Secondary load frequency control for multi-microgrids: HiL real-time simulation

被引:96
作者
Gheisarnejad, Meysam [1 ]
Khooban, Mohammad Hassan [2 ]
机构
[1] Islamic Azad Univ, Najafabad Branch, Dept Elect Engn, Esfahan, Iran
[2] Aalborg Univ, Dept Energy Technol, Pontoppidanstr 101, DK-9220 Aalborg, Denmark
关键词
Renewable energy sources; Microgrid; Load frequency control; JAYA algorithm; FUZZY-PID CONTROLLER; CONTROL STRATEGY; ENERGY-SYSTEMS; OPTIMIZATION; ALGORITHM; GENERATION; DESIGN; GRIDS;
D O I
10.1007/s00500-018-3243-5
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The intermittent feature of renewable energy sources leads to the mismatch between supply and load demand on microgrids. In such circumstance, the system experiences large fluctuations, if the secondary load frequency control (LFC) mechanism is unable to compensate the mismatch. In this issue, this paper presents a well-structured combination of the fuzzy PD and cascade PI-PD controllers named FPD/PI-PD controller as a supplementary (secondary) controller for the secondary load frequency control in the islanded multi-microgrid (MMG). Additionally, two modifications to the JAYA algorithm are made to enhance the diversity of the initial population and ameliorate the global searching ability in the iterative process. Afterward, the improved JAYA algorithm, referred to as IJAYA, is employed for fine-tuning the proposed structured controller installed in areas of the studied MMG. The superiority of the proposed IJAYA is validated by comparative analysis with genetic algorithm and basic JAYA in a similar structure of the PID controller. Furthermore, it will be shown that the proposed FPD/PI-PD controller employing IJAYA provides a higher degree of stability in suppressing the responses deviations as compared with the conventional PID and FPID controller structures. Finally, the novel optimal proposed approach is validated and implemented in the hardware-in-the-loop (HIL) based on OPAL-RT to integrate the fidelity of physical simulation and the flexibility of numerical simulation.
引用
收藏
页码:5785 / 5798
页数:14
相关论文
共 37 条
[1]   Hybrid renewable energy systems for power generation in stand-alone applications: A review [J].
Bajpai, Prabodh ;
Dash, Vaishalee .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2012, 16 (05) :2926-2939
[2]   Intelligent Frequency Control in an AC Microgrid: Online PSO-Based Fuzzy Tuning Approach [J].
Bevrani, H. ;
Habibi, F. ;
Babahajyani, P. ;
Watanabe, M. ;
Mitani, Y. .
IEEE TRANSACTIONS ON SMART GRID, 2012, 3 (04) :1935-1944
[3]  
Chowdhury AH, 2014, 2014 INTERNATIONAL CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (ICECE), P548, DOI 10.1109/ICECE.2014.7026975
[4]  
Chowdhury S., 2009, Microgrids and active distribution nerworks
[5]   GA based frequency controller for solar thermal-diesel-wind hybrid energy generation/energy storage system [J].
Das, Dulal Ch ;
Roy, A. K. ;
Sinha, N. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2012, 43 (01) :262-279
[6]   Efficient frequency controllers for autonomous two-area hybrid microgrid system using social-spider optimiser [J].
El-Fergany, Attia A. ;
El-Hameed, Mohammed A. .
IET GENERATION TRANSMISSION & DISTRIBUTION, 2017, 11 (03) :637-648
[7]   Frequency control in isolated island by using parallel operated battery systems applying H∞ control theory based on droop characteristics [J].
Goya, T. ;
Omine, E. ;
Kinjyo, Y. ;
Senjyu, T. ;
Yona, A. ;
Urasaki, N. ;
Funabashi, T. .
IET RENEWABLE POWER GENERATION, 2011, 5 (02) :160-166
[8]   Multi-microgrid energy systems operation incorporating distribution-interline power flow controller [J].
Kargarian, Amin ;
Rahmani, Mohsen .
ELECTRIC POWER SYSTEMS RESEARCH, 2015, 129 :208-216
[9]   A self-tuning load frequency control strategy for microgrids: Human brain emotional learning [J].
Khalghani, Mohammad Reza ;
Khooban, Mohammad Hassan ;
Mahboubi-Moghaddam, Esmaeil ;
Vafamand, Navid ;
Goodarzi, Mohammad .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2016, 75 :311-319
[10]   Analysis, control and design of speed control of electric vehicles delayed model: multi-objective fuzzy fractional-order PIλDμ controller [J].
Khooban, Mohammad Hassan ;
ShaSadeghi, Mokhtar ;
Niknam, Taher ;
Blaabjerg, Frede .
IET SCIENCE MEASUREMENT & TECHNOLOGY, 2017, 11 (03) :249-261