To minimize real-time errors in a Photovoltaic (PV) system performances must be forecasted through precise simulation design before continuing into a practical application. However, due to the scarcity of data in datasheets and the inherent transcendental connections are between PV current and PV voltage, to determining the Single Diode Model (SDM) parameters becomes a more challenging problems. This paper offers a simulated study of a SDM and Double Diode Model (DDM) solar PV system under various irradiation represents, and the performance was developed by incorporating an optimization-based Maximum Power Point (MPP) tracking techniques. According to the present simulation presented in this article, a mathematical model for a SDM/DDM as well as optimization methodologies has been estimated MATLAB platform. The present MPP circuit model designed and compared with BAT optimization algorithms. The nonlinear relationship between Voltage (V) - Current (I) and Voltage (V) –Power (W) acknowledged as characteristic curves for different temperature (∘c) and irradiance (W/m2) values are verified in numerical simulation results. MPP tracking power and efficiency are examined for maximum power (Pmax) to test the optimization based system. The simulation results show that the BAT optimization model was achieved the highest tracking efficiency better than other heuristic algorithms.

Design and development of extract maximum power from single-double diode PV model for different environmental condition using BAT optimization algorithm

A super-lift mechanism has made tremendous progress in DC/DC conversion technology. In comparison to the asymmetrical form of MLI, the novel Asymmetric Multilevel Inverter (AMLI) technology proposes a minimized number of components. The Fuzzy-PI (Proportional integral) and Modified Genetic Algorithm (MGA) utilizes to minimize the harmonic content considerably using a variety of modulation index and firing angle values in open-loop and closed-loop control. This architecture for designing single-phase 7-level AMLI with an intelligent algorithm proposed for Renewable Energy (RE) applications. This circuit uses a single MOSFET switch with less switching stress and a single DC source. The effectiveness of the proposed MGA optimization eliminates the lower-order harmonics. MGA and Fuzzy-PI based Distributed Power Flow Intelligent Control (DPFIC) algorithms are applied with multilevel structures while maintaining the fundamental frequency for both MATLAB platform and hardware implementation. During this analysis, the losses is also find to investigate the influence of modulation index and output power factor on inverter efficiency. Simulations and experimental findings confirm the proposed inverter capacity to create high-quality multilayer output voltage. However, the proposed closed loop simulation circuit gives 0.47% minimum THD level, and 10.4% in experimental results.

Experimental investigation and comparative harmonic optimization of AMLI incorporate modified genetic algorithm using for power quality improvement

Design and Investigation of Solar PV Fed Single-Source Voltage-Lift Multilevel Inverter Using Intelligent Controllers

Testing and performance evaluation of water pump irrigation system using voltage-lift multilevel inverter

A proposed hybrid approaches are incorporated in Electric Vehicle (EV) fast charging station (FCS) using (RES). Hybrid approach is improved by Adaptive Hybrid Particle Swarm Optimization (AHPSO) named as AHWPSO, moreover the proposed work Grey Wolf Optimization (GWO) is assist with adaptive hybridize PSO algorithm. Therefore, an overall pricing cost should be reduced maximum Electric Vehicle Charging Station (EVCS) with minimal installation. This simulation work is verified an adaptive time varying weightage parameters to increase the AHWPSO particle diversity factor. Proposed algorithm is incorporated with improve the novelty, and compared the results are recent version of PSO used for EVCS. Its increase the charging ability, energy loss minimization, voltage deviation reduction, and cost minimization. A distribution micro-grid capacity and demand are tested. Similarly, low to peak period energy variations are controlled by proposed algorithm with reduced capacitor bank. Overall control algorithm code is executed buy MATLAB/Simulink platform, the performance of this work listed, and compare to the existing approaches with achievement of maximum efficiency.

An advanced electrical vehicle charging station using adaptive hybrid particle swarm optimization intended for renewable energy system for simultaneous distributions

Investigation on load harmonic reduction through solar-power utilization in intermittent SSFI using particle swarm, genetic, and modified firefly optimization algorithms

A new Symmetric Solar Fed Inverter (SSFI) proposed with a reduced number of components compared to the classical, modified, conventional type of Multilevel Inverter (MLI). The objective of this architecture is to design fifteen-level SSFI, this circuit uses a single switch with minimizing harmonics, and Modulation Index (MI) values. Power Quality (PQ) is developed by using the optimization algorithms like as Particle Swarm Optimization (PSO), Genetic algorithm (GA), Modified Firefly Algorithm (MFA). It’s determined to generate the gating pulse and finding optimum firing angle values calculate as per the input of MPP intelligent controller schemes. The proposed circuit is solar fed inverter used for optimization techniques governed by switching controller approach delivers a major task. The comparison is made for different optimization algorithm has significantly reduced the harmonic content by varying the modulation index and switching angle values. SSFI generates low distortion output uses through without any additional filter component through utilizing MATLAB Simulink software (2020a). The SSFI circuit assist Xilinx Spartan 3-AN Filed Program Gate Array (FPGA) tuned by optimization techniques are presented for the effectiveness of the proposed model. 

A Voltage lift performance is an excellent role to DC/DC conversion topology. The Voltage Lift Multilevel Inverter (VL-MLI) topology is suggested with minimal number of components compared to the conventional multilevel inverter (MLI). In this method, the Modified Particle Swarm Optimization (MPSO) conveys a primary task for the VL-MLI using Half Height (H-H) method, it determine the required optimum switching angles to eliminate desired value of harmonics. The simulation circuit for fifteen level output uses single switch voltage-lift inverter fed with resistive and inductive loads (R &amp; L load). The power quality is developed by voltage-lift multilevel inverter with minimized harmonics under the various Modulation Index (MI) while varied from 0.1 up to 1. The circuit is designed in a Field Programmable Gate Array (FPGA), which includes the MPSO rules for fast convergence to reduce the lower order harmonics and finds the best optimum switching angle values. To report this problem the H-H has implemented with MPSO to reduce minimum Total Harmonic Distortion (THD) for simulation circuit using Proteus 7.7 simulink tool. Due to the absence of multiple switches, filter and inductor element exposes for novelty of the proposed system. The comparative analysis has been carried-out with existing optimization and modulation methods. 

Design and experimental investigation on VL-MLI intended for half height (H-H) method to improve power quality using modified particle swarm optimization (MPSO) algorithm

Scott A. Whattam

Papers

Investigation on load harmonic reduction through solar-power utilization in intermittent SSFI using particle swarm, genetic, and modified firefly optimization algorithms

Investigation on load harmonic reduction through solar-power utilization in intermittent SSFI using particle swarm, genetic, and modified firefly optimization algorithms

Design and experimental investigation on VL-MLI intended for half height (H-H) method to improve power quality using modified particle swarm optimization (MPSO) algorithm