A Nature-Inspired Optimization-Based Optimum Fuzzy Logic Photovoltaic Inverter Controller Utilizing an eZdsp F28335 Board

Mutlag, Ammar Hussein; Mohamed, Azah; Shareef, Hussain

doi:10.3390/en9030120

Cited by 24 publications

(12 citation statements)

References 36 publications

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“…All these steps are implemented using the TMS320F28335 board. The mean absolute error (MAE) is applied an optimization problem as in equation (3) to minimize the output error of the voltage source inverter [20]. …”

Section: Introductionmentioning

confidence: 99%

An Efficient Control Implementation for Inverter Based Harmony Search Algorithm

Najeeb¹,

Daniyal²,

Razali³

et al. 2017

IJPEDS

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This research implements a PI controller based on harmony search (HS) optimization algorithm for voltage source inverter to improve the output performance under step load change conditions. The HS algorithm aims to handle the trial and error procedure used in finding the PI parameters and then apply the proposed control algorithm via the eZdsp TMS320F28355 board to link the inverter prototype with the Matlab Simulink. The mean absolute error (MAE) is used as an optimization problem to minimize the output voltage error for the developed controller (PI-HS) as compared to the PI controller based particale swarm optimization algorithm (PI-PSO). Based on the experimental results obtained, it is noted that the proposed controller (PI-HS) provides a good dynamic performance, robustness, constant voltage amplitude, and fast response in terms of overshoot, transient, and steadystate. Keyword:eZdsp TMS320F28335 board Harmony search PI controller SPWM with its C code Voltage source inverter Copyright © 2017 Institute of Advanced Engineering and Science.All rights reserved. Corresponding Author:Mushtaq Najeeb, Faculty of Electrical and Electronics Engineering, Pekan Campus, Universiti Malaysia Pahang, 26600, Pekan, Pahang, Malaysia. Email: eng.mushtaq2004@gmail.com INTRODUCTIONThe topic of the voltage source inverter is playing an important role nowadays in research area to generate an AC output for different applications [1]- [5]. An inverter device is required to convert a DC to an AC source because of the most applications are connected to the AC loads [6]- [9]. So, the main important feature of the inverter design is its controller improvement. In addition, the controller ability is to provide a good dynamic performance, keep a constant output voltage waveform and frequency regardless of different loads are connected [10]- [11].Therefore, there are a lot of various control algorithms have been carried out in the literature to solve the voltage control problems. The author in [12] has implemented a PI controller with a PWM algorithm for the PV inverter system using eZdsp F2812 board to keep the voltage waveform as a sinusoidal. Similarly, the researchers in [13] have also proposed a conventional controller of proportional-integral design to control the boost converter for the inverter system in order to get a good performance. In a related research, a field programmable gate array (FPGA) has been used in the PV inverter systems to develop the control algorithm described in [14]-[15] but it considered a time consuming task because it needs a wide knowledge in software programming. For a real time hardware setup, the reference [16] has used the platform of dSPACE DS1104 control unit to implement the PI controller of three-phase PV inverter system for a good dynamic performance. Also, same control unit has been used in [17] to enable the user to develop the control

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Section: Introductionmentioning

confidence: 99%

An Efficient Control Implementation for Inverter Based Harmony Search Algorithm

Najeeb¹,

Daniyal²,

Razali³

et al. 2017

IJPEDS

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“…Moreover, a capability of power inverter to have quickly recovering from any transient that affected by peripheral disturbances in spite of quality initiating of power problems [5].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the single-phase photovoltaic grid-connected cascaded H-bridge multilevel inverters

Hamad¹

2017

IJATEE

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“…The projectile suggests random solutions for corresponding problems to be solved by LSA. More details about LSA and basic ideas can be found in [30,31]. The step leaders are formed in the first phase because transition projectiles are ejected from the thunder cell in a random direction.…”

Section: Overview Of Lightning Search Algorithmmentioning

confidence: 99%

Hybrid LSA-ANN Based Home Energy Management Scheduling Controller for Residential Demand Response Strategy

et al. 2016

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Demand response (DR) program can shift peak time load to off-peak time, thereby reducing greenhouse gas emissions and allowing energy conservation. In this study, the home energy management scheduling controller of the residential DR strategy is proposed using the hybrid lightning search algorithm (LSA)-based artificial neural network (ANN) to predict the optimal ON/OFF status for home appliances. Consequently, the scheduled operation of several appliances is improved in terms of cost savings. In the proposed approach, a set of the most common residential appliances are modeled, and their activation is controlled by the hybrid LSA-ANN based home energy management scheduling controller. Four appliances, namely, air conditioner, water heater, refrigerator, and washing machine (WM), are developed by Matlab/Simulink according to customer preferences and priority of appliances. The ANN controller has to be tuned properly using suitable learning rate value and number of nodes in the hidden layers to schedule the appliances optimally. Given that finding proper ANN tuning parameters is difficult, the LSA optimization is hybridized with ANN to improve the ANN performances by selecting the optimum values of neurons in each hidden layer and learning rate. Therefore, the ON/OFF estimation accuracy by ANN can be improved. Results of the hybrid LSA-ANN are compared with those of hybrid particle swarm optimization (PSO) based ANN to validate the developed algorithm. Results show that the hybrid LSA-ANN outperforms the hybrid PSO based ANN. The proposed scheduling algorithm can significantly reduce the peak-hour energy consumption during the DR event by up to 9.7138% considering four appliances per 7-h period.Keywords: lightning search algorithm (LSA); home energy management system (HEMS); artificial neural network (ANN); load scheduling; residential demand response (DR)

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A Nature-Inspired Optimization-Based Optimum Fuzzy Logic Photovoltaic Inverter Controller Utilizing an eZdsp F28335 Board

Cited by 24 publications

References 36 publications

An Efficient Control Implementation for Inverter Based Harmony Search Algorithm

An Efficient Control Implementation for Inverter Based Harmony Search Algorithm

Analysis of the single-phase photovoltaic grid-connected cascaded H-bridge multilevel inverters

Hybrid LSA-ANN Based Home Energy Management Scheduling Controller for Residential Demand Response Strategy

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