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E-raamat: Modeling and Simulation of Complex Power Systems

(RWTH Aachen University, Institute for Automation of Complex Power Systems, Germany), (RWTH-Aachen, Germany)
  • Formaat: EPUB+DRM
  • Sari: Energy Engineering
  • Ilmumisaeg: 24-Aug-2022
  • Kirjastus: Institution of Engineering and Technology
  • Keel: eng
  • ISBN-13: 9781785614057
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Modeling and Simulation of Complex Power SystemsSuurem pilt
  • Formaat: EPUB+DRM
  • Sari: Energy Engineering
  • Ilmumisaeg: 24-Aug-2022
  • Kirjastus: Institution of Engineering and Technology
  • Keel: eng
  • ISBN-13: 9781785614057
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Modern power systems are highly complex due to increasing shares of intermittent renewable energy and distributed generation. Research requires computer simulation and modeling, and knowledge of methods and algorithms.



This book presents key concepts of modeling and simulation of power systems. The book introduces the two main families of techniques for computer-based simulation of dynamic systems, and methods that allow parallel simulation execution. The coverage includes digital simulation, topological methods, state space methods, parallelization methods, simulation under uncertainty, phasor simulation, switching systems simulation as well as real-time simulation and hardware in the loop testing. Examples, exercises and a set of simulation solvers implemented in Matlab® and Python are also provided.



Modeling and Simulation of Complex Power Systems is an invaluable tool for researchers in industry and academia, and advanced students.
About the authors xv
Additional contributors xvii
1 Introduction
1(4)
Antonello Monti
Andrea Benigni
1.1 The structure of the book
2(1)
1.2 How to use the book
3(2)
Supplementary material
4(1)
2 Digital simulation
5(16)
Andrea Benigni
2.1 Euler forward method
7(1)
2.2 Backward Euler method
8(4)
2.3 Trapezoidal rule method
12(1)
2.4 Predictor and corrector method
13(1)
2.5 Runge-Kutta methods
13(3)
2.6 Adams-Bashforth and Adams-Moulton methods
16(2)
2.7 Accuracy comparison
18(3)
Exercises
18(2)
References
20(1)
3 Nodal methods
21(42)
Antonello Monti
Andrea Benigni
3.1 Nodal analysis
23(2)
3.2 Matrix stamp
25(3)
3.2.1 Resistor
25(1)
3.2.2 Ideal current source
26(1)
3.2.3 Real current source
26(1)
3.2.4 Real voltage source
27(1)
3.3 Modified nodal analysis
28(4)
3.4 Resistive companion
32(12)
3.4.1 Resistive companion solution flow
33(3)
3.4.2 Inductor and capacitor in resistive companion
36(8)
3.5 Numerical methods for the solution of linear systems
44(3)
3.5.1 Gaussian elimination
44(3)
3.6 Controlled sources
47(16)
3.6.1 VCCS
47(1)
3.6.2 VCVS
48(1)
3.6.3 CCCS
49(1)
3.6.4 CCVS
50(8)
Exercises
58(4)
References
62(1)
4 State-space methods
63(32)
Andrea Benigni
Antonello Monti
4.1 State-space modeling
64(3)
4.2 Circuit modeling
67(5)
4.3 Discretization
72(3)
4.4 Automated state-space modeling
75(6)
4.5 Simulation of state-space model
81(1)
4.6 Signal flow solver
82(6)
4.7 From state-space to transfer function representation
88(7)
Exercises
90(4)
References
94(1)
5 Parallelization methods
95(40)
Andrea Benigni
5.1 Introduction
95(1)
5.2 Case study 1: parallelize the simulation of a ship power system
96(3)
5.3 Case study 2: parallelize the simulation of the IEEE 34 And IEEE 123 distribution network
99(2)
5.4 Diakoptics
101(9)
5.5 State-space nodal method (SSN)
110(1)
5.6 Transmission line modeling and the waveform relaxation-based method
