Intelligent Frequency Control in an AC Microgrid: Online PSO-Based Fuzzy Tuning Approach

被引:434
作者
Bevrani, H. [1 ]
Habibi, F. [1 ]
Babahajyani, P. [2 ]
Watanabe, M. [3 ]
Mitani, Y. [3 ]
机构
[1] Univ Kurdistan, Sanandaj 6617715175, Iran
[2] Isfahan Univ Technol, Esfahan 8415683111, Iran
[3] Kyushu Inst Technol, Kitakyushu, Fukuoka 8040011, Japan
关键词
Fuzzy logic; intelligent control; microgrid; optimal tuning; particle swarm optimization; secondary frequency control; RENEWABLE ENERGY-SOURCES;
D O I
10.1109/TSG.2012.2196806
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Modern power systems require increased intelligence and flexibility in the control and optimization to ensure the capability of maintaining a generation-load balance, following serious disturbances. This issue is becoming more significant today due to the increasing number of microgrids (MGs). The MGs mostly use renewable energies in electrical power production that are varying naturally. These changes and usual uncertainties in power systems cause the classic controllers to be unable to provide a proper performance over a wide range of operating conditions. In response to this challenge, the present paper addresses a new online intelligent approach by using a combination of the fuzzy logic and the particle swarm optimization (PSO) techniques for optimal tuning of the most popular existing proportional-integral (PI) based frequency controllers in the ac MG systems. The control design methodology is examined on an ac MG case study. The performance of the proposed intelligent control synthesis is compared with the pure fuzzy PI and the Ziegler-Nichols PI control design methods.
引用
收藏
页码:1935 / 1944
页数:10
相关论文
共 28 条
[1]  
[Anonymous], MICROGRIDS ACTIVE DI
[2]  
[Anonymous], 2001, Swarm Intelligence
[3]  
[Anonymous], 2004, ANT COLONY OPTIMIZAT
[4]   Energy Management in Autonomous Microgrid Using Stability-Constrained Droop Control of Inverters [J].
Barklund, E. ;
Pogaku, Nagaraju ;
Prodanovic, Milan ;
Hernandez-Aramburo, C. ;
Green, Tim C. .
IEEE TRANSACTIONS ON POWER ELECTRONICS, 2008, 23 (05) :2346-2352
[5]  
Bevrani H, 2011, INTELLIGENT AUTOMATIC GENERATION CONTROL, P1
[6]   Renewable energy sources and frequency regulation: survey and new perspectives [J].
Bevrani, H. ;
Ghosh, A. ;
Ledwich, G. .
IET RENEWABLE POWER GENERATION, 2010, 4 (05) :438-457
[7]   Fuzzy Logic-Based Load-Frequency Control Concerning High Penetration of Wind Turbines [J].
Bevrani, Hassan ;
Daneshmand, Pourya Ranjbar .
IEEE SYSTEMS JOURNAL, 2012, 6 (01) :173-180
[8]  
Bevrani H, 2009, POWER ELECTRON POWER, P1, DOI 10.1007/978-0-387-84878-5_1
[9]   Micro-grids project, Part 1: Analysis of rural electrification with high content of renewable energy sources in Senegal [J].
Camblong, H. ;
Sarr, J. ;
Niang, A. T. ;
Curea, O. ;
Alzola, J. A. ;
Sylla, E. H. ;
Santos, M. .
RENEWABLE ENERGY, 2009, 34 (10) :2141-2150
[10]   Load-frequency control: a GA-based multi-agent reinforcement learning [J].
Daneshfar, F. ;
Bevrani, H. .
IET GENERATION TRANSMISSION & DISTRIBUTION, 2010, 4 (01) :13-26