Workshop: PowerFactory Applications for Power System Analysis. Kasetsart University 0.3.04.2015

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Prof Francisco M. Gonzalez-Longatt PhD | [email protected] | Copyright © 2015 1/132

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Agenda• Introduction

• Experience and Wisdom

• Foreword

• Book Structure• Book Chapters – General Overview

• Closure

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This section presents a general overview about “The Book”

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Introduction (1/2)• The complexity of power-system analysis has grown significantly along with

the fast development of renewable energy resources in recent years.

• It is required of taking advantage of the powerful computers and sophisticated simulation packages like DigSILENT PowerFactory for modelling and simulation purposes.

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Introduction (2/2)• There is a lack of knowledge on practical/theoretical principles regarding

"how to" apply modern power systems software in power system analysis.

• This book presents a comprehensive set of guidelines and applications of DIgSILENT PowerFactory for different types of power systems studies.

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This Section shows how the experience and wisdom of several people is contained in The Book”

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Experience and Wisdom• This book combines years of technical/practical experience of more than 50

experts users/developers of DigSILENT PowerFactory (>50 countries) anddeep understanding of academic on power system analysis.

Dr. Jose Luis RuedaEditor

Dr. F. Gonzalez-LongattEditor

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This Section presents the key aspects of the foreword.

It is written by Dr. M. Schmieg Dr.-Ing. Martin Schmieg Managing Director bei

DIgSILENT GmbH Stuttgart Und Umgebung Deutschland

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Foreword• In 1987, the Kraftwerke Mainz-Wiesbaden, Germany (KMW AG), became

the first official and registered user of the DIgSILENT software.

• The fact that after some 27 years, KMW AG’s PowerFactory installations are still maintained is a definite indicator that any possible initial doubt was unwarranted.

• In fact, over the past several years, the user base has grown considerably, establishing a large user community of highly qualified, experienced and creative users.

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Foreword• It has been the intention of the PowerFactory developers from the very

beginning to provide a highly flexible power system analysis tool applicable to practically all areas of power generation, transmission, distribution and industry.

• Since late 1990, renewable generation based on wind and photovoltaics, along with new HVDC transmission technologies, has driven a new and fast-growing sector whose simulation needs include complex, non-traditional applications.

• In addition, the integration of power system analysis tasks with asset management systems and online applications (GIS, SCADA) as well as closed-loop applications (especially in Smart Grids) has increased the demand for flexible process signal interfaces and bidirectional data exchange capabilities.

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Foreword• PowerFactory extends this flexibility even further via the provision of

powerful scripting tools allowing the user to develop specific applications according to individual needs.

• This first issue of the PowerFactory Applications for Power System Analysis serves as an impressive demonstration of the wide range of power system analysis applications that can be handled by the PowerFactory software.

• In addition, the solutions described for a certain analysis task will motivate and help other users to make use of the software’s flexibility and give guidance regarding possible solution options.

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Foreword• “We thank all authors who have contributed to this book, initiated by Francisco

Gonzalez-Longatt and José Luis Rueda, for sharing their valuablePowerFactory experiences and solutions”.

• The topics presented are also of great interest to the PowerFactory development team in their endeavours to optimize further releases and develop even more flexible functions.

Dr.-Ing. Martin Schmieg Managing Director bei

DIgSILENT GmbH Stuttgart Und Umgebung Deutschland

August 2014

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Book Structure (1/2)

Quasi-Dynamic Simulation

Simulation Unsymmetrical Conditions and Contingency

Analysis

Chapter 1

Chapter 2

Chapter 3

Probabilistic load flow

Chapter 4

Unbalanced Power Flow

Chapter 5

Optimal Power Flow

Chapter 6

Assessing the Renewable Energy Sources

Integration

Modelling of AGC

Chapter 7

CCGTModelling

Chapter 8

DFIG Modelling

Chapter 9

Parameterized Modal Analysis

Chapter 10

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Book Structure (2/2)

Risk Assessment

Mean–Variance Mapping Optimization

Chapter 11

Chapter 12

Chapter 13

MATLAB/Simulink Interface

Chapter 14

Simulation Automation and Management

Chapter 15

Hardware‐in‐the‐Loop Applications

Chapter 16

Hardware in Hardware‐In‐Loop

P & Q in Wind Farm

Chapter 17

FACTS Modelling

Chapter 18

Multi‐terminalHVDC

Chapter 19

Cluster of Induction Generator

Chapter 20

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Centre d’Innovació Tecnològica en Convertidors Estàtics i Accionaments, Departament d’Enginyeria ElèctricaUniversitat Politècnica de CatalunyaBarcelona, Spaine-mail: [email protected] Quasi-Dynamic

Simulation

Chapter 1

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Chapter 1• This chapter demonstrates the application of load flow analysis using

electrical power system planning software.

