CHAPTER 5 Conclusion
5.1 Future work and recommendations
attaining accurate solar spectrum simulation.
In the context of the limitations of the study, time and resources were perhaps the main issues of concern. Prior to initiating the process of fabricating the LED solar simulator, the researcher failed to attain a key milestone which was to develop a light concentrator. The task was to be implemented in collaboration between the researcher and the laboratory technician, but to the increased workload on the technician and time constraints, the researcher managed to develop a smaller version which was used in this study. By doing so the researcher demonstrated the ability to be proactive and versatile by coping with emerging challenges to meet project objectives. However, the significance of the limitations on the outcomes of the results are considerably minimal since the small light concentrator managed to achieve relevant results during the experimentation phase. Additionally, a key lesson that emerged with regards to the limitations was the need for adequate resources in developing highly efficient LED solar simulators. LED solar simulators are resource intensive to fabricate ranging from the light concentrators and computer software required for light intensity management. As result, adequate short term and long‐term resource particularly financial should be considered to ensure that the LED solar simulator developed can be effectively and sustainably used to match the solar spectrum.
5.1
Future work and recommendations
Based on the research design considered in this study in addition to the outcomes realised, there are number of key implications for future studies that can be recommended. The number of wavelengths used should be significantly increased to improve the prospects of LED solar simulators in efficiently matching the solar spectrum.
This was a key insight in this research that should set precedence for future studies in the area. Similarly, future studies should place more emphasis on incorporating adequate LED controls to facilitate the process of managing the intensity of wavelengths based on changes in temperature. Achieving a control environment, a primary objective of all LED solar simulators hence the need to incorporate reliable software control systems to regulate intensity, classification, size and uniformity. Additionally, it is recommended that future research studies should allocate adequate time in its research designs for developing an effective LED solar simulator. This is based on the evidence from this study which highlighted the potential time‐consuming nature in the fabrication stages. The researcher was subjected to significant pressure to complete the project despite the limited time available to deliver some of the time intensive project milestones such as fabricating the light concentrator. As a result, there is need to accommodate adequate time in future research designs to avoid the prospects of compromising on the quality of the experimentation process. Additionally, the outcomes of the results have the potential to contribute towards the development of a tuneable close match LED simulator.
Another key recommendation for future research involves the analysis phase which is the final major phase of the solar simulator design methodology. In this phase, the performance of the solar simulator is analysed in order to give the solar simulator a classification based on the American Society for Testing and Materials (ASTM) class specifications. This specification rates solar simulators from Class A to Class C. Other popular class specifications are the International Electro‐technical Commission (IEC) and the Japanese Industrial Standards (JIS).
5.1.1
Performance Analysis
In order to determine the performance, and thus the classification, of the solar simulator, tests are done on three parameters: spectral match, irradiance spatial non‐ uniformity, and temporal instability. The class is determined by the lowest rating achieved across these three categories. Table 9 below shows the thresholds for each class rating in each parameter.
Table 9: ASTM Class Specifications [39]
Classification Spectral Match (each interval)
Irradiance Spatial Non-
Uniformity Temporal Instability
Class A 0.75–1.25 2% 2% Class B 0.6–1.4 5% 5% Class C 0.4–2.0 10% 10%
5.1.2
Spectral Match
The spectral match refers to the similarity to a reference spectrum. This is determined by ‘measuring the distribution irradiance as a percentage of the total irradiance across specific wavebands’ [40]. According to ASTM specifications, there are three standard reference spectra for different conditions. These are direct (AM1.5D), global (AM1.5G) and extra‐terrestrial (AM0). The distribution of the irradiance performance requirements is seen in Table 10 below.
Table 10: Distribution of Irradiance Performance Requirements [41] Wavelength (nm) Percentage of Total Irradiance (AM1.5G) 400‐500 18.4% 500‐600 19.9% 600‐700 18.4% 700‐800 14.9% 800‐900 12.5% 900‐1100 15.9%
𝐴𝑐𝑡𝑢𝑎𝑙 𝑝𝑒𝑟𝑐𝑒𝑛𝑡𝑎𝑔𝑒 𝑜𝑓 𝐼𝑟𝑟𝑎𝑑𝑖𝑎𝑛𝑐𝑒
. . (8) Where; [41] 𝑆 𝜆 Is the spectral irradiance of the light source. 𝜆 Is the ending point of a wavelength band. 𝜆 Is the starting point of a wavelength band.It is essential for the design and construction of a solar simulator to be capable of simulating the expected irradiance as the spectral match depends on the spectral irradiance of the specific light source being utilised. The uniformity of the light intensity distribution across the test plane can be measured by Spatial Non‐Uniformity. There are different standards in how many uniformly spaced test positions are necessary so as to calculate spatial non‐uniformity with the IEC standards requiring the use of 64 test positions. However, the ASTM specifies only 36 test positions. [41]
Where; [41] 𝐸 Is the maximum irradiance in the test plane. 𝐸 Is the mean irradiance in the test plane.
5.1.3
Spatial Non‐Uniformity
In order to test non‐uniformity, the irradiance is mapped over the test area. The test area is divided into smaller test positions to measure the uniformity value. For the ASTM specifications, it is recommended that the test area is divided into 36 smaller test positions [42]. The values for these smaller test positions are compared in order to determine the non‐uniformity across the entire test area, using Equation 1 below:𝑁𝑜𝑛
𝑢𝑛𝑖𝑓𝑜𝑟𝑚𝑖𝑡𝑦 %
100%
(10)
5.1.4
Temporal Instability
In measuring the temporal instability, it was necessary to measure both the short‐term instability (STI) and long‐term instability (LTI). It is calculated using Equation 2 below after measuring ‘the irradiance of the simulator beam over a specified time period’ [43].
𝑇𝑒𝑚𝑝𝑜𝑟𝑎𝑙 𝑖𝑛𝑠𝑡𝑎𝑏𝑖𝑙𝑖𝑡𝑦 %
100%
(11)6
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