Monte Carlo Computation of Power Generation Production Costs under Operating Constraints

Valenzuela,; Mazumdar,

doi:10.1109/mper.2001.4311143

Cited by 10 publications

(12 citation statements)

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“…Planned and forced outages are described for each individual power plant with an hourly time resolution. The occurrence of forced outages in a certain hour is simulated with Semi-Markov chains describing the alternating process between the availability and the unavailability state of a power plant [26], [27]. Failure and repair rates are thereby expressed with the mean time to failure and the mean time to repair [28].…”

Section: A Scenario Tree Toolmentioning

confidence: 99%

Stochastic Optimization Model to Study the Operational Impacts of High Wind Penetrations in Ireland

Meibom

Barth

Hasche

et al. 2011

IEEE Trans. Power Syst.

318

190

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The UCD community has made this article openly available. Please share how this access benefits you. Your story matters! (@ucd_oa) Some rights reserved. For more information, please see the item record link above. Systems, in press, 2010 1  Abstract-A stochastic mixed integer linear optimization scheduling model minimizing system operation costs and treating load and wind power production as stochastic inputs is presented. The schedules are updated in a rolling manner as more up to date information becomes available. This is a fundamental change relative to day-ahead unit commitment approaches. The need for reserves dependent on forecast horizon and share of wind power has been estimated with a statistical model combining load and wind power forecast errors with scenarios of forced outages. The model is used to study operational impacts of future high wind penetrations for the island of Ireland. Results show that at least 6000 MW of wind (34 % of energy demand) can be integrated into the island of Ireland without significant curtailment and reliability problems. IEEE Transactions on PowerIndex Terms-Wind power, unit commitment and dispatch, reserves, forecast errors, energy policy. NOMENCLATURE Indices: i, IUnit, set of units r I Set units in region r

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Section: A Scenario Tree Toolmentioning

confidence: 99%

Stochastic Optimization Model to Study the Operational Impacts of High Wind Penetrations in Ireland

Meibom

Barth

Hasche

et al. 2011

IEEE Trans. Power Syst.

318

190

View full text Add to dashboard Cite

show abstract

“…The time series of forced outages for each conventional unit are simulated using semi-markov chains [13], where the failure and repair rates are expressed by the mean time to failure and the mean time to repair. The methodology used in the STT is derived from that presented in the All Island Grid Study (AIGS) [14] and is detailed in brief below.…”

Section: B Forced Outagesmentioning

confidence: 99%

Wind Power Scenario Tree Tool: Development and Methodology

Lowery

O’Malley

2013

Reliability and Risk Evaluation of Wind Integrated Power Systems

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Abstract-Driven by a trend towards renewable forms of generation, in particular wind, the nature of power system operation is changing. With respect to wind power, the uncertainty of the wind becomes an issue which must be considered. Through the use of wind forecasting, this uncertainty may be managed. The error inherent in forecasting will impact system reliability and cost as will inaccuracies in assumptions about the forecast error. This paper presents the methodology adopted for use in a Scenario Tree Tool constructed to allow for closer examination of the effect of forecast error assumptions and properties in unit commitment scheduling models.

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“…The time series of forced outages for each conventional unit are simulated using semi-markov chains [22], where the failure and repair rates are expressed by the mean time to failure and the mean time to repair. The methodology used in this study is unchanged from that presented in the All Island Grid Study (AIGS) [23].…”

Section: A the Scenario Tree Toolmentioning

confidence: 99%

Impact of wind forecast error statistics upon unit commitment

Lowery¹,

O’Malley

2013

2013 IEEE Power &Amp; Energy Society General Meeting

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Abstract-Driven by a trend towards renewable forms of generation, in particular wind, the nature of power system operation is changing. Systems with high wind penetrations should be capable of managing the uncertainty contained within the wind power forecasts. Stochastic unit commitment with rolling planning and input scenarios, based on wind forecasts, is one way of achieving this. Here a scenario tree tool is developed which allows forecast error statistics to be altered and facilitates the study of how these statistics impact on unit commitment and system operation. It is shown the largest individual impact on system operation is from the inclusion of variance and that variance, kurtosis and skewness together produced the error information with the lowest system cost. Similar impacts for inaccurate error statistics are observed but generalisation of these results will need more studies on a range of test systems.

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Monte Carlo Computation of Power Generation Production Costs under Operating Constraints

Cited by 10 publications

References 0 publications

Stochastic Optimization Model to Study the Operational Impacts of High Wind Penetrations in Ireland

Stochastic Optimization Model to Study the Operational Impacts of High Wind Penetrations in Ireland

Wind Power Scenario Tree Tool: Development and Methodology

Impact of wind forecast error statistics upon unit commitment

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