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IET ENERGY ENGINEERING 147
Distribution Systems
Analysis and Automation

Other volumes in this series:
Volume 1 Power Circuit Breaker Theory and Design C.H. Flurscheim (Editor)
Volume 4 Industrial Microwave Heating A.C. Metaxas and R.J. Meredith
Volume 7 Insulators for High Voltages J.S.T. Looms
Volume 8 Variable Frequency AC Motor Drive Systems D. Finney
Volume 10 SF6 Switchgear H.M. Ryan and G.R. Jones
Volume 11 Conduction and Induction Heating E.J. Davies
Volume 13 Statistical Techniques for High Voltage Engineering W. Hauschild and
W. Mosch
Volume 14 Uninterruptible Power Supplies J. Platts and J.D. St Aubyn (Editors)
Volume 15 Digital Protection for Power Systems A.T. Johns and S.K. Salman
Volume 16 Electricity Economics and Planning T.W. Berrie
Volume 18 Vacuum Switchgear A. Greenwood
Volume 19 Electrical Safety: A guide to causes and prevention of hazards
J. Maxwell Adams
Volume 21 Electricity Distribution Network Design, 2nd Edition E. Lakervi and
E.J. Holmes
Volume 22 Artificial Intelligence Techniques in Power Systems K. Warwick, A.O. Ekwue
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Volume 24 Power System Commissioning and Maintenance Practice K. Harker
Volume 25 Engineers’ Handbook of Industrial Microwave Heating R.J. Meredith
Volume 26 Small Electric Motors H. Moczala et al.
Volume 27 AC–DC Power System Analysis J. Arrillaga and B.C. Smith
Volume 29 High Voltage Direct Current Transmission, 2nd Edition J. Arrillaga
Volume 30 Flexible AC Transmission Systems (FACTS) Y.-H. Song (Editor)
Volume 31 Embedded Generation N. Jenkins et al.
Volume 32 High Voltage Engineering and Testing, 2nd Edition H.M. Ryan (Editor)
Volume 33 Overvoltage Protection of Low-Voltage Systems, Revised Edition P. Hasse
Volume 36 Voltage Quality in Electrical Power Systems J. Schlabbach et al.
Volume 37 Electrical Steels for Rotating Machines P. Beckley
Volume 38 The Electric Car: Development and future of battery, hybrid and fuel-cell
cars M. Westbrook
Volume 39 Power Systems Electromagnetic Transients Simulation J. Arrillaga and
N. Watson
Volume 40 Advances in High Voltage Engineering M. Haddad and D. Warne
Volume 41 Electrical Operation of Electrostatic Precipitators K. Parker
Volume 43 Thermal Power Plant Simulation and Control D. Flynn
Volume 44 Economic Evaluation of Projects in the Electricity Supply Industry
H. Khatib
Volume 45 Propulsion Systems for Hybrid Vehicles J. Miller
Volume 46 Distribution Switchgear S. Stewart
Volume 47 Protection of Electricity Distribution Networks, 2nd Edition J. Gers and
E. Holmes
Volume 48 Wood Pole Overhead Lines B. Wareing
Volume 49 Electric Fuses, 3rd Edition A. Wright and G. Newbery
Volume 50 Wind Power Integration: Connection and system operational aspects
B. Fox et al.
Volume 51 Short Circuit Currents J. Schlabbach
Volume 52 Nuclear Power J. Wood
Volume 53 Condition Assessment of High Voltage Insulation in Power System
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Volume 55 Local Energy: Distributed generation of heat and power J. Wood
Volume 56 Condition Monitoring of Rotating Electrical Machines P. Tavner, L. Ran,
J. Penman and H. Sedding
Volume 57 The Control Techniques Drives and Controls Handbook, 2nd Edition
B. Drury
Volume 58 Lightning Protection V. Cooray (Editor)
Volume 59 Ultracapacitor Applications J.M. Miller

Volume 62 Lightning Electromagnetics V. Cooray
Volume 63 Energy Storage for Power Systems, 2nd Edition A. Ter-Gazarian
Volume 65 Protection of Electricity Distribution Networks, 3rd Edition J. Gers
Volume 66 High Voltage Engineering Testing, 3rd Edition H. Ryan (Editor)
Volume 67 Multicore Simulation of Power System Transients F.M. Uriate
Volume 68 Distribution System Analysis and Automation J. Gers
Volume 69 The Lightening Flash, 2nd Edition V. Cooray (Editor)
Volume 70 Economic Evaluation of Projects in the Electricity Supply Industry,
3rd Edition H. Khatib
Volume 72 Control Circuits in Power Electronics: Practical issues in design and
implementation M. Castilla (Editor)
Volume 73 Wide Area Monitoring, Protection and Control Systems: The enabler for
smarter grids A. Vaccaro and A. Zobaa (Editors)
Volume 74 Power Electronic Converters and Systems: Frontiers and applications A.M.
Trzynadlowski (Editor)
Volume 75 Power Distribution Automation B. Das (Editor)
Volume 76 Power System Stability: Modelling, analysis and control Abdelhay A.
Sallam and Om P. Malik
Volume 78 Numerical Analysis of Power System Transients and Dynamics A. Ametani
(Editor)
Volume 79 Vehicle-to-Grid: Linking electric vehicles to the smart grid J. Lu and
J. Hossain (Editors)
Volume 81 Cyber-Physical-Social Systems and Constructs in Electric Power
Engineering S. Suryanarayanan, R. Roche and T.M. Hansen (Editors)
Volume 82 Periodic Control of Power Electronic Converters F. Blaabjerg, K. Zhou,
D. Wang and Y. Yang
Volume 86 Advances in Power System Modelling, Control and Stability Analysis
F. Milano (Editor)
Volume 87 Cogeneration: Technologies, optimisation and implementation C.A.
Frangopoulos (Editor)
Volume 88 Smarter Energy: From smart metering to the smart grid H. Sun, N.
Hatziargyriou, H.V. Poor, L. Carpanini and M.A. Sánchez Fornié (Editors)
Volume 89 Hydrogen Production, Separation and Purification for Energy A. Basile,
F. Dalena, J. Tong and T.N. Veziroğlu (Editors)
Volume 90 Clean Energy Microgrids S. Obara and J. Morel (Editors)
Volume 91 Fuzzy Logic Control in Energy Systems with Design Applications
in MATLAB‡
/Simulink‡
İ.H. Altaş
Volume 92 Power Quality in Future Electrical Power Systems A.F. Zobaa and S.H.E.A.
Aleem (Editors)
Volume 93 Cogeneration and District Energy Systems: Modelling, analysis and
optimization M.A. Rosen and S. Koohi-Fayegh
Volume 94 Introduction to the Smart Grid: Concepts, technologies and evolution
S.K. Salman
Volume 95 Communication, Control and Security Challenges for the Smart Grid S.M.
Muyeen and S. Rahman (Editors)
Volume 96 Industrial Power Systems with Distributed and Embedded
Generation R Belu
Volume 97 Synchronized Phasor Measurements for Smart Grids M.J.B. Reddy and D.K.
Mohanta (Editors)
Volume 98 Large Scale Grid Integration of Renewable Energy Sources A. Moreno-
Munoz (Editor)
Volume 100 Modeling and Dynamic Behaviour of Hydropower Plants N. Kishor and
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Volume 101 Methane and Hydrogen for Energy Storage R. Carriveau and D.S.-K. Ting
Volume 104 Power Transformer Condition Monitoring and Diagnosis A. Abu-Siada
(Editor)
Volume 106 Surface Passivation of Industrial Crystalline Silicon Solar Cells J. John
(Editor)

