With increasing installations of photovoltaic (PV) systems, interest in power forecasting has also increased. Inaccurate forecasts would result in substantial economic losses and system reliability issues. The correlation between weather variables and PV power is critical to ensure the efficient use of energy in PV systems. A key step toward accurate power forecasting is estimating the output from a PV system based on known environmental input data. In this research, all available weather data are used to predict the PV power. Meteorological and power data are then analyzed using a statistical approach to identify the order of significance of the input variables. Then, a predictive model is suggested as a function of irradiance, ambient temperature, wind speed, and relative humidity. The model produces a root mean square error of 4.957% and a mean absolute percentage error of 5.468% during the measurement period and over the entire range of irradiation.

A bifacial solar module has a structure that allows the rear electrode to be added to the existing silicon photovoltaic module structure. Thus, it can capture energy from both the front and rear sides of the module. In this paper, modeling is suggested to estimate the amount of energy generated from the rear of the bifacial photovoltaic module. After calculating the amount of irradiance from the rear side, the estimated power generation is compared with the real power output from the rear side of the module. The experiments were performed using four different environments with different albedos. The theoretical prediction of the model shows a maximum of 5% and average of 1.86% error in the measurement data. Based on the nature of the bifacial solar module, which receives additional irradiance from the rear side, this study compared the output amounts with respect to different rear environments. Recently, installation of floating Photovoltaic has been increasing. As the reflection of irradiation from the water surface occurs, the positive influence of the installation with the bifacial photovoltaic can be expected. We are confident that this research will contribute to zero energy construction by designing systems based on bifacial PV module with high performance ratio when applying solar power in a microgrid environment, which is the future energy.

No abstract

This work is a case study of 905 households, to present methods for optimizing the capacity of photovoltaic sytems (PVs)/energy storage systems (ESSs) for household to reach a desired energy self-sufficiency (70% to 90%). In order to calculate the capacity of PV and ESSs that would enhance the energy self-sufficiency of families in rural areas, the solar radiance data of the target area for the last five years and the average monthly power usage in the previous year were collected. Then, households with an average energy consumption of 250 kWh per month were chosen for this research. According to the simulation done using Solar Pro, the optimized capacities of PVs and ESSs are 2.67 kW and 7.15 kW, respectively, in order to achieve 90% energy self-sufficiency. We visualized the change in the optimum capacity of PVs and ESSs for the desired energy self-sufficiency. This study would be the base work for forming a grid-distributed energy network system by expanding the system to a national scale.

Unlike conventional photovoltaic (PV) modules that generate power by absorbing light through the front side only, a bifacial PV module can generate power by absorbing light through the rear as well as the front, which would lead to an enhancement of power generation. Particularly, bifacial PV modules would have the advantage of lower power loss in shaded environments than monofacial PV modules, thanks to the light absorbed through the rear side. To predict the power of a bifacial PV module in a shaded environment, modeling is suggested by considering the shaded areas, the operational status of the bypass diodes, and the temperature of the bifacial PV module. To verify the power prediction of a bifacial PV module with a shaded area, modeled and measured powers are compared, showing error rates of 7.28%. From the results of the power loss experiments for bifacial and monofacial PV modules in shaded environments, it is confirmed that the bifacial PV module shows a relatively low power loss rate when compared with the monofacial PV module, with a power loss rate being 87.26% of the rate for the monofacial PV module. Index Terms-Bifacial c-Si PV module, bypass diode, shading. I. INTRODUCTION O NE of the major interests of the photovoltaic (PV) power plant operators is the reduction in the installation cost of PV power generation systems [1]. It has been reported that the price of PV modules accounted for 24% of the unit cost of commercial PV power systems in 2018 [2]. One of the possible ways for lowering the cost of installing a PV power system would be the development of a highly efficient solar cell and module that could generate higher power for a given area. A bifacial PV module is a highly efficient PV module that can absorb light not only through the front, but also through the rear. Power generated through the rear side of a bifacial PV module varies with different reflective conditions [3]. However, the standardization of the output of a bifacial c-Si PV module under standard test condition (STC) was in