Hardware validation of hybrid MPPT technique via Novel ML controller and P&O method

The proposed paper deals with the hardware validation of Hybrid Maximum power point tracking (MPPT) technique via Novel ML (Monotonous Learning) Controller & Perturb & Observe (P&O) Method. MPPT methods find its inability in handling periodic variation against tiny change in irra...

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Bibliographic Details
Main Authors: Uma Yadav, Anju Gupta, Rajesh kr Ahuja
Format: Article
Language:English
Published: Elsevier 2022-12-01
Series:Energy Reports
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352484722020029
Description
Summary:The proposed paper deals with the hardware validation of Hybrid Maximum power point tracking (MPPT) technique via Novel ML (Monotonous Learning) Controller & Perturb & Observe (P&O) Method. MPPT methods find its inability in handling periodic variation against tiny change in irradiance and temperature. Further, it also shows its inability in enhancing its dynamic responsiveness when irradiance varies quickly. To overcome these problems, this paper proposed a Novel ML controller incorporated with P&O method along with its hardware validation to confirm the suitability of this Novel controller in practical environment. Novel ML Controller can manage periodic fluctuations whenever there is a little irradiance to eliminate mistakes and steady state oscillations. To improve dynamic responsiveness when irradiance fluctuates fast, we are using P&O approach without dead time. The presented paper also discusses the design, stability analysis, hardware validation of proposed Novel ML Controller along with MATLAB simulation.
ISSN:2352-4847