2 Years Impact Factor:
2.85
5 Years Impact Factor: 1.53
Author: G.Varalaxmi, M.Dambika ,P.vignesh , Mrs K.Hemalatha
Abstract:
The integration of renewable energy sources such as solar and wind power into the energy grid has revolutionized power generation and consumption. Smart inverters, which are key components in these systems, play a crucial role in converting and regulating electrical power between the energy source and the grid. The inverter's motor speed (n_k) directly impacts its performance and the efficiency of energy conversion. Accurate forecasting of motor speed is therefore essential for optimizing the operation of inverters and ensuring the stability and efficiency of energy systems. The concept of smart inverters has evolved significantly over the past few decades, with advancements in power electronics, digital control systems, and machine learning techniques. Early inverter systems relied on basic control algorithms and manual adjustments, which often led to suboptimal performance. Over time, more sophisticated algorithms and models have been developed to improve the precision and re
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