Study of the effect of fixed-pitch wind turbine blades on energy production in wind farms

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1 Study of the effect of fixed-pitch wind turbine blades on energy production in wind farms Á.M. Costa, J.A. Orosa, Feliciano Fraguela and Rebeca Bouzón Department of Energy and Marine Propulsion, Universidade da Coruña, c/paseo de Ronda, 51, 1511 A Coruña (Spain) This study investigated the performance and power output of a wind farm connected to a network during 3 years of operation. It includes a complete register of operational data for 32 existing turbines, and all data has been analysed to study the actual efficiency of the wind farm. The study also illustrates the variation of wind speed and energy annually and monthly during the entire study period. In addition, for the utilization of wind energy, two systems used power control. The power delivered by the wind turbine must be limited to avoid overloading certain components (especially, generator, transformer, and gearbox). The two control systems are stall regulation and the regulation blade by varying the blade pitch angle. Keywords: fixed pitch; blades; wind turbine; wind power 1. Introduction The amount of energy contained in or provided by air masses that move traffic in the lower layers of the atmosphere represents a level of relatively high-energy potential, especially in certain local and seasonal conditions. Thus, the effort in conducting this energy transformation into a useful form and using it in favourable conditions of efficiency and profitability, considering the level of development of wind energy conversion technologies, is justified. The wind forms from the expansion and air convection caused by different absorption of solar energy on Earth. Globally, these thermal effects are combined with dynamic effects due to Earth's rotation, resulting in atmospheric general circulation. Besides this situation scale, there are significant local and temporal variations caused by geography and climate [1-3]. Thus, the energy resource wind, considering from the perspective of its availability as a supply source, has specific features: It is an energy source with substantial temporal variations, small and large scale of time and space, both surface and height, with a random component that largely affects its total variation. Generally there are two ways in which wind energy can be used significantly. The first is the use of large turbines in wind farms integrated into a power system and the second is through hybrid systems including wind power with other renewable and conventional systems [4-8]. Simultaneously, consider that the wind energy available per unit area exposed to the wind is proportional to the cube of the speed, so that small variations in wind speed sensitivity involve variations in the energy supplied. Wind characteristics importantly influence several areas of work related to systems of wind energy utilization: In the most favourable site selection for the installation of wind systems, given the local wind marked differences. In the estimate or forecast of energy production and the overall operation of wind system, where values are considered in distributions of wind daily, seasonal, directional, etc. in specific locations or interest. In the design of system that takes into account the average conditions representative and extreme wind conditions. In the wind system operation and regulation, which involve aspects such as wind prediction to plan real-time operation, and wind characteristics that influence the operation strategy (start, stop, orientation, etc.) and factors that affect maintenance or system life (blast, turbulence, etc.). These properties that allow evaluation and characterization of wind as an energy source is a work area of particular importance in the use of wind power, therefore, for knowing the wind regime that will be under the wind system, it is necessary to optimize energy applications to predict the operating conditions and performance. The main objective of this study was to evaluate the performance of middle-class turbines in real operating conditions connected to the power supply of the wind farm [9, 1]. Turbines performance calculations are aimed at determining the annual and monthly variations of energy production and wind speed. The work also includes evaluation of the operating power consumption and determination of the capacity factor. The wind farm examined in this study is located in the northwest Spain and consists of 32 wind turbines; these turbines have a power of 66 kw and a rotor diameter of 46 m and a total nominal power of 2112 kw and estimated annual production of 52 GWh for an equivalent of 25 h/year at full load. FORMATEX

