Solar photovoltaic (PV) systems under partial shading conditions (PSCs) have a nonmonotonic P – V characteristic with multiple local maximum power points, which makes the existing maximum power point tracking (MPPT) algorithms unsatisfactory performance for global MPPT, if not invalid. This paper proposes a novel overall distribution (OD) MPPT algorithm to rapidly search the area near the global maximum power points, which is further integrated with the particle swarm optimization (PSO) MPPT algorithm to improve the accuracy of MPPT. Through simulations and experimentations, the higher effectiveness and accuracy of the proposed OD-PSO MPPT algorithm in solar PV systems is demonstrated in comparison to two existing artificial intelligence MPPT algorithms.

An Overall Distribution Particle Swarm Optimization MPPT Algorithm for Photovoltaic System Under Partial Shading

This paper presents a concise and an organized review of various maximum power point tracking (MPPT) algorithms implemented in the photovoltaic (PV) generation system useable under partial shading condition Various algorithms, PV modeling techniques, PV array configurations and controller topologies have been widely explored till date But, every technique always has its advantages as well as disadvantages simultaneously; as a result, a proper literature review is essential while designing a PV generation system (PGS) under partial shading condition In this paper, the detailed review of MPPT algorithms has been done The review on MPPT techniques has been classified into mainly four essential groups The first among them includes all the new MPPT optimization algorithms, the second group includes the hybrid MPPT algorithms, the third category includes new modeling approach, and the fourth category includes the various converter topologies This paper provides an accessible reference to undertake mass research works in PV systems in the near future under partial shading condition

A review on MPPT techniques of PV system under partial shading condition

Novel bio-inspired memetic salp swarm algorithm and application to MPPT for PV systems considering partial shading condition

This paper proposes an enhanced adaptive perturb and observe (EA-PO second, modified incremental conduction; third, cuckoo search; and fourth, the hybrid ant colony optimization-P&O. The results show that the proposed method tracks the global peak successfully under distinctive patterns of partial shading, when other algorithms fail occasionally. On top of that, it improves the tracking speed by two to three times, while efficiency is maintained over 99%.

An Enhanced Adaptive P&O MPPT for Fast and Efficient Tracking Under Varying Environmental Conditions

In photovoltaic (PV) power generation, partial shading is an unavoidable complication that significantly reduces the efficiency of the overall system Under this condition, the PV system produces a multiple-peak function in its output power characteristic Thus, a reliable technique is required to track the global maximum power point (GMPP) within an appropriate time This study aims to employ a hybrid evolutionary algorithm called the DEPSO technique, a combination of the differential evolutionary (DE) algorithm and particle swarm optimization (PSO), to detect the maximum power point under partial shading conditions The paper starts with a brief description about the behavior of PV systems under partial shading conditions Then, the DEPSO technique along with its implementation in maximum power point tracking (MPPT) is explained in detail Finally, Simulation and experimental results are presented to verify the performance of the proposed technique under different partial shading conditions Results prove the advantages of the proposed method, such as its reliability, system-independence, and accuracy in tracking the GMPP under partial shading conditions

Simulation and Hardware Implementation of New Maximum Power Point Tracking Technique for Partially Shaded PV System Using Hybrid DEPSO Method

Maximum power point tracking (MPPT) is an integral part of a system of energy conversion using photovoltaic (PV) arrays. The power-voltage characteristic of PV arrays operating under partial shading conditions exhibits multiple local maximum power points (LMPPs). In this paper, a new method has been presented to track the global maximum power point (GMPP) of PV. Compared with the past proposed global MPPT techniques, the method proposed in this paper has the advantages of determining whether partial shading is present, calculating the number of peaks on P – V curves, and predicting the locations of GMPP and LMPP. The new method can quickly find GMPP, and avoid much energy loss due to blind scan. The experimental results verify that the proposed method guarantees convergence to the global MPP under partial shading conditions.

An Improved MPPT Controller for Photovoltaic System Under Partial Shading Condition

5G-enabled ultra-sensitive fluorescence sensor for proactive prognosis of COVID-19.

Most researchers use wavelet transforms to extract features from a time-domain transient response from analog circuits to train classifiers such as neural networks (NNs) and support vector machines (SVMs) for analog circuit diagnostics. In this paper, we have proposed some new feature selection methods from a time-domain transient response, and compared the diagnostic results based on a least squares SVM (LS-SVM) using different time-domain feature vectors. First, we have improved two traditional feature selection methods: (a) using the mean and standard deviation in wavelet transform features, and (b) using the mean, standard deviation, skewness, kurtosis, and entropy in statistical property features. Then, a conventional time-domain feature vector based on the impulse response properties of a control system has been proposed. The simulation experiments for a leapfrog filter and a nonlinear rectifier show that: (1) the two improved methods have better accuracy than the traditional methods; (2) the proposed conventional time-domain feature vector is effective in the diagnostics of analog circuits—over 99 % for both of the two example circuits; (3) the proposed diagnostic method can diagnose soft faults, hard faults, and multi-faults, regardless of component tolerances and nonlinearity effects.

Shulin Tian

Papers

An Improved MPPT Controller for Photovoltaic System Under Partial Shading Condition

5G-enabled ultra-sensitive fluorescence sensor for proactive prognosis of COVID-19.

Diagnostics of Analog Circuits Based on LS-SVM Using Time-Domain Features

Aptamer-based lateral flow assay on-site biosensors.

Electrochemical vitamin sensors: A critical review