Statistical Wind Speed Interpolation for Simulating Aggregated Wind Energy Production under System Studies

Gibescu, Madeleine; Ummels, B.C.; Kling, W.L.

doi:10.1109/pmaps.2006.360413

Cited by 32 publications

(22 citation statements)

References 10 publications

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“…Wind speed time series for the study period at planned wind park locations are created such that the spatial correlation between the sites is taken into account. The development of wind power output data is described in more detail in [9] and [10].…”

Section: Load and Wind Power Variabilitymentioning

confidence: 99%

Impacts of Wind Power on Thermal Generation Unit Commitment and Dispatch

Ummels

Gibescu

Pelgrum

et al. 2007

IEEE Trans. On Energy Conversion

552

258

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Abstract-This paper proposes a new simulation method that can fully assess the impacts of large-scale wind power on system operations from cost, reliability, and environmental perspectives. The method uses a time series of observed and predicted 15-min average wind speeds at foreseen onshore-and offshore-wind farm locations. A Unit Commitment and Economic Dispatch (UC-ED) tool is adapted to allow for frequent revisions of conventional generation unit schedules, using information on current wind energy output and forecasts for the next 36 h. This is deemed the most faithful way of simulating actual operations and short-term planning activities for a system with large wind power penetration. The problem formulation includes ramp-rate constraints for generation schedules and for reserve activation, and minimum up-time and down-time of conventional units. Results are shown for a realistic future scenario of the Dutch power system. It is shown that problems such as insufficient regulating and reserve power-which are typically associated with the variablility and limited predictability of wind power-can only be assessed in conjunction with the specifics of the conventional generation system that wind power is integrated into. For the thermal system with a large share of combined heat and power (CHP) investigated here, wind power forecasting does not provide significant benefits for optimal unit commitment and dispatch. Minimum load problems do occur, which result in wasted wind in amounts increasing with the wind power installed.Index Terms-Power system integration, unit commitment and economic dispatch, wind power, wind power forecast.

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Section: Load and Wind Power Variabilitymentioning

confidence: 99%

Impacts of Wind Power on Thermal Generation Unit Commitment and Dispatch

Ummels

Gibescu

Pelgrum

et al. 2007

IEEE Trans. On Energy Conversion

552

258

View full text Add to dashboard Cite

show abstract

“…Gibescu et al, 2006). Figure B1 shows the correspondence between mean and standard deviation for all the stations at each season in 2007 and the corresponding linear fits.…”

Section: Appendix Amentioning

confidence: 96%

Statistical analysis of observed and simulated hourly surface wind in the vicinity of the Panama Canal

Cheng¹,

Georgakakos²

2011

Intl Journal of Climatology

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Surface wind patterns at the Panama Canal vicinity are identified on the basis of 6 years of observed hourly surface wind data and with the use of high-resolution numerical model simulations. Statistical analysis of the observed wind at various stations in the Panama Canal is presented, together with the analysis of simulated surface wind fields that are obtained from the MM5 mesoscale meteorological model using surface wind assimilation and forced by North American regional reanalysis data. The performance analysis indicates that the 2-km-resolution MM5 model surface wind simulations have skill when compared with the observations at the measurement sites. The analysis of the wind fields for the period [2002][2003][2004][2005][2006][2007] shows that the dry season (January to April) is more spatially and temporally coherent than the wet season in the region. The simulated wind shows that the average wind speed reaches up to 7-8 m s −1 and the frequency of exceeding 5 m s −1 reaches up to 0.7-0.8 in Lake Gatun, the entrance/exit of the Canal in the Caribbean and Pacific coasts, and at high elevations. The dry season exhibits higher climatological wind speeds and exceedence frequencies than the wet season but the wet season shows greater spatial variability. For both seasons, the morning hours have lower average winds than the evening hours. The analysis underlines the significant influence of convection, sea breeze and local conditions (elevation gradients and land surface cover) in the observed and simulated surface wind patterns.The information presented herein, particularly as regards the Canal centerline results, may be useful for identifying the effects of air pollution from sources aboard transiting cargo ships on large communities in the Canal vicinity (e.g. Panama City). Information presented is also relevant to regional wind energy studies and fog formation analyses.

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“…And finally in section 4.5 the method to create wind power time series is explained. The methods described in the sections 4.3-4.5 were developed for this purpose by the authors (Brand, 2006;Gibescu et al, 2006;Gibescu et al, 2009). …”

Section: Outlinementioning

confidence: 99%