• Energy Research

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.

Fault detection and repair of the components of photovoltaic (PV) systems are essential to avoid economic losses and facility accidents, thereby ensuring reliable and safe systems. This article presents a method to detect faults in a PV system based on power ratio (PR), voltage ratio (VR), and current ratio (IR). The lower control limit (LCL) and upper control limit (UCL) of each ratio were defined using the data of a test site system under normal operating conditions. If PR exceeded the set range, the algorithm considered a fault. Subsequently, PR and IR were examined via the algorithm to diagnose faults in the system as series, parallel, or total faults. The results showed that PR exceeded the designated range between LCL (0.93) and UCL (1.02) by dropping to 0.91–0.68, 0.88–0.62, and 0.66–0.33 for series, total, and parallel faults, respectively. Moreover, VR exceeded the LCL (0.99) and UCL (1.01) by 0.95–0.69 and 0.91–0.62 for series and total faults, respectively, but not under parallel faults condition. IR did not change in series and total faults but exceeded the range of LCL (0.93) and UCL (1.05) by dropping to 0.66–0.33. Thus, faults in PV systems can be detected and diagnosed by analyzing quantitative output values.

In this paper, a design technique for constructing a renewable-energy-based power system based on a customer’s power load is proposed. The proposed design technique adopts a second renewable energy power source in charge of the base load and is an improved method of the referenced studies with one type of renewable energy power source. In this proposed method, fuel cells are adopted as the base power source, and PV (photovoltaic) power generation and an ESS (energy storage system) are adopted as the power generation sources that supply the middle-load and peak-load power. When the fuel cell is applied as a base power source through the method designed in this study, a cost reduction of approximately 30.03% is expected, compared to a system that does not use a base power source. In addition, the criteria for securing a system’s power supply stability and the economics when fuel cells are adopted are analyzed in terms of the system’s installation cost.

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.

An optimal design method is proposed in this paper to improve the safety and price competitiveness of floating photovoltaic (PV) systems. From the standards for grounding by the International Electrotechnical Commission (IEC) 60364, the Electrical Equipment Technology Standards (EETS) are set up for the grounding resistance to be less than or equal to 10 Ω for high voltage (above 750 V DC) and extra high voltage (above 7000 V) systems. In order to satisfy this criterion, a parallel connection of grounding electrodes is essential in the system. Furthermore, inter-electrode interference should be considered to reflect the resistance increase due to the potential increase between electrodes. Therefore, in this study, the parallel grounding resistance according to the distance and number of electrodes, as well as the arrangement method were theoretically predicted and compared with the measured values. For the first time, the design of grounding electrodes has been applied to real floating PV systems and is expected to satisfy EETS.

Underwater grounding methods could be applied in deep water for grounding a floating PV (photovoltaic) system. However, the depth at which the electrodes should be located is a controversial subject. In this study, grounding resistance was measured for the first time by analyzing the water temperature at different water depths in an area where a floating PV system is installed. The theoretical calculation of the grounding resistance has a maximum error range of 8% compared to the experimentally measured data. In order to meet the electrical safety standards of a floating PV system, a number of electrodes were connected in parallel. In addition, the distance between electrodes and number of electrodes were considered in the test to obtain a formula for the grounding resistance. In addition, the coefficient of corrosion was obtained from an electrode installed underwater a year ago, and it was added to the formula. Through this analysis, it is possible to predict the grounding resistance prior to installing the floating PV system. Furthermore, the electrical safety of the floating PV system could be achieved by considering the seasonal changes in water temperature.

This paper proposes a method for estimating the load pattern for optimal planning of stand-alone renewable microgrids and verifies when the basic data for microgrid design are limited. To estimate a proper load pattern for optimal microgrid design when the data obtained in advance are insufficient, the least squares method is used to compare the similarity of annual power consumption between the subject area and eight islands in Korea whose actual load patterns were previously obtained. Similarity is compared in terms of annual (every month), seasonal, bi-monthly, and monthly averages. To verify the validity of the proposed estimation method, the applied proposed estimation method is used for two islands that have already installed a microgrid consisting of photovoltaic, wind power, energy storage systems, and diesel generators. In comparing the actual data from the two islands, the costs of electricity in terms of microgrid operations show improvements of 37.2% and 29.8%, respectively.