3.1.1. Converter Failure Rates vs. Wind-Turbine Capacity Factors
The field-data compiled and evaluated in the Innovation Cluster covers WTs with different generator-converter concepts, of a multitude of manufacturers and at sites with a variety of wind regimes. The latter has not been taken into consideration in our previous presentations and comparisons of converter failure rates. This raises the question if certain groups of WTs (such as e.g., the EESG-based WTs in our dataset) exhibit particularly low converter failure rates mainly due to the fact that they might rarely be operating at full load. Taking into consideration the different capacity factors of the investigated turbines adds therefore an important piece to the picture.
The following analysis seeks to answer the question if there is a systematic difference in converter failure rates between turbines operating at low capacity factors and such operating at high capacity factors. For this purpose, all WTs with at least one year of SCADA data for calculating the capacity factor are grouped by manufacturer and their average capacity factor (clustered in bins of 10%). Average converter-system and phase-module failure rates are calculated for each of these groups.
presents these failure rates over the capacity-factor ranges for turbines of different generator-converter concepts and manufacturers. Only failure rates calculated based on data from at least 30 WT operating years are included in the diagrams in order to avoid values afflicted with a very large uncertainty.
As Figure 2
shows, most WTs represented in the dataset operate at capacity factors between 10% and 30%. From WTs operating at higher capacity factors, only phase-module failure data has been available, so only these are found in Figure 2
b. The less data a failure-rate value is based on, the larger is the confidence interval, which is directly related to the higher uncertainty.
Major differences with respect to the average failure rates can be observed among the WT groups of different manufacturers, with the overall converter failure rates ranging up to 1.66 a−1 per WT and the maximum phase-module failure rates reaching 0.35 a−1 per WT. The most relevant finding with respect to the guiding question raised above is that only in single cases (the group of EESG-based WTs and the group of DFIG-based WTs denoted DFIG5), the failure rate increases with the capacity factor. In other cases (namely the WT groups DFIG3 and DFIG6), the WTs operating at higher capacity factors experienced the lower phase-module failure rates.
In an overall view, for the majority of investigated WTs, the failure rates of both the phase modules and the complete converter system show no relevant correlation with the capacity factor and thus with the average electrical load of the WTs. Instead, the results underline that the manufacturer (and with that the WT and converter design) has a much stronger impact on the converter reliability than the generator-converter concept (DFIG, IG + FPC, EESG) or the capacity factor of a WT.
3.1.2. Seasonal Variation of Phase-module Failure Rates
As presented in [35
], we observed a pronounced seasonal pattern in the phase-module failures in fleets in India and Scandinavia, with maximum failure rates occurring during periods with high absolute ambient humidity. This has been a strong indication that moisture and/or condensation play an important role in the incidence of converter failures. At the same time, it was surprising to find that at first sight no such pattern could be identified for the WT fleet in Germany. In view of the fact that the evaluated turbine fleets have liquid-cooled converters while air-cooled converters prevail in the German fleet, this observation raises the question if the cooling concept of the converter influences the system’s susceptibility to humidity.
In the following, the analysis of the seasonal variation of phase-module failure rates is substantially extended and deepened: While the results presented in [35
] have been limited to the monthly phase-module failure rates in India and Scandinavia, the following analysis includes the WT fleet in Germany. Furthermore, the analysis is deepened by differentiating between turbines with liquid-cooled vs. air-cooled converter systems and by taking into consideration the operating point of the WTs preceding the failures where this information is available.
shows the situation in the Indian fleet, which consists solely of onshore turbines with liquid-cooled converters. It displays the average phase-module failure rates along with the monthly average values of wind speed, ambient temperature, relative humidity and dew-point temperature throughout the year. The dew-point temperature, i.e., the temperature below which the airborne water vapor condenses to liquid water, is a function of the absolute humidity and hence determined by the ambient temperature and relative humidity.
The wind-speed information is based on WT SCADA data from the evaluated fleet. The monthly average values of temperature and humidity are derived from climate data from [38
] by averaging over the regions of interest as well as over several years. The color scale in the bar chart of Figure 3
indicates in which load range (characterized by the 10min-average value of the WT active power P10min
normalized with the rated power Prated
of the WT) the turbine operated in the 10min-interval before the failure occurred. Please see [35
] for a detailed description on how this value is determined. In case of the areas in grey color, no information about the operating point has been available.
clearly shows the temporal pattern in the phase-module failure behavior and the accumulation of failures during the months with highest absolute humidity in the ambient air. The large portion of failures without operating-point information limits the interpretation of the top diagram in Figure 3
, but some indications can nevertheless be obtained: Only a small portion of the failures occurred at full-load operation of the WTs. In none of the cases, for which the operating point could be determined, the failure initiated in an “overload” situation with P10min
. Instead, most failures occurred in low part-load operation. In this operating regime, the losses in the converter are low and with these also their heating effect, which promotes high relative humidity and the risk of condensation inside the converter cabinet. It is interesting to note that the occurrence of converter failures is not limited to periods in which the turbines feed active power to the grid, but that these occur also in zero-load situations (with P10min
≤ 0 kW), e.g., during idling or start of the turbines.
