Forecasting the Wind to Reach Significant Penetration Levels of Wind Energy

Marquis, Melinda; Wilczak, J. M.; Ahlstrom, Mark; Sharp, John T.; Stern, Ariel Dora; Smith, James C.; Calvert, Stan

doi:10.1175/2011bams3033.1

Cited by 85 publications

(50 citation statements)

References 9 publications

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“…Thus, this study lays the groundwork for future investigations to compare the power output of the WFP scheme to the observed power production, which can be conducted with nacelle anemometer measurements (St. Martin et al 2017). Since mesoscale modelling is crucial in predicting power production in wind farms (Marquis et al 2011;Jiménez et al 2015;Wilczak et al 2015), comparisons of predicted and observed power output can help to identify areas for improvement in the WFP scheme in the WRF model. Moreover, accurate representation of wind farms in numerical weather prediction models is important for both simulating windenergy production and planning for energy infrastructure (Jacobson et al 2015;MacDonald et al 2016).…”

Section: Discussionmentioning

confidence: 99%

Observing and Simulating Wind-Turbine Wakes During the Evening Transition

Lee

Lundquist

2017

Boundary-Layer Meteorol

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Wind-turbine-wake evolution during the evening transition introduces variability to wind-farm power production at a time of day typically characterized by high electricity demand. During the evening transition, the atmosphere evolves from an unstable to a stable regime, and vertical stratification of the wind profile develops as the residual planetary boundary layer decouples from the surface layer. The evolution of wind-turbine wakes during the evening transition is examined from two perspectives: wake observations from single turbines, and simulations of multiple turbine wakes using the mesoscale Weather Research and Forecasting (WRF) model. Throughout the evening transition, the wake's wind-speed deficit and turbulence enhancement are confined within the rotor layer when the atmospheric stability changes from unstable to stable. The height variations of maximum upwind-downwind differences of wind speed and turbulence intensity gradually decrease during the evening transition. After verifying the WRF-model-simulated upwind wind speed, wind direction and turbulent kinetic energy profiles with observations, the wind-farm-scale wake evolution during the evening transition is investigated using the WRF-model wind-farm parametrization scheme. As the evening progresses, due to the presence of the wind farm, the modelled hub-height wind-speed deficit monotonically increases, the relative turbulence enhancement at hub height grows by 50%, and the downwind surface sensible heat flux increases, reducing surface cooling. Overall, the intensifying wakes from upwind turbines respond to the evolving atmospheric boundary layer during the evening transition, and undermine the power production of downwind turbines in the evening.

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Section: Discussionmentioning

confidence: 99%

Observing and Simulating Wind-Turbine Wakes During the Evening Transition

Lee

Lundquist

2017

Boundary-Layer Meteorol

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“…The vertical levels are further stretched beyond the boundary layer. In past research involving the WRF WFP scheme, the selections of vertical resolution within the rotor layer include 9-18 m in , about 10-16 m in Volker et al (2015), about 15 m in Fitch et al (2012Fitch et al ( , 2013a and , about 20 m in Miller et al (2015) and Vautard et al (2014), about 22 m in Lee and Lundquist (2017), and about 40 m in Eriksson et al (2015) and Jiménez et al (2015). Moreover, the Mellor-Yamada-Nakanishi-Niino (MYNN) level 2.5 planetary boundary layer (PBL) scheme is required for the WFP in the WRF model version 3.8.1 .…”

Section: Modellingmentioning

confidence: 99%

“…In recent years, numerical weather prediction (NWP) models have become an indispensable tool in the wind-energy industry, not only in day-to-day wind-energy production forecasts , but also to support wide-scale windpower penetration (Marquis et al, 2011) and wind resource assessment. To forecast power production accurately at wind farms, the simulation tools should resolve all physical processes relevant to the wind field, including possible impacts of the wind turbines themselves.…”

Section: Introductionmentioning

confidence: 99%

“…The WRF WFP has been widely used to assess the impacts of onshore and offshore wind farms at different spatial scales and in different stability regimes (Eriksson et al, 2015;Fitch et al, 2013a, b;Jiménez et al, 2015;Lee and Lundquist, 2017;Miller et al, 2015;Vautard et al, 2014). Whereas WFP predictions have been compared to power production of offshore wind farms for a limited set of WSs (Jiménez et al, 2015), here we explore a range of WSs, wind direction (WD), turbulence, and atmospheric stability conditions.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

Lee

Lundquist

2017

Geosci. Model Dev.

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Abstract. Forecasts of wind-power production are necessary to facilitate the integration of wind energy into power grids, and these forecasts should incorporate the impact of windturbine wakes. This paper focuses on a case study of four diurnal cycles with significant power production, and assesses the skill of the wind farm parameterization (WFP) distributed with the Weather Research and Forecasting (WRF) model version 3.8.1, as well as its sensitivity to model configuration. After validating the simulated ambient flow with observations, we quantify the value of the WFP as it accounts for wake impacts on power production of downwind turbines. We also illustrate with statistical significance that a vertical grid with approximately 12 m vertical resolution is necessary for reproducing the observed power production. Further, the WFP overestimates wake effects and hence underestimates downwind power production during high wind speed, highly stable, and low turbulence conditions. We also find the WFP performance is independent of the number of wind turbines per model grid cell and the upwind-downwind position of turbines. Rather, the ability of the WFP to predict power production is most dependent on the skill of the WRF model in simulating the ambient wind speed.

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“…Stateof-the-art load forecasts can achieve high accuracy in the day-ahead stage. In contrast to load forecasting, the variable wind generation is very difficult to be accurately predicted at 24 − 36 hours ahead, only short-term (hours ahead) prediction is of acceptable confidence; see Monteiro et al (2009) and Marquis et al (2011).…”

Section: Power System Schedulingmentioning

confidence: 99%

Space-time wind speed forecasting for improved power system dispatch

Zhu

Genton

et al. 2014

TEST

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In order to support large scale integration of wind power, state-of-the-art wind speed forecasting methods should provide accurate and adequate information to enable efficient scheduling of wind power in electric energy systems. In this article, space-time wind forecasts are incorporated into power system economic dispatch models. First, we proposed a new space-time wind forecasting model, which generalizes and improves upon a so-called regime-switching space-time model by allowing the forecast regimes to vary with the dominant wind direction and with the seasons. Then, results from the new wind forecasting model are implemented into a power system economic dispatch model, which takes into account both spatial and temporal wind speed correlations. This, in turn, leads to an overall more cost-effective scheduling of system-wide wind generation portfolio. The potential economic benefits arise in the system-wide generation cost savings and in the ancillary service cost savings. This is illustrated in a test system in the northwest region of the U.S. Compared with persistent and autoregressive models, our proposed method could lead to annual integration cost savings on the scale of tens of millions of dollars in regions with high wind penetration, such as Texas and the Northwest.

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Forecasting the Wind to Reach Significant Penetration Levels of Wind Energy

Abstract: Improved weather forecasts help system operators know with greater accuracy how much variable renewable energy can be generated and how much other electric power they will need.

Cited by 85 publications

References 9 publications

Observing and Simulating Wind-Turbine Wakes During the Evening Transition

Observing and Simulating Wind-Turbine Wakes During the Evening Transition

Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data

Space-time wind speed forecasting for improved power system dispatch

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