Implementation of Distributed Fuzzy Load Control to an Autonomous Wind Diesel System
Science Journal of Energy Engineering
Volume 6, Issue 1, March 2018, Pages: 18-26
Received: Feb. 16, 2018; Accepted: Mar. 7, 2018; Published: Apr. 12, 2018
Views 727      Downloads 36
Authors
Hla Myo Tun, Department of Electronic Engineering, Yangon Technological University, Yangon, Republic of the Union of Myanmar
Zaw Min Naing, Department of Electrical and Electronic Engineering, Institute of Research and Innovation, Yangon, Republic of the Union of Myanmar
Win Khaing Moe, Department of Electrical and Electronic Engineering, Institute of Research and Innovation, Yangon, Republic of the Union of Myanmar
Maung Maung Latt, Department of Electronic Engineering, Technological University (Taungoo), Taungoo, Republic of the Union of Myanmar
Article Tools
Follow on us
Abstract
Many autonomous power systems are powered by diesel generators alone, which results in greater operating costs than interconnected grids. It is therefore desirable to integrate renewable energy sources such as wind into these mini grids. However, due to the fluctuating power generation from the wind resource, the varying load profile and the relatively low system inertia, technical difficulties arise in terms of system stability and efficient operation. Typically the penetration of wind energy on such systems is limited to 30%. Distributed intelligent load control can be used to increase wind penetration and cut diesel fuel consumption, whilst maintaining system stability. This thesis describes the development and application of a distributed intelligent load control system. The development of a self-tuning fuzzy controller and the construction of a laboratory wind-diesel test rig are discussed. The development of a dynamic Wind-Diesel computer model is also described. Finally the results of tests carried out on a Wind-Diesel system consisting of a 45kW stall regulated wind turbine and a 48kW diesel generator are discussed. The results were encouraging demonstrating that distributed fuzzy load control is a low cost and effective technique, which can be applied to small or large hybrid systems. The simulation results are developed by MATLAB.
Keywords
Distributed Fuzzy Load Control, Autonomous Wind Diesel System, Hybrid System, MATLAB, Energy Engineering
To cite this article
Hla Myo Tun, Zaw Min Naing, Win Khaing Moe, Maung Maung Latt, Implementation of Distributed Fuzzy Load Control to an Autonomous Wind Diesel System, Science Journal of Energy Engineering. Vol. 6, No. 1, 2018, pp. 18-26. doi: 10.11648/j.sjee.20180601.13
Copyright
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
[1]
T. Anderson, A. Doig, D. Rees, S. Khennas, “Rural Energy Services, A Handbook for Sustainable Energy Development.” Intermediate Technology Publications, London, 1999, pp 3-11.
[2]
S. K. Aditya, D. Das, “Application of Battery Energy Storage to Load Frequency Control of an Isolated Power System.”, International Journal of Energy Research, 23, 1999, pp247-258.
[3]
W. M. Somerville. “Fair Isle renewed”, Proceedings of the British Wind Energy Association Conference 1999, pp263-280.
[4]
Stevenson, W. G, Somerville, W. M, “Optimal use of wind and diesel generation on a remote Scottish Island”, Proceedings of the European Wind Energy Association Conference 1984, Part2, pp 681-684.
[5]
P. Taylor, N. Jenkins, C. Robb. “Distributed Intelligent Load Control of Autonomous Renewable Energy Systems”, Proceedings of the British Wind Energy Association Conference 1999, pp255-263.
[6]
K. Pandiaraj, P. Taylor, N. Jenkins, C. Robb. “Distributed load control of autonomous renewable energy systems”, Accepted for publication by IEEE Transactions on Energy Conversion, 1999.
[7]
Y. Song, A. T. Johns, “Applications of Fuzzy Logic in Power Systems.” Power Engineering Journal, October 1997, pp 219-222.
ADDRESS
Science Publishing Group
1 Rockefeller Plaza,
10th and 11th Floors,
New York, NY 10020
U.S.A.
Tel: (001)347-983-5186