Wind energy harvesting optimization considering turbulence and downstream using artificial salmon tracking algorithm

Alternative energy has recently gained popularity due to the search for potential sources such as wind power, where existing technical development is harnessed to harvest natural energy sources. The wind farm is one of the most commonly studied crops, and downstream assesses the influence of speed and turbulence on the 24-hour operation. These experiments used an artificial fish tracking algorithm to demonstrate the impact of models, speed reduction, and large space on the performance of the wind farm. It also affects energy production in terms of energy harvesting and awakening power of the wind farm. On the performance side, the impact of the wake is very important to know the downstream and turbulence impacts. Due to the turbulence of the wind, which causes various loads on the blades comparable to the downstream after the wind flow, it can be exposed to a variety of conditions during operation within 24 hours.