Abstract A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea. The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are: Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil componen...

Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model [presentation]

The power generated by a wind turbine largely depends on the wind speed. During time periods with identical hub-height wind speeds but different shapes to the wind profile, a turbine will produce different amounts of power. This variability may be induced by atmospheric stability, which affects profiles of mean wind speed, direction and turbulence across the rotor disk. Our letter examines turbine power generation data, segregated by atmospheric stability, in order to investigate power performance dependences at a West Coast North American wind farm. The dependence of power on stability is clear, regardless of whether time periods are segregated by three-dimensional turbulence, turbulence intensity or wind shear. The power generated at a given wind speed is higher under stable conditions and lower under strongly convective conditions: average power output differences approach 15%. Wind energy resource assessment and day ahead power forecasting could benefit from increased accuracy if atmospheric stability impacts were measured and appropriately incorporated in power forecasts, e.g., through the generation of power curves based on a range of turbulence regimes.

/pdf/atmospheric-stability-affects-wind-turbine-power-collection-5g4jrjnn30.pdf

Atmospheric Stability Affects Wind Turbine Power Collection

High-quality tall mast and wind lidar measurements over the North and Baltic Seas are used to validate the wind climatology produced from winds simulated by the Weather, Research and Forecasting (WRF) model in analysis mode. Biases in annual mean wind speed between model and observations at heights around 100 m are smaller than 3.2% at offshore sites, except for those that are affected by the wake of a wind farm or the coastline. These biases are smaller than those obtained by using winds directly from the reanalysis. We study the sensitivity of the WRF-simulated wind climatology to various model setup parameters. The results of the year-long sensitivity simulations show that the long-term mean wind speed simulated by the WRF model offshore in the region studied is quite insensitive to the global reanalysis, the number of vertical levels, and the horizontal resolution of the sea surface temperature used as lower boundary conditions. Also, the strength and form (grid vs spectral) of the nudging is quite irrelevant for the mean wind speed at 100 m. Large sensitivity is found to the choice of boundary layer parametrization, and to the length of the period that is discarded as spin-up to produce a wind climatology. It is found that the spin-up period for the boundary layer winds is likely larger than 12 h over land and could affect the wind climatology for points offshore for quite a distance downstream from the coast.

Wind climate estimation using WRF model output: method and model sensitivities over the sea

In the face of the broad political call for an “energy turnaround”, we are currently witnessing three essential trends with regard to energy infrastructure planning, energy generation and storage: from planned production towards fluctuating production on the basis of renewable energy sources, from centralized generation towards decentralized generation and from expensive energy carriers towards cost-free energy carriers. These changes necessitate considerable modifications of the energy infrastructure. Even though most of these modifications are inherently motivated by geospatial questions and challenges, the integration of energy system models and Geographic Information Systems (GIS) is still in its infancy. This paper analyzes the shortcomings of previous approaches in using GIS in renewable energy-related projects, extracts distinct challenges from these previous efforts and, finally, defines a set of core future research avenues for GIS-based energy infrastructure planning with a focus on the use of renewable energy. These future research avenues comprise the availability base data and their “geospatial awareness”, the development of a generic and unified data model, the usage of volunteered geographic information (VGI) and crowdsourced data in analysis processes, the integration of 3D building models and 3D data analysis, the incorporation of network topologies into GIS, the harmonization of the heterogeneous views on aggregation issues in the fields of energy and GIS, fine-grained energy demand estimation from freely-available data sources, decentralized storage facility planning, the investigation of GIS-based public participation mechanisms, the transition from purely structural to operational planning, data privacy aspects and, finally, the development of a new dynamic power market design.

https://www.mdpi.com/2220-9964/3/2/662/pdf

GIS-Based Planning and Modeling for Renewable Energy: Challenges and Future Research Avenues

This paper reports on an evaluation of the relative roles of choice of parameterization scheme and terrain representation in the Weather Research and Forecasting (WRF) mesoscale model, in the context of a regional wind resource assessment. As a first step, 32 configurations using two different schemes for microphysics, cumulus, planetary boundary layer (PBL), or shortwave and longwave radiation were evaluated. In a second step, wind estimates that were obtained from various experiments with different spatial resolution (1, 3, and 9 km) were assessed. Estimates were tested against data from four stations, located in southern Spain, that provided hourly wind speed and direction data at 40 m above ground level. Results from the first analysis showed that wind speed standard deviation (STD) and bias values were mainly sensitive to the PBL parameterization selection, with STD differences up to 10% and bias differences between −15% and 10%. The second analysis showed a weak influence of spatial resoluti...

