Microsoft Word - 17011.docx 124 Mathematical and Software Engineering, Vol. 3, No. 1 (2017), 124-138. Varεpsilon Ltd, varepsilon.com Comparative Analysis of the Solar Potential of Offshore and Onshore Photovoltaic Power System Anyanime Tim Umoette 1 , Simeon Ozuomba2*, Nseobong I. Okpura3 1Department of Electrical/Electronic Engineering, Akwa Ibom State University Mkpat Enin, Akwa Ibom State, Nigeria. 2,3Department of Electrical/Electronic and Computer Engineering, University of Uyo, AkwaIbom, Nigeria. * corresponding author: simeonoz@yahoo.com Abstract In this paper, comparative analyses of performance parameters of onshore and offshore PV system are conducted and the result showed that the offshore PV system has better performance in terms of higher energy yield and performance ratio as well as improved temperature de-rating factor due to it lower cell temperature. The study is conducted for PV array site around Bar Beach in Lagos, Nigeria. Meteorological data from NASA website and PV array with total area of 268�� are used for the study. According to the results, the offshore ambient temperature is about 5.57% less than that of onshore, the offshore wind speed is 74.86% more than that of the onshore, whereas, the offshore effective PV cell temperature is 9.96% less than that of the onshore . The cumulative effect of the differences in atmospheric parameters on the PV cell temperature also resulted to 1.99% higher and better offshore de-rating factor over that of the onshore as well as 1.99% improvement in energy output, the specific energy yield and performance ratio. Evidently, the offshore PV with lower effective cell temperature performed better than the onshore PV system. Keywords: Photovoltaic; Standalone PV System; Cell Temperature; Temperature De-rating factor; Onshore PV System; Offshore PV System. 1. Introduction Over the years, solar energy has become very important source of energy all over the world, more especially in developing countries such as Nigeria [1]. Furthermore, in Nigeria, due to the perennial severe shortfall in energy supply from the national grid, most residential and commercial consumers are resorting to alternative form of energy to meet their energy demands [2]. In this wise, photovoltaic (PV) energy system has become the best choice for alternative energy source for Nigerian energy consumers given the abundant solar radiations that are readily available all over the country, all year round. In addition, in recent years, the added advantages of lower cell temperature of water cooled or floating PV systems have gained much attention of researchers [3,4]. However, Nigerians are yet to key into such advancement in PV power technology. Particularly, most tourist centers by seashores are still powered by diesel generators despite the higher solar energy potential that the sea climate with lower ambient 125 temperature can afford for PV power installation [5,6,7] In view of this oversight, this paper seeks to examine the performance of PV installation on seashore of Bar Beach in Lagos state of Nigeria and then compare the performance with that of offshore PV installation. According studies, PV power plants’ performance depends on numerous parameters that amount to many loss mechanisms [8,9,10]. Notably, the specific losses associated with a given PV plant can be categorized into two groups, namely, system losses and capture losses. Capture losses are caused by factors such as attenuation of the incoming light, soiling of PV module surface, ambient temperature, electrical mismatching , among others [9, 11]. For instance, module output power reduces as module temperature increases. Dirt and dust that do accumulate on the PV module surface block some of the sunlight reaching the