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An isolated hybrid system comprised of a dispatchable and a non-dispatchable power generation sources, is proposed to supply the load of a remote village in the west coast region of The Gambia. The thesis presents an artificial neural network (ANN) based approach to tune the parameters of the frequency regulator in hybrid wind/diesel power system for isolated area power supply. The multi-layer feed-forward ANN with the error back-propagation training is employed to tune the frequency regulator in the simulation of hybrid system under different load and wind conditions. Using MATLAB/Simulink, dynamic simulations are performed to investigate the interaction between these two power sources for the load management, and the voltage and frequency behaviors during wind speed and load variations. Simulation results show that the wind turbine and the diesel generator can be operated suitably in parallel. During simulation, the frequency and voltage regulators used in the proposed hybrid system performed fairly well under wind speed variations and load changing conditions. A good frequency regulator interface, which is around 50Hz is observed for nearly the entire period of operation.

Table of Contents

Abstract……………………………………………………………………………… i
Table of contents…………………………………………………………………… ii
List of figures……………………………………………………………………… iv
List of Tables……………………………………………………………………… vi

Chapter 1 Introduction………………………………....................... 1
1.1 Background…………………………………………………............................ 1
1.2 Motivation of thesis……………………………………………...................... 2
1.3 Research method…………………………………………………………….. 3
1.4 Thesis outline………………………………………………………………... 4

Chapter 2 Modeling the wind diesel power system………..……... 5
2.1 Wind Turbine Modeling……………………………………………………… 7
2.2 Self-excited Induction Generator Modeling………………………………….. 11
2.2.1 Induction Machine…………………………………………………….. 13
2.2.2 Equivalent electrical circuit of induction machine……………………. 13
2.2.3 Self-excited induction generator (SEIG)……………………………… 14
2.3 Diesel generator system…………………………………………………….. 27
2.3.1 Diesel engine model………………………………………………….. 28
2.3.2 Synchronous generator model and equivalent circuit………………… 29
2.3.3 Parameters identification……………………………………………… 35

Chapter 3 Introduction to neural networks…………………….. 38
3.1 Basic concept of a neural network.................................................................. 38
3.2 The need for neural networks......................................................................... 39
3.2.1 Human brain learning principle............................................................ 42
3.2.2 Classification of neural network architecture………………………… 45
3.2.3 Network learning strategies…………………………………………... 46
3.3 Backpropagation neural network…………………………………………… 48
3.3.1 The neural network learning methods………………………………… 51
3.3.2 The implementation of BPNN……………………………………….. 55

Chapter 4 Hybrid wind diesel system and Simulation results……… 58
4.1 Hybrid wind diesel system………………………………………………. 58
4.1.1 System frequency control…………………………………………. 60
4.1.2 Control principle………………………………………………….. 63
4.2 Simulation results and discussion………………………………………… 65
4.2.1 Case 1: fixed wind speed with fixed load………..……………….. 67
4.2.2 Case 2: change in wind speed with fixed load……………………. 69
4.2.3 Case 3: fixed wind speed with variable loads ……………………. 75
4.2.4 Case 4: variable speed with variable loads ..……………………… 79

Chapter 5 Conclusion…………………………………………… 85
5.1 Conclusion………………………………………………………………. 85
5.2 proposed research topic…………………………………………………. 86

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