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Model-based Fault-tolerant Control to Guarantee the Performance of a Hybrid Wind-Diesel Power System in a Microgrid Configuration
- Source :
- ANT/SEIT
- Publication Year :
- 2013
- Publisher :
- Elsevier BV, 2013.
-
Abstract
- This paper presents a comparison of two different adaptive control schemes for improving the performance of a hybrid wind-diesel power system in an islanded microgrid configuration against the baseline controller, IEEE type 1 automatic voltage regulator (AVR). The first scheme uses a model reference adaptive controller (MRAC) with a proportional-integral-derivative (PID) controller tuned by a genetic algorithm (GA) to control the speed of the diesel engine (DE) for regulating the frequency of the power system and uses a classical MRAC for controlling the voltage amplitude of the synchronous machine (SM). The second scheme uses a MRAC with a PID controller tuned by a GA to control the speed of the DE, and a MRAC with an artificial neural network (ANN) and a PID controller tuned by a GA for controlling the voltage amplitude of the SM. Different operating conditions of the microgrid and fault scenarios in the diesel engine generator (DEG) were tested: 1) decrease in the performance of the diesel engine actuator (40% and 80%), 2) sudden connection of 0.5 MW load, and 3) a 3-phase fault with duration of 0.5seconds. Dynamic models of the microgrid components are presented in detail and the proposed microgrid and its fault-tolerant control (FTC) are implemented and tested in the Simpower Systems of MATLAB/Simulink® simulation environment. The simulation results showed that the use of ANNs in combination with model-based adaptive controllers improves the FTC system performance in comparison with the baseline controller.
- Subjects :
- Adaptive control
Model-based Control
business.industry
Computer science
Real-time computing
Fault-tolerant Control
PID controller
Distributed Generation
Voltage regulator
Fault (power engineering)
Diesel engine
Voltage amplitude
Electric power system
Diesel fuel
Artificial Intelligence
Control theory
Distributed generation
General Earth and Planetary Sciences
Microgrid
Microgrids
Actuator
business
Synchronous motor
General Environmental Science
Subjects
Details
- ISSN :
- 18770509
- Volume :
- 19
- Database :
- OpenAIRE
- Journal :
- Procedia Computer Science
- Accession number :
- edsair.doi.dedup.....f6c524a34a598d616fb8131a7da99d78