•

• Description about the load flow command and different components availablein PowerFactory for modelling are given, and how to model the power systemnetwork is explained.

• Furthermore, project planning principle is explained through three casestudies.

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Chapter 1• In first case

study, network topology for low-voltage network is explained and how to select the network component to fulfil the network constraints is demonstrated.

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Chapter 1• In second case study, medium-voltage network is developed and different

power control options are demonstrated to determine the power and voltageoperating point of the sources.

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Chapter 1• In addition, method of controlling reactive power flow and frequency variation

due to imbalance in power have been simulated.

• In third case study, application of a load profiling has been developed for low-voltage distribution network.

• In this study, variation of the load throughout a year has been analysed.

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J.M. Roldan-FernandezEscuela Superior de IngenieríaUniversidad de Sevilla20134 Sevilla, Spaine-mail: [email protected]

Simulation Unsymmetrical Conditions and Contingency

Analysis

Chapter 2

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Chapter 2• DIgSILENT PowerFactory is a powerful software which includes a power

system analysis function designed to cope with large power system powerflows, and it handles both DC and AC lines, including all phase combinations(3ph,2ph and single phase), with/without neutral conductor and groundwires, for both single circuit and mutually coupled parallel circuits.

• Although power systems are designed and normally operated in balanced(symmetrical) three-phase sinusoidal conditions, there are certain situations thatcan cause undesired conditions, namely the unbalanced conditions.

• Uneven distribution of single-phase loads is one of the main unbalancedconditions in distribution level.

• The objective of this chapter is to provide an extensive review of the mainfeatures of steady-state analysis which are included in PowerFactory.

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Chapter 2• Steady-state analysis in PowerFactory covers the normal operation (ComLdf)

and the contingency analysis (ComSimoutage).

• This chapter has been divided into three distinct parts. The first part presents the main features of modelling overhead transmission lines (ElmTow, TypTow, TypGeo).

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Chapter 2• Steady-state analysis in PowerFactory covers the normal operation (ComLdf)

and the contingency analysis (ComSimoutage).

• This chapter has been divided into three distinct parts. The first part presents the main features of modelling overhead transmission lines (ElmTow, TypTow, TypGeo).

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Chapter 2• Secondly, power flow analysis

(ComLfd) under unbalanced conditions is illustrated.

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Chapter 2

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Chapter 2

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Chapter 2• The third part of this chapter deals with the

security assessment or contingency analysis for single time-phase contingency analysis.

• The deterministic assessment of failureeffects under contingencies within a singleperiod (ComOutage, Com-Nmink,ComSimoutage) is also analysed.

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Chapter 2

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Chapter 2

CONTINGENCY: Line 5-7

Transmission lines modelled using ElmLne

This is the Paul M. Anderson 9-bus Test system [1]. It is the classical WSCC 3-machine, 9-bus

3-machines developed by EPRI Copyright 1967.

[1] P.M. Anderson and A.A. Fouad. "Power System Control and Stability". IEEE Press. 2002

Bus 9

230.61.0018.4

Bus 6225.70.981.0

Bus 8234.71.0214.9

Bus 5218.60.95-7.6

Bus 7234.11.0224.8

Bus 4230.21.00-1.9

Bus 314.11.0217.5

Bus 218.41.0230.3

Bus 117.21.040.1

fglongatt Load Flow

PowerFactory 15.0.1

P.M. Anderson Test System

Prof Francisco M. Gonzalez-Longatt PhD http://www.fglongatt.org [email protected]

Project:

Graphic: Grid

Date: 8/28/2014

Annex:

RMS-Simulation,balanced 01:59:99 min

Nodes

Line-Line Voltage, Magnitude [kV]

Voltage, Magnitude [p.u.]

Voltage, Angle [deg]

Branches

Active Power [MW]

Reactive Power [Mvar

Current, Magnitude [

Line 4-5129.1

-113.9-45.60.324

115.542.3

0.309Load A

113.945.6

0.324

T193.4

-65.7-66.50.234

65.771.5

3.268

G~

G139.2

65.771.5

3.268

G ~

G365.1

82.98.9

3.406

G~

G283.7

159.719.0

5.032

T381.4

-82.9-5.0

0.204

82.98.9

3.406

T2156.9

159.719.0

5.032

-159.7-3.6

0.394Load C

97.434.1

0.258

Line 6-9140.1

142.5-10.80.352

-134.98.2

0.346

Line 8-968.4

60.1-33.10.172

-59.615.8

0.152

Line 7-8157.1

159.73.6

0.394

-157.6-1.0

0.394

Line 5-70.00.0

-0.00.000

Line 5-70.0

0.0-0.0

0.000

Load B

84.528.2

0.228

Line 4-663.4

-49.824.1

0.139

50.4-36.40.159

DIg

SIL

EN

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Chapter 2• Final contribution of this chapter is a set of time domain simulations (rms)

demonstrating the effect of the contingencies.

