Understanding the availability of wind turbines (WT) is vital to maximize WT energy production and minimize the capital payback period. Previous work on this subject concentrated on reliability and the location of WT failure modes rather than root causes. This paper concentrates on the influence of weather and WT location on failure rate and downtime, to try to understand root causes and the consequences of failure. The paper goes further than a previous study, which used Windstats data from the whole of Denmark, by considering a limited population of identical WTs at three locations on the German Nordzee, Ostzee and in western Germany, using data from WMEP and local weather stations. This new study focuses more precisely than the previous study by using more reliable data. The data were analysed to find the WT failures and weather conditions and then cross-correlate them. To confirm their representativeness, the reliability characteristics of these smaller WT populatio ns followed the average trends of the overall WMEP survey. However, clear differences were observed in the failure behaviour of the WTs at the three locations. Annual periodicity was seen in the weather data, as expected, but not in individual WT population failure data. However, clear cross-correlations can be seen between WT failures and weather data, in particular wind speed, maximum temperature and humidity. These cross-correlations were more convincing than those found in the earlier, larger Danish study, vindicating the more focused approach. It is also clear from the analysis that Operation & Maintenance also has an impact on WT failure rates. These factors will be important for the operation of offshore WTs with the work indicating how weather conditions may affect offshore WT failure rates
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Power system inertia is falling as more energy is supplied by renewable generators, and there are concerns about the frequency controls required to guarantee satisfactory system performance. The majority of research into the negative effect of low inertia has focused on poor dynamic response following major disturbances, when the transient frequency dip can become unacceptable. However, another important practical concernkeeping average frequency deviations within acceptable limits -was mainly out of the sight of the research community. In this manuscript we present a method for finding the frequency probability density function (PDF) for a given power system. We pass from an initial stochastic dynamic model to deterministic equations for the frequency PDF, which are analyzed to uncover key system parameters influencing frequency deviations. We show that system inertia has little effect on the frequency PDF, making virtual inertia services insufficient for keeping frequency close to nominal under ambient load fluctuations. We establish, that aggregate system droop and deadband width are the only parameters that have major influence on the average frequency deviations, suggesting that energy storage might be an excellent solution for tight frequency regulation. We also show that changing the governor deadband width does not significantly affect generator movement..
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