**6. Performance Comparison**

Taking the measured turbine performance we can predict the power production versus wind speed. Based on manufacturers published performance curved our turbine can be compared to existing commercial turbines. Wind data was recorded at a proposed turbine test site on a costal facing ridge at an altitude of 400m at Banjaran Relau in Kedah, Malaysia. This gave slightly higher wind speeds than the turbine test site atop the mechanical engi‐ neering building. A sample of the wind data is shown in figure 14.

The wind speed data exhibits a diurnal pattern with some marine layer pumping associated with the proximity to the coast with the highest winds speeds in the afternoon. Additionally is can be seen that there can be several days, eg. day 13 to 18 in figure 14, with very little wind underscoring the need for significant storage capacity.

**Figure 14.** Wind speed the Banjaran Relau turbine test site in Kedah, Malaysia

Additional measurements made on the turbine bearings indicated frictional losses account for 23W at 300 rpm. This is approximately 10% of the electrical power produced. The use of automotive bearings is perhaps not optimal from a friction stand point, thus with improve‐ ments in the bearings it may be possible to improve the turbine output by something on the

**Figure 13.** Electrical power versus wind speed at 9 degree attack angle with 6 ohm load

neering building. A sample of the wind data is shown in figure 14.

wind underscoring the need for significant storage capacity.

Looking back at figure 9 we can see that a 200W output should occur at approximately 300rpm with the 6 ohm load. Using this to calculate the TSR at a 4.2m/s wind speed we come up with a TRS of 17, close to our assumed value of 16, and significantly higher than

Taking the measured turbine performance we can predict the power production versus wind speed. Based on manufacturers published performance curved our turbine can be compared to existing commercial turbines. Wind data was recorded at a proposed turbine test site on a costal facing ridge at an altitude of 400m at Banjaran Relau in Kedah, Malaysia. This gave slightly higher wind speeds than the turbine test site atop the mechanical engi‐

The wind speed data exhibits a diurnal pattern with some marine layer pumping associated with the proximity to the coast with the highest winds speeds in the afternoon. Additionally is can be seen that there can be several days, eg. day 13 to 18 in figure 14, with very little

order of perhaps 5% or so.

280 Advances in Wind Power

the conventional value of 8.

**6. Performance Comparison**

**Figure 15.** Wind probability and predicted electrical power production versus wind speed for several commercial tur‐ bines, and the turbine developed in this study.

Figure 15 shows the power produced by three small commercial turbines, and the one de‐ veloped in this study versus wind speed, as well as the wind probability at the turbine test site. As the optimized turbine will be spinning at a higher rotational speed than the other turbines, the controller will begin electrical breaking at wind speeds above 7m/s, effectively negating the turbine's output above this speed. This is not overly restrictive as the wind rarely blows at speeds above 7m/s for more than a few minutes per month.

It can be seen that the optimized turbine produces significantly more power than the com‐ mercial turbines at the lower wind speeds, and of course significantly less power at the higher speeds the other turbines are rated for. This is expected as the optimized turbine has a larger swept area, and has been tuned for low wind speed operation.

Multiplying the generator's power times the wind speed probability at each wind speed, we can derive the normalized power production curves of figure 16. Peak power probability for this data set is at 3m/s, with a lower peak in the power probability curve at 4.5m/s. As the wind speed at the test site never exceeded 7m/s for any significant amount of time the opti‐ mized turbine is shown to generate 3 to 4 times more power than the commercial turbines over the whole available wind speed range. There is a dip in the wind probability data at around 4m/s in the data over the period sampled due to the limited amount of data. In gen‐ eral we would expect a fairly smooth wind probability profile with a peak between 3.5 and 4.5m/s at this wind site.

**Figure 16.** Comparison of normalize wind power for various wind turbines

Power production in a 5 m/s wind is expected to be around 350W, and in a region produc‐ ing this wind for 4.8 hours of production per day, should result in 1.68 kWh of energy pro‐ duction per day. Assuming storage losses of 30% associated with charge/discharge of batteries and power transmission this will result in about 1.2kWh of usable energy per day, close to our initial estimate of 1.3kWh per day required for a rural dwelling. Thus it is ex‐ pected that a purpose designed 2.25m radius wind turbine of relatively simple construction is sufficient to power a single rural dwelling in the windier parts of SEA.

#### **7. Conclusion**

Most commercial turbines are designed for relatively high wind speeds, around 10m/s, pro‐ duce insignificant amounts of power below 5m/s. Taking a conventional axial flux, direct drive horizontal axis 3-blade wind turbine as the starting point we were able to optimize the turbine and generator for lower wind speed operation and achieve a significantly higher power output than existing commercial turbines at lower wind speeds. Further optimization of the turbine is possible and should focus on airfoil shape, blade weight and construction and bearing friction. While the use of larger blades will increase the cost and weight of the turbine and tower it is still believed that wind power can be a viable alternative even in re‐ gions of relatively low winds.