Volume 107 Bifacial Photovoltaics: Technology, applications and economics J. Libal
and R. Kopecek (Editors)
Volume 108 Fault Diagnosis of Induction Motors J. Faiz, V. Ghorbanian, and G. Joksimović
Volume 110 High Voltage Power Network Construction K. Harker
Volume 111 Energy Storage at Different Voltage Levels: Technology, integration, and
market aspects A.F. Zobaa, P.F. Ribeiro, S.H.A. Aleem, and S.N. Afifi (Editors)
Volume 112 Wireless Power Transfer: Theory, technology and application N. Shinohara
Volume 115 DC Distribution Systems and Microgrids T. Dragičević, F. Blaabjerg, and
P. Wheeler
Volume 117 Structural Control and Fault Detection of Wind Turbine Systems H.
R. Karimi
Volume 119 Thermal Power Plant Control and Instrumentation: The control of boilers
and HRSGs, 2nd Edition D. Lindsley, J. Grist, and D. Parker
Volume 120 Fault Diagnosis for Robust Inverter Power Drives A. Ginart (Editor)
Volume 123 Power Systems Electromagnetic Transients Simulation, 2nd Edition
N. Watson and J. Arrillaga
Volume 124 Power Market Transformation B. Murray
Volume 125 Wind Energy Modeling and Simulation Volume 1: Atmosphere and plant
P. Veers (Editor)
Volume 126 Diagnosis and Fault Tolerance of Electrical Machines, Power Electronics
and Drives A.J.M. Cardoso
Volume 128 Characterization of Wide Bandgap Power Semiconductor Devices F. Wang,
Z. Zhang, and E.A. Jones
Volume 129 Renewable Energy from the Oceans: From wave, tidal and gradient
systems to offshore wind and solar D. Coiro and T. Sant (Editors)
Volume 130 Wind and Solar Based Energy Systems for Communities R. Carriveau and
D.S.-K. Ting (Editors)
Volume 131 Metaheuristic Optimization in Power Engineering J. Radosavljević
Volume 132 Power Line Communication Systems for Smart Grids I.R.S Casella and
A. Anpalagan
Volume 139 Variability, Scalability and Stability of Microgrids S.M. Muyeen, S.M. Islam,
and F. Blaabjerg (Editors)
Volume 145 Condition Monitoring of Rotating Electrical Machines P. Tavner, L. Ran, and
C. Crabtree
Volume 146 Energy Storage for Power Systems, 3rd Edition A.G. Ter-Gazarian
Volume 155 Energy Generation and Efficiency Technologies for Green Residential
Buildings D. Ting and R. Carriveau (Editors)
Volume 157 Electrical Steels, 2 Volumes A. Moses, K. Jenkins, P. Anderson, and H. Stanbury
Volume 172 Lighting interaction with Power Systems, 2 Volumes A. Piantini (Editor)
Volume 905 Power System Protection, 4 Volumes

Distribution Systems
Analysis and Automation
2nd Edition
Juan M. Gers
The Institution of Engineering and Technology

Published by The Institution of Engineering and Technology, London, United Kingdom
The Institution of Engineering and Technology is registered as a Charity in England &
Wales (no. 211014) and Scotland (no. SC038698).
† The Institution of Engineering and Technology 2020
First published 2013
Second Edition published 2020
This publication is copyright under the Berne Convention and the Universal Copyright
Convention. All rights reserved. Apart from any fair dealing for the purposes of research
or private study, or criticism or review, as permitted under the Copyright, Designs and
Patents Act 1988, this publication may be reproduced, stored or transmitted, in any
form or by any means, only with the prior permission in writing of the publishers, or in
the case of reprographic reproduction in accordance with the terms of licences issued
by the Copyright Licensing Agency. Enquiries concerning reproduction outside those
terms should be sent to the publisher at the undermentioned address:
The Institution of Engineering and Technology
Michael Faraday House
Six Hills Way, Stevenage
Herts, SG1 2AY, United Kingdom
www.theiet.org
While the author and publisher believe that the information and guidance given in this
work are correct, all parties must rely upon their own skill and judgement when making
use of them. Neither the author nor publisher assumes any liability to anyone for any
loss or damage caused by any error or omission in the work, whether such an error or
omission is the result of negligence or any other cause. Any and all such liability is
disclaimed.
The moral rights of the author to be identified as author of this work have been
asserted by him in accordance with the Copyright, Designs and Patents Act 1988.
British Library Cataloguing in Publication Data
A catalogue record for this product is available from the British Library
ISBN 978-1-78561-871-0 (hardback)
ISBN 978-1-78561-872-7 (PDF)
Typeset in India by MPS Limited
Printed in the UK by CPI Group (UK) Ltd, Croydon

To the loving memory of my late father Jose Gers and my
brothers Jose Alejandro and Carlos Mauricio.

This page intentionally left blank

Contents
List of figures xv
List of tables xxv
About the author xxvii
Preface xxix
1 Smart Grid overview 1
1.1 Smart Grid for distribution systems 1
1.2 Definitions of Smart Grid 3
1.3 Benefits of the Smart Grid on distribution systems 5
1.3.1 Enhancing reliability 6
1.3.2 Improving system efficiency 6
1.3.3 Distributed energy resources 6
1.3.4 Optimizing asset utilization and efficient operation 6
1.4 Maturity Models for Smart Grid applications 6
1.4.1 Smart Grid Maturity Model 7
1.4.2 Benefits of using a Smart Grid Maturity Model 7
1.4.3 Genesis and components of an SGMM 8
1.4.4 Development process of an SGMM 8
1.4.5 Levels and domains of the SGMM 10
1.4.6 Results and analysis obtained by SGMM 13
1.4.7 Example case 14
1.5 Prioritization in Smart Grid projects 18
1.6 Cost–benefit analysis 21
1.6.1 Definition of benefits 21
1.6.2 Cost–benefit analysis methodologies 21
Reference 23
Further reading 23
2 Distribution automation functions 25
2.1 Electrical system automation 26
2.2 EMS functional scope 27
2.3 DMS functional scope 28
2.4 Functionality of DMS 28
2.4.1 Steady-state performance improvement 29
2.4.2 Dynamic performance improvement 30
2.5 Outage management systems 33
2.6 Geographic information systems 35

