Wind power generation reliability analysis and modeling

D'Annunzio, Claudine; Santoso, Surya

doi:10.1109/pes.2005.1489483

Cited by 13 publications

(5 citation statements)

References 9 publications

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“…These indices are often employed in conventional electrical PS, the standard reliability test system is the IEEE-RTS, as a reference and simulation model. The most common indices used are as follows 94,114–116 : loss of load expectation (LOLE), measured in hours per year; capacity outage probability table; load duration curve; forced outage rate (FOR); loss of energy expectation, measured in MWh/year; frequency of loss of load (FLOL), measured occurrence/year; duration per interruption, measured hour/occurrence; load not supplied per interruption, MW per occurrence; energy not supplied interruption, MWh/occurrence, 93,95 , time to fail (TTF) and Bayesian Network (BN), 117,118 , yearly interruption cost, interruption energy assessment rate; 96,119,120 expected generated wind energy 120,121 among others: wind generation interrupted energy benefit, wind generation interrupted cost benefit, equivalent capacity rate and load carrying capacity benefit ratio.…”

Section: Wind Energy and Its Implicationsmentioning

confidence: 99%

Review on methodological and normative advances in assessment and estimation of wind energy

López-Manrique

Macías-Melo

Aguilar-Castro

et al. 2019

Energy & Environment

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In this study, we present a review of articles that address the state of the art in wind energy from different perspectives, specifically focusing on the criteria used for wind energy assessment and wind turbine standards, along with an overview of the technologies necessary to make reliable Wind Power-Grid penetration more efficient. Wind power dynamics are also considered from the perspective of their intermittency and the nature of wind speed variability in order to establish appropriate sampling times for measurements and monitoring. The literature discussed is representative of the technological and methodological advances dedicated to the development, adaptation and application of statistical, computational, numerical and artificial intelligence tools for an assessment of wind energy and wind power forecasting. These applications and methodologies commonly use data registers measured in very short, short, medium and long-term measurement campaigns. Finally, literature on wind power social, environmental and economic policies and trends in costs-capacity-addition and their impact are reviewed from a global perspective. In light of today’s concerns with global warming, it is essential that wind energy interact steadily on the grid with experienced operators and high automatic-control technology worldwide.

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Section: Wind Energy and Its Implicationsmentioning

confidence: 99%

Review on methodological and normative advances in assessment and estimation of wind energy

López-Manrique

Macías-Melo

Aguilar-Castro

et al. 2019

Energy & Environment

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“…Deshmukh and Ramakumar in [11] have used a Weibull distribution for wind speed modelling. Also, Weibull distribution for wind speed modelling in [3,10,12] and [20] was used. Giorseto and Utsurogi in [14], Wang, Dai, Hui and Thomas in [34] and Attvwa and El-Saadany in [4] have used Rayleigh distribution for wind speed modelling.…”

Section: Wind Speed Modelmentioning

confidence: 99%

Reliability model of different wind power plant configuration using sequential monte carlo simulation

Topić¹,

Šljivac²,

Stojkov³

2016

EiN

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Wind turbine's main components are namely: rotor (hub and blades), brake, gearbox, generator, electronic control system, yaw system, nacelle, drive train, anemometer and tower. According to [2], Topić D, ŠljivAc D, STojkov M. Reliability model of different wind power plant configuration using sequential monte carlo simulation. Eksploatacja i Niezawodnosc -Maintenance and Reliability 2016; 18 (2): 237-244, http://dx

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“…[9] introduces operation strategies of wind farm along with energy storage and evaluates the system reliability; however, it has not considered the storage system failure or its comparison with conventional generating units. Reference [10] evaluates the impact of wind power generation on system reliability using analytical approach. An algorithm to simulate the hourly wind speed using a time-series auto regressive and moving average (ARMA) model is presented in [11].…”

Section: Introductionmentioning

confidence: 99%

Reliability improvement of power system utilizing BESS with wind farm

Shahooei

Fotuhi‐Firuzabad

Abbaspour

2015

2015 IEEE 15th International Conference on Environment and Electrical Engineering (EEEIC)

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In this paper, the effect of wind power generation on power system reliability is investigated. Furthermore, reliability improvement of power system using integrated battery energy storage system and wind farm will be evaluated. Growing demand for electrical energy, gradual diminishing of fossil fuel resources and environmental pollution due to continuous exploitation of them, have led to inevitable change of energy sources in power generation. Due to the random nature of wind speed, the power output of a wind farm is fluctuating; as a result, it does not have a proper control capability. The growing penetration of wind power generation in power system could cause various problems in different areas such as power quality, system stability and reliability. Utilizing Energy Storage Systems (ESS) is a solution to overcome the variable nature of wind turbine generation.

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Wind power generation reliability analysis and modeling

Cited by 13 publications

References 9 publications

Review on methodological and normative advances in assessment and estimation of wind energy

Review on methodological and normative advances in assessment and estimation of wind energy

Reliability model of different wind power plant configuration using sequential monte carlo simulation

Reliability improvement of power system utilizing BESS with wind farm

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