How Greylag Geese helps farmers use solar energy more effectively

Solar energy has long promised to provide sustainable solutions for farmers who want to power irrigation pumps, storage facilities and processing equipment. But standard solar photovoltaic (PV) systems are usually short and strive to maintain peak efficiency in changing weather conditions. A new study from the University of Annamalai may have found a way to solve this approach – by drawing inspiration from the way Greylag Geese flies.

Posted in Energy storage and saving,This study explores how a bioinspired optimization method called Greylag Goose optimization (GGO) significantly improves solar PV performance. When used in conjunction with a dedicated seven-stage inverter, the system not only extracts more energy from the sun but also provides a more stable, higher quality power supply, which is essential for protecting sensitive agricultural machinery.

Smarter ways to track the sun

The core of the problem is how solar photovoltaic systems find and maintain their maximum power output. The traditional maximum power tracking (MPPT) method may be ineffective, especially when it occurs due to cloud coverage, temperature changes, or dust accumulation.

The GGO algorithm is inspired by how Greyragge adjusts its strata to save energy during long-term migration and continuously fine-tune the working points of solar PV arrays. This allows it to adapt dynamically, optimizing energy capture in real time.

“This study marks a critical development for agricultural renewable energy,” said Dr. K. Rajaram, principal investigator of the study. “By combining the GGO algorithm with a seven-stage inverter, we have created a system that not only maximizes the extraction of energy, but also guarantees a stable and high-quality power supply, which is crucial for the smooth operation of agricultural machinery.”

Cleaning power, smoother operation

Another challenge in agricultural energy use is the quality of power generation. Many standard inverters convert DC batteries from solar panels to AC power supplies with high harmonic distortion (THD), which can lead to unstable performance of irrigation pumps, refrigeration units, and other farm equipment.

The researchers solved this problem by integrating a seven-stage inverter that produces smoother “staircase” AC waveforms with fewer sudden transitions. When paired with the GGO algorithm, the system achieved only 1.95% lower THD – performing better than the alternatives to SALP group optimization (6.14%) and genetic algorithm (10.84%).

Real impact on farmers

For farmers, it has a great impact. More efficient solar photovoltaic systems mean lower energy costs and lower reliance on fossil fuels. More stable power also translates into less equipment failure and less downtime. Furthermore, the system is able to seamlessly switch between grid connections and off-grid modes, which is particularly useful for rural agricultural environments with unreliable grid access.

Apart from individual farms, this technology could also play a role in broader efforts to expand sustainable agriculture and energy independence. As the agricultural sector faces increasing pressure to reduce carbon emissions and operate more efficiently, innovations such as GGO-based optimization can provide scalable, cost-effective solutions.

What’s next?

Although the study focuses on simulations, the next step is real-world implementation. Performing field testing under different environmental conditions will be key to verifying the long-term reliability and economic viability of the technology.

With the need for intelligent, adaptive energy solutions, bioinspired algorithms like GGO could become a key part of the renewable energy landscape. Whether in the sky or on the farm, nature’s efficiency can still teach us.

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