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Enhancing MPPT in partially shaded PV modules: a novel approach using adaptive reinforcement learning with neural network architecture

100%

Leelavathi M. , Suresh K. V.

Bulletin of the Polish Academy of Sciences. Technical Sciences

2024

tom Vol. 72, nr 4

art. no. e150112

The occurrence of partial shading in solar power systems presents a substantial challenge with widespread implications, sparking extensive research, notably in the field of maximum power point tracking (MPPT). This study emphasizes the critical process of accurately tracking the maximum power points with the characteristic curves of photovoltaic (PV) modules under real-time, diverse partial shading patterns. It explores the various stages of the tracking process and the methodologies employed for optimization. While conventional methods show effectiveness, they often fall short in swiftly and accurately tracking maximum power points with minimal errors. To address this limitation, this research introduces a novel machine learning approach known as adaptive reinforcement learning with neural network architecture (ARL-NNA) for MPPT. The results obtained from ARL-NNA are compared with existing algorithms using the same experimental data. Furthermore, the outcomes are validated through different factors and processing time measurements. The findings conclusively demonstrate the efficacy and superiority of the proposed algorithm in effectively tracking maximum power points in PV characteristic curves, providing a promising solution for optimizing solar energy generation in partial shading patterns. This study significantly impacts various realms of electrical engineering including power engineering, power electronics, industrial electronics, solid-state electronics, energy technology, and other related field of engineering and technology.

High performance of direct power control for a doubly fed induction generator based on adaptive fuzzy second order sliding mode controller in wind energy conversion system

100%

Cherifi D. , Miloud Y. , Mostefai M.

Przegląd Elektrotechniczny

2023

tom R. 99, nr 11

66--74

In this paper, adaptive fuzzy second order sliding mode direct power control strategy is applied for a doubly fed induction generator based wind energy generation system. The conventional direct power control with hysteresis regulators has significant active and reactive power ripples at steady-state operation and also the switching frequency varies in a wide range. The proposed direct power control reduces active, reactive and current ripples. It also narrows down the switching frequency variations in induction machine control. The stator active power reference is given through the fuzzy logic MPPT algorithm to extract the maximum of wind power available at the turbine pales. The simulation results show that the proposed direct power control provides significantly improved control performance especially when compared to the conventional direct power control control.

W tym artykule zastosowano adaptacyjną strategię sterowania mocą ślizgową rozmytą drugiego rzędu w dwustronnie zasilanym systemie wytwarzania energii wiatrowej opartym na generatorze indukcyjnym. Konwencjonalna bezpośrednia regulacja mocy z regulatorami histerezy ma znaczne wahania mocy czynnej i biernej podczas pracy w stanie ustalonym, a także częstotliwość przełączania zmienia się w szerokim zakresie. Zaproponowana bezpośrednia regulacja mocy ogranicza tętnienia czynne, bierne i prądowe. Zawęża również zmiany częstotliwości przełączania w sterowaniu maszyną indukcyjną. Wartość odniesienia mocy czynnej stojana jest podawana za pomocą algorytmu MPPT z logiką rozmytą w celu wyodrębnienia maksymalnej mocy wiatru dostępnej na łopatkach turbiny. Wyniki symulacji pokazują, że proponowana bezpośrednia regulacja mocy zapewnia znacznie lepszą wydajność regulacji, zwłaszcza w porównaniu z konwencjonalną bezpośrednią regulacją mocy.

Banes and boons of perturb & observe, incremental conductance and modified regula falsi methods for sustainable PV energy generation

80%

Gopal Y. , Kumar K. , Birla D. , Lalwani M.

tom Vol. 97, nr 1

35--43

Maximum power point tracking (MPPT) optimizes overall power generation in photovoltaic (PV) applications. The voltagepower characteristics of PV array operating under variable irradiance and temperature conditions exhibit numerous local maximum power points (MPP). This paper presents the optimization method of MPP tracking, based on the modified Regula Falsi method (MRFM). Results of this method are compared with the conventional perturb & observe (P&O) method and the incremental conductance (IC) method. The modified Regula Falsi method has better convergence, lower oscillation time, less power loss and enhanced output power than the other two methods. To obtain a stable voltage from a solar array, a DC-DC Cuk converter is used. It can step-up and step-down the voltage level according to load requirement. Results have been verified on the MATLAB platform in variable environmental conditions.