2 In this paper, dataset was analyzed during 3 years of actual operation of the wind farm. The wind farm energy production is calculated monthly based on the 1-min readings of wind farms energy counters, while the average of the variation of wind speed is calculated from the operating records for this period. 2. Results The determination regarding whether 1 year of operation produced more energy than the other is difficult. However, due to variations in daily and seasonal characteristics of wind, it is necessary to evaluate the wind farm performance by investigating not just one year, but several years of operation. Moreover, this work allowed a better representation of the status of wind energy specifically in a wind farm and allowed a more accurate comparison with other parks. 2.1 Annual energy production The wind farm energy production in a given year is overseen by the total units (megawatts) of power generated by all turbines during that year. Figure 1 shows the variation of the total energy production of the wind farm studied during normal operation over the 3 years of study. The second year of the study had lower energy production as compared to the other years. Figure 2 shows that the wind speed was lower in the second year of study, which explains why it is the year of lower energy production. Annual Energy Production (MWh) 6,2 6,1 6, 5,9 5,8 5,7 5,6 5,5 5,4 5,3 Years Fig. 1 Annual variation in wind energy production at the wind farm Annual variation of wind speed (m/s) Years Fig. 2 Annual variation of wind speed 582 FORMATEX 213

3 Figures 3 and 4 show monthly changes of wind speed and energy generated, respectively, during the study time. In fact, in of the second year, the wind reached an average speed of 4.54 m/s (Figure 3), and wind turbines were almost in the operating limit for low speed and energy production at 3189 MWh (Figure 4). In contrast, the of the first year showed greater energy production with 8477 MWh under a mean wind speed of 12 m/s, and the of the third year showed energy production of 9258 MWh under a mean wind speed of m/s. Average Wind Speed (m/s) Fig. 3 Monthly variation of wind speed 1, Anual Energy Production (MWh) 9, 8, 7, 6, 5, 4, 3, 2, 1, Fig. 4 Monthly variation of wind speed at all reporting period The comparison of different months averages during the study period is shown in Figure 5. From these data, focusing on the average values obtained in each months of the study period, Figure 6 shows that the minimum wind speeds reaching the wind farm were in the months of,,, and ; thus, the energy production in those months were the minimum. In contrast, in the months of and, the greatest average wind speed and thus higher monthly energy production was seen. FORMATEX

4 1, 9, Variation of Wind Energy Production 8, 7, 6, 5, 4, 3, 2, 1, Fig. 5 Monthly variation of wind speed throughout the study period 8, 16. 7, 14. 6, 12. 5, 1. MWh 4, 8. m/s 3, 6. 2, Month Average Energy Production (MWh) Month Average Wind Speed (m/s) 4. 1, Operating hours and equivalents hours Fig. 6 Monthly average energy production and wind speed The actual operating hours for which the turbines are in operation or ready to function is significant. Figure 7 shows the actual operating hours of the wind farm during the 3 years of study. Another parameter to consider is the equivalent hours, which is the ratio of the power generated by the wind farm in a given month and the installed power in it. That is, it gives the measure of how many hours of operation at full power wind farm is required to produce total energy in a given month, or, the number of hours that wind turbines should have been set to the nominal power to produce the same amount of energy in the time period considered. 7 6 Operating Hours Average Operating Hours Equivalents Hours Fig. 7 Operating hours vs. equivalents hours 584 FORMATEX 213

5 2.3 Capacity factor Wind turbines are usually acquired through aftermarket service contracts lasting for 2 5 years, which include guarantees and preventive and corrective maintenance that could be adopted after the expiry of the contract period. However, severe and unexpected failures can occur between the planned maintenance intervals (time-based maintenance, TBM), causing loss of money, time, and energy production. Moreover, the maintenance after the occurrence of failures can lead to catastrophic failure of critical components, producing severe consequences in regard to safety, health, and environment. The annual or monthly production of energy is easily understandable as is the total units of power (kilowatt) actually produced by a wind turbine or a wind farm in that period. A more concrete way to achieve the annual energy output of a wind turbine is to consider the capacity factor of the turbine in its particular location. This factor is given as the ratio of the actual annual energy production for the theoretical maximum output, if the machine is running at its rated power throughout the year. Furthermore, the capacity factor can be calculated with the ratio of equivalent hours and total number of hours in the study period. Similarly, the capacity factor can be calculated for any period as monthly and quarterly capacity factor. It is dimensionless and thus can be given in percentage by multiplying by 1. Although, theoretically, capacity factors can vary from % to 1%, in practice, the value of the capacity factor must be greater than 2% for a power generation system, either a wind turbine or a wind farm, preliminarily deemed economically feasible. Generally, it is in the range of 2% to 7%, and mostly approximately 3%. The value of this factor is actually affected by the intermittent nature of wind, availability of the machine, and the efficiency of the turbine. It can also be influenced by other causes of loss of interaction energy of the matrix as the transmission or which does not take into account the performance characteristics of the machine. In this case, significant differences were found between the different capacity factors. Figure 8 shows these changes in monthly capacity factor. It can be observed that even in same months in different years, this factor varies according to the variation of the ratio of equivalent hours and total hours each month. A specific value cannot be extrapolated from one year to another for the same. The average values for the 3-year study of the wind farm are.4,.36, and.39, respectively. In 3 years, this factor was greater than.35, and thus it is estimated that a park works optimally Capacity Factor Fig. 8 Capacity factor Figure 9 shows the variation of changes in the annual capacity factor, which shows that the summer months (,,, and ) tend to have the lowest values, indicating that production is worst during these months. This factor can be taken into account in studies of wind over a long period of time. However, they are not conclusive for analyzing daily or monthly parks. FORMATEX

