A synchronization of PV source by using bacterial foraging optimization based PI controller to reduce day-time grid dependency

Kumar, Ajay; Gupta, Nitin; Gupta, Vikas

doi:10.1109/itcosp.2017.8303155

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…BFOA is also applied successfully in cancellation of active noise [41]. In [42], a grid-connected PV system founded on an active shunt power filter (ASPF) method is presented. In controlling the dc-link voltage with PI controller, it is quite tough because of the presence of changing loads, BFOA is applied to determine the optimal parameters of PI controller in this paper.…”

Section: Bacteria Foraging Optimization Algorithm (Bfoa)mentioning

confidence: 99%

Maximum Power Point Tracking Algorithm for Advanced Photovoltaic Systems

Srinivas

Swapna

2022

IJRITCC

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Photovoltaic (PV) systems are the major nonconventional sources for power generation for present power strategy. The power of PV system has rapid increase because of its unpolluted, less noise and limited maintenance. But whole PV system has two main disadvantages drawbacks, that is, the power generation of it is quite low and the output power is nonlinear, which is influenced by climatic conditions, namely environmental temperature and the solar irradiation. The natural limiting factor is that PV potential in respect of temperature and irradiation has nonlinear output behavior. An automated power tracking method, for example, maximum power point tracking (MPPT), is necessarily applied to improve the power generation of PV systems. The MPPT methods undergo serious challenges when the PV system is under partial shade condition because PV shows several peaks in power. Hence, the exploration method might easily be misguided and might trapped to the local maxima. Therefore, a reasonable exploratory method must be constructed, which has to determine the global maxima for PV of shaded partially. The traditional approaches namely constant voltage tracking (CVT), perturb and observe (P&O), hill climbing (HC), Incremental Conductance (INC), and fractional open circuit voltage (FOCV) methods, indeed some of their improved types, are quite incompetent in tracking the global MPP (GMPP). Traditional techniques and soft computing-based bio-inspired and nature-inspired algorithms applied to MPPT were reviewed to explore the possibility for research while optimizing the PV system with global maximum output power under partially shading conditions. This paper is aimed to review, compare, and analyze almost all the techniques that implemented so far. Further this paper provides adequate details about algorithms that focuses to derive improved MPPT under non-uniform irradiation. Each algorithm got merits and demerits of its own with respect to the converging speed, computing time, complexity of coding, hardware suitability, stability and so on.

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Section: Bacteria Foraging Optimization Algorithm (Bfoa)mentioning

confidence: 99%

Maximum Power Point Tracking Algorithm for Advanced Photovoltaic Systems

Srinivas

Swapna

2022

IJRITCC

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“…BFOA has also been implemented for active noise cancellation systems successfully [77]. Authors in reference [78] presented a grid-tied PV system based on an active shunt power filter (ASPF) technique. As controlling a dc-link voltage using PI controller is difficult due to the existence of varying loads, in this paper BFOA is used to optimize the PI controller parameters.…”

Section: Elimination and Dispersalmentioning

confidence: 99%

Nature-Inspired MPPT Algorithms for Partially Shaded PV Systems: A Comparative Study

et al. 2019

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PV generating sources are one of the most promising power generation systems in today’s power scenario. The inherent potential barrier that PV possesses with respect to irradiation and temperature is its nonlinear power output characteristics. An intelligent power tracking scheme, e.g., maximum power point tracking (MPPT), is mandatorily employed to increase the power delivery of a PV system. The MPPT schemes experiences severe setbacks when the PV is even shaded partially as PV exhibits multiple power peaks. Therefore, the search mechanism gets deceived and gets stuck with the local maxima. Hence, a rational search mechanism should be developed, which will find the global maxima for a partially shaded PV. The conventional techniques like fractional open circuit voltage (FOCV), hill climbing (HC) method, perturb and observe (P&O), etc., even in their modified versions, are not competent enough to track the global MPP (GMPP). Nature-inspired and bio-inspired MPPT techniques have been proposed by the researchers to optimize the power output of a PV system during partially shaded conditions (PSCs). This paper reviews, compares, and analyzes them. This article renders firsthand information to those in the field of research, who seek interest in the performance enhancement of PV system during inhomogeneous irradiation. Each algorithm has its own advantages and disadvantages in terms of convergence speed, coding complexity, hardware compatibility, stability, etc. Overall, the authors have presented the logic of each global search MPPT algorithms and its comparisons, and also have reviewed the performance enhancement of these techniques when these algorithms are hybridized.

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A synchronization of PV source by using bacterial foraging optimization based PI controller to reduce day-time grid dependency

Cited by 3 publications

References 14 publications

Maximum Power Point Tracking Algorithm for Advanced Photovoltaic Systems

Maximum Power Point Tracking Algorithm for Advanced Photovoltaic Systems

Nature-Inspired MPPT Algorithms for Partially Shaded PV Systems: A Comparative Study

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