module and thereby reduce the module output power. On the other hand, system losses are caused by factors such as wiring losses, inverter inefficiency losses and transformer conversion losses [9,11]. For example, the inverters used in most PV systems have peak efficiencies that are less than 100%. Consequently, some of the DC power generated by the PV modules is lost in the DC to AC conversion process. The cumulative effect of all the losses are captured as de-rating factor used to reduce the STC rated power of the PV module to the actual value that is dependent on the particular system components and environmental factors for the given PV installation. As such, in order to compare different PV installation some performance parameters that capture some or all of the system and environmental factors are required [10,12]. Among others, the three most commonly used parameters are the yearly energy output of the PV installation, the specific energy yield and the performance ratio plant [13,14,15,16,17,18,19]. One common basis for comparing PV modules is through the use of Standard Test Condition (STC) in specifying PV parameters; where the STC is given as 1000 �/�� Irradiance, 25°C cell temperature, and AM1.5 Spectrum [20,21,22,23]. In particular, manufacturers often specify the peak power (Wp) output of a PV panel. The peak power value specifies the output power achieved by a PV module under Standard Test Conditions with peak solar radiation of 1,000 ��. In practice, the maximum power a PV installation can produce will usually be significantly lower than the peak power rating. One reason for this is that peak solar radiation of 1,000 �� is a high level of solar radiation achieved only in very sunny conditions. The actual solar radiation received in most cases will often be less than the peak solar radiation figure and will also be dependent on other system losses and capture losses associated with the PV installation. Essentially, in most PV installations, the actual energy output of the PV is less than the rated peak energy output of the PV. The ratio of the actual power output to the peak power output is known as the performance ratio. The performance ratio (PR) is usually expressed in percentage. PR refers to the ratio of the actual energy output and the theoretical energy output of the PV [24]. Hence, PR shows the percentage of the energy that is actually delivered to the load after subtracting the energy loss due to various system and capture losses associated with the PV installation. Another key PV performance parameter considered in this paper is the specific energy yield. The specific energy yield is the net energy output divided by the nameplate DC power at the standard test condition (STC) of an installed PV array [25,26,27]. It represents the number of hours the PV array would need to operate at its rated power or peak rating to provide the same energy. The units are hours or kWh/kWp. The three key performance parameters, namely, yearly energy output of the PV installation, the specific energy yield and the performance ratio are used in this paper to compare the 126 performance of offshore and onshore PV installations sited around Bar Beach in Lagos state, Nigeria. The aim is to demonstrate the benefit of siting PV installation around the beach with it lower ambient temperature and higher wind speed when compared to the onshore environment. 