In analogy with the previous diagrams, Figure 4
presents the situation observed in the WT fleet in Scandinavia. It consists of WTs located in both onshore and offshore sites. As in the previous case, all considered WTs have liquid-cooled converters. Note that the wind-speed values are based solely on the SCADA data of the offshore WTs. As in the present analysis the focus is on the seasonal variation of the wind speed through the course of the year and not on the exact absolute values of the wind speed, this is considered an acceptable approximation. The monthly average values of temperature and humidity are calculated from climate data by [39
] (data from [27
illustrates again the previously shown accumulation of phase-module failures during the months with highest absolute humidity. However, the evaluation of the operating point preceding failure provides interesting additional information: The portion of phase-module failures occurred during operation close to, at or above rated power is found to be much higher in this fleet. This is not surprising in strong-wind months such as December to January, but comes at first sight unexpected in the low-wind month August. Taking into consideration the strong influence of both ambient temperature and WT active power on the air temperature inside the converter cabinets revealed by field measurements in the Scandinavian fleet, the higher-load failures in August are likely attributable to overheating. Another interesting observation from Figure 4
is the increased occurrence of failures from zero- or low part-load operation during May to October, i.e., during the months with highest absolute ambient humidity or dew-point temperature, respectively.
Finally, Figure 5
presents the corresponding diagrams for the large WT fleet in Germany covered by the Innovation Cluster dataset. All evaluated WTs in Germany are located onshore. In contrast to the Indian and the Scandinavian fleets analyzed above, the German fleet includes both WTs with air-cooled and WTs with liquid-cooled converters. The seasonal variation of the phase-module failure rates is presented separately for these two cases in the upper two diagrams of Figure 5
. The wind-speed information is based on WT SCADA data from the evaluated fleet. The climate data is derived from temperature and humidity data obtained from [41
] by averaging over different regions in Germany and over several years.
In the interpretation of Figure 5
, it should be noted that the number of phase-module failures in WTs with liquid-cooled converter is considerably lower than in the other cases. The scatter in the monthly failure rates, which is a result of the scarce underlying failure data and particularly visible in the large month-to-month variation during January-April, makes it harder to identify any seasonal pattern. In addition, operating-point information is available only for a part of the phase-module failures. Nevertheless, the figure allows the interesting observation that also in the German fleet increased average phase-module failure rates are encountered during June–October, but solely in WTs with liquid-cooled converter. Among the failures with information about the preceding operating point, failures from zero load or low part-load operation are clearly prevailing, especially during summer and autumn, i.e., the months with highest absolute humidity. This is in agreement with the observations in the Indian and Scandinavian fleets with liquid-cooled converters. It is worth recalling in this context that the dew-point temperatures included in Figure 3
, Figure 4
, Figure 5
are monthly average values. Measurements undertaken inside WT converter cabinets in both Germany and Scandinavia have shown that dew-point temperatures larger than 20 °C occur inside the cabinets, i.e., values lying far above the monthly average values of the dew-point temperature shown in the diagrams above.
In contrast to the previous cases, a reversed temporal failure pattern is observed in the German WT fleet with air-cooled converters: There are particularly few phase-module failures during summer and autumn. Instead, increased failure rates are observed during December to March, i.e., during the months with the on average highest wind speeds.
Another example of a pronounced seasonal accumulation of electrical-system failures can be found in the literature: In [42
], failure statistics from a large wind farm with 1.5 MW turbines located in the Chinese Jiangsu province are presented, which are based on a total of 254 WT operating years. A comparison of the monthly failure rates reveals a massively increased failure rate in the electrical system during the months July and August. While this is related to high ambient temperatures in the paper, it can as likely be attributed to the by far highest absolute humidity (as visible in dew-point temperature data from this region obtainable e.g., from [38
]) being present during these months.
The results presented in this section give further support to the hypothesis that high humidity (i.e., moisture and condensation) has a negative effect on phase-module reliability. Furthermore, in combination with the results presented in [42
], they make clear that this effect is encountered in the most different parts and climate zones of the world. An important new finding has evolved from the separate analysis of WTs with liquid-cooled and air-cooled converters located in Germany. The different failure patterns observed in these two fleets suggest that the high susceptibility to humidity is an issue mainly related to WTs with liquid-cooled converters.