Maximum power point tracking using adjustable gain based model reference adaptive control

Sahu, Pankaj; Dey, Rajiv

doi:10.1007/s43236-021-00336-3

Cited by 3 publications

(2 citation statements)

References 19 publications

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“…In the work of Hekss et al, 28 a new algorithm was proposed based on the modified model reference adaptive control combined with the incremental conductance algorithm, to achieve fast the maximum power point (MPP) under the variation of irradiance and temperature. Sahu and Dey 29 developed an adjustable gain-based model with a reference adaptive control scheme for the MPPT to guarantee the system stability under rapidly changing environmental conditions. To control the MPPT for a PV system, an indirect adaptive control technique was proposed and compared with various MPPTs.…”

Section: Dc/dc Converter Modelingmentioning

confidence: 99%

Optimization sizing of an autonomous photovoltaic-battery microgrid system

Amara

Toumi

Salah

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article describes a photovoltaic-battery microgrid system used for isolated sites. Indeed, a 50 kW photovoltaic panel is associated with a boost converter. To guarantee more reliable and economical energy supply, a battery storage system is included within the microgrid system. To determine the optimal sizing of the microgrid system, many approaches have been proposed. However, these approaches need a big database applied throughout a year, which can make the sizing more expensive and required a long computing time. In this article, a new approach is proposed, using real weather data (solar radiation and ambient temperature). It is based on two technical criteria; the deficiency of power supply probability and the relative excess power generated to study the system reliability and two economic criteria; the energy cost and the total net present cost to study the system cost. Compared to other approaches, sizing results applied for a year can be deduced using just the month when the microgrid system can work at the optimum conditions with optimal configuration (photovoltaic power and battery) achieving a minimal cost energy without deficiency of power supply probability, which make the sizing simpler and less expensive. The results obtained prove the effectiveness of the proposed approach in sizing problem. All results have been checked carrying out MATLAB simulations using real weather data.

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Section: Dc/dc Converter Modelingmentioning

confidence: 99%

Optimization sizing of an autonomous photovoltaic-battery microgrid system

Amara

Toumi

Salah

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part I:

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“…Due to its special characteristics and ease of execution, MRAC is designed for MPP applications. The MRAC required only reference and array voltage as input [29,30]. The MRAC primarily consists of a process, adaptation gain, and reference model as illustrated in Figure 7.…”

Section: Model Reference Adaptive Controlmentioning

confidence: 99%

A novel robust model reference adaptive MPPT controller for Photovoltaic systems

Manna¹,

Singh²,

Akella³

et al. 2022

Scientia Iranica

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Solar photovoltaic (SPV) power generation has been more popular throughout the world in recent years due to its recyclable and eco-friendly nature. As a result, extracting the maximum power from SPV systems is important. Our contribution to this problem is to harvest maximum power under changes in ambient conditions and parametric variations. This paper presents a novel robust model reference adaptive maximum power point tracking controller (RMRAC-MPPT) for PV systems under five different cases including temperature, load, irradiance, boost converter capacitance, and inductance variations. To assess the robustness of the proposed method, MATLAB/Simulink software is used to compare it to the state-of-the-art techniques such as INC, P&O, FLC, Adaptive FLC, SMC, back stepping-SMC, PI, iRCS-MPC, P&O-MPC, ANFIS, BAT-FLC, and IPID. The verification of the proposed method is also tested in a laboratory-based OPAL-RT real-time simulator. It is evident that the proposed MPPT technique improves maximum power point (MPP) tracking capabilities while reducing steady-state oscillations. Furthermore, with five different parameter variations, the time duration to capture MPP is 1.5ms, which is significantly faster than other state-of-the-art 2 techniques. In addition, the proposed technique has a tracking efficiency of 99.75% and an overall system efficiency of 96%.

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