2. Description of the Case Study, Lagos Bar Beach Lagos is Nigeria’s commercial capital, as well as the second most populous and second fastest-growing city in Africa and the seventh fastest-growing city in the world [28,29]. Lagos Bar Beach is the main (inner city) beach, the most accessible and most visited beach in Lagos. At latitude of 6.422290° and longitude of 3.411700, Bar Beach is located in Victoria Island which is an affluent business and residential area in Lagos Island of Lagos state. The beach runs from the west by the Institute of Oceanography all the way to Eko Hotel toward the east. Bar Beach is named after the sand bars that characterized the Lagos Atlantic Ocean coastline which stretch up to 100 kilometres [30]. Due to large influx of tourist, the beach is lined with numerous shops and recreational facilities. Also, there are several hotels sited all around the beach. 3. Methodology and Algorithms 3.1. Methodology In this study, among other things, the output energy, the specific energy yield and the performance ratio of offshore and onshore PV array located at around Lagos Bar Beach are determined. The study is based on meteorological data obtained from NASA website and PV array that consists of Schott ASE-260-DG-FT/250W PV modules with total array area of 268m�. 3.2 Meteorological Data for Lagos Bar Beach 3.2.1. Onshore Meteorological Data for Bar Beach Lagos Lagos Bar Beach is located at latitude of 6.422290° and longitude of 3.411700°. Hence, from NASA website, onshore meteorological data for the given latitude and longitude are used for the study. The meteorological data, in Table 1, include the monthly averaged daily insolation incident on a horizontal surface, the monthly averaged daily insolation incident on an equator-pointed optimally tilted surface, the daily mean air temperature, and the monthly averaged wind speed at 10 m above the sea level. Generally, solar irradiation is provided as kWh/m�. However, it can be stated as daily Peak Sun Hours (PSH) [31]. This is the equivalent number of hours of solar irradiance of 1 kWh/m�. Hence, in Table 1, solar irradiations (H� and H�) of say 5 kWh/m �/ day is equivalent to 5h in PSH. 3.2.2. Offshore Meteorological Data for Bar Beach Lagos (i) Offshore Ambient Temperature in °C (��): The offshore (or sea) ambient temperature (T�) is related to the onshore (or land) ambient temperature (T�) as follows [31,32]: �� = 5.0+0.75"�# ) (1) From Table 1, the annual average onshore ambient temperature (T�) is 25.74°C, then the annual average offshore ambient temperature (T$) is given as; %& = '.( + (.)'∗ +'.), = +,.-('°/ (ii) Offshore Wind Speed in m/s (011): The offshore (or sea) wind speed (2��) is related to the onshore (or land) wind speed (2�#) as follows [34,35,36]: 127 233 = 1.62+1.17"2�#) (2) From Table 1, the annual average onshore wind speed (V$�) is 2.8 "�/6), then the annual average offshore wind speed (V$$) is given as; 0&& = 8.9++8.8)"+.: ) = ,.:;9"1?/<+/@AB) Monthly Averaged Daily Insolation Incident On An Equator-Pointed Tilted Surface, At Tilt Angle Of 15.5° ">1?/<+/@AB) The Daily Mean Air Temperature "°C) Monthly Averaged Wind Speed At 10 m Above The Sea Level "�/6) �� �� �D EFD Jan 5.28 5.87 26.1 3.28 Feb 5.49 5.71 26.6 3.4 Mar 5.46 5.43 26.5 3.17 Apr 5.21 5.14 26.6 2.76 May 4.76 4.75 26.5 2.37 Jun 4.04 4.04 25.7 2.46 Jul 3.95 3.94 24.8 2.92 Aug 3.98 3.93 24.5 3.06 Sep 4.09 4.04 24.8 2.77 Oct 4.55 4.61 25.2 2.24 Nov 4.95 5.35 25.7 2.41 Dec 5.17 5.88 26 2.88 Annual 4.74 4.89 25.74 2.8 (Source: NASA website at: https://eosweb.larc.nasa.gov/cgi-bin/sse/grid.cgi and https://eosweb.larc.nasa.gov/cgi-bin/sse/grid.cgi?&num=184097&lat=6.422&submit=Submit&hgt=100&veg=17&s itelev=&email=&p=grid_id&p=ret_tlt0&p=T10M&p=wspd10arpt&step=2&lon=3.412) 3.3. PV Cell Temperatures for Lagos Bar Beach Onshore Cell Temperature: The onshore PV cell temperature (�G#) is given as follows [37]: �G# = 0.943 ∗ �# + 0.095 ∗ K −1.528∗ 23# + 0.3529 (3) Where; K is the daily or monthly or yearly average insulation. In this paper, G is the daily insolation incident on a tilted surface (H�) which the annual average has been determined in table 1 as 4.89kWh/m�/day or 4.89h in terms of PSH. Also, from table 1, the annual average onshore (or land) ambient temperature (T�) is 25.74°C and the onshore (or land) wind speed temperature (2�#) is 2.8m/s, hence, %OA = (.;,-∗ +'.),+ (.