East/West (E/W) vertical bifacial photovoltaic (PV) modules can achieve higher profits than the conventional North/South (N/S) tilted configuration depending on the design choices and external conditions. In this study a model based on 2D view factor concept is developed to estimate the power generated by a large-scale bifacial PV farm, considering the non-uniformity of the incident irradiance and the spectral impact. A validation using measured data is performed, focusing on the non-uniformity of the rear irradiance. This model is used to compare the profitability between E/W vertical and N/S tilted PV farm configurations, considering higher prices during noon with respect to morning/evening periods. The results identify the ratio between these two price values as the key variable that influences the comparison between the PV farm configurations. Specifically, a sufficiently high price ratio ensures the higher profitability of E/W vertical modules, however, the exact value is dependent on the location and the design variables. In general, higher row-to-row distance and lower diffuse fraction enhance the profitability of the E/W vertical over the N/S tilted configuration. On the other hand, elevation of the modules, curtailment strategies and hybrid solutions have a minor influence.@en

In this chapter, we introduce the physic principle and applications of bifacial PV technology. We present different bifacial PV cell and module technologies as well as investigate the advantages of using bifacial PV technology in the field. We describe the measurement and modeling of Albedo, which is one of the important factors for the energy yield of bifacial PV technology. For an accurate assessment of the performance ratio of bifacial PV strings, it is necessary to measure the albedo irradiance using an albedometer or the front- and rear-side plane of array (POA) irradiance. We also discuss the advanced techniques for the characterization of bifacial PV modules. By means of simulation, we give insight into what boundary conditions result in new bifacial technology gains and the influence of the mounting position of irradiance sensors. We executed several simulations by varying the sensor positions on the rear side of the PV modules, different places, different albedo numbers, mounting heights, different geographical locations with various tilts, seasons, and weather types. To validate the simulation results, we performed various experiments in the field under different conditions. The results prove that the bifacial gain is highly dependent on the mounting heights of PV modules, tilt angles, weather conditions, latitude, and location.@en

There are several sensors available in the market to measure the plane-of-array irradiance for photovoltaic applications. The prices of these sensors vary according to the design, calibration procedure, and conducted characterization. In this article, two types of silicon-based sensors with and without temperature correction capabilities are compared with a high-accuracy thermopile pyranometer to check their performance. The obtained results showed that silicon-based sensors deviate from the output of the pyranometers. The tested silicon-based pyranometers overestimate the irradiance with the median bias deviations of around 1.43% (with the average measured irradiance of 256 W/m2). For temperature-corrected silicon pyranometer, the bias deviation is 0.07% with the deviation range of -6.5%-10% (with the average measured irradiance of 257 W/m2). A working-class reference cell was also tested, resulting in a bias deviation of -1.74% and the deviation range of -13%-7% (with the average measured irradiance of 304 W/m2). The effect of air mass on the performance of cost-effective sensors was additionally analyzed. Within the measurement time window, the result also showed that for the silicon-based sensors under tests, the effects of the environmental conditions have the following qualitative order of influence: angle of incidence > red-shift > temperature. The performance of silicon-based sensors also showed seasonal dependence, being more accurate during summertime and wintertime, respectively, for the silicon pyranometer and the working-class reference cell. Finally, using the statistical evaluation, simple linear correction functions are introduced for silicon-based sensors.

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The deposition of dust, soil, and microfibers resulting from the surroundings, as well as the growth of minute pollens like moss and fungi, contributes toward photovoltaic (PV) module soiling. Soiling is a widely recognized factor that significantly reduces the power production by acting as a barrier for effective light absorption by the module. The estimated loss in the irradiance and power can be determined with the help of a soiling ratio (SR) parameter, which is the ratio of the short-circuit current (I_sc) or the maximum power produced (P_max) by a soiled module to a clean one. The measured SR is normally not constant throughout a day but changes with the position of the Sun and the amount of dust on the module. This paper proposes an empirical equation to determine the SR at any instant of time of the day based on the Sun's angle of incidence on the module and a single SR value measured at the mid of the day. First, an indoor experiment was done to examine the angular loss dependence of two totally different dust colors for the same SR at normal light incidence. Next, in an outdoor experiment, the SR of an artificially soiled module was measured over the course of the day for three conditions of high, medium, and low daily average irradiance due to variation in cloudiness. Then, an empirical equation is introduced based on an incident angle modifier for soiled and cleaned PV modules. The proposed equation was further used to determine the SR. Finally, the average residuals between the measured and the modeled SRs were determined with the help of root-mean-square deviation. The results showed that the modeled SR was determined with a deviation of ±0.21% and ±0.28%, respectively, for high-and medium-irradiance days, whereas the deviation increased to ±1.04% in the case of low irradiance due to clouds.

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We present an investigation into the accuracy of irradiance measurement due to the number of sensors. Satellite-derived irradiance data is used to estimate the spatial irradiance distribution and a measurement uncertainty analysis is provided.@en