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Control Strategies for the DAB Based PV Interface System
- Source :
- PLoS ONE, Vol 11, Iss 8, p e0161856 (2016), PLoS ONE
- Publication Year :
- 2016
- Publisher :
- Public Library of Science (PLoS), 2016.
-
Abstract
- This paper presents an interface system based on the Dual Active Bridge (DAB) converter for Photovoltaic (PV) arrays. Two control strategies are proposed for the DAB converter to harvest the maximum power from the PV array. The first strategy is based on a simple PI controller to regulate the terminal PV voltage through the phase shift angle of the DAB converter. The Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) technique is utilized to set the reference of the PV terminal voltage. The second strategy presented in this paper employs the Artificial Neural Network (ANN) to directly set the phase shift angle of the DAB converter that results in harvesting maximum power. This feed-forward strategy overcomes the stability issues of the feedback strategy. The proposed PV interface systems are modeled and simulated using MATLAB/SIMULINK and the EMTDC/PSCAD software packages. The simulation results reveal accurate and fast response of the proposed systems. The dynamic performance of the proposed feed-forward strategy outdoes that of the feedback strategy in terms of accuracy and response time. Moreover, an experimental prototype is built to test and validate the proposed PV interface system.
- Subjects :
- Computer science
Interface (computing)
PID controller
lcsh:Medicine
02 engineering and technology
Maximum power point tracking
law.invention
law
0202 electrical engineering, electronic engineering, information engineering
lcsh:Science
Multidisciplinary
Electric Power Supplies
Physics
Applied Mathematics
Simulation and Modeling
Photovoltaic system
Equipment Design
Capacitor
Electrical network
Photovoltaic Power
Physical Sciences
Engineering and Technology
Computer-Aided Design
Alternative Energy
Electrical Engineering
Algorithms
Research Article
Computer and Information Sciences
Maximum power principle
020209 energy
Capacitors
Research and Analysis Methods
Artificial Intelligence
Control theory
Prototypes
Computer Simulation
Artificial Neural Networks
Computational Neuroscience
business.industry
020208 electrical & electronic engineering
lcsh:R
Biology and Life Sciences
Computational Biology
Square Waves
Models, Theoretical
Energy and Power
Technology Development
Waves
Alternative energy
Cognitive Science
lcsh:Q
Electronics
business
Mathematics
Neuroscience
Electrical Circuits
Voltage
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 11
- Issue :
- 8
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....1d0a16d5c2ad428b8ce061af1ea04af5