(;'∗,.:;−8.'+:∗+.:∗ (.-'+; %OA = 20.8061°C Offshore Cell Temperature: The offshore floating PV cell temperature (�G3) is given 128 as follows [37]: �G3 = 0.943 ∗ �3 + 0.095 ∗K −1.528 ∗233 + 0.3529 (4) Where; K is the daily or monthly or yearly average insulation. Again, K in this paper is 4.89kWh/m�/day or 4.89h in terms of PSH. Also, from table 1, the annual average offshore (or sea ambient temperature (T$) is 24.305°C and the offshore (or sea) wind speed temperature (2�$) is 4.896m/s. �PF = (.;,-∗ +,.-('+ (.(;'∗,.:;−8.'+:∗,.:;9∗ (.-'+; �PF = 16.24525°C 3.4. PV Cell De-Rating Factors for Lagos Bar Beach 3.4.1. Onshore PV Cell Temperature De-rating Factor The general expression relating the PV cell temperature and the PV cell temperature de-rating factor is given as follows [38]: STUVW = 1 −"X"�GUYY,UZZ −�[\])) (5) Where X is the power temperature coefficients; 0.40%°C for the selected PV module T̂ _``,_aa is the effective avearage daily cell temperature, where; T̂ _``,_aa = �G n#o + �[\] = �G# + �[\] (6) Generally, Tq�r = 25°C . Hence, for the onshore, T̂ _``,_aa is represented as T̂ _``,_aa"�) and the PV cell temperature de-rating factor represented as STUVW"#) is given as; T̂ _``,_aa"�) = �G n#o + �[\] = �G# + �[\] (7) %Otuu,tvv"A) = +(.:(98+ +' = 45.8061°/ STUVW"#) = 1−"X"T̂ _``,_aa"�) −�[\])) = 1 −"X" �G# + �[\] −�[\])) (8) STUVW"#) = 1−X"�G#) (9) Where, X must be divided by 100 if is given in %. vwt1?/< +/ @AB = 4.89h in terms of PSH. Hence, ²­E_®_�³�´µ"D) = "8)9.,);-(- ) "8+')",.:;) = 107872.97 Wh ²­E_®_�³�´µ"D) = 107. 87297 kWh 3.6.3. The De-Rated Output Power of the Offshore PV Modules Similarly, the de-rated output power of the offshore PV modules can be determine as follows [43]: ���_©ª"3) = "���)«SnG/#G¬ «STUVW"3)¬ (17) where ���_©ª"3) is the de-rated output power of the offshore PV modules 132 ��� is the module power at STC = 250�� SnG/#G is the DC to AC de-rating factor = 0.77 STUVW"3) is the offshore temperature de-rating factor = 0.935019 �­E_®¯"F) = "+'() "(.))) "(.;-'(8;) = 179.9911575 3.6.4. The Daily Energy Output From the offshore PV modules °��_©_\�\��"3) = «���_©ª"3) ¬ "���)"±\) (18) where °��_©_\�\��"3) is the daily energy output from the offshore PV modules ���_©ª"3)is the de-rated output power of the offshore PV modules =179.9911575 ��� is the number of modules = 125 ±\ is the irradiation for the tilt and azimuth angle of the array = 4.89 >1?/< +/ @AB ±\ = 4.89h in terms of PSH. Hence, ²­E_®_�³�´µ"F) = "8);.;;88')' ) "8+')",.:;) ²­E_®_�³�´µ"F) = 110019.60Wh = 110.01960kWh 3.7. Determination of the Specific Energy Yield of the PV Array The total rated power of the array at STC is W¶���·_q�r where [43]; W¶���·_q�r = "���)x"���) (19) ��� is the module power at STC = 250�� ��� is the number of modules = 125 Therefore, �´¹¹Dº_»�¼ = "+'()½"8+') = -8+'( Wp= -8.+'( kWp 3.7.1. The Specific Energy Yield for the Onshore PV Array The actual yearly energy output from the onshore PV modules is given as; °�o�"#) = «°��_©_\�\��"#)¬ "365) (20) where °�o�"#) is the actual yearly energy output from the onshore PV modules °��_©_\�\��"#) is the daily energy output from the onshore PV modules ²¾º¾"D) = "8():)+.;)�¿/ÀDº) "-9' ÀDº/º{D¹) ²¾º¾"D) = 39373634.05Wh/year = 39373.63405 kWh/year The Specific Energy Yield for the onshore PV ( ÁÂÃ"#)) is expressed in kWh per kWp and it can be calculated as follows [43]: ÁÂÃ"#)) = ÄÅÆÅ"Ç) �ÈÉÉÊË_ÌÍÎ (21) »­Ï"D)) = -;-)-.9-,(' Ð�¿/º{D¹ -8.