Technical Performance and Probabilistic Energy Yield Assessment of a 620 MWp Bifacial Grid-Connected Photovoltaic Power Plant in an Area Located in the Eastern Part of the Absheron Peninsula of Azerbaijan

The sun is a vast, reliable engine, but capturing its energy to power a modern grid requires more than just placing panels in a field. It demands a precise understanding of how light hits a surface, how that light turns into electricity, and how the surrounding environment changes the outcome. In the world of large-scale solar power, engineers must predict exactly how much energy a plant will produce over a year, accounting for everything from the angle of the sun to the dust settling on the glass. This is especially true for newer, more complex systems that use panels capable of catching light from both sides, known as bifacial modules. These panels can harvest sunlight reflected off the ground, but their performance depends heavily on the color of the soil, the height of the panels, and the spacing between rows. Before a single wire is connected to the grid, developers run detailed computer simulations to forecast the plant's output, ensuring the project is financially sound and technically viable.

In a recent study, researchers applied this rigorous forecasting method to a proposed massive solar farm on the eastern side of the Absheron Peninsula in Azerbaijan. This area, a low-lying coastal plain, was selected for a project designed to generate enough electricity to power hundreds of thousands of homes. The team used sophisticated software to model a plant with a capacity of 620 megawatts, a size that places it among the largest solar installations in the region. The design called for a field of bifacial panels mounted on the ground, angled toward the south to maximize their exposure to the sun throughout the day. Crucially, the researchers did not wait for the plant to be built, nor did they analyze a running facility; instead, they conducted a single simulation review using PVsyst software to construct a digital twin of the entire system. They fed this model historical weather data and specific details about the equipment to simulate a full year of operation, rather than auditing measured plant performance.

The simulation painted a picture of a highly efficient system. By the end of the first simulated year, the virtual plant was predicted to inject 886.81 gigawatt-hours of electricity into the national grid. To put this in perspective, the plant was expected to produce 1,430 kilowatt-hours of energy for every single kilowatt of installed capacity. This high output is a result of the location's strong sunlight and the careful engineering of the plant's layout. The panels were arranged in rows with a specific spacing to ensure that the shadow of one row did not fall on the next for too long, a balance that allows the system to capture light without losing too much to shading. The computer model showed that the plant would operate with a performance ratio of nearly 90 percent, meaning that the system loses very little energy to heat, wiring resistance, or other inefficiencies compared to its theoretical maximum.

A key feature of this design is the use of bifacial panels, which can generate power from light hitting their back side as well as the front. In this simulation, the ground beneath the panels acted as a reflector, bouncing sunlight up onto the rear of the modules. The researchers found that this effect added a net gain of 9.2 percent to the total energy collected. This gain was not automatic; it depended on the ground having a certain reflectivity and the panels being mounted at a specific height of 1.6 meters to allow light to reach the back. The model also accounted for the fact that the panels would get hot in the summer, which slightly reduces their efficiency, and that dust would accumulate on the surface, requiring a small loss in output. Despite these real-world factors, the system remained remarkably robust, with the computer showing that the panels would only lose a tiny fraction of energy due to the inverters, the devices that convert the electricity, being slightly smaller than the total power the panels could generate.

Because weather varies from year to year, a single number for annual production is not enough for investors and lenders who need to know the worst-case scenarios. The researchers therefore applied a statistical method to estimate how much the production might drop in a less sunny year. They calculated that there is a 90 percent chance the plant will produce at least 836.9 gigawatt-hours in any given year, and a 95 percent chance it will produce at least 822.9 gigawatt-hours. These figures provide a safety margin, ensuring that even if the sun is less generous than the average year, the plant will still generate enough power to meet its financial obligations. The study also highlighted that the specific mix of equipment, including the choice of inverters and the layout of the electrical cables, was optimized to keep losses low, with the system wasting only a fraction of a percent of energy due to the panels generating more power than the inverters could immediately handle.

The author of the study were careful to note that these results are based on a single computer simulation, not on measurements from a running power plant. While the numbers are promising, they rely on assumptions about the ground conditions, the cleanliness of the panels, and the behavior of the equipment that have not yet been tested in the field. The study serves as a blueprint, showing that the design is sound and the location is suitable, but it also points out that the final confirmation of these numbers will only come once the plant is built and operating. The researchers identified that the actual color of the soil, the real-world amount of dust, and the precise electrical connections will need to be verified to ensure the plant performs exactly as the digital model predicts. Until then, the simulation stands as a strong indicator that this corner of the Absheron Peninsula is well-suited to host a major source of clean energy, capable of delivering reliable power to the grid with high efficiency and minimal waste.