ASSESSMENT OF SOLAR ENERGY AND WIND PARAMETERS IN NAIVASHA, KENYA

* L. Thimo 1 , J. Kamau 2 and R. Kinyua 1 . 1. Institute of Environmental and Energy Technology, Jomo Kenyatta University of Agriculture and Technology. 2. Department of Physics. Jomo Kenyatta university of Agriculture and Technology. ...................................................................................................................... Manuscript Info Abstract ......................... ........................................................................ Manuscript History


ISSN: 2320-5407
Int. J. Adv. Res. 5 (5), 495-502 496 systems electricity is generated by Solar PV and stored in batteries to be used at night when there no irradiance. Ongrid solar systems are integrated to the grid and power generated by Solar PV is fed to the grid (Solar Direct , 2015). Solar PV modules are designed to operate at standards test conditions of 1 kW/m 2, 25 0 C for the cells to generate maximum current. However it is not practically possible for a module to operate at this conditions, each cell usually has a standard voltage output of between (0.5-0.6V) depending with cell type (monocrystalline or polycrystalline). Monocrystalline cells have higher efficiency than polycrystalline since they are made from high grade silicon, its efficiency rate is typically between 15-20% while the efficiency of polycrystalline is typically between 13-14% (S. Steven & Luque, 2003).
……………………….……….. (1) Efficiency of the module is relative to the demission, therefore; …………. (2) The solar PV power generation is dependent to solar irradiance in a day which is affected by several conditions for instance; cloud, dust, shadow casted on the module and high temperatures of the modules. Where I is the system current (charging current), Isc is the module short circuit current, Irr. Daily is irradiance per day.
In previous years several studies have been conducted within series of span to show the potential of solar energy in different part of Kenya. Okoola, (1997) observed that insolation reach its peak during the afternoon session. Barman, (2011) analyzed that annual insolation of Nairobi as 2100kWh/m 2 . Both researchers conducted the assessment alone but never showed the level of the need in terms of future energy for the purpose of heat or electricity generation and no comparison of available energy sources was done.
Wasike et al., (2014) assessed solar radiation in Thika and Nairobi area to provide information on the solar energy source of the two regions using Gunn-Bellani and Pyranometer to collect data for analysis. From the analysis, it was concluded that the average annual daily insolation ranged from 4-6 kWh/m 2 /day and the average monthly daily insolation range from 3-7 kWh/m 2 /day, and these shows that the region is endowed with enough insolation for solar energy application.
Omwando et al., (2011) investigated solar energy potential in Nakuru between longitudes 35 o 28'and 35 o 36'East and latitudes 0 o 12'and 1 o 10'South its altitude is 1859 m above the sea level. From the insolation values as measured for Nakuru municipality, the minimum monthly recorded value is 4.8 kWh/m 2 /day. Results revealed that Nakuru has a moderate to high solar energy potential, with an average daily insolation of 6.9 kWh/m 2 . In November, 1997 the maximum value recorded is 9.8 kWh/m 2 /day in February the same year, in dry hot seasons a lot of solar radiation penetrates the earth's atmosphere (Okoola, 1997).The researchers did not show any comparison between solar energy and other available energy sources. This study compared the solar and wind parameters in Naivasha-Nakuru country.
Wind:-Wind turbines converts the energy of moving air into useful mechanical or electrical energy, wind turbine needs more maintenance than Solar PV but with moderate wind speeds greater than 4.5 m/s will often produce more energy than similar priced solar panels. (Riezeret al., 2000).
In the process of producing electrical energy from wind using wind power generators, there is numerous energy losses. At rotor, there is aerodynamic loss of around 60% of wind power input. Furthermore, there are mechanical losses of around 4% as the speed increasers, such as gears. Electrical and mechanical losses of around 6% at generator (Manwell et al., 2012.) 497 A wind turbine performance is characterized by its power curve which relates wind turbine power output to the hub height and wind speed. Wind turbines produce much more power at higher wind speeds than at lower wind speeds until the wind speed reaches the cut out speed, the power curve below shows the power output of a typical wind turbine operating at lower and steady wind speeds (Riezer et al., 2000). According to Power law, wind speed depend with the heights due the effects of terrerains, the wind speed near the ground lower as compered to some height above, equation (4)
According Rayleigh and wellbull wind speed probability can be estimated based on the wind data at the monitoring station or using the model called "Weibull distribution" or "Rayleigh distribution" if wind data is not available at the project site. Weibull distribution determines two parameters k and c which represents wind speed, Rayleigh distribution is a special case of Weibull distribution where only parameter k and average wind speed is needed (Manwell et al.,2012), (Kantar & Usta , 2008 Where : air density , A: Area, ̅ : average wind speed, k: shape factor, c: scale factor.

Study site and methodology:-
The data was collected in Naivasha, Nakuru county Kenya, the latitude of Naivasha is -0.717178, and the longitude is 36.431026 with the GPS coordinates of 0° 43' 1.8408'' S and 36° 25' 51.6936'' E.

Solar:-
The data used in this study was the mean irradiance per day (W/m 2 ) in seven hours of sunshine; the irradiance/second data were recorded at the height of 6m by use of a thermopile (Pyranometer) MS-602Sensor. Temperatures were also measured and recorded by Hioki data logging system for the sampled period of time.
Wind:-Wind speeds (m/s) mean data was recorded 24 hours a day for period of three months; wind sensor kit was installed at height of 6m. However using the power law (equation.4) the wind spends was elevated to a height of 10m. The statistical analysis of the data using Excel (Microsoft office) and origin software as research tool was done to determine the mean and generating illustration curves.  6 illustrates site experiment setup for data collection procedures. Four solar PV modules, two N70, 12V batteries (connected in series) were used to supply power to the data logging system. The system was installed at a height of above 6m to ensure no shade casted by any tall obstacles, regular maintenance was carried out to ensure the solar radiation sensor (Pyranometer) and other equipment was free from dust.

Conclusion and Recommendation:-
Naivasha was observed to be potentially viable site for solar systems installation, the result illustrated that the minimum insolation recorded every day for 90 days. A total 18.58kWh/m 2 was available per day during sampled period of this study, this is technically viable for power generation for a home system and for commercial use. The insolation reported by (Omwando et.al, 2014) for Nakuru county was lower as compered with the findings of this study. Using solar PV as well as solar water heater for domestic/commercial use will be one of the environmental conservation remedy.
Wind parameters were not so impressive at height of 10m, and only small wind turbine with cut in wind speed (2-2.5m/s) may be considered for power generation. Windmills would be a bit appropriate to pumping water for commercial and for domestic use. Naivasha is semi-arid and water is quite scarce in particular sessions. Wind speed results were comparable with the findings by (Maina, et al., 2016). However due to wind turbines mechanical challenges and regular maintenance, the results of this study found solar PV module would be ideal for power generation in this particular site.
This research would recommend the investors in hotels, lodges restaurants, learning institutions and hospitals to install solar systems i.e solar PV for power generation and solar water heating system and utilize them as remedy to save energy and reduce the electricity bill nearly by 60%. The researchers also recommend for more research to be

Wind speed
Wind speed at 6m Wind speed at 10m 502 carried out particularly for assessing solar and wind energy potential in all parts of Kenya in order to have a reliable data for designing solar or wind energy systems.
The researcher would like to acknowledge the support from JICA through BRIGHT Project and Institute of Environmental and Energy Technology, Jomo Kenyatta university of Agriculture and Technology.