+'( Ð�} = 8+';.;'9+:;9 kWh per kWp 3.7.2. The Specific Energy Yield for the Offshore PV Array 133 The actual yearly energy output from the offshore PV modules is given as; °�o�"3) = «°��_©_\�\��"3)¬ "365) (22) where °�o�"3) is the actual yearly energy output from the offshore PV modules °��_©_\�\��"3) is the daily energy output from the offshore PV modules ²¾º¾"F) = "88((8;.9(�¿ /ÀDº) "-9' ÀDº/º{D¹) ²¾º¾"F) = 40157154Wh/year = 40157.154kWh/year The Specific Energy Yield for the offshore PV ( ÁÂÃ"3)) is expressed in kWh per kWp and it can be calculated as follows [43]: ÁÂÃ"3)) = ÄÅÆÅ"Ñ) �ÈÉÉÊË_ÌÍÎ (23) »­Ï"F)) = ,(8').8', Ð�¿/º{D¹ -8.+'( Ð�} = 8+:'.(+:;+: kWh per kWp 3.8. The Performance Ratio for the Onshore PV Array The performance ratio (PR) ratio is a reflection of the system losses and it is used to assess the installation quality. The performance ratio for the onshore PV array can be computed as follows [43]: ÂÒ"#) = ÄÅÆÅ"Ç) ÄÓÔÕÇÖ (24) Where ÂÒ"#) is the performance ratio for the onshore PV array °�o�"#) is the actual yearly energy yield from the onshore PV system °�nU#Y is the ideal energy output of the array. Now, ×Ø@tAu = «�´¹¹Dº_»�¼¬x"��Ï) (25) Where �´¹¹Dº_»�¼ is the total rated power of the array at STC = 31.250 kWp Ù%Ú is the yearly average daily irradiation, "inÛ�ℎ/� �ÝÞ ℎ ) incident on a tilted surface Ù%Ú = -9'"Ù% ) (26) �� is the daily averaged irradiation, "inÛ�ℎ/� �ÝÞ ℎ ) incident on a tilted surface = = 4.89 >1?/<+/@AB or 4.89h Therefore , ×Ø@tAu = "-9')x"Ù% )x«�´¹¹Dº_»�¼¬ (27) ×Ø@tAu = "-9')½",.:; )½"-8.+'() = 55776.5625 kWh Now, °�o�"#) = 39373.63405 kWh/year. Then; ­¯"D) = ²¾º¾"D) ²ßÀ{Dà = -;-)-.9-,(' ''))9.'9+' = (.)('; 3.9. The Performance Ratio for the Offshore PV Array 134 The performance ratio (PR) ratio is a reflection of the system losses and it is used to assess the installation quality. The performance ratio for the offshore PV array can be computed as follows [43]: ÂÒ"3) = ÄÅÆÅ"Ñ) ÄÓÔÕÇÖ (28) where ÂÒ"#) is the performance ratio for the offshore PV array °�o�"3) is the actual yearly energy yield from the offshore PV system °�nU#Y is the ideal energy output of the array. Again, ×Ø@tAu = "-9')x"4.89 )x"31.250) = 55776.5625 kWh Now, °�o�"3) = 40157.154 kWh/year. Then; ­¯"D) = ²¾º¾"F) ²ßÀ{Dà = ,(8').8', ''))9.'9+' = (.)+( 4. Results and Discussion The summary of the results obtained from the foregoing computations are presented in Table 3 along with the percentage increase or decrease between each pair of parameters obtained for the offshore and onshore PV array. According to the results, the offshore ambient temperature is about 5.57% less than that of onshore whereas, the offshore wind speed is 74.86% more than that of the onshore. Furthermore, the offshore effective PV cell temperature is 9.96% less than that of the onshore . The cumulative effect of the differences in atmospheric parameters on the PV cell temperature also resulted to 1.99% higher and better offshore de-rating factor over that of the onshore. Similar to the temperature de-rate factor, in all the other performance parameters considered in Table 3, the offshore PV has 1.99% improvement over that of the onshore. In all, it can be stated that in the onshore and offshore PV systems that are considered, where all the system configurations are the same except the atmospheric (ambient temperature and wind speed) parameters, the effective cell temperature and hence the temperature de-rating factor becomes the differentiating factor. Particularly, all the performance parameters considered and compared are proportionally the same as the temperature de-rating factor. In any case, the study has been based on annual average values of solar radiation and atmospheric parameters. The results for daily and monthly values may well differ from the annual values. However, such daily and monthly analyses are not considered here due to space constraint. However, from the annual results, the offshore system performs better than the onshore PV system with about 1.99% higher daily and yearly energy output. 