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In this study, it was investigated how changes in spectral solar radiation effects the output of photovoltaic modules. First, there was a precise examination of the seasonal changes in spectral solar radiation. Consequently, it was found that the ratio of spectral solar radiation available for solar cell utilization, to global solar radiation, changes from season to season. It varied, from 5% for polycrystalline silicon cells, to 14% for amorphous silicon cells, throughout one year. Obviously a cell made from amorphous silicon is more severely effected by seasonal variations. Next, the seasonal changes of photovoltaic module output were examined. The output was calculated by the conventional output evaluation method using irradiance and cell temperature. This calculated value and the subsequently measured value were accumulated and the two values compared. As a result, the accumulated output of photovoltaic modules was confirmed as changing seasonally in the same way as spectral solar radiation. The output ratio of polycrystalline silicon was found to change by 4%, while that of amorphous silicon varied by 20%. Hence the seasonal variations in spectral solar radiation should be taken into account for optimum photovoltaic power system design.

This paper presents an application of a neural network for the identification of the optimal operating point of PV modules for the real time maximum power tracking control. The output power from the modules depends on the environmental factors such as insolation, cell temperature, and so on. Therefore, accurate identification of optima[ operating point and real time continuous control are required to achieve the maximum output efficiency. The proposed neural network has a quite simple structure and provides a highly accurate identification of the optimal operating point and also a highly accurate estimation of the maximum power from the PV modules. Keywords: PV module, Neural Network, Poly-crystalline Silicon, Maximum power tracking control, Real time control

In this paper a methodology for the selection of the optimum photovoltaic module for a specific site is developed. The selection is based on the capacity factors (CF) of the available PV modules. Long term irradiance data recorded for every hour of the day for 30 years are used. These data are used to calculate the probability density function of the irradiance for different hours of a typical day in a month. The irradiance probability density function and the manufacturer's specifications on PV modules are used to calculate the capacity factors for the PV modules. The PV module with the highest average capacity factor for the specific site is the optimal and recommended PV module. In this paper the price per installed maximum peak watt is approximately the same for different modules and hence the cost is not an issue.

The analysis focuses on a comparative evaluation of emissions from conventional private passenger vehicles versus the environmental burdens of electric passenger vehicles. The batteries of electric passenger vehicles are loaded during daily working hours partly via silicon-based PV panels covering the vehicle parking areas (solar service stations), and partly via the public electric grid. The data base refers to Western Germany, and the tentative time period is around 2005. The analysis is based on detailed data collections for the fabrication of technical silicon, multi- and monocrystalline standard, MIS-I cells, and amorphous cells. The information on substance discharges into the environment permitted an environmental assessment to be made via evaluation criteria, quantitatively expressed as burden values. The results lead to the following main conclusions on the environmental impacts of Si-PV cells and to the major recommendations for PV development focuses: To substitute Si-PV for substance-emitting technologies is environmentally beneficial, but due to its manufacturing processes PV is not a zero emitter; supporting structures should be as low-weight as possible with minimized material requirements for low emissions from PV-system fabrication; PV only makes sense for applications relevant to the energy economy with high-efficiency modules and minimized electricity demand to enable solar supply shares to be as high as possible; and highest development priority should be given to the industrial fabrication maturity of high-efficiency modules.

A photovoltaic (PV) generator is a nonlinear device having insolation-dependent volt-ampere characteristics. Because of its relatively high cost, the system designer is interested in optimum matching of the motor and its mechanical load to the PV generator so that maximum power is obtained during the entire operating period. However, since the maximum-power point varies with solar insolation, it is difficult to achieve an optimum matching that is valid for all insolation levels. In this paper it is shown that for maximum power, the generator current must be directly proportional to insolation. This remarkable property is utilized to achieve insolation-independent optimum matching. A shunt dc motor driving a centrifugal water pump is supplied from a PV generator via a step-up converter whose duty ratio is controlled using a current-locked feedback loop.

A method to evaluate the room temperature effect in deteriorating the performance of flat plate PV systems is investigated. The calculations, applied to crystalline Silicon arrays, show a significant energy loss with respect to reference temperature conditions, especially in correspondence to the sites with highest insolation, in which the effect can amount up to about 15%. As a consequence, the previous projections about kW h cost for large scale PV power stations should be rectified by introducing a correction factor accounting for thermal effects. The calculations were carried out for 64 zones, particularly suitable for siting PV plants and distributed among 15 countries over a latitude belt ranging from about 40 degrees North to 15 degrees South. For each zone, it was accounted both for room temperature and insolation historical data. The final results show a linear correlation between yearly global sun radiation density and room temperature effect, which appears quite general, so that, for any other site within the same latitude belt, it is possible to account for thermal effect on PV kW h cost simply by knowing the global sun radiation density on horizontal surface (usually the only experimental available datum).