2.6.1 AM/FM functions 37
2.6.2 Database management 37
2.7 Communication options 37
2.8 Supervisory control and data acquisition 37
2.8.1 SCADA functions 38
2.8.2 System architecture 42
2.9 Synchrophasors and its application in power systems 46
2.9.1 Definition 46
2.9.2 Application of PMUs 47
Further reading 53
3 Fundamentals of distribution system analysis 55
3.1 Electrical circuit laws 55
3.1.1 Ohm’s law 55
3.1.2 Kirchhoff’s voltage law 55
3.1.3 Kirchhoff’s current law 55
3.2 Circuit theorems 56
3.2.1 Thévenin’s theorem 56
3.2.2 Star/Delta transform 56
3.2.3 Superposition theorem 57
3.3 Power AC circuits 57
3.4 PU normalization 62
3.5 Load flow 66
3.5.1 Formulation of the load flow problem 67
3.5.2 Newton–Raphson method 68
3.5.3 Type of buses 71
3.5.4 Application of the Newton–Raphson method to solve
load flows 71
3.5.5 Decoupling method 74
3.6 Radial load flow concepts 86
3.6.1 Theoretical background 89
3.6.2 Distribution network models 96
3.6.3 Nodes and branches identification 96
3.6.4 Illustration of nodes and branches identification 97
3.6.5 Algorithm to develop radial load flow 98
3.7 Power system analysis tool 99
3.7.1 New tendencies in PSAT applications 102
3.7.2 Advanced simulations in PSATs based on load
flow concept 103
3.8 Proposed exercises 110
Further reading 113
4 Short circuit calculation 115
4.1 Nature of short circuit currents 115
4.2 Calculation of fault duty values 122
x Distribution systems analysis and automation, 2nd edition

4.3 Fault calculation for symmetrical faults 125
4.4 Symmetrical components 126
4.4.1 Importance and construction of sequence networks 130
4.4.2 Calculation of asymmetrical faults using symmetrical
components 132
4.4.3 Equivalent impedances for a power system 134
4.4.4 Supplying the current and voltage signals to
protection systems 134
References 145
Further reading 145
5 Reliability of distribution systems 147
5.1 Network modeling 147
5.2 Network reduction 151
5.3 Quality indices 152
References 159
Further reading 160
6 Reconfiguration and restoration of distribution systems 161
6.1 Optimal topology 161
6.2 Location of switches controlled remotely 169
6.2.1 Considerations to increase reliability 169
6.2.2 Considerations to increase flexibility 172
6.3 Feeder reconfiguration for improving operating conditions 181
6.4 Feeder reconfiguration for service restoration 181
6.4.1 Fault location, isolation, and service restoration 182
6.4.2 Manual restoration vs. FLISR 184
6.4.3 Restrictions on restoration 185
6.4.4 FLISR central intelligence 187
6.4.5 FLISR-distributed intelligence 189
6.4.6 FLISR local intelligence 193
References 196
Further reading 196
7 Voltage/VAR control 199
7.1 Definition of voltage regulation 201
7.2 Options to improve voltage regulation 201
7.3 Voltage regulators 202
7.4 Capacitor application in distribution systems 204
7.4.1 Feeder model 209
7.4.2 Capacitor location and sizing 210
7.4.3 Reduction in power losses with one capacitor bank 211
7.4.4 Reduction in power losses with two capacitor banks 212
Contents xi

7.4.5 Losses reduction with three capacitor banks 213
7.4.6 Consideration of several capacitor banks 214
7.4.7 Capacitor sizing and location using software 215
7.5 Modeling of distribution feeders, including VVC equipment 217
7.6 Voltage/VAR control considering SCADA 218
7.7 Requirements for Volt/VAR control 223
7.8 Integrated Volt/VAR control 225
References 228
Further reading 228
8 Harmonic analysis 231
8.1 General considerations about harmonics 231
8.2 Mathematical background 234
8.3 Verification of harmonic values 235
8.4 Parallel resonance 235
8.5 Series resonance 237
8.6 Validation of harmonic values 238
8.6.1 Harmonic limits 238
8.6.2 Voltage distortion limits 238
8.6.3 Current distortion limits 238
8.7 Verification of harmonic values 239
8.8 Resizing and relocation of capacitor banks 240
8.9 Models 241
8.9.1 Harmonic sources 243
8.9.2 System model 243
8.9.3 Load model 243
8.9.4 Branch model 243
8.10 Derating transformers 249
Further reading 251
9 Modern protection of distribution systems 253
9.1 Fundamentals of overcurrent protection 253
9.1.1 Protection coordination principles 253
9.1.2 Criteria for setting instantaneous units 254
9.1.3 Setting time-delay relays 255
9.1.4 Setting overcurrent relays using software techniques 258
9.2 Coordination across Dy transformers 258
9.3 Protection equipment installed along the feeders 263
9.3.1 Reclosers 266
9.3.2 Sectionalizers 272
9.3.3 Fuses 275
9.4 Setting criteria 280
9.4.1 Fuse–fuse coordination 281
9.4.2 Recloser–fuse coordination 282
xii Distribution systems analysis and automation, 2nd edition

9.4.3 Recloser–sectionalizer coordination 285
9.4.4 Recloser–sectionalizer–fuse coordination 286
9.4.5 Recloser–recloser coordination 288
9.4.6 Recloser–relay coordination 288
9.5 Protection considerations when distributed generation
is available 290
9.5.1 Short circuit levels 290
9.5.2 Synchronization 290
9.5.3 Overcurrent protection 290
9.5.4 Adaptive protection 290
Further reading 294
10 Distributed generation and energy storage systems 297
10.1 Current situation of renewable generation 297
10.2 Solar plants 297
10.2.1 PV cell model 298
10.2.2 Inverters 301
10.2.3 Grid-connected and stand-alone systems 303
10.3 Wind generation 313
10.3.1 Drag and lift blades 316
10.3.2 Rotor axis orientation 317
10.3.3 Number of blades 317
10.3.4 Speed of rotation 318
10.3.5 Generator types 318
10.3.6 Control systems 322
10.3.7 Wind farms 323
10.4 Small hydroelectric plants 325
10.5 Energy storage systems 326
10.5.1 Electromechanical storage 329
10.5.2 Electrochemical storage 329
References 333
11 Fundamentals on microgrid technology 337
11.1 Introduction to microgrids 337
11.2 Microgrid components 338
11.3 Classification of microgrids 339
11.3.1 Classification by configuration 339
11.3.2 Classification by AC/DC type 339
11.3.3 Classification by modes of operation 340
11.3.4 Classification by feeder location 340
11.4 Microgrid control 341
11.4.1 Centralized control 342
11.4.2 Decentralized control 343
Contents xiii

