Companies need to occupy a unique market share to survive in a highly competitive business world. One of the possibilities to create a unique market share is innovation. The purpose of this study was to investigate the level of innovative work behavior, type of organizational culture and the relation between innovative work behavior and organizational culture. This case study was conducted at a manufacturer of packaging machines and could be used as an example for other companies that worked within a highly innovative work field. The employees perceived the current dominant culture as a market culture and were convinced they could improve their innovative work behavior as shown by the higher average scores on preferred innovative work behavior than the current level of innovative work behavior. The preferred organizational culture was a family culture. Even though the literature confirms that family and market cultures will enhance innovative work behavior, the results from the questionnaire only show a significant correlation between the market culture and innovative work behavior in the organization. It is concluded that a transition of the current market culture towards a more family culture is needed, but in the meantime the market culture should be preserved.
Accurate short‐term power forecasts are crucial for the reliable and efficient integration of wind energy in power systems and electricity markets. Typically, forecasts for hours to days ahead are based on the output of numerical weather prediction models, and with the advance of computing power, the spatial and temporal resolutions of these models have increased substantially. However, high‐resolution forecasts often exhibit spatial and/or temporal displacement errors, and when regarding typical average performance metrics, they often perform worse than smoother forecasts from lower‐resolution models. Recent computational advances have enabled the use of large‐eddy simulations (LESs) in the context of operational weather forecasting, yielding turbulence‐resolving weather forecasts with a spatial resolution of 100 m or finer and a temporal resolution of 30 seconds or less. This paper is a proof‐of‐concept study on the prospect of leveraging these ultra high‐resolution weather models for operational forecasting at Horns Rev I in Denmark. It is shown that temporal smoothing of the forecasts clearly improves their skill, even for the benchmark resolution forecast, although potentially valuable high‐frequency information is lost. Therefore, a statistical post‐processing approach is explored on the basis of smoothing and feature engineering from the high‐frequency signal. The results indicate that for wind farm forecasting, using information content from both the standard and LES resolution models improves the forecast accuracy, especially with a feature selection stage, compared with using the information content solely from either source.
Abstract. In this article the aeroelastic loads on a 10 MW turbine in response to extreme events (low-level jet, shear, veer and turbulence intensity) selected from a year-long large-eddy simulation (LES) on a site at the North Sea are evaluated. These events are generated with a high-fidelity LES wind model and fed into an aeroelastic tool using two different aerodynamic models: a model based on blade element momentum (BEM) and a free vortex wake model. Then the aeroelastic loads are calculated and compared with the loads from the IEC standards. It was found that the loads from all these events remain within those of the IEC design loads. Moreover, the accuracy of BEM-based methods for modelling such wind conditions showed a considerable overprediction compared to the free vortex wake model for the events with extreme shear and/or veer.
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