• Also a DPL is included for calculation the frequency of inertia centre.

4.60193.66152.72121.78080.8404-0.1000 [s]

1.009

1.006

1.003

1.000

0.997

0.994

FrequencyOfInertiaCentre: Frequency of Inertia Centre in p.u.FrequencyOfInertiaCentre: Frequency, G2 in p.u.

FrequencyOfInertiaCentre: Frequency, G1 in p.u.

FrequencyOfInertiaCentre: Frequency, G3 in p.u.

0.362 s 1.006

0.462 s 1.002

4.60193.66152.72121.78080.8404-0.1000 [s]

210.00

180.00

150.00

120.00

90.00

60.00

Line 7-8: Loading in %

0.452 s199.274 %

0.005 s101.750 %

fglongatt PowerFactory Applications for Power System Analysis FOIC

Frequency of Inertia Centre and Line Loading Single Contingency

Date: 8/28/2014

Annex: 1 /2

DIg

SIL

EN

T

Frequency of Inertia Centre: Frame

Frequency of Inertia Centre Calculation - FRAMEDeveloped by Dr Francisco M. Gonzalez-Longatt

28 August 2014

FeqDSLElmDsl*

0

1

2

Freq G1ElmPhi*

cosPhi

sinPhi

0

1

2

Freq G3ElmPhi*

cosPhi

sinPhi

0

1

2

Freq G2ElmPhi*

cosPhi

sinPhi

0

1

2

Frequency of Inertia Centre: Frame

feq

f30

f20

f10

DIg

SIL

EN

T

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S. Teimourzadeh B. Mohammadi-Ivatloo (&)

Faculty of Electrical and Computer Engineering, University of Tabriz,

29 Bahman Blvd, Tabriz, Iran

e-mail: [email protected]

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Chapter 3• Electric power system could be known as the most complex, large-scale

human-built assembly.

• Power system engineers are deal with several challenging problems such aspower system operating, planning, and protection.

• Different types of studies should be carried out in order to handle differentproblems of power system.

• However, like many other engineering endeavours, future operating conditions,and operating criteria could not be predicted with certainty.

• Load increment, generation scheduling, and power system topology aremost uncertain conditions in which power system engineers are deal withthem.

• Therefore, in order to drive a reliable system, along with deterministic studies,probabilistic studies should be carried out.

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Chapter 3• In most of the computer packages such as DIgSILENT PowerFactory and

PSSE/PTI, deterministic analysis tools such as deterministic power flow(DLF) are available.

• However, probabilistic characteristic of these studies is not included in thesoftware.

• In this chapter, a probabilistic power flow (PLF) analysis module forDIgSILENT PowerFactory is proposed.

• The proposed module is implemented using DPL.

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Chapter 3• Two different PLF analysis methods are incorporated in the proposed module

including.

• Monte Carlo simulation and point estimate method.

• The user can select the desired algorithm for PLF analysis.

• A line-by-line explanation is provided for the written DPL code.

• The application of the proposed module is investigated using illustrativeexample incorporating IEEE 14-bus standard test system.

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Chapter 3• The main contribution of this

Chapter in creating two DPL script for probabilistic load flow.

• Classic Monte Carlo simulation

• Point estimate method.

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P.M. De Oliveira-De Jesus A.A. Rojas Q

Conversion and Energy Delivery Department, Simon Bolivar University,

AP. 89000, Caracas, Venezuela


Chapter 4Unbalanced Power Flow Analysis in Distribution Systems Using TRX Matrix: Implementation Using DIgSILENTProgramming LanguagePaulo M. De Oliveira-De Jesus, Andres A. Rojas Qand Francisco M. Gonzalez-Longatt

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Chapter 4• In this chapter, a generalized model to solve multigrounded distribution

networks under DIgSILENT platform taking into account current flows andvoltages across neutral and ground paths is presented.

• The fundamental idea developed in this work is solving the 5-wire power flowproblem using a unique matrix called TRX that includes all feedercharacteristics related to phase, neutral, and equivalent ground paths.

• Proposed power flow routines are run from MATLAB engine usingDIgSILENT databases.

• The method is suitable to be applied on unbalanced aerial and undergrounddistribution systems with distributed generation.

• Proposed methodology has been successfully applied in an illustrative testsystem.

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Chapter 4• One of the contribution of this chapter is interfacing PowerFactory and Matlab

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V. Hinojosa-Mateus L. Pérez-Andrades

Department of Electrical Engineering, Universidad Técnica Federico Santa María,

Valparaíso, Avenida España 1680, Valparaíso, Chile


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Chapter 5• This research presents an application of different formulations to solve the DC

optimal power flow problem.