11.5 Microgrid protection 343
11.6 Benefits of microgrids 346
11.6.1 Economic benefits of a microgrid 347
11.6.2 Technical benefits of a microgrid 348
11.6.3 Environmental and social benefits of a microgrid 350
References 357
12 Communications in Smart Grids 359
12.1 ISO–OSI model 359
12.2 Communication solutions for the power system world 361
12.2.1 Communication solutions in AMI 362
12.2.2 Distribution network communications 362
12.3 Transmission mediums 364
12.3.1 Wired and electric mediums 364
12.3.2 Wireless mediums 364
12.3.3 Optical mediums 365
12.4 Information security as the crucial element in smart networks 365
12.5 Cybersecurity 366
12.6 IEC 61850 overview 366
12.6.1 Standard documents and features of IEC 61850 370
12.6.2 System configuration language (SCL) 375
12.6.3 Configuration and verification of GOOSE messages 377
12.6.4 Configuration of the system 380
12.6.5 System verification test 380
12.6.6 Substation IT network 380
12.6.7 Process bus 381
12.6.8 Communications redundancy networks IEC 618590 382
References 383
Further reading 384
13 Interoperability concepts in power electric systems 387
13.1 Elements required for interoperability 388
13.2 Information exchange processes 388
13.3 Data models and international standards 390
13.4 Implementation of common information models 396
References 398
Further reading 399
Index 401
xiv Distribution systems analysis and automation, 2nd edition

List of figures
1.1 Power system as envisaged in 1982 (from “Automated power
distribution,” published by IEEE Spectrum, April 1982) 2
1.2 Smart Grid concept 5
1.3 Smart Grid components 5
1.4 Some organizations that use the SGMM (taken from the
Carnegie Mellon Software Engineering Institute) 9
1.5 Example of results obtained from the SGMM (taken from
the Carnegie Mellon Software Engineering Institute) 13
1.6 Example of results in Grid Operations (GO) domain 15
1.7 Graphical example of results after applying the SGMM 17
1.8 Definition of the Smart Grid benefits, by the SGCT 22
2.1 Typical installation of a switch on an overhead
distribution feeder 25
2.2 Main benefits of distribution automation 26
2.3 Power system automation components 27
2.4 Network management EMS/DMS 27
2.5 Screenshots of typical EMS 28
2.6 Screenshots of a typical DMS 29
2.7 Illustration of power line communication (PLC) 30
2.8 (a) Modulation for the outbound signal and
(b) modulation for the inbound signal 30
2.9 Comparison of restoration time with and without DA 31
2.10 Trouble call system 32
2.11 Work order illustration 33
2.12 DMS/OMS integration 35
2.13 Outage management system report 36
2.14 OMS trouble call ticket 36
2.15 Example of a GIS 37
2.16 Typical communication methods 38
2.17 SCADA illustration 39
2.18 SCADA functions: supervisory control 40
2.19 SCADA functions: data acquisition 40

2.20 Relationship of SCADA with databases 41
2.21 Control center general scheme 43
2.22 Single master station, multiple RTU, radial circuit 45
2.23 Single master station, data concentrator, or gateway 45
2.24 Multiple master stations, LAN/WAN substation
connection using routers 45
2.25 Sinusoidal waveform from its phasorial representation 47
2.26 PMU’s integration with the current communication system 48
2.27 Transmission line model 49
2.28 Transferred power through a line 51
2.29 Integration of a distributed generation source using PMUs 53
3.1 (a) Circuit before using Thévenin’s theorem and
(b) circuit after using the Thévenin’s theorem 56
3.2 Star/Delta equivalent 57
3.3 (a) Circuit complete and (b) solution using
superposition theorem 57
3.4 Relationship of current, voltage, and power in
electrical circuits 58
3.5 System for Example 3.1 59
3.6 Power losses for different voltage angles 61
3.8 Power losses for different voltage angles 63
3.9 Electrical system for Example 3.3 65
3.10 Illustration of a power system board simulator 66
3.11 Representation of a three-node system with current sources 67
3.12 Illustration of the Newton–Raphson concept 69
3.13 Illustration of types of buses for load flow analysis 72
3.14 Flow chart for load flow analysis using NR algorithm 74
3.15 Two-bus system with load at the end bus 74
3.16 Illustration of the relationship between P and q 75
3.17 Illustration of the relationship between Q and V 75
3.18 Power system for Example 3.6 77
3.19 Load flow results in pu for the system of Example 3.6 83
3.20 Load flow results in real magnitudes for the
system of Example 3.6 84
3.21 Single-line diagram for Example 3.7 85
3.22 Portion of the power system of Example 3.7 91
3.23 Bus voltage results considering a capacitor bank
at 13.2 kV Willow bus 92
3.24 Bus voltage results of Example 3.7 considering tap
changer operation 93
xvi Distribution systems analysis and automation, 2nd edition

3.25 Bus voltage results of Example 3.7 considering a new line 94
3.26 Two node systems 95
3.27 Two-feeder system with numbers and letters nomenclature 97
3.28 Two-feeder identification for the example system 98
3.29 Load flow for radial systems 100
3.30 Grounded Wye–Grounded Wye step-down
transformer with balanced load 101
3.31 Distribution network without optimal capacitor placement 104
3.32 Distribution network with optimal capacitor
placement simulation 105
3.33 Losses on the network without optimal topology analysis 106
3.34 Losses on the network with optimal topology analysis 107
3.35 Load flow results without optimal power flow 109
3.36 Load flow results with optimal power flow 111
3.37 Element names on the network 112
4.1 L–R circuit 115
4.2 Impedance components 117
4.3 Variation of fault current due to the DC component
when (a) a q ¼ 0; (b) a q ¼ p
2 118
4.4 Results for Example 4.1 120
4.5 Transient SC current at generator terminals 121
4.6 Variation of current with time during a fault at
generator terminals 121
4.7 Variation of generator reactance during a fault 122
4.8 Multiplying factors for 3 Ph and L–L ground faults 123
4.9 Short circuit total current 125
4.11 Short circuit variation for Example 4.3 127
4.12 Excerpt of the famous paper by C.L. Fortescue 128
4.13 Illustration of symmetrical components 129
4.14 Magnitudes of the positive sequence network 129
4.15 Symmetrical components of an unbalanced three-phase system 131
4.16 Representation of sequence impedances: (a) 3-phase
positive-sequence; (b) single phase positive-sequence
equivalent; (c) 3-phase negative-sequence; (d) single phase
negative-sequence equivalent; (e) 3-phase zero-sequence;
and (f) single phase zero-sequence equivalent 133
4.17 Representation of sequence networks for (a) Line-to-earth
fault; (b) Line-to-line fault; and (c) Line-to-line-to-earth fault 135
4.18 Sequence currents and voltages for different types of faults 136
4.19 Single line diagram for Example 4.4 137
List of figures xvii

