Intelligent Systems and Signal Processing in Power Engineering

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Springer Science & Business Media, Sep 23, 2007 - Technology & Engineering - 372 pages
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Power engineering has become a multidisciplinary field ranging from linear algebra, electronics, signal processing to artificial intelligence including recent trends like bio-inspired computation, lateral computing and so on. In this book, Ukil builds the bridge between these inter-disciplinary power engineering practices. The book looks into two major fields used in modern power systems: intelligent systems and the signal processing.

The intelligent systems section comprises of fuzzy logic, neural network and support vector machine. The author looks at relevant theories on the topics without assuming much particular background. Following the theoretical basics, he studies their applications in various problems in power engineering, like, load forecasting, phase balancing, or disturbance analysis. These application studies are of two types: full application studies explained like in-depth case-studies, and semi-developed application ideas with scope for further extension. This is followed by pointers to further research information.

In the second part, the book leads into the signal processing from the basics of the system theory, followed by fundamentals of different signal processing transforms with examples. A section follows about the sampling technique and the digital filters which are the ultimate processing tools. The theoretical basics are substantiated by some of the applications in power engineering, both in-depth and semi-developed as before. This also ends up with pointers to further research information.

“Intelligent Systems and Signal Processing in Power Engineering” is helpful for students, researchers and engineers, trying to solve power engineering problems using intelligent systems and signal processing, or seeking applications of intelligent systems and signal processing in power engineering.

 

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Well-structured book covering important aspects of the theory supported by real applications. Additionally, I found the literature information section very useful as a starting point for projects. I definitely recommend the book for power engg grad students, also people looking for inter-disciplinary power engg problems & solution approaches. 

Contents

412 Applications
162
413 Pros and Cons
163
42 Basics about Statistical Learning Theory
164
422 Statistical Learning Theory
165
423 Vapnik Chervonenkis VC Dimension
167
424 Structural Risk Minimization
169
43 Support Vector Machine
171
432 Optimal Separating Hyperplane
174

223 Fuzzy Set Theory
12
224 Classical Set Theory vs Fuzzy Set Theory
24
225 Example
27
23 Fuzzy System Design
28
231 Fuzzification
29
233 Defuzzification
34
24 Application Example
35
241 Brake Test Application
36
242 Fuzzification
37
243 Fuzzy Inference
40
244 Defuzzification
42
245 Conclusion
45
References
46
251 Feeder Representation
47
252 Proposed Technique
48
253 Designing Fuzzy Controller
49
254 Results
51
References
55
26 Energy Efficient Operation
56
263 Final Output
57
References
58
References
59
282 Energy Consumption Modeling
60
Reference
61
Reference
62
2102 Fuzzy Logic and Power Engineering
63
2104 Fault Analysis
64
2105 Power Systems Protection
65
2108 Power Flow Analysis
66
2109 Power Systems Equipments Control
67
21011 Harmonic Analysis
68
21013 Power Systems Security
69
21015 Power Systems Stabilizer
70
21016 Power Quality
71
21019 Rotating Machines
72
21020 Energy Economy Market Management
73
21023 Power Electronics
74
Neural Network
75
311 History and Background
76
313 Pros and Cons
78
322 Structure of a Neuron
79
323 Transfer Function
81
324 Architecture of the ANN
84
325 Steps to Construct a Neural Network
85
331 The Delta Rule
86
332 Gradient Descent
87
333 Energy Equivalence
88
335 The Hebb Rule
92
34 Different Networks
93
342 Multilayer Perceptrons MLP
94
343 Backpropagation BP Network
95
344 Radial Basis Function RBF Network
96
345 Hopfield Network
104
346 Adaline
105
348 Special Networks
108
349 Special Issues in NN Training
111
35 Examples
114
Boolean Logic Operation
115
352 Pattern Recognition
117
353 Incomplete Pattern Recognition
120
References
126
36 Load Forecasting
127
361 Data set for the Application Study
128
362 Use of Neural Networks
129
364 Backpropagation Network
131
365 Radial Basis Function Network
134
References
137
37 Feeder Load Balancing
138
371 Phase Balancing Problem
139
373 Neural Networkbased Solution
140
374 Network Training
141
375 Results
142
References
143
381 Simple Ground Fault Classifier
144
Reference
145
References
146
References
147
311 Research Information
148
3113 Electrical Load Forecasting
149
3114 Fault Locator Analysis
150
3115 Power Systems Protection
151
3116 Harmonic Analysis
152
3118 Power Flow Analysis
153
31110 Power Systems Operation
154
31112 Power Systems Reliability
155
31114 Renewable Energy
156
31116 Rotating Machines
157
31117 Power Quality
158
31120 Power Electronics
159
Support Vector Machine
161
433 Support Vectors
179
434 Convex Optimization Problem
181
435 Overlapping Classes
183
436 Nonlinear Classifier
185
437 Kernel Method
186
438 Support Vector Regression
193
439 Procedure to use SVM
199
4310 SVMs and NNs
201
References
204
44 Fault Classification
205
443 Fault Classifier
206
444 SVM Simulation
208
References
211
45 Load Forecasting
212
452 Additional Task
213
463 Reactor Ring Down
215
References
217
47 Research Information
218
473 Load Forecasting
219
474 Disturbance Fault Analysis
220
476 Harmonic Analysis
221
478 Power Systems Operation
222
4710 Load Flow
223
4713 Power Systems Stability
224
4717 Transformers
225
Signal Processing
227
511 History and Background
228
512 Applications
229
52 DSP Overview
230
521 Digital to Analog Converter DAC
231
522 Analog to Digital Converter ADC
233
523 Quantization
234
53 Signals and Systems
236
531 DiscreteTime Signals
237
532 Important Discretetime Signals
239
533 Linear ShiftInvariant LSI System
241
534 System Theory Basics
245
535 Convolution
249
54 Laplace Fourier ZTransform
252
542 Fourier Transform
257
543 ZTransform
265
55 DSP Fundamentals
277
551 Discrete Fourier Series
278
552 DiscreteTime Fourier Transform DTFT
279
553 Discrete Fourier Transform
280
554 Circular Convolution
287
555 Synopsis
291
562 The Sampling Theorem
293
563 Aliasing
294
564 Sample and Hold
295
565 Zeroorder Hold
296
566 Decimation
300
568 Decimation Interpolation
301
IIR and FIR
307
573 Design of Digital Filters
311
574 Design ofIIR Filters
315
575 Design of FIR Filters
320
References
327
58 Harmonic Filtering
328
582 Specification Analysis
329
583 Filter Design
330
584 Harmonic Filtering of the Signal
333
References
334
59 Digital Fault Recorder and Disturbance Analysis
335
593 Digital Recording Equipments
336
594 Digital Fault Recorder
337
595 Disturbance Analysis Using DFR Data
339
References
347
5102 FFTbased Harmonic Analysis
348
5104 Frequency Estimation
349
5112 Phasor Estimation
351
512 Digital Relaying
352
513 Research Information
353
5133 Disturbance Fault Analysis
354
5134 Power Systems Protection
355
5136 Transient Analysis
356
5137 Phasor Measurement and Analysis
357
5138 Frequency Measurement Control
358
5139 Harmonic Analysis
359
51310 Power Systems Equipments Control
360
51311 Power Systems Operation
361
51312 Power Quality
362
51313 Load Flow
363
51316 State Estimation
364
51319 Power Management
365
51323 Rotating Machines
366
51324 Power Electronics
367
Index
369
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