135 Table 3: Summary of the onshore and offshore performance parameters. S/ N Parameter Onshore Offshore Percentage (%) Increase or Decrease of Offshore Parameter over the Onshore Parameters 1 The annual average ambient temperature (in °C) 25.74 24.305 -5.57 2 The annual average wind speed ( in m/s) 2.8 4.896 74.86 3 The effective average daily PV cell temperature (in °C) 45.8061 41.24525 -9.96 4 PV Cell Temperature De-rating Factor 0.9167756 0.935019 1.99 5 De-Rated Output Power Of PV Modules (watts) 176.479 179.991 1.99 6 The Daily Energy Output of the PV Array (Wh/day) 107.873 110.0196 1.99 7 The actual yearly energy output (kWh/year) 39373.634 40157.154 1.99 8 The Specific Energy Yield of PV Array (in kWh per kWp ) 1259.956 1285.029 1.99 9 Performance Ratio 0.706 0.72 1.98 5. Conclusion and Recommendation 5.1. Conclusion Comparative analyses of the energy yield and other performance parameters of onshore and offshore PV system are conducted and the result showed that the offshore PV system has better performance in terms of higher energy output, better temperature de-rating factor due to lower cell temperature. It has also been found that for the onshore and offshore system analysed with the same system configuration except for the differences in atmospheric parameters, namely , ambient air temperature and wind speed, the main performance differentiating factor is the effective cell temperature and its resultant temperature de-rating factor. The lower the effective call temperature, the higher and better the temperature de-rating factor and hence the better the system performance parameters such as yearly energy, specific energy yield and performance ratio. Consequently, the offshore PV with lower effective cell temperature performed better than the onshore PV system. 5.2. Recommendation for Further Studies The study so far has considered the annual average values of the solar radiation and atmospheric parameters, the daily and monthly variations are also essential and require. The sizing and economic analysis of the offshore PV system are also needed. All these require further studies so as to provide more detailed techno-economic advantages of the offshore PV over the onshore PV system. 136 References [1] Foroudastan, Saeed D., and Olivia Dees. Solar power and sustainability in developing countries. Proceedings of the international conference on renewable energy for developing countries. 2006, 1-13. [2] Azodo, Adinife Patrick. Electric power supply, main source and backing: A survey of residential utilization features. International Journal of Research Studies in Management 3.2 (2014), 87-102. [3] Choi, Young-Kwan. A study on power generation analysis of floating PV system considering environmental impact. International Journal of Software Engineering and Its Applications 8.1 (2014), 75-84. [4] Chaniotakis, Efstratios. Modelling and analysis of water cooled photovoltaics. Department of Mechanical Engineering University of Strathclyde (2001), 1-84. [5] Shaaban, Mohamed, and J. O. Petinrin. Renewable energy potentials in Nigeria: meeting rural energy needs. Renewable and Sustainable Energy Reviews 29 (2014): 72-84. [6] Offiong, A. Assessing the Economic and Environmental Prospects of stand-By solar powered systems in Nigeria. Journal of Applied Sciences and Environmental Management 7.1 (2004): 37-42. [7] Ugwu, H. U., Nwankwojike, B. N., Ogbonnaya, E. A., & Ekoi, E. J. (2012). Energy and Economic losses due to constant power outages in Nigeria. Nigerian Journal of Technology, 31(2), 181-188. [8] Dobos, A. P. (2014). PVWatts version 5 manual. National Renewable Energy Laboratory, September. [9] Woyte, A., Richter, M., Moser, D., Mau, S., Reich, N. and Jahn, U., Monitoring of photovoltaic systems: good practices and systematic analysis. Proc. 28th European Photovoltaic Solar Energy Conference. 