6 Annual Variation of Capacity Factor Technical availability Fig. 9 Annual variation of capacity factor Another factor to consider in the production of energy in a wind farm is the technical availability, which is defined as the percentage of time in a given period that a machine is ready for operation, which is high (about 98%) in wind turbines. However, this is due to the rapid and frequent maintenance and not at a good level of reliability and maintenance management. This technical availability is calculated based on the total hours of machine production subtracted by the number of hours of preventive and corrective maintenance, modifications, and retrofits or errors of wind turbines or wind farm. Moreover, in Figure 1, the technical availability of the park can be seen in each month of the study, with annual averages of 97.86%, 98.72%, and 97.62%, respectively. It can be said that it is around average values established for the operation of this equipment, but there are better values at less than 97% and even 96% of the technical availability in the months of,, and of the first year and,, and of the third year. The annual technical availability during these 2 years is below established as valid values for this parameter. 1% 99% Technical Availability 98% 97% 96% 95% 94% 93% 2.5 Power curves Fig. 1 Technical availability Power curves of three significant turbines 32 that comprise the wind farm are shown in Figures 11, 12, and 13. These curves are calculated with data obtained in the 1-min period of study during 3 years so that the density of the sample is very high. If the regression of each is calculated, the values of the coefficients of determination (r 2 ) can be estimated, which shows the percentage of variability in the data explained by the association between the two variables. These regression coefficients calculated for the simulation of wind turbines are.9583,.9771, and.9898, respectively, for each of the 586 FORMATEX 213

7 three taken as an example, indicating the high correlation of the power curve obtained by wind turbines and equation obtained with these regressions Power (kw) Wind Speed (m/s) Fig. 11 Power Curve Aero Power (kw) Wind Speed (m/s) Fig. 12 Power Curve Aero 32 FORMATEX

8 7 6 5 Power (kw) Wind Speed (m/s) Fig. 13 Power Curve Aero 17 Once the three curves obtained function of these three wind turbines, they can be compared with the power curve given by the manufacturer for this model of wind turbine. Figure 14 shows the bold power curve given by the manufacturer. We have represented in greyscale three power curves exemplary calculated above. In this way, we could compare the actual performance with the theoretical performance. The studied wind farm had some aerodynamic losses regulation turbines (stall, passive), which have rotor blades bolted onto the hub at a fixed angle. Designing the blades this way increases the speed of wind flow around the blade profile of the surface by swirling, thereby producing greater sustenance and lower drag forces against power increase. Thus, it is a decrease of the power in the power curve, the average speed since the park was expected around 14 m/s, with average speeds in the study period from 8.15, 7.23, and 7.97 m/s, respectively, for each year, as shown in Figure Power (kw) Wind Speed (m/s) Fig. 14 Comparison of the power curve and the real curves 3. Discussion Current designs of wind turbines can be classified into fixed-pitch blade and blade variable pitch wind turbine. The studied wind farm had some aerodynamic losses regulation turbines (stall, passive), which have rotor blades bolted onto the hub at a fixed angle. The major advantage of this blade type is the simplicity of the equipment and its cost. High wind speeds do not optimally exploit the aerodynamic properties of the blades, with consequent loss of energy captured. 588 FORMATEX 213