Analysis of WRF Model Wind Estimate Sensitivity to Physics Parameterization Choice and Terrain Representation in Andalusia (Southern Spain)

configured with horizontal grid spacing ranging from 27 km in the outermost telescoping to 333 m in the innermost domains and verified with observations collected at four 50-m towers in west-central Nevada during July and December 2007. Moment-based and spectral verification metrics showed that the performance of WRF was superior to MM5. The modeling results were more accurate at 50 m than at 10 m AGL. Both models accurately simulated the mean near-surface wind shear; however, WRF (MM5) generally overestimated (underestimated) mean wind speeds at these levels. The dispersion errors were the dominant component of the root-mean square errors. The major weakness of WRF was the overestimation of the intensity and frequency of strong nocturnal thermally driven flows and their sub-diurnal scale variability, while the main weaknesses of MM5 were larger biases, underestimation of the frequency of stronger daytime winds in the mixed layer and underestimation of the observed spectral kinetic energy of the major energy-containing motions. Neither of the verification metrics showed systematic improvement in the models’ accuracy with increasing the horizontal resolution and the share of dispersion errors increased with increased resolution. However, a profound improvement in the moment-based accuracy was found for the mean vertical wind shear and the temporal variability of wind speed, in particular for summer daytime simulations of the thermally driven flows. The most prominent spectral accuracy improvement among the primary energy-containing frequency bands was found for both models in the summertime diurnal periods. Also, the improvement for WRF (MM5) was more (less) apparent for longer-than-diurnal than for sub-diurnal periods. Finally, the study shows that at least near-kilometer horizontal grid spacing is necessary for dynamical downscaling of near-surface wind speed climate over complex terrain; however, some of the physics options might be less appropriate for grid spacing nearing the scales of the energy-containing turbulent eddies, i.e., resolutions of several hundred meters. In addition to the effects of the lower boundary, the accuracy of the lateral boundary conditions of the parent domains also controls the onset and evolution of the thermally driven flows.

/pdf/sub-kilometer-dynamical-downscaling-of-near-surface-winds-in-kbgs7bl515.pdf

Sub-kilometer dynamical downscaling of near-surface winds in complex terrain using WRF and MM5 mesoscale models

A detailed description of the meteorological conditions of the Washoe Valley (Nevada) and simulations that examine the predictability of the westerly high wind event known as the Washoe Zephyr are presented. Numerical weather model prediction skill is computed for day-ahead (24–48 h) forecasts of wind speed at a meteorological tower on the Virginia Hills range relative to a persistence forecast based on a seasonal climatology constructed of hourly mean observations. The model predictions are shown to be more skillful than a climatology based on seasonal and hourly means during winter and less skillful than the seasonal-hourly climatology (SHC) during summer. Overall skill of the forecasted winds tends to increase with finer horizontal grid spacing. Phase errors compose the largest component of the error decomposition and large phase errors are associated with the onset and decay of the diurnally forced Washoe Zephyr during summer and synoptically forced high wind events and valley rotors during wi...

Day-Ahead Predictability of Complex Terrain Flows for Wind Resource Production: A Case Study of the Washoe Zephyr

The main issues related to assessment and forecasting of the wind and wind energy have been reviewed. These include the limitations and advantages of wind forecasting and assessment of the wind power density, especially considering trends of increasing penetration of wind-generated power into the utility grid and storage of wind-generated power. Accurate forecasting of the wind power density over a large range of spatial and temporal scales is a critical issue for planning and operations of wind farms. A review of various prediction tools, from simple statistical models to highly complex numerical techniques, was performed for this purpose. The influence of wind variability, atmospheric stability, turbulence, and the low-level jets on wind power density are elaborated on in detail. Furthermore, prediction and assessment of future wind energy resources and their economic implications as well as environmental concerns such as birds’ habitats and routes, viewpoint aesthetics, and noise are also discussed in this study. Some climate projection studies indicate minor changes in the wind resources comparable to differences in global models results while others argue that the wind resources will be reduced due to global warming and they call for harvesting wind energy at the maximum rate as soon as possible.

/pdf/a-review-of-challenges-in-assessment-and-forecasting-of-wind-4pteb7jwya.pdf

A review of challenges in assessment and forecasting of wind energy resources

The main objectives of this project were to conduct a tall-tower and sodar field campaign in complex terrain, investigate wind properties relevant to wind energy assessment, and evaluate high-resolution models with fixed and adaptive grid structures. Two 60-m towers at Virginia Peak ridges near Washoe Valley, Nevada, were instrumented with cup and vane anemometers as well as sonic anemometers, and an acoustic sounder (hereafter sodar) was installed near one of the towers. The towers were located 2,700 m apart with a vertical distance of 140 m elevation between their bases. Each tower had a downhill exposure of rolling complex terrain, with the nearby valley floor 3,200 m to the west and 800 m below the summit. Cup anemometers were installed at both towers at 20, 40, and 60 m, wind vanes at 20 and 60 m, and sonic anemometers at 20 and 60 m. The sodar measurements were nominally provided every 10 m in vertical distance from 40 to 200 m with the quality of the data generally decreasing with height. Surface air temperature, atmospheric pressure, and radiation measurements were conducted at 1.5 m AGL at both of the towers. Although the plan was to conduct a 1-year period ofmore » data collection, we extended the period (October 5, 2012 through February 24, 2014) to cover for possible data loss from instrument or communication problems. We also present a preliminary analysis of the towers and sodar data, including a detailed inventory of available and missing data as well as outliers. The analysis additionally includes calculation of the Weibull parameters, turbulence intensity, and initial computation of wind power density at various heights.« less

/pdf/tall-tower-wind-energy-monitoring-and-numerical-model-2rv4vj8zns.pdf

Kristian Horvath

Papers

Sub-kilometer dynamical downscaling of near-surface winds in complex terrain using WRF and MM5 mesoscale models

Day-Ahead Predictability of Complex Terrain Flows for Wind Resource Production: A Case Study of the Washoe Zephyr

A review of challenges in assessment and forecasting of wind energy resources

Tall Tower Wind Energy Monitoring and Numerical Model Validation in Northern Nevada