Data-centric predictive control with tuna swarm optimization-backpropagation neural networks for enhanced wind turbine performance

Wei Li and Ravi Kumar Pandit

Renewable Energy, 2024, vol. 237, issue PC

Abstract: Wind energy is a significant renewable resource, but its efficient harnessing requires advanced control systems. This study presents a Data-Centric Predictive Control (DPC) system, enhanced by a Tuna Swarm Optimization-Backpropagation Neural Network (TSO-BPNN) for predictive wind turbine control. It's like a smart tool that uses innovative fusion of deep learning, predictive Control, and reinforcement learning. Unlike traditional control methods, the proposed approach uses real-time data to optimize turbine performance in response to fluctuating wind conditions.

Keywords: Deep neural networks; TSO-BPNN; Model predictive control; Reinforcement learning; Wind turbine control (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:237:y:2024:i:pc:s0960148124018895

DOI: 10.1016/j.renene.2024.121821

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