4.20 Positive sequence diagram for Example 4.4 138
4.21 Sequence network connection for a single-phase
fault of Example 4.4 139
4.22 Solution of Example 4.4 by using a PSAT for
a three-phase fault 140
4.23 Reduced diagrams for the fault analysis in Example 4.5 141
4.24 Impedance diagram for the three-phase fault in node
The Ridges 115 kV 142
4.25 Solution of Example 4.5 by using a software package 143
4.26 Diagram for exercise 2 144
5.1 Repairable components in series—both must work
for success 148
5.2 Repairable components in parallel—one or both
must work for success 149
5.3 Diagram system for Example 5.1 149
5.4 Diagram system results for the first part of Example 5.1 150
5.5 Diagram system results for the second part of Example 5.1 151
5.6 An example of network reduction 152
5.7 Minimal cut sets of a simple system 152
5.8 Representation of events used in calculating indices 156
5.9 Elements of exercise: (a) case a and (b) case b 159
6.1 Three feeder-distribution system 162
6.2 Radial distribution network with normally closed
and open switches 163
6.3 Basic algorithm for the reconfiguration of distribution
networks 164
6.4 Two-feeder system showing location of potential
opening points 165
6.5 Initial topology of case study 168
6.6 Optimal topology considering loss reduction 169
6.7 System diagram for Example 6.2 171
6.8 Results for scenario (a) of Example 6.2 173
6.9 Results for scenario (b) of Example 6.2 174
6.10 Results for scenario (c) of Example 6.2 175
6.11 Results for scenario (d) of Example 6.2 176
6.12 Results for scenario (e) of Example 6.2 177
6.13 Location of switches in distribution systems 178
6.14 Two-feeder system showing location of switches
controlled remotely 179
xviii Distribution systems analysis and automation, 2nd edition

6.15 Three-feeder system illustrating switch location for service
restoration with no tie switches (a) and tie switches (b) 180
6.16 Distribution system illustrating loss reduction 182
6.17 Normal configuration 183
6.18 Fault clearing by relay at B1—Step 1 184
6.19 Fault isolation by opening corresponding switches—Step 2 185
6.20 Reclosing B1—Step 3 (upstream restoration) 186
6.21 Reconfiguration by operating switches NO and
NC—Step 4 (downstream restoration) 187
6.22 Three-feeder system illustrating switch location
for service restoration 188
6.23 Time to fix faults for typical systems 188
6.24 Loading for normal condition 189
6.25 Loading after reconfiguration 190
6.26 Detection of a fault in an FLISR with central intelligence.
Reproduced by permission of ALSTOM 191
6.27 Fault isolation by opening corresponding feeder.
6.28 Upstream restoration. Reproduced by permission of ALSTOM 192
6.29 Possible downstream restoration plan with FLISR.
6.30 Selection of the best option for restoration. Reproduced by
permission of ALSTOM 193
6.31 Downstream restoration of healthy distributed system section.
6.32 Example of an FLISR-distributed intelligence solution
sequence: (a) normal configuration; (b) Fault in Team 6;
(c) Fault is detected and initiates opening of switches;
and (d) Service is restored to all the unfaulted segments 194
6.33 Example of a distribution system with FLISR local
intelligence 195
6.34 Fault between R03 and R04 195
6.35 Final topology after local intelligence operation 196
7.1 Rated voltages specified for the United States 200
7.2 Voltage regulation limits in the United States 200
7.3 Schematic of a single-phase 32-step voltage regulator 203
7.4 Voltage profile with step-type voltage regulators 203
7.5 Diagrams for Example 7.1: (a) system diagram and
(b) equivalent circuit 205
7.6 Voltage and current vector diagram for the base case 206
7.7 Power diagram for the base case 207
List of figures xix

7.8 Current profiles for feeders with uniformly distributed loads 210
7.9 Distribution feeder with one capacitor bank 211
7.10 Distribution feeder with two capacitor banks 213
7.11 Distribution system to illustrate application of capacitors 215
7.12 Feeder used for the illustration 216
7.13 Layout of the feeder used in the modeling 217
7.14 Typical voltage regulator modeling input data 218
7.15 Load flow run for the system used with VVC 219
7.16 Components of a VVC assisted with SCADA 220
7.18 VAR dispatch processor control module for Example 7.2 221
7.19 VAR dispatch processor control module for all capacitor
banks in Example 7.2 222
7.20 Voltage-control processor module for Example 7.2 222
7.21 Voltage-control processor results comparison for Example 7.2 223
7.22 Volt/VAR modules applied for Example 7.2 224
7.23 Integrated Volt/VAR control, including DG 226
7.24 Context diagram for centralized integrated Volt/VAR control 226
7.25 Context diagram for decentralized integrated Volt/VAR control 227
7.26 Diagrams of list item 2 in Section 7.9 228
8.1 Connection of equipment producing parallel resonance 236
8.2 Connection of equipment producing series resonance 237
8.3 Z versus W in series resonance filters 238
8.4 General flow of harmonic currents in radial power system:
(a) without power capacitor and (b) with power capacitor 240
8.5 System example for illustrate harmonic evaluation
procedure: (a) Feeder with harmonic sources and
(b) Two-node system equivalent 242
8.6 Simplified diagram of the system 244
8.7 (a) Model for fundamental frequency and (b) model
for harmonic h 245
8.8 Circuit for fundamental frequency 246
8.9 Circuit for fifth harmonic 246
9.1 Time–current operating characteristics of overcurrent relays:
(a) Definite current; (b) Definite time; (c) Inverse time;
and (d) Inverse time with instantaneous unit 253
9.2 Overcurrent relay coordination procedure in a
distribution system 254
9.3 Overcurrent inverse-time relay curves associated
with the two breakers on the same feeder 255
9.4 Typical ANSI/IEEE and IEC overcurrent relay curves 257
xx Distribution systems analysis and automation, 2nd edition

9.5 Coordination of overcurrent relays for a Dy transformer 259
9.6 Power system of Example 9.1 259
9.7 Specifications of relay Beckwith M-7651.
Reproduced by permission of Beckwith Electric 260
9.8 Relay coordination curves for Example 9.1 263
9.9 Remote supervisory PMH models. Reproduced by
permission of SC 264
9.10 PME Pad-Mounted Gear. Reproduced by permission of SC 265
9.11 Time–current curves for reclosers 267
9.12 Typical sequence for recloser operation 267
9.13 Types of single-phase reclosers: (a) NOJA OSM;
(b) COOPER NOVA; and (c) COOPER D 269
9.14 Types of three-phase reclosers: (a) GW Viper-LT;
(b) SCHNEIDER U; (c) ABB OVR; and (d) Hawker
Siddeley Switchgear GVR 269
9.15 COOPER Kyle type VSA20A 270
9.16 Option to locate reclosers 271
9.17 Types of sectionalizers: (a) COOPER GH; (b) Hawker
Siddeley Switchgear; and (c) COOPER GN3VE 273
9.18 Untanked view of a sectionalizer 274
9.19 Sectionalizers application where two feeders of system
are protected 275
9.20 Sectionalizers application where one branch system
is protected 276
9.21 Sectionalizers application where one branch system
is protected 279
9.22 Characteristics of typical fuse links: (a) 200K fuse
link and (b) 200T fuse link 279
9.23 Criteria for fuse–fuse coordination 281
9.24 Time–current characteristics for fuse–fuse coordination 282
9.25 Criteria for source-side fuse and recloser coordination 284
9.26 Criteria for load-side fuse and recloser coordination 286
9.27 Coordination of one recloser with three sectionalizers 286
9.28 Portion of a distribution feeder 287
9.29 Phase–current curves 289
9.30 Example of adaptive protection setting with a RTU device 291
9.31 Single-line diagram for exercise 1 292
9.32 Single-line diagram for exercise 2 293
10.1 A typical PV cell 298
10.2 I–V characteristic of a PV cell 299
10.3 P–V characteristic of a PV cell 300
List of figures xxi