• The classical DC optimization problem is reformulated using the powertransmission distribution factors (PTDF).

• The main advantage of this formulation is the reduction of the decisionvariables in the optimization problem.

• In this chapter, the interior-point algorithm to solve the DC optimizationproblem is programmed using DIgSILENT Programming Language (DPL).

• In order to evaluate and compare the solution obtained by the algorithm, thesimulations results are validated using MatPower.

• The proposed formulation has been implemented and validated with differenttest power systems.

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Chapter 5• The results of the proposed algorithm demonstrate both the feasibility of

applying the methodology to the DC optimal power flow problem and thepotential applicability of the approach in medium- and large-scale powersystems.

• The simulations performed in this chapter validate the formulation proposed inthis study to solve the DCOPF problem.

• Finally, this application adds a new dimension to the DIgSILENT PowerFactory by allowing the creation of new optimization algorithms to solveoperation and planning problems.

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Chapter 5• One of the contribution of this Chapter is development of a complex DPL for

OPF using a very specific method.

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A.I. Nikolaidis C.A. Charalambous

Department of Electrical and Computer Engineering, University of Cyprus,

75 Kallipoleos Avenue, P.O. Box 20537, 1678 Nicosia, Cyprus


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Chapter 6• The increasing penetration of intermittent energy sources in existing power

systems heavily impacts the planning and operational processes of systemoperators.

• Therefore, refined approaches are required to address the techno economicissues introduced by the stochastic nature of renewable energy sources, in anattempt to harness the maximum benefit possible.

• To address these challenges, this work capitalizes on a set of technicalperformance indices.

• These indices are attempting to quantify some operational impacts byproviding an operational and/or long-term planning tool for assessing therenewable energy penetration in transmission networks.

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Chapter 6• The modelling and simulation case studies are facilitated within the powerful

grid simulator DIgSILENT which enables for fast and reliable execution of awide spectrum of computing procedures.

•

• In particular, this chapter showcases how DIgSILENT’s programminglanguage (DPL) is utilized to create several automated scenarios that mayexplore potential topologies of a test system as per the systems’ operators andplanners’ possible interests.

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Chapter 6• One of the contributions is a DPL.

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V. Pavlovsky A. Steliuk

DMCC Engineering Ltd., Peremogy Ave, 56, Kiev 03056, Ukraine


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Chapter 7• Frequency stability and active power control is one of the principle tasks of

improving the security and reliability of power system operation.

• The chapter covers the various aspects of simulation of frequency control inpower systems.

• The chapter is divided into three parts. In the first part, the elements of thefrequency control are considered and main equations are presented.

• In the second part, PowerFactory software model of automatic generationcontrol (AGC) is considered.

• In the third part, the results of load flow and transient simulation are presented.

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Chapter 7• In the first part, the elements of the frequency control are considered and main

equations are presented.

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Chapter 7

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Chapter 7

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Chapter 7

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Chapter 7

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L. Meegahapola

School of Electrical, Computer and Telecommunications Engineering, Faculty of Engineering and Information Sciences, University of Wollongong, Northfields Avenue,

Wollongong 2500, Australia


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Chapter 8• response characteristics, as compared to other conventional (synchronous)

generation technologies, which can significantly influence power systemdynamics and stability during disturbances in the network.

• Many power systems are seeing increasing penetrations of combined cycle gasturbines (CCGTs), along with variable renewables, such as wind and solargeneration, so an improved understanding of gas turbine characteristicsduring high- and low-frequency events and network faults is required inorder to mitigate potential adverse system impacts.

• In particular, the impact of ambient conditions on unit rating, the temperaturecontrol system, gas turbine compressor intake, and associated components suchas inlet guide vanes (IGVs) must be accurately modelled, particularly whenoperating at high output, in order to accurately assess the impact of CCGTs onstability issues.

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Chapter 8• Therefore, this chapter aims to provide a comprehensive guide to developing a

CCGT model using the DIgSILENT dynamic simulation language (DSL),including model initialisation. In addition, modelling of an open cycle gasturbine (OCGT) will be presented.

• Finally, a dynamic comparison of the CCGT and OCGT models will beexamined using a demonstration test system.

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Chapter 8

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Chapter 8• The speed governor and combustor system

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Chapter 8• The exhaust temperature measurement and control system

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Chapter 8• The VIGV and airflow control system

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Chapter 8• The steam turbine model

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Chapter 8

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J.L. Rueda

Department of Electrical Sustainable Energy, Delft University of Technology,

Mekelweg 4, 2628 CD Delft, The Netherlands


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Chapter 9• Due to its variable nature, the increasing penetration of wind power plants into

power systems poses new challenges for reliable and secure operation.