9 Furthermore, control systems exist for changing the pitch angle of the blade, also called as variable pitch, and has the ability to rotate the blades along their longitudinal axis for controlling power according to the wind conditions and maximizing the aerodynamic efficiency of the rotor. This system allows a nominal power extraction for wind speeds above what was rated, allowing a safety system with high speed winds. The advantages that justify their use include the following: Varying the angle of inclination of the blade, one can optimize the utilization of wind energy in the entire speed range, very particularly above the nominal speed of the turbine. With variable pitch, the mechanical loads on the blades and other wind turbine are smaller, enabling a lighter and lower cost of blade. In zones where noise is a problem, the variable pitch decreases at high wind speeds or limits noise generation at any wind speed. The turbine can be adjusted by software to work at an output lower than the established networks, usually very weak case. However, if using turbines that have aerodynamic losses, regulation is used for changing the blade pitch angle to obtain more efficient power curve for the wind speed at a given time. By achieving this and considering the availability of the machine, it will be equal to that obtained on average in this time period; this will increase wind farm capacity factor, and thus there will be a greater number of equivalent hours (Figure 7). This translates into a significant increase in the production of wind farm with the same natural resources without increasing the environmental impact caused by these facilities in work zones. By having an aerodynamic losses regulation, regulation would be recommended from time to time to adjust the angle of attack with the expected average rate for that period. But this regulation is virtually ruled out by all companies for the high cost of performing. 4. Conclusions The wind power industry has developed significantly in recent decades and is conducting high penetration of wind power in the electrical networks. This paper describes the operation of turbines of a wind farm and the status of wind energy on that farm during 3 years of actual operation. Wind technology is mature, but the focus of scientific attention should be directed to integration of these teams in the regional, national, and international power networks. This will require new technical and economic models of wind energy production and their networks. The first wind farms produced electricity from a low quality, which had to be compensated by other power producers. Today, although it has improved in the signal turns to the network, it is still poor by almost unpredictable variations in environmental conditions, making additional power, but not replacing the traditional sources. In addition, it can be concluded that although wind energy production has a great development in recent years, one cannot forget that all wind farms installed worldwide have rather primitive or undeveloped with technology, which is not apt for greater energy efficiency from this natural energy source. Thus, it is advisable to update these obsolete technologies by advanced technologies that are much more efficient with the same environmental impact. References [1] Orosa, J.A A new stochastic approach to weather condition for wind energy applications. Energy Education Science and Technology Part A: Energy Science and Research. 212;28(2): [2] Roshan, G., Orosa, J.A. 21. Simulation of the global warming effect on outdoor thermal comfort conditions. Int. J. Environ. Sci. Tech., 21;7 (3): [3] Orosa, J.A., García-Bustelo, E.J., Pérez., J.A. 29, Galician climatic change effect on wind power production. PowerEng 29. The 2º International Conference on Power Engineering, Energy and Electrical Devices. Lisbon. 29. [4] Orosa, J.A., García-Bustelo, E.J., Grueiro, T World quests for future energy production. IJES International Journal of Energy Science. IJES 211;1 (2): [5] Orosa, J.A., Oliveira, A.C Realistic solutions for wind power production with climate change. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. 211;32:1-8. [6] Orosa, J.A., García-Bustelo, E.J., Oliveira, A.C. Experimental test of low wind turbines concentrators. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. 212;34: 13. [7] Orosa, J.A., García-Bustelo, E.J., Pérez, J.A. 29. Wind turbine concentrator design based on moist air phase change. PowerEng 29. The 2º International Conference on Power Engineering, Energy and Electrical Devices. Lisbon. 29. [8] Orosa, J.A., García-Bustelo, E.J. Oliveira, A.C. Low speed wind concentrator design. IECON9. Porto. 29. [9] Orosa, J.A., Oliveira, A.C., Costa, A.M. New procedure for wind farm maintenance. Industrial Management & Data Systems, 21;11. [1] Costa, A.M., Orosa, J.A. Indicadores de costos de mantenimiento. Mantenimiento: ingeniería industrial y de edificios, 21;24, FORMATEX