2013. [10] Makrides, G., Zinsser, B., Norton, M., and Georghiou, George E. Performance of photovoltaics under actual operating conditions. INTECH Open Access Publisher, Third Generation Photovoltaics, Chapter 8, Book edited by Vasilis Fthenakis 2012. [11] Chimtavee, A., and N. Ketjoy. PV generator performance evaluation and load analysis of the PV microgrid system in Thailand. Procedia Engineering 32 (2012): 384-391. [12] Gouws, Rupert, and Lukhwareni, Thendo. Factors influencing the performance and efficiency of solar water pumping systems: A review. (2012), International Journal of Physical Sciences, Vol. 7(48), 6169-6180. [13] Babatunde, A.A., and Abbasoglu, S. Evaluation of field data and simulation results of a photovoltaic system in countries with high solar radiation. Turkish Journal of Electrical Engineering & Computer Sciences 23.6 (2015): 1608-1618. [14] Abdulrahman A.A., and Abdullah S.M. (2015). Performance Analysis of a Photovoltaic System Koya -Kurdistan of Iraq. International Journal of Computer Science and Electronics Engineering (IJCSEE) Volume 3, Issue 2. [15] Dierauf, T., Growitz, A., Kurtz, S., Cruz, J.L.B., Riley, E., Hansen, C., Weather-corrected performance ratio, Rep. NREL/TP-5200–57991, 2013. 137 [16] Muñoz, Y., Zafra, D., Acevedo, V., Ospino, A. (2014) Analysis of energy production with different photovoltaic technologies in the Colombian geography. IOP Conference Series: Materials Science and Engineering, 59. [17] Chioncel, C.P., Augustinov, L., Chioncel, P., Gillich, N., Tiran, G.O. (2009) Performance ratio of a photovoltaic plant. Bulletin Of Engineering, University Politehnica Timisoara/Fascicule 2 (2009): 555-58. [18] Marion, B., Adelstein, J., Boyle, K., Hayden, H., Hammond, B., Fletcher, T., Canada, B., Narang, D., Kimber, A., Mitchell, L., Rich, G., Townsend, T. Performance parameters for grid-connected PV systems. Photovoltaic Specialists Conference, 2005. Conference Record of the Thirty-first IEEE. IEEE, 2005. [19] Hamzeh, A., Hamed, S., Al-Omari, Z., Sandouk, A. and Aldahim, First Year Performance of a PV Plant in Jordan Compared to PV Plants in the Region. International Journal of Renewable Energy Research (IJRER) 5.4 (2015): 983-990. [20] Hu, Yang. PV module performance under real-world test conditions–a data analytics approach. Diss. Case Western Reserve University, 2014. [21] Marion, B., Kroposki, B., Emery, K., Cueto, J.del, Myers, D., and Osterwald, C.. Validation of photovoltaic module energy ratings procedure at NREL. Golden, Colo, USA: National Renewable Energy Laboratory, NREL/TP-520-26909, 1999. [22] Trancossi, M. Testing performance, weathering and aging of photovoltaic modules. ASME 2011 5th International Conference on Energy Sustainability. American Society of Mechanical Engineers, 2011, ES2011-54625, 1375-1382. [23] Cameron, C.P., Boyson, W.E., and Riley, D.M. Comparison of PV system performance-model predictions with measured PV system performance. Photovoltaic Specialists Conference, 2008. PVSC'08. 