• Considering that model-based time-domain simulation constitutes a widely usedapproach for assessing the power system dynamic performance as well as formaking proper decisions concerning operational and planning securitystrategies, there has been a great research effort, especially in the last decade, tocover different issues on modelling of wind generation systems (WGS).

• Remarkably, the development of models that entail a compromise betweenaccuracy and simplicity is one of the main concerns for enabling thesimulation of large-scale systems.

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Chapter 9• This chapter addresses the implementation of two simplified models of WGs by

using the functionalities of DIgSILENT simulation language (DSL).

• The first model is the reduced third-order model of the doubly fed inductiongenerator (DFIG), for which suitable models for multiple point tracking, therotor-side controller (RSC), current controller, and speed and pitch controllerare adopted.

• The second model constitutes a generic equivalent model, which can be usedfor representation of the stationary and dynamic response of wind power plantscomprising several DFIGs.

• RMS-type simulation results are presented to illustrate the suitability of theadopted modelling approaches.

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S. Pizarro-Gálvez

SYSTEP Ingeniería y Diseños, Las Condes, 7550171 Santiago, Chile


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Chapter 10• A parameterized modal analysis is proposed to evaluate power system

small-signal stability and a simulation procedure using DIgSILENTprogramming language (DPL) is presented for this purpose.

• Modal analysis, or small-signal stability analysis, refers to the ability of asystem to withstand small perturbations around an equilibrium point withoutreaching instability or displaying sustained oscillations.

• This is an important problem in real systems as sustained oscillations may causemechanical failures in generating units and make the system vulnerable to thepoint of losing stability.

• In order to define the most critical scenario, the standard approach employedby the industry is to consider the system at its maximum loading.

• This chapter proposes that critical scenarios should be further sought as in evenlighter loading conditions, low-frequency oscillations may dangerously appear.

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Chapter 10• Using DPL, the system modal analysis is parameterized in order to search for

critical operating points.

• To validate the importance of employing a parameterized modal analysis, a realcase is studied: the Northern Chile Interconnected System.

• The obtained results applying parameterized modal analysis show that thesystem in a real operation only requires minor deviations from the programmedoperating points to incur in dangerous low-frequency oscillations.

• These results validate the importance of searching for critical scenarios andDPL scripting is used to program the steps of the proposed analysis.

• The scripts and applications presented in this chapter set the basis for additionaldevelopment to identify critical scenarios for modal analysis in other realsystems.

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Chapter 10

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J.L. Rueda

Intelligent Electrical Power Systems, Department of Electrical Sustainable Energy,

Delft University of Technology, Mekelweg 4, 2628 CD Delft, The Netherlands


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Chapter 11• The use of probabilistic framework is of great importance for the

development of comprehensive approaches, which are suitable for coping withincreasing uncertainties in power system operation and planning.

• While huge effort has been put in the past into the conception of probabilisticmethods to deal with stochastic load flow calculation, there is an increasinginterest on the development of new approaches to ascertain theimplications of changing operating conditions in terms of power systemdynamic performance.

• Among the main concerns on this regard is the determination of the degree ofexposure to poorly damped low frequency oscillations (LFOs), which occurtypically in the range of 0.1–1.0 Hz.

• This chapter concerns the implementation of a Monte Carlo (MC)-basedapproach for evaluation of oscillatory instability risk by using thefunctionalities for modelling and programming of DIgSILENT PowerFactory.

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Chapter 11• Particularly, the DIgSILENT programming language (DPL) is used to

structure the steps of the MC repetitive procedure, namely sampling ofuncertain input variables, automated scenario generation, and storage of Eigenanalysis outcomes.

• The chapter also illustrates the implementation of the PST 16 benchmarksystem, which has a relative large size, and is appropriated to study differentkinds of stability problems, especially LFOs.

• Based on characteristic parameters of the European power systems, differentbuilt-in models available in DIgSILENT are used to model the systemcomponents.

• Numerical experiments performed on this system support the relevance of theMC-based approach.

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Chapter 11

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J.C. Cepeda

Corporación Centro Nacional de Control de Energía—CENACE,

Av. Atacazo and Panamericana Sur km 0, Quito, Ecuador


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Chapter 12• The development and application of heuristic optimization algorithms have

gained a renewed interest due to the limitations of classical optimization toolsfor tackling several hard-to-solve problems in different engineering fields.

• Due to the complex nature of power system dynamics, electrical engineeringoptimization problems usually present a discontinuous multimodal and non-convex landscape that necessarily has to be handled by heuristic optimizationalgorithms.

