 99%

Universal Generating Function Based Probabilistic Production Simulation Approach Considering Wind Speed Correlation

Zhou

Wang

et al. 2017

Energies

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Due to the volatile and correlated nature of wind speed, a high share of wind power penetration poses challenges to power system production simulation. Existing power system probabilistic production simulation approaches are in short of considering the time-varying characteristics of wind power and load, as well as the correlation between wind speeds at the same time, which brings about some problems in planning and analysis for the power system with high wind power penetration. Based on universal generating function (UGF), this paper proposes a novel probabilistic production simulation approach considering wind speed correlation. UGF is utilized to develop the chronological models of wind power that characterizes wind speed correlation simultaneously, as well as the chronological models of conventional generation sources and load. The supply and demand are matched chronologically to not only obtain generation schedules, but also reliability indices both at each simulation interval and the whole period. The proposed approach has been tested on the improved IEEE-RTS 79 test system and is compared with the Monte Carlo approach and the sequence operation theory approach. The results verified the proposed approach with the merits of computation simplicity and accuracy.

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Bibliography

2018

Electric Power Grid Reliability Evaluation

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A Wind Farm Reliability Model Considering Both Wind Variability and Turbine Forced Outages

Cited by 85 publications

References 35 publications

Impact of wind turbines reliability models on the power generation system reliability

Impact of wind turbines reliability models on the power generation system reliability

Universal Generating Function Based Probabilistic Production Simulation Approach Considering Wind Speed Correlation

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