Bifacial photovoltaic (PV) modules can generate power even from rear-side solar irradiance. Consequently, the rear side of the bifacial PV module must not be hindered by structures. However, structures such as beams are often installed behind modules to ensure structural strength and for various other reasons. In such cases, the output power of the bifacial module is reduced because of partial shading on the rear side. This study entailed an analysis of the albedo dependence of the bifacial gain losses in bifacial modules due to inherent partial shading produced by rear-side support structures (e.g., mounting, frame, and beams). An analysis method combining ray tracing and electrical circuit simulation was implemented and verified through field experiments. The results demonstrate that the bifacial gain decreases nonlinearly at high albedo when the beam is closely attached to the rear side of the module. This loss is reduced by half upon placing the beam at a distance equivalent to the thickness of the beam from the module. The results also indicate the mismatch loss caused by each part of the module's support structure.

Conventional tilted photovoltaic systems often experience reduced electricity generation and potential damage due to snow accumulation. In contrast, vertical bifacial photovoltaic systems demonstrate greater resilience against snow-related damage, making them particularly suitable for snowy regions. This study explores the electricity generation characteristics of vertical bifacial photovoltaic systems in areas where snow depths exceed 1 meter, through both experimental and simulation analyses. Experiments conducted on a vertical bifacial system over two winter seasons showed no signs of damage or breakage. Additionally, during snowy periods, the power generation ratio relative to global horizontal irradiance increased by 55%, primarily due to irradiance reflected from the snow surface. However, this gain was offset by a 17% decrease due to partial shading by snow. Furthermore, integrating ray tracing with electrical circuit analysis revealed that implementing separate maximum power point tracking for the upper and lower sections of a single-row vertical bifacial photovoltaic array could alleviate losses in electricity generation caused by deep snow covering the photovoltaic cells. This study advances our understanding of the impact of snow on the power generation of vertical bifacial photovoltaic systems in heavy-snow regions and is expected to contribute to the development of more efficient designs in the future.

An optimal tilt-angle control based on artificial intelligence (AI control) for tracking bifacial photovoltaic (BPV) systems is developed in this study, and its effectiveness and characteristics are examined by simulating a virtual system over five years. Using deep reinforcement learning (deep RL), the algorithm autonomously learns the control strategy in real time from when the system starts to operate. Even with limited deep RL input variables, such as global horizontal irradiance, time, tilt angle, and power, the proposed AI control successfully learns and achieves a 4.0–9.2% higher electrical-energy yield in high-albedo cases (0.5 and 0.8) as compared to traditional sun-tracking control; however, the energy yield of AI control is slightly lower in low-albedo cases (0.2). AI control also demonstrates a superior performance when there are seasonal changes in albedo. Moreover, AI control is robust against long-term system degradation by manipulating the database used for reward setting.

Vertical bifacial photovoltaic (VBPV) systems are promising for deployment in snowy regions, where sunlight reflected from snow-covered ground enhances rear-side irradiance. However, the low solar altitude during winter increases mutual shading between arrays, leading to mismatch losses. This study evaluates the effectiveness of a separated-string configuration—where the upper and lower module strings are electrically independent—in reducing shading losses under varying snow conditions, array spacings, and azimuth angles. Field measurements were conducted on an 80 kW_DC (40 kW_AC) agrivoltaic VBPV system installed in Hokkaido, Japan. The data were analyzed using simulations that integrate ray tracing and cell-level circuit modeling. Results indicate that increased ground albedo due to snow enhances winter electricity generation per unit solar irradiation by a factor of 1.7. However, for the tested system with a 10 m array spacing, the annual relative improvement achieved by the separated-string configuration was less than 1% due to the low occurrence of partial shading. Under simulated conditions with narrower 4 m array spacing and array azimuth angles of 150° and 180°, the relative improvement in winter exceeded 2.5%, reaching 3.7% and 9.2%, respectively. These findings suggest that the separated-string configuration is an effective design strategy primarily for VBPV systems with narrow array spacing in snowy, high-latitude regions characterized by high surface albedo.