• While most of the pioneer heuristic optimization approaches, such as geneticalgorithms, particle swarm optimization, and differential evolution, areundergoing different types of modifications and extensions in order to improvetheir performance, great focus is also being put into the development of newapproaches aiming at conceptual simplicity, easy adaptability for a varietyof optimization-based applications, and outstanding performance.

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Chapter 12• The mean–variance mapping optimization (MVMO) is a recent contribution

to the family of evolutionary optimization algorithms.

• Its novel search mechanism performs within a normalized range of the searchspace for all optimization variables and follows a single parent–offspring pairapproach.

• Besides, MVMO is characterized by a continuously updated knowledge archivestoring the n-best solutions achieved so far, from which a special mappingfunction, which accounts for the mean and variance of the optimizationvariables, is applied for mutation operation.

• In this way, the algorithm proceeds by projecting randomly selected variablesonto the corresponding mapping function that guides the solution toward thebest set achieved so far.

• Despite the orientation on the best solution, the algorithm keeps on searchingglobally.

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Chapter 12• This chapter addresses key aspects concerning the implementation of MVMO

by using DIgSILENT programming language (DPL).

• An exemplary application on the coordinated tuning of power systemsupplementary damping controllers is presented and discussed in order tohighlight the feasibility and effectiveness of structuring MVMO-basedapplications in DIg- SILENT PowerFactory environment.

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Chapter 12

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S.K. Kerahroudi, M.M. Alamuti, G.A. Taylor.

Brunel Institute of Power Systems, BIPS, Brunel University, London, UK


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Chapter 13• Simulation tools are the most economical solution for modelling and design of

various components of large-scale power systems.

• However, as the complexity in the integrated electric power network grows, theneed for more comprehensive simulation tools rises.

• Modern simulation tools have therefore been developed in line with this everincreasing need by means of integration of improved user interfaces.

• Interfacing of the simulation tool to an external program/ mathematical toolextends the capability of the simulation tool in a more effective execution of thesimulation, particularly in an area where the external program/ algorithmprovides more advanced technique and flexibility, e.g. the advanced controlsystem design in MATLAB control toolbox.

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Chapter 13• This chapter describes the process of interfacing DIgSILENT PowerFactory to

MATLAB/Simulink program.

• Two study cases will be presented in this chapter. These study cases are set upand provided to allow the readers to understand the process and steps of linkingDIgSILENT PowerFactory to the MATLAB/Simulink program.

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M. Stifter, S. Kadam and B. Bletterie.

Energy Department, AIT Austrian Institute of Technology, Giefinggasse 2,

1210 Vienna, Austria


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Chapter 14• In this chapter, some principles of simulation automation are explained,

which are helpful for investigating a large number of simulation scenarios.

• Parameters of data models often need to be changed for a certain range orresults need to be post-processed.

• It is demonstrated how PowerFactory’s built-in scripting language is used toautomatically assign external profiles (characteristics) and how scriptparameters can be altered and the simulation controlled externally in batch styleprograms.

• An example project shows the implementation of a local voltage controller byutilising the scripting language.

• Simulation parameters are taken from Microsoft Excel for parametric studiesand results are stored back into the spreadsheet.

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Chapter 14

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Batch Simulations via RCOM• Batch Simulations via RCOM

• Until PowerFactory Version 14.x, the file folder ENGINE provided the so-called RCOM interface for sending control commands via remote procedure call.

• Since version 15.1 RCOM is no longer officially supported and it is recommended to use the Python/API functionality for this purpose.

RCOM command file for batch control of PowerFactory

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M. Stifter, F. Andrén, R. Schwalbe and W. Tremmel.

Energy Department, AIT Austrian Institute of Technology, Giefinggasse 2, 1210 Vienna,

Austria


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Chapter 15• Various possibilities exist to interface the power system model and simulation

engine of PowerFactory.

• These interfaces open applications for co-simulation, real-time simulation forcontroller hardware-in-the-loop (HIL) set-ups or automation and control ofsimulation.

• This chapter gives a comprehensive overview of the various interfacesPowerFactory provides—namely to MATLAB, external C++ functions,OPC, RCOM, API and DGS—as well as typical applications for their use.

• An example for connecting to an external controller for automated voltagecontrol of an on load tap changer using common TCP/IP connections iselaborated in detail.

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PF with other models and simulators• MATLAB: PowerFactory build-in interface (DSL) for co-simulation

• DLL: Using external DLL in DSL components (e.g.: TCP/IP sockets) and DPL scripts

• OPC: Industrial standard interface—OPC client—in use with multi-agent systems and controller hardware in the loop

• RCOM: Remote communication—remote procedure call interface for using

• PowerFactory in engine mode (e.g. automated simulation)

• API: Direct control of PowerFactory internal data model and advanced functionality (e.g. co-simulation)

• DGS: file format for exchanging data models and geographical information

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Overview of interfaces provided by PowerFactory

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MATLAB interface in PowerFactory

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DSL Functions Linked to External DLLs

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DPL Functions Linked to External DLLs• Similar to the external implemented DSL functions for dynamic/transient

analysis, the DPL interpreter can be extended by user-defined functions to be used for steady state analysis

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OPC—OLE for Process Communication• OPC server connects client processes which run normally in real time such as

automation and control components.