10.4 Real PV cell equivalent circuit 301
10.5 Power inverter operation scheme 301
10.6 One-phase square wave inverter 301
10.7 Three-phase sine wave PWM inverter: (a) equivalent circuit,
(b) resultant waveform, and (c) fundamental wave modulation 302
10.8 Inverter system for a PV module as a DG unit: (a) PV module,
(b) MPPT, (c) energy storage, (d) DC:DC converter,
(e) DC:AC converter, (f) isolation, and (g) output filter 302
10.9 Centralized and decentralized PV systems 303
10.10 Grid-connected PV system example 304
10.11 Load flow of the PV system through 1 day 305
10.12 Daily solar radiation per month for Example 10.2 307
10.13 Variation of series and parallel modules with temperature 310
10.14 PV arrangement for Example 10.2 314
10.15 Air parcel interacting with a wind turbine rotor 314
10.16 Power coefficient as a function of the TSR 316
10.17 Mechanical structure of a HAWT 317
10.18 Single-bladed, two-bladed, three-bladed, and multibladed
wind turbines 318
10.19 Torque-speed characteristic of an FSWT 319
10.20 Equivalent circuit of a Type 1 generator 319
10.21 Circuit diagram of a Type 1 generator 320
10.27 Phases of wind power generation 323
10.28 Wind farm layout 324
10.29 Small-scale hydropower plant 325
10.30 Schematic diagram of a hydroelectric power plant
with water reservoir 326
10.31 Integration of a PV system with energy storage
in the power system 327
10.32 Example of a load flow profile through one typical day 328
10.33 NiMH battery state of charge operation 330
10.34 I–V curve for exercise 2 331
10.35 Curve for exercise 3 332
10.36 CP vs TSR curve for exercise 7 333
11.1 A general scheme of a microgrid 338
11.2 Typical distribution system management structure 341
xxii Distribution systems analysis and automation, 2nd edition

11.3 Centralized control structure 342
11.4 Protection system features 344
11.5 Microgrid for Example 11.1 345
11.6 Short circuit analysis for three different scenarios
for Example 11.1 346
11.7 Short circuit analysis for three different scenarios
for the PV and wind turbine nodes for Example 11.1 346
11.8 Microgrid operation strategies 347
11.9 Two-feeder microgrid for Example 11.2 349
11.10 Reconfigured microgrid for Example 11.2 351
11.11 Lines whose ends have to change their status 352
11.12 Radial distribution system for exercise 1 353
11.13 Microgrid for exercise 2 354
11.14 Load and generation profiles for exercise 2 355
11.15 Microgrid for exercise 4 356
12.1 OSI model 360
12.2 TCP/IP link applying OSI model 360
12.3 Communication options in the Smart Grids 361
12.4 Message communication OSI-7 stack 363
12.5 Virtual and real world 371
12.6 Physical and logical device 372
12.7 Substation engineering process using SCL language 376
12.8 System single line diagram 378
12.9 Logic of breaker failure scheme 378
12.10 Proprietary configuration tools used for the configuration
of IEDs 379
12.11 Test connections used for standalone IEC 61850–based IED 381
12.12 Substation network—process bus and station bus 382
13.1 Information exchange between two application elements 390
13.2 Example circuit (a) as a line diagram; (b) with CIM mappings 391
13.3 Transformer class diagram 393
13.4 Example of (a) power system representation and
(b) CIM/XML representation 394
13.5 Elements for implementing interoperability in information
systems 396
13.6 Stages in a CIM implementation 397
List of figures xxiii

List of tables
1.1 Example of results after applying the SGMM 17
1.2 Criteria for prioritizing Smart Grid projects by using the AHP 18
1.3 Subcriteria for prioritizing Smart Grid projects 19
1.4 Alternatives proposed for reaching the objectives
of Smart Grid projects 19
1.5 Summary of different approaches to estimate the
Smart Grid cost–benefits 22
2.1 Traditional and DMS-based DA applications 34
3.1 Values for Example 3.5 71
3.2 Values of voltages for Example 3.6 77
3.3 Values of impedances for Example 3.6 77
3.4 Initial input data for Example 3.6 78
3.5 Rated bus voltages for Example 3.7 86
3.6 HV transformer data for power system of Example 3.7 87
3.7 MV transformer data for power system of Example 3.7 88
3.8 Generator data for power system of Example 3.7 89
3.9 Bus data for power system of Example 3.7 89
3.10 Line data for power system of Example 3.7 90
3.11 Losses on the network without optimal topology analysis 107
3.12 Losses on the network with optimal topology analysis 108
3.13 Total results on the network without optimal power flow 110
3.14 Total results on the network with optimal power flow 112
3.15 Contingency N-1, results for elements with limit violations 112
3.16 Contingency N-2, results for L1-L2 contingency 112
4.1 Short circuit currents nomenclature for standards
ANSI/IEEE and IEC 125
5.1 Example of outage data 154
5.2 Planned and unplanned SAIDI, without exceptional events 157
5.3 Planned and unplanned SAIFI, without exceptional events 158
5.4 Database for exercise 3 159
6.1 Data of feeders encompassed within the prototype 166
6.2 Result of reconfiguration analysis 167
6.3 Options where the highest losses reductions are obtained 168
6.4 Load data for Example 6.2 172
6.5 Line data for Example 6.2 172
6.6 Comparison of reliability data for node N11 under
different scenarios 178

6.7 Reconfiguration options for the previous system 181
6.8 Reconfiguration options for system of Example 6.3 187
6.9 Loading values of Example 6.4 190
7.1 Results comparison for Example 7.1 208
7.2 Comparison between shunt capacitor and series capacitor 209
7.3 Results of software simulation 216
8.1 Summary of power quality variation categories.
Reproduced by permission of Dranetz 232
8.2 Categories and typical characteristics of power system
electromagnetic phenomena. Taken from IEEE Std. 1159-2009 233
8.3 Harmonic voltage distortion limits in % of nominal fundamental
frequency voltage. Taken from IEEE Std. 519-2014 239
8.4 Current distortion limits. Taken from IEEE Std. 519-2014 239
8.5 Summary of results Example 8.1 248
8.6 Currents for different harmonic orders 251
9.1 IEEE and IEC constants for standards, overcurrent relays 257
9.2 Summary of fault conditions 258
9.3 Short circuit calculation for power system of Example 9.1 261
9.4 Summary of relay settings for Example 9.1 262
9.5 Maximum fault current in amperes, rms SC
Standard Speed Fuse Links 283
9.6 K factor for the source side fuse link 284
9.7 K factor for the load side fuse link 285
10.1 Basic home appliances and typical power consumption
for Example 10.2 306
10.2 Energy demand per home appliance for Example 10.2 306
10.3 Demand/irradiation ratio per month for Example 10.2 308
10.4 Typical PV module datasheet for Example 10.2 308
10.5 Charge regulator datasheet for Example 10.2 312
10.6 Inverter datasheet for Example 10.2 313
11.1 Microgrid control methods comparison 344
11.2 Total losses for the given system in Example 11.2 350
11.3 Element losses for the given system in Example 11.2 350
11.4 Total losses for the new topology for Example 11.2 351
11.5 Line losses for the new topology for Example 11.2 351
11.6 Total losses comparison for the given system, the new
topology, and mesh configuration for Example 11.2 352
11.7 Load and generation profiles data for exercise 3 356
11.8 Switches operation sequence for exercise 4 357
12.1 Requirements for cybersecurity 367
12.2 Protection logical nodes defined by IEC 61850-7-4 Ed. 2 373
12.3 Protection logical nodes defined by IEC 61850-5 Ed. 2 374
13.1 Architecture of the principles of interoperability 389
xxvi Distribution systems analysis and automation, 2nd edition