111(2)
5.7 Latency insertion method
113(11)
5.7.1 Latency insertion method for power electronics simulation
117(3)
5.7.2 Latency insertion method combined with state space and nodal methods
120(4)
5.8 LB-LMC method
124(4)
5.9 Exercises
128(7)
References
130(5)
6 Simulation under uncertainty
135(34)
Matthew Milton
Andrea Benigni
Antonello Monti
6.1 Introduction
135(1)
6.2 Case studies
136(7)
6.2.1 Case study 1: ship system analysis under uncertainty
136(4)
6.2.2 Uncertainty sources in the simulation of distribution networks
140(3)
6.3 Uncertainty and statistics
143(3)
6.4 Monte Carlo
146(8)
6.4.1 Theory
147(4)
6.4.2 Computation of Monte Carlo simulations
151(2)
6.4.3 QMC
153(1)
6.5 Polynomial chaos
154(8)
6.5.1 Theory
155(2)
6.5.2 Statistical moments
157(1)
6.5.3 Inner product calculation
157(1)
6.5.4 Basic algebra using polynomial chaos
158(4)
6.6 Non-intrusive polynomial chaos
162(2)
6.6.1 Definition of collocation points
162(1)
6.6.2 Evaluation
162(1)
6.6.3 Expansion coefficients of the target variable
163(1)
6.7 Exercises
164(5)
References
167(2)
7 Simulation language specification--Modelica
169(26)
Jan Dinkelbach
Markus Mirz
Antonello Monti
Andrea Benigni
7.1 Example 1: Simulation of electrical and thermal components considering the impact of a building heating system on the voltage level in a distribution grid
169(1)
7.2 Example 2: Static voltage assessment of a distribution grid with high penetration of photovoltaics
170(3)
7.3 Example 3: Transient characteristics of synchronous generator models
173(2)
7.4 Example 4: Simulation of electrical and mechanical components considering the start of an asynchronous induction machine
175(1)
7.5 Introduction to Modelica
176(1)
7.6 Fundamentals of the Modelica language
177(1)
7.7 Hello World using Modelica
177(2)
7.8 Electrical component modeling by equations
179(1)
7.9 Object-oriented modeling by inheritance
180(1)
7.10 System modeling by composition
181(2)
7.11 Hybrid modeling
183(2)
7.12 Further modeling formalisms
185(1)
7.13 Implementation and execution of Modelica
186(1)
7.14 Exercises
186(2)
7.14.1 Task 1
186(1)
7.14.2 Task 2
187(1)
7.15 Exercises--solutions
188(7)
7.15.1 Task 1--solution
188(2)
7.15.2 Task 2--solution
190(2)
References
192(3)
8 Dynamic phasors
195(26)
Jan Dinkelbach
Markus Mirz
Antonello Monti
8.1 Simulation examples
195(3)
8.1.1 Synchronous generator three-phase fault
195(1)
8.1.2 Grid simulation using diakoptics
196(2)
8.2 Introduction
198(1)
8.3 Comparison to electromechanical simulation
198(1)
8.4 Bandpass signals and baseband representation
199(2)
8.5 Extracting dynamic phasors from real signals
201(2)
8.6 Modeling dynamic systems using dynamic phasors
203(1)
8.7 Dynamic phasor power system component models
204(1)
8.7.1 Inductance model
204(1)
8.7.2 Capacitance model
204(1)
8.8 Dynamic phasors and resistive companion models
204(2)
8.8.1 Inductance model
205(1)
8.8.2 Capacitance model
206(1)
8.9 Resistive companion simulation example
206(3)
8.10 Accuracy
209(4)
8.11 DP and EMT accuracy simulation example
213(2)
8.12 Summary
215(6)
References
219(2)
9 Modeling of converters as switching circuits
221(22)
Ferdinanda Ponci
Antonello Monti
9.1 Simulation of power electronics systems
221(2)
9.2 Role of power electronics in power systems
223(2)
9.3 Modelling and simulation of power electronics in power systems
225(1)
9.4 Converter models
225(1)
9.5 Averaged models
226(1)
9.6 Averaged circuits
226(2)
9.7 Averaged switching elements
228(2)
9.7.1 Linearization