• External data link (ComLink) is a built-in OPC client.

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RCOM—Remote Procedure Call• Until version 14.x, the so-called ENGINE folder was part of the installation.

• RCOM is well suited for simulation automation since it is possible to change for instance DPL script parameters or other model attributes.

Java code snippet for connecting via RCOM

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API—Application Programming Interface• Basically, everything you can do in PowerFactory can be done via the API!!!

• It exposes internal model and objects of the network data as well as analysis functions and results to be dynamically linked into any C++ application environment.

Use of the API in a stand‐alone C++ application

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API Python• Since version 15.1, a Python wrapper for the API has been provided.

• Since Python is an interpreter based programming language no compiler is necessary to use the C++ API.

• Python scripts can be directly used within PowerFactory or used for running the application in engine mode and controlling it from an external application

Python code for activating and accessing PowerFactory

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Summary Interfaces for Co-simulation

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R. Srinivasan

Electrical Power Systems Engineer, Alstom Grid, Redmond, WA 98052, USA


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Chapter 16• Rapid prototyping and validation of power system controllers have always

been a challenge.

• With a rapid increase in distributed energy resources (DERs) and power-electronics-based power system devices, the systems that control today’selectrical grid infrastructure are set to become more complex than ever,especially on the distribution front.

• Thus, rapid prototyping and validation of new complex control systemsrequire testing with extensive set of test cases involving a multitude of powersystem components.

• The numerous types of variable involved, such as topology, energy flow, faultconditions, autonomous control systems, and protective device operation, mostof which are stochastic in nature, naturally compound the problem ofprototyping and validation.

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Chapter 16• In such a scenario, using a hardware-in-loop (HIL) to test all possible test

conditions is quite unrealistic.

• This chapter is about introducing DIgSILENT’s PowerFactory as a goodsoftware stand-in for Power Systems in HIL testing.

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J.C. Cepeda (&)

Research and Development Department, Corporación Centro Nacional de Control

de Energía—CENACE, Av. Atacazo and Panamericana Sur km 0, Quito, Ecuador

e-mail: [email protected]; [email protected]

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Chapter 17• An electric power system (EPS) must meet certain requirements that allow a

continuous supply of demand at minimum cost and with the least environmentalimpact.

• For this purpose, several system controllers, such as the flexible alternatingcurrent transmission system (FACTS) devices, might be integrated into thegrid, and so they should be included as part of the power system modelling insimulation programs.

• The addition of a new device in the transmission grid requires several studiesthat consider the analysis of the system for a wide variety of normal andstressed operating conditions, including maintenance situations.

• Thus, the integration of FACTS devices in the transmission network requiresthe development of static studies and dynamic analysis concerning stabilitysimulation.

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Chapter 17• These types of studies are important for proper system planning and operation.

• Although DIgSILENT PowerFactory has several dynamic models to representto a number of power system components, its model library does not include asufficient variety of dynamic models of FACTS devices.

• Only the model of the static var system (SVS) is already included in its library.

• However, in addition to typical functions for power system analysis,DIgSILENT PowerFactory offers versatility to model new components using itsprogramming language DIgSILENT simulation language (DSL).

• The present chapter describes the methodology for including the followingmodels of FACTS devices into DIgSILENT PowerFactory: thyristorcontrolled series compensator (TCSC), static series synchronouscompensator (SSSC), static synchronous compensator (STATCOM) andunified power flow controller (UPFC).

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Chapter 17• Additionally, power oscillation damper (POD) is also incorporated into the

models in order to improve oscillatory conditions.

• The models that will be described correspond to the so-called simplifiedmodels that are designed to be used in stability studies of EPSs (i.e.electromechanical transients).

• Finally, simulations are performed in a test power system that show thedynamic behaviour of the implemented FACTS devices and allow theircorresponding validation.

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Chapter 17• Stage 1: DSL programming

• Stage 2: Model initialization

• Stage 3: Linking the outputs of FACTS controllers to physical grid objects

• Stage 4: Interfacing controllers and active grid objects

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Chapter 17DSL implementation of TCSC: a TCSC controller, b POD controller, c TCSC composite frame

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M. Qian, D. Zhao,D. Jiang and L. Zhu.

