This article demonstrates how neural algorithms improve wind farm performance in agro industries, indicating potential for operational efficiency.
The article discusses a neural network embedded as a model in the database program that can process more and more cases (situations), scaling the database by exchanging with similar complexes in the SCADA system. A wind turbine with large-chord blades spins up independently, and then the blade chord decreases and automatically adjusts to the corresponding wind speed with the achievement of the maximum coefficient Cp. In a storm wind, the blade chord decreases even more in size, interceptors are released, breaking the blade. The described actions are performed by a subordinate object (the wind turbine blade mechanization control system) under command and full control with the corresponding case registration by the database, based on artificial intelligence algorithms. Thus, the maximum coefficient Cp is achieved in the entire range of operating wind speeds, and the range itself is significantly expanded.
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Bolkov et al. (2025) studied this question.
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