229(1)
9.7.2 Considerations on the averaged models
230(1)
9.8 State-space models
230(6)
9.8.1 Continuous time models
231(3)
9.8.2 Discrete time models
234(1)
9.8.3 Generalized state-space models
234(1)
9.8.4 Linearization of state-space models
234(2)
9.9 Implementing a switch
236(2)
9.9.1 Ideal switch
236(1)
9.9.2 Switching of parameter value
236(1)
9.9.3 Switching of companion source
237(1)
9.10 Resistive companion model of converters
238(5)
Problems
241(1)
References
242(1)
10 Real-time and hardware-in-the-Ioop simulation
243(28)
Christian Dufour
Jean Belanger
10.1 Introduction
243(1)
10.2 Model-based design and real-time simulation
244(2)
10.3 General considerations about real-time simulation
246(8)
10.3.1 The constraint of real-time
246(1)
10.3.2 Stiffness issues
246(1)
10.3.3 Simulator bandwidth considerations
247(1)
10.3.4 Achieving very low latency for HIL application
247(1)
10.3.5 Effective parallel processing for fast EMT simulation
248(2)
10.3.6 FPGA-based multi-rate simulators
250(1)
10.3.7 Advanced parallel solvers without artificial delays or stublines: application to active distribution networks
251(2)
10.3.8 The need for iterations in real-time
253(1)
10.4 Phasor-mode real-time simulation
254(1)
10.5 Modem RTS requirements
255(3)
10.5.1 Simulator I/O requirements
256(2)
10.6 Rapid control prototyping and HIL testing
258(1)
10.7 Power grids real-time simulation applications
258(6)
10.7.1 Statistical protection system study
258(2)
10.7.2 Monte Carlo tests for power grid switching surge system studies
260(2)
10.7.3 Multi-level modular converter in HVDC applications
262(1)
10.7.4 High-end super-large power grid simulations
263(1)
10.8 Motor drive and FPGA-based real-time simulation applications
264(4)
10.8.1 Industrial motor drive design and testing using CPU models
264(2)
10.8.2 FPGA modeling of SRM and PMSM motor drives
266(2)
10.9 Conclusion
268(3)
References
268(3)
11 Octsim/a solver for dynamic system simulation
271(24)
Antonello Monti
Nika Khosravi
Martina Josevski
Zhiyu Pan
11.1 Introduction
271(1)
11.2 Solver description
272(1)
11.3 Solver structure
272(2)
11.4 Solver functionalities
274(1)
11.5 Solver implementation and validatlbn
275(9)
11.5.1 Implementation details
275(2)
11.5.2 Comparison with Simulink
277(3)
11.5.3 Octsim code examples
280(1)
11.5.4 Control system simulation
280(3)
11.5.5 Electric circuit simulation
283(1)
11.6 Example for hybrid system (buck converter with voltage control)
284(3)
11.7 Conclusion
287(1)
11.8 User manual
288(7)
References 295(2)
Index 297
Antonello Monti is the professor-director at the Institute for Automation of Complex Power Systems, RWTH Aachen University, Germany. Prior to this, he worked at the University of South Carolina (USA), where he was associate director of the Virtual Test Bed (VTB) project on computational simulation and visualisation of modern power distribution. Since 2019 he has also a joined appointment at Fraunhofer FIT as part of the Center for Digital Energy Aachen.



Andrea Benigni is a full professor at RWTH-Aachen and director of the Institute of Energy and Climate Research: Energy Systems Engineering (IEK-10) at the Juelich research center, Germany. He received the B.Sc. and M.Sc. degrees from Politecnico di Milano, Milano and the Ph.D. degree from RWTH-Aachen University, Aachen, Germany. From 2014 to 2019, he was an Assistant Professor with the Department of Electrical Engineering, University of South Carolina, Columbia, SC, USA.
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