33rd IEEE. IEEE, 2008, 1-6. [24] Eyigün, S., Güler, Ö., Turkey Solar Potential and Viability of Solar Photovoltaic Power Plant in Central Anatolia. International Renewable Energy Congress, 2010, ID 159, 94-99. [25] Kullmann, S., Specific energy yield of low-power amorphous silicon and crystalline silicon photovoltaic modules in a simulated off-grid, battery-based system. Diss. Humboldt State University, 2009. http://hdl.handle.net/2148/484. [26] Van Sark, W., Bosselaar, L., Gerrissen, P., Esmeijer, K.B.D., Moraitis, P., Van den Donker, M., Emsbroek, G., Update of the Dutch PV specific yield for determination of PV contribution to renewable energy production: 25% more energy!. Proceedings of the 29th EUR-PSEC (2014): 4095-4097. [27] Chioncel, C.P., Kohake, D., Augustinov, L., Chioncel, P., Tiran, G.O. Yield factors of a photovoltaic plant. Acta Tech Corvin Bull Eng (Fascicule) 2 (2010): 63-66. [28] Ikebude, S.C., and Adebimpe, Y.A., The Forceful Relocation of Citizens within a Country: A Case Study of Lagos State, Nigeria, Thesis, 2014, Diaconia University of Applied Sciences, Helsinki Unit. [29] Alufohai, A.J., The Lagos State 2010 Mortgage Law and the Supply of Housing." FIG Working Week. 2013. [30] Eruotor, V., The Economic Importance of Tourism in Developing Countries: Case Study, Lagos, Nigeria, Thesis, Centria University of Applied Sciences, 2014. 138 [31] Ryu, J., Jang, W. S., Kim, J., Jung, Y., Engel, B. A., & Lim, K. J. (2016). Development of Field Pollutant Load Estimation Module and Linkage of QUAL2E with Watershed-Scale L-THIA ACN Model. Water, 8(7), 292. [32] Stefan, H.G., & Preud'homme, E.B. (1993). Stream Temperature Estimation from Air Temperature, Paper No. 92096 of the Water Resources Bulletin. [33] Al Riza, D.F., and Gilani, S.I.H., Standalone Photovoltaic System Sizing using Peak Sun Hour Method and Evaluation by TRNSYS Simulation. International Journal of Renewable Energy Research (IJRER) 4.1 (2014): 109-114. [34] Hsu, S.A. (1986). Determination of wind stress (drag) coefficient for coastal waters under variable meteorological and oceanographic conditions. Coastal Engineering Proceedings, Chapter 20, 286-292. [35] Hsu, S.A. Correction of land-based wind data for offshore applications: a further evaluation. Journal of physical oceanography 16.2 (1986): 390-394. [36] Hsieh, B.B., Johnson, B.H., and Richards, D.R., A Three-Dimensional Numerical Model Study for the Chesapeake and Delaware Canal and Adjacent Bays. No. WES/TR/HL-93-4. ARMY ENGINEER WATERWAYS EXPERIMENT STATION VICKSBURG MS HYDRAULICS LAB, 1993, ADA266272. [37] Muzathik, A.M., Photovoltaic Modules Operating Temperature Estimation Using a Simple Correlation. International Journal of Energy Engineering 4.4 (2014): 151-158. [38] Ishaq, M., Ibrahim, U. H., and Abubakar, H., Design of an Off Grid Photovoltaic System: A Case Study of Government Technical College, Wudil, Kano State. International Journal of Technology Enhancements and Emerging Engineering Research 2.12 (2013): 175-181. [39] Solar World, PVWatts estimated performance data. Solar World Technical Bulletin: Retrieved May 7, 2016, from http://la.solarworld.com/~/media/www/files/technical-bulletins/pv-watts-estimate d-performance-data.pdf [40] Mermoud, A., PVsyst: Software for the study and simulation of photovoltaic systems. ISE, University of Geneva, www. pvsyst. com (2012). [41] Karki, P., Adhikary, B., and Sherpa, K., Comparative study of grid-tied photovoltaic (PV) system in Kathmandu and Berlin using PVsyst. Sustainable Energy Technologies (ICSET), 2012 IEEE Third International Conference on. IEEE, 2012, DOI: 10.1109/ICSET.2012.6357397. [42] Gerstmaier, T., Gomez, M., Gombert, A., Mermoud, A. and Lejeune, T., Validation of the PVSyst Performance Model for the Concentrix CPV Technology. AIP Conference Proceedings-American Institute of Physics. Vol. 1407, 2011, 366. [43] IRENA, Design of Grid Connect PV systems, Palau Workshop on harmonised technical guidelines and grid stability assessment from 8-12 April 2012 in the Republic of Palau, The International Renewable Energy Agency (IRENA). Copyright © 2017 Anyanime Tim Umoette, Simeon Ozuomba, and Nseobong I. Okpura. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.