Renewable Energy Department, China Electric Power Research Institute, Nanjing, China

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Chapter 18• The integration of large-capacity wind energies into a power system creates big

challenges to the power system operation and control due to the intrinsicintermittence of wind energies, which constrains further developments of windpower generation.

• Countries around the world including Europe, USA and China have all madeGrid Codes with clear requirements on active and reactive power controls in awind farm.

• By effective active and reactive power controls, wind power curtailments canbe substantially reduced.

• Furthermore, there have been no mature simulation and analysis platforms inChina on testing correctness and rationality of wind farm control strategies sofar.

• This chapter reports our research as well as engineering practices on building anintegrated active and reactive power control system for wind farms usingPowerFactory and MATLAB.

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Chapter 18• The highlights that make this work unique are as follows:

• (i) the integration of PowerFactory and MATLAB makes the active andreactive power control modelling efficient and flexible;

• (ii) both the real measurements of wind speeds and the active powerforecasted from history data are inputted in text file format to each windgenerator in PowerFactory;

• (iii) the reactive power control capabilities of wind generators are fully utilizedto reduce the scale of the reactive power compensations installed in a wind farmor from the grid.

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Requirements on P and Q Control of Wind Farms in China• Control modes on active power

• Limit mode• Balance mode • Delta mode

• Control modes on reactive power• Voltage control mode• Reactive power control mode• Power factor control mode

DFIG Model structure based on controlled current source interface

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Chapter 18

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Chapter 18

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Chapter 18

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Chapter 18

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F.M. Gonzalez-Longatt

School of Electronic, Electrical and Systems Engineering, Loughborough University,

LE11 3TU Loughborough, UK


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Chapter 19• The North Sea has a vast potential for renewable energy generation: offshore

wind power, tidal and wave energy.• The voltage source converter (VSC) and high voltage direct current

(HVDC) systems are more flexible than their AC counterparts.• This offers distinct advantages for integrating offshore wind farms to inland

grid system.• It seems that advances on technologies open the door for VSCHVDC systems at

higher voltage and at higher power range, which is making multi-terminalHVDC (MTDC) system technically feasible.

• The control system for MTDC consists of a central master controller and localterminal controllers at the site of each converter station.

• The terminal controllers (outer controllers) are mainly responsible for activepower control, reactive power control, DC voltage regulation and AC voltageregulation.

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Chapter 19• Typical MTDC consists of several VSC-HVDC terminals connected together,

and different operation mode and controllers allows them interact together.• DC voltage controllers play a very important role on the DC network

performance.• There are several DC voltage control strategies possible: voltage margin, two-

stage direct voltage controller, three-stage direct voltage controller, voltagedroop, etc.

• The contribution of this book’s chapter is to present some of the main aspectsregarding the modelling and simulation of two control strategies: voltagemargin method (VMM) and standard voltage droop (SVD).

• To this end, theoretical aspects of controllers are presented and are used todevelop DIgSILENT simulation language (DSL) models.

• The developed models are used to evaluate the performance a simple 3-terminalHVDC system.

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Chapter 19

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Chapter 19

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F.M. Gonzalez-Longatt

School of Electronic, Electrical and Systems Engineering, Loughborough University,

Loughborough LE11 3TU, UK


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Chapter 20• The induction generator (IG) is widely used in many applications due to its

simplicity and ease of operation.• Typical applications involve the following: split-shaft micro-turbines

(SSMT), mini-hydro (MH), and fixed-speed wind turbines (FSWT).• The accurate knowledge of the machine parameters is especially important in

order to establish the performance of the IG as well as to directly affect itsoperational and control characteristics.

• The problem of IG parameter estimation results specially complicated to solvewhen a cluster of IG is interconnected to create of virtual power plant (VPP).

• Then, it is desirable to have an effective method to estimate the parameters ofan equivalent model for a cluster of IG (which does not require detaileddefinition of the power plant structure and parameters) by using novel digitalmeasurement equipment such as phasor measurement units (PMU) intransmission and distribution networks.

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Chapter 20• This chapter presents a method for the estimation of an equivalent mode

(named as EqMCIG App) for a cluster of IG, based on the response to a systemfrequency disturbance.

• The performance and robustness of the method are evaluated using twodifferent test systems where the EqMCIG is identified using the variablemetric method (VMM).

• Numerical results demonstrate the viewpoint and effectiveness of the proposedmethodology.

• This chapter have three main contributions: (i) Performing “parameterestimation” using ComIdent command (ii) The use of DSL model on modelparameter identification (composite Frame, block definition—BlkDef) (iii) Useof a “Measurement File” object (ElmFile) as inputs variables.

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Chapter 20

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Chapter 20

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Chapter 20

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Chapter 20

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Book’s Website

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New Forum

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Closure

There are so many things to do…

Planning and Operating Smart Grid

Next step…

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