Hardware validation of hybrid MPPT technique via Novel ML controller and P&O method. (December 2022)

• Record Type: Journal Article
• Authors: Yadav, Uma; Gupta, Anju; Ahuja, Rajesh kr
• Is Part Of: Energy reports. Volume 8(2022)Supplement 14
• Page Start: 77
• Page End: 84
• Publication Date: 2022-12
• Subjects: Monotous Learning (ML) controller -- P&O method -- MPPT -- PV -- Cells, Renewable energy; Power resources -- Periodicals; Energy industries -- Periodicals; Power resources; Periodicals; Electronic journals; 621.04205
• DOI: 10.1016/j.egyr.2022.10.067
• Languages: English
• ISSNs: 2352-4847

Abstract

Abstract: 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.