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Adaptive PI secondary control for smart autonomous microgrid systems
Author(s) -
Mahmoud Magdi S.,
Hussain S. Azher
Publication year - 2015
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2559
Subject(s) - microgrid , control theory (sociology) , controller (irrigation) , pid controller , control engineering , computer science , artificial neural network , open loop controller , control (management) , engineering , temperature control , artificial intelligence , closed loop , agronomy , biology
Summary In this paper, the authors present a neural‐network‐based distributed secondary control to regulate the output voltage and frequency of a smart autonomous microgrid system. Generally, the secondary controller is implemented in a centralized manner using a fixed‐gain proportional‐plus‐integral controller which may perform well under certain operating conditions only. Also the failure of centralized controller implies no secondary control action for the entire system. The control technique proposed in this paper is a distributed one and makes use of neural network (NN) concept to improve the performance of system. A well‐trained NN supplies the controller with suitable gains according to each operating point. Before training the NN, evolutionary optimization technique, differential evolution , is employed to obtain the optimal gains of controller at each operating load condition which forms the training set for NN. Simulation results show that the proposed controller damps the oscillations caused by load changes, restores the output voltage and frequency of the system to their nominal values, and maintains proper load sharing property of the baseline controller. The performance of the controller is also compared with fixed‐gain controller. Copyright © 2015 John Wiley & Sons, Ltd.