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

被引:2
作者
Yadav, Uma [1 ]
Gupta, Anju [1 ]
Ahuja, Rajesh Kr [1 ]
机构
[1] JC Bose Univ Sci & technol, Dept Elect Engn, YMCA, Faridabad, India
关键词
Monotous Learning (ML) controller; P&O method; MPPT; PV; Cells; Renewable energy; POWER POINT TRACKING; PHOTOVOLTAIC SYSTEMS; GENERATION; ARRAYS;
D O I
10.1016/j.egyr.2022.10.067
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
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.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:77 / 84
页数:8
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