About the author
Juan M. Gers obtained his undergraduate degree as Electrical Engineer from the
Universidad del Valle in Cali, Colombia in 1977. In 1981, he finished a master’s
degree in Power Systems Studies at the University of Salford in England, and his
doctorate with research in distribution systems and automatization at the University
of Strathclyde in Scotland in 1998. He was a professor at the Universidad del Valle
in Colombia for more than 20 years and has been working as adjunct instructor at
the Gonzaga University for more than 10 years. Dr. Gers served as the Vice
Minister of Mines and Energy of Colombia in 2002. He is the author of Protection
of Electricity Distribution Networks, is a Chartered Engineer of the IET and
participates in several groups of the Power System Relaying and Control
Committee of the IEEE.

Preface
There has been a great progress on Distribution Systems technology during the last
years which encouraged the update of the first edition of this book that was pub-
lished seven years ago. Undoubtedly, the reliability of the electrical system and the
efficiency of the energy supply, depend largely on the Distribution Systems.
New developments have been achieved in different topics and in particular in
switching and protective equipment, communication and automation. The evolu-
tion of Distributed Generation has advanced dramatically as well as the incor-
poration of Microgrids due to the growing concern for energy availability and cost
of kWh, in some portions of electrical systems. Undoubtedly, the overall concept
of the energy supply has experienced huge changes motivated mainly by the
Distribution Systems.
The book keeps its original idea where the material has been prepared based
on discussions on many international meetings, real applications on utility systems
and personal research. The topics are elaborated first presenting the fundamental
concepts but also the current state of the art as far as it was practical. The structure
of this edition, although it is similar to that of the first edition, includes new
material and exercises. Two new chapters were added to complement the content of
the first edition. Chapter 10 covers Distributed Generation and Energy Storage
Systems and Chapter 11 presents the foundations of Microgrids Technology.
All examples were reviewed and complemented and new ones were added with
illustrations in MATLAB
. The scripts are included for readers and students to
follow the corresponding solution.
I am indebted to several colleagues for their generous help but in particular to
Carlo Viggiano and Juan Guardiola for their contribution to compile the material
and test the exercises. Thanks are also due to Henry Smit for his contribution on
reviewing several chapters. Other colleagues have contributed greatly with ideas
and supply of reference sources. Thanks are given in particular to Leinyker
Palacios, Andrej Souvent, Hugo Monterrubio, Jose Munoz, and Luis Aragon.
I express my sincere gratitude to Dr. Luigi Busarello for allowing me to use the
NEPLAN Software for different exercises, which helped to illustrate the overall
material. The examples and exercises that required a PSAT were all actually
done using NEPLAN. My recognition will go always to Prof. K L Lo from
Strathclyde University in the UK who introduced me to Distribution Automation
concepts and gave me good guidance in my first year working on the field. I am
also indebted to N Srinivasan of MPS Limited and Christoph von Friedeburg,

Olivia Wilkins, and other associates of IET for their help and assistance during the
progress of the book.
My deepest thanks are always with my wife Pilar, our daughter Angela Marı́a,
and our sons Juan Felipe and Juan Jose who have been a source of support and
enthusiasm with the many hours devoted to the preparation of this edition.
Juan M Gers
Weston, April 2020
xxx Distribution systems analysis and automation, 2nd edition

Chapter 1
Smart Grids overview
Smart Grid is a rather new concept that includes aspects of energy generation,
transmission, and distribution and aims for a more reliable service, higher effi-
ciency, more security, two-way utility-user communications, and promotion of
green energy among other goals.
Smart Grid has been mainly associated with remote metering, which was later
called AMR (automatic meter reading). The activities of AMR were encompassed
within those of a broader field that was eventually called AMI (advanced metering
infrastructure). Clearly, the metering system is one of the major elements of the
Smart Grid but certainly is not the only one. Many elements are included in the
overall field of Smart Grids. Those pertaining to distribution systems and in par-
ticular to the automation of distribution systems (or distribution automation) will be
considered in this book.
1.1 Smart Grid for distribution systems
Distribution systems have been operated, with only occasional manual setting
changes and a rather primitive automation that is known today as local intelligence.
Automation in fact was first implemented on generation and transmission systems
and gradually became popular also on distribution systems. Recently, in response to
the growing demand to improve reliability and efficiency of the power system,
more automation was introduced to distribution systems.
A good example of local intelligence is that used in reclosers operating in
coordination with sectionalizers. After a local fault, reclosers start a set of reclosing
operations, before locking out. Other good example is the operation of capacitor
bank switches that rely on local signals, such as voltage level, power factor, or
even time.
The Smart Grid policy requirements as outlined in the Energy Independence
and Security Act (EISA) of December 2007 give a better understanding of the
benefits and challenges of distribution automation for all of its stakeholders.
The ideas behind Smart Grids evolved from greater attention that Distribution
Systems started to receive in the 1980s. Until then most of the attention was given
to Generation and Transmission systems. Figure 1.1, taken from the paper
“Automated power distribution” by Arthur C. M. Chen, published by IEEE spec-
trum in April 1982, shows a representation of a projected distribution system. The

paper anticipated immediate detection and isolation of a faulted feeder and a
reduction of the amount of time a line crew should spend to locate and fix it. It also
referred to the increase of more distributed generation, called by then as dispersed
storage and generation systems. Finally, the paper made a point on the importance
of distribution automation for maintaining a reliable supply and to reduce operating
costs. It is really interesting to see how all those provisions are now a reality.
Battery
or fuel cells,
1–25 MW
Solar or
wind
sources
(100 kW to
1 MW)
Photovoltaic
power supply, up
to 100 kW
Generating plant
Step-up transformers
Circuit breakers
Transmission system
Transformers in
bulk power
substation
Dispersed
storage and
generation
(DSG)
Subtransmission
system
DSG
Distribution
substation
Three-phase,
primary feeder
Sectionalizing
switch
Primary
circuits
One-phase,
lateral feeder
Distribution
transformer
Services
Home
DSG
Figure 1.1 Power system as envisaged in 1982 (from “Automated power
distribution,” published by IEEE Spectrum, April 1982)
2 Distribution systems analysis and automation, 2nd edition

