Backtracking Search Optimization Algorithm Based MPPT Technique for Solar PV System

Sriram, Mounika; Ravindra, K.

doi:10.1007/978-3-030-24318-0_59

Cited by 6 publications

(4 citation statements)

References 7 publications

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“…Let A and B are two optimal Pareto sets obtained with two different algorithms. The C‐metric maps ordered pair ( A , B ) to the interval [0 1] and it is defined as 38

CV ((), A, B) = \frac{|({}, b \in B, a \in A such that a \leq b)|}{B}

…”

Section: Resultsmentioning

confidence: 99%

“…To determine the optimization problem solution, the resulting objective functions should be optimized while satisfying all the parameters and system constraints. BSA is a recently developed meta-heuristic population-based iterative evolutionary algorithm (EA) that employs a unique strategy 38,39 to generate trail individuals for solving complex numerical problems. Using the old population and binary integer-valued matrix (map) concepts, it can handle multi-dimensional problems.…”

Section: Overview Of Pmbsamentioning

confidence: 99%

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A multi‐objective approach for the optimal design of a standalone hybrid renewable energy system

Anilkumar

Kollu

Rayapudi

et al. 2021

Intl J of Energy Research

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Dependency on alternative energy sources has increased due to the depletion of fossil fuel and their costs. Even though the usage of renewable energy sources (RESs) has significantly reduced these problems, there are quite a few challenges like reliability, lower efficiency, and high cost which can be overcome by the integration of multiple RES to meet the energy demand. In this study, a multi-objective approach is proposed to get the best optimal sizing configuration of a standalone hybrid renewable energy system (HRES) by choosing the minimization of the total cost of the system and loss of power supply probability. In this regard, wind turbines, solar photovoltaic (PV), battery storage systems, biomass, and diesel generators are used to design HRES. The proposed approach deals with the intermittent nature of wind and solar PV power generation using Weibull distribution to model wind speed and solar irradiance. The normal distribution is used to model the load demand. The backtracking search algorithm capable of solving single-objective optimization problems is modified to handle the multi-objective optimization problem and to find the optimal sizes of wind turbines, solar PV, battery storage system, diesel, and biomass generators for efficient HRES performance.

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“…Let A and B are two optimal Pareto sets obtained with two different algorithms. The C‐metric maps ordered pair ( A , B ) to the interval [0 1] and it is defined as 38

CV ((), A, B) = \frac{|({}, b \in B, a \in A such that a \leq b)|}{B}

…”

Section: Resultsmentioning

confidence: 99%

Section: Overview Of Pmbsamentioning

confidence: 99%

A multi‐objective approach for the optimal design of a standalone hybrid renewable energy system

Anilkumar

Kollu

Rayapudi

et al. 2021

Intl J of Energy Research

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“…According to the recent study [86], the standard BSA was coupled with [87] proposed a new algorithm, in which BSA is blended with stochastic ranking (SR) to minimise the MVS problems. This newly introduced algorithm is called SRBSAMVS.…”

Section: Bsa-based Mppt Algorithmmentioning

confidence: 99%

Operational framework for recent advances in backtracking search optimisation algorithm: A systematic review and performance evaluation

Hassan

Rashid

2020

Applied Mathematics and Computation

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Backtracking search optimisation algorithm (BSA) is a commonly used meta-heuristic optimisation algorithm and was proposed by Civicioglu in 2013. When it was first used, it exhibited its strong potential for solving numerical optimisation problems. Additionally, the experiments conducted in previous studies demonstrated the successful performance of BSA and its non-sensitivity toward the several types of optimisation problems.This success of BSA motivated researchers to work on expanding it, e.g., developing its improved versions or employing it for different applications and problem domains. However, there is a lack of literature review on BSA; therefore, reviewing the aforementioned modifications and applications systematically will aid further development of the algorithm. This paper provides a systematic review and meta-analysis that emphasise on reviewing the related studies and recent developments on BSA. Hence, the objectives of this work are twofold: (i) First, two frameworks for depicting the main extensions and the uses of BSA are proposed. The first framework is a general framework to depict the main extensions of BSA, whereas the second is an operational framework to present the expansion procedures of BSA to guide the researchers who are working on improving it. (ii) Second, the experiments conducted in this study fairly compare the analytical performance of BSA with four other competitive algorithms: differential evolution (DE), particle swarm optimisation (PSO), artificial bee colony (ABC), and firefly (FF) on 16 different hardness scores of the benchmark functions with different initial control parameters such as problem dimensions and search space. The experimental results indicate that BSA is statistically superior than the aforementioned algorithms in solving different cohorts of numerical optimisation problems such as problems with different levels of hardness score, problem dimensions, and search spaces. This study can act as a systematic and meta-analysis guide for the scholars who are working on improving BSA.In artificial intelligence (AI), besides the existing traditional symbolic and statistical methods [1], computational intelligence (CI) has emerged as a recent research area [2]. According to [3], CI deals with collections of nature-inspired algorithms and approaches that in turn have been used to deal with complex practical problems that cannot be feasibly or effectively solved by traditional methods. CI comprises three subfields: fuzzy logic, evolutionary computation, and neural network.The concept of swarm intelligence (SI) is a part of evolutionary computation. It deals with artificial and natural systems that comprise several individuals and possess the ability of self-organisation and decentralised control.This concept, which was primarily initiated by Gerardo Beni and Jing Wang in 1989 in the context of cellular robotic systems, is used in AI [4]. Typically, the SI system comprises a collection of agents. The agents interact with their own environment or with each other. SI syst...

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“…Many algorithms such as perturb & observe (P&O) 10‐14 or hill climbing (HC), 15‐17 incremental conductance (IC), 18‐25 fractional short‐circuit current or open‐circuit voltage, 26 and artificial intelligence techniques 27‐31 have been proposed as an MPPT controller. All of the above methods control the duty cycle of the DC‐DC converter.…”

Section: Introductionmentioning

confidence: 99%

Design of an intelligent MPPT for a PV array mounted on a satellite considering outer space

Noroozi

Shayanfar

Nasirian

2021

Int Trans Electr Energ Syst

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In this study, a model reference adaptive state-dependent Riccati equation (MRASDRE) is proposed as a maximum power point tracking (MPPT) controller to extract the maximum power from a photovoltaic (PV) array mounted on an orbiting satellite. In the structure of the proposed MPPT, a fuzzy logic controller (FLC) is used to estimate the reference voltage of the PV array at the maximum power point (MPP), and an adaptive mechanism is used to compensate for the difference between the PV system and the reference model. The model reference generates the duty cycle for damping the oscillations of the DC-DC converter and tracking the MPP. A Lyapunov stability theory is used to obtain an adaption law to tune the gains of the adaptive mechanism. Hence, the stability of the closed system can be guaranteed, and the maximum power point (MPP) can be captured. To evaluate the performance of the proposed MPPT used in an orbiting satellite, the outer space environment is simulated. Also, an electrical power supply (EPS) is proposed to manage the generation and consumption of satellites. The efficiency of the proposed MPPT is verified in the simulation tests.

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Backtracking Search Optimization Algorithm Based MPPT Technique for Solar PV System

Cited by 6 publications

References 7 publications

A multi‐objective approach for the optimal design of a standalone hybrid renewable energy system

A multi‐objective approach for the optimal design of a standalone hybrid renewable energy system

Operational framework for recent advances in backtracking search optimisation algorithm: A systematic review and performance evaluation

Design of an intelligent MPPT for a PV array mounted on a satellite considering outer space

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