Next Article in Journal
Implementation, Comparison and Application of an Average Simulation Model of a Wind Turbine Driven Doubly Fed Induction Generator
Previous Article in Journal
Controllability and Leader-Based Feedback for Tracking the Synchronization of a Linear-Switched Reluctance Machine Network
Article Menu
Issue 11 (November) cover image

Export Article

Open AccessArticle
Energies 2017, 10(11), 1720; doi:10.3390/en10111720

A Fuzzy-Based PI Controller for Power Management of a Grid-Connected PV-SOFC Hybrid System

1
Institute of Power Engineering (IPE), Universit Tenaga Nasional, Selangor 43000, Malaysia
2
Department of Electronics and Communication Engineering, Universiti Tenaga Nasional, Selangor 43000, Malaysia
3
Department of Electrical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia
4
Power Electronics and Renewable Energy Research Laboratory (PEARL), University of Malaya, Kuala Lumpur 50603, Malaysia
*
Author to whom correspondence should be addressed.
Academic Editor: William Holderbaum
Received: 11 September 2017 / Revised: 13 October 2017 / Accepted: 16 October 2017 / Published: 27 October 2017
(This article belongs to the Section Electrical Power and Energy System)
View Full-Text   |   Download PDF [3624 KB, uploaded 27 October 2017]   |  

Abstract

Solar power generation is intermittent in nature. It is nearly impossible for a photovoltaic (PV) system to supply power continuously and consistently to a varying load. Operating a controllable source like a fuel cell in parallel with PV can be a solution to supply power to variable loads. In order to coordinate the power supply from fuel cells and PVs, a power management system needs to be designed for the microgrid system. This paper presents a power management system for a grid-connected PV and solid oxide fuel cell (SOFC), considering variation in the load and solar radiation. The objective of the proposed system is to minimize the power drawn from the grid and operate the SOFC within a specific power range. Since the PV is operated at the maximum power point, the power management involves the control of SOFC active power where a proportional and integral (PI) controller is used. The control parameters of the PI controller Kp (proportional constant) and Ti (integral time constant) are determined by the genetic algorithm (GA) and simplex method. In addition, a fuzzy logic controller is also developed to generate appropriate control parameters for the PI controller. The performance of the controllers is evaluated by minimizing the integral of time multiplied by absolute error (ITAE) criterion. Simulation results showed that the fuzzy-based PI controller outperforms the PI controller tuned by the GA and simplex method in managing the power from the hybrid source effectively under variations of load and solar radiation. View Full-Text
Keywords: distributed generation; fuel cell; fuzzy logic controller; hybrid system; power management; photovoltaic distributed generation; fuel cell; fuzzy logic controller; hybrid system; power management; photovoltaic
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Sukumar, S.; Marsadek, M.; Ramasamy, A.; Mokhlis, H.; Mekhilef, S. A Fuzzy-Based PI Controller for Power Management of a Grid-Connected PV-SOFC Hybrid System. Energies 2017, 10, 1720.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top