Governments and utilities funding the development and modernization of grids
have defined the functions required for Smart Grids. According to the United States
Department of Energy’s Modern Grid Initiative Report, a modern Smart Grid must
satisfy the following requirements:
● motivate consumers to actively participate in operations of the grid,
● be able to heal itself,
● resist attack,
● provide a higher quality power that will save money wasted during outages,
● accommodate all generation and storage options,
● enable electricity markets to flourish,
● run more efficiently,
● enable higher penetration of intermittent power generation sources.
In order to achieve the goals of Smart Grid mentioned above and in particular
the improvement in reliability, security, and efficiency, it is essential to have a
well-developed digital technology. Among the significant challenges facing
development of an Smart Grid are the cost of implementing it, and the new
standards that regulatory bodies have to enact. Interoperability standards cer-
tainly will allow the operation of highly interconnected systems that include
distributed generation plants.
Another challenge that the implementation of Smart Grid and distribution
automation faces is the huge variety of technologies produced by multiple vendors.
Establishing a proper development path is highly recommended to any utility
before embarking on a comprehensive project. Maturity Models that are discussed
in a latter chapter help one to establish this plan.
The implementation of the new technologies of Smart Grid will bring about
changes that need to be addressed. For example, the connection of small generation
plants on distribution feeders brings the possibility of having short circuit currents
in two ways, and therefore the feeders should not be regarded as radial any longer.
Problems with reclosing features should be closely examined to avoid out of syn-
chronism closing. Likewise, the connection of charging stations for electrical
vehicles will change the normal operation of the feeders.
Smart Grid has the great advantage of allowing two-way communication, i.e.,
utility–user and user–utility. This will allow a better and more effective relationship
between the user and the utility. The latter will be able to monitor and control small
appliances of each user. The user will have in turn the great advantage of getting
information regarding the consumption level, new rates available, and load man-
agement schemes. This of course would require powerful communication systems
that need to be flexible and reliable.
1.2 Definitions of Smart Grid
Many definitions have been written to describe Smart Grids. Every utility might
have its own definition. Some possible meaningful definitions are the following.
Smart Grids overview 3

EPRI: the intelligent grid
“A Smart Grid is one that incorporates information and communications technol-
ogy into every aspect of electricity generation, delivery and consumption in order
to minimize environmental impact, enhance markets, improve reliability and ser-
vice, and reduce costs and improve efficiency.”
Xcel energy: the Smart Grid
“While details vary greatly, the general definition of a smart grid is an intelligent,
auto balancing, self-monitoring power grid that accepts any source of fuel (coal,
sun, wind) and transforms it into a consumer’s end use (heat, light, warm water)
with minimal human intervention.
It is a system that will allow society to optimize the use of renewable energy
sources and minimize our collective environmental footprint.
It is a grid that has the ability to sense when a part of its system is overloaded
and reroute power to reduce that overload and prevent a potential outage situation;
a grid that enables real-time communication between the consumer and utility
allowing us to optimize a consumer’s energy usage based on environmental and/or
price preferences.”
DOE (department of energy) definition
“An automated, widely distributed energy delivery network, the Smart Grid will be
characterized by a two-way flow of electricity and information and will be capable
of monitoring everything from power plants to customer preferences to individual
appliances. It incorporates into the grid the benefits of distributed computing and
communications to deliver real-time information and enable the near-instantaneous
balance of supply and demand at the device level.
People are often confused by the terms Smart Grid and smart meters. Are they
not the same thing? Not exactly. Metering is just one of hundreds of possible
applications that constitute the Smart Grid; a smart meter is a good example of an
enabling technology that makes it possible to extract value from two-way com-
munication in support of distributed technologies and consumer participation.”
The BC hydro definition of Smart Grid
“Smart Grid refers to a modern, intelligent electricity transmission and distribution
system that incorporates traditional and advanced power engineering to enhance grid
performance and support a wide array of functionality for customers and the economy.
In other words: modernization and automation of the current power delivery system.”
In summary, Smart Grid refers to a sustainable modernization of the electricity
grid, integrating information and communication technologies to intelligently
manage and operate generation, transmission, distribution, consumption, or even
the electric energy market. This concept is illustrated in Figure 1.2.
TheSmartGridcomponentscomprisemanyoralmostalloftheelementsoftheutility
andtherelationshipsamongtheelementsthatconstitutethem.Figure1.3includessomeof
these elements, like smart meters, generation, transmission, substation, and feeders.

1.3 Benefits of the Smart Grid on distribution systems
The benefits of implementing an Smart Grid are many. They can be summarized in
the following categories.
Electrical
components
IT
Smart
Grid
Communications
Figure 1.2 Smart Grid concept
Smart
Grid
Smart meters
Smart generation Smart feeders
Smart substation
Smart transmission
Figure 1.3 Smart Grid components

1.3.1 Enhancing reliability
The Smart Grid dramatically reduces the cost of power disturbances. This can be
achieved by means of system reconfiguration using switches placed along the
feeders. Communications and control technologies greatly help one to isolate faults
and allow a faster restoration of service.
1.3.2 Improving system efficiency
The reduction of losses in electrical systems, both technical and nontechnical, is a
purpose of every utility in the world. It not only reduces the demanded power but
also contributes to the environment. The reduction of system losses results in
capital deferral that gives an attractive payback of the investments. Power capaci-
tors, voltage regulators, and proper design criteria are required to achieve this.
1.3.3 Distributed energy resources
Construction of generation plants at the user level is more frequent every day.
These sources are referred to as distributed generation or distributed energy
resources and are getting much attention from government authorities and envir-
onmental institutions as they reduce the pollution levels that some plants have, in
particular those burning coal and oil. Distributed energy resources also contribute
to better operating conditions of distribution systems as they are sources connected
directly to the users’ loads, increasing control of the voltage.
1.3.4 Optimizing asset utilization and efficient operation
Real-time data makes it possible to more effectively utilize assets during both
normal and adverse conditions and to reduce the costs of outages. This results in a
longer service life of the assets.
1.4 Maturity Models for Smart Grid applications
Utilities are aware of the need to implement Distribution Automation and Smart
Grid programs. It is easy to appreciate the various individual efforts being
made, given the number of existing applications. However, there is a lack of
definite procedures and recommended practices to help utility organizations
establish an order of priority in their implementation and development of these
technologies.
Developing a Maturity Model is important for modern grid management and
for selecting the best way of creating a sustainable path toward integration. This
involves tools such as having a common strategy and vision, which not only helps
in the development of an organized work plan but also allows for the imple-
mentation of profitable projects as is needed.
The Maturity Model helps utilities to implement Smart Grid application by
prioritizing tasks and measuring the progress achieved. It also helps one to identify the
characteristics of the organization by designing a roadmap and by promoting the

exchange of common terms among internal and external actors. All share experiences
with the community and prepare the organization to undertake the required changes.
Maturity Models, very common in information technology (IT) organizations,
help an organization assess its methods and processes according to management
criteria. The key to achieving a Maturity Model is a good strategy and a good vision
in the Smart Grid context. The Maturity Model covers three major elements:
communications, IT, and electrical components.
This chapter discusses the joint efforts among different entities that have come
together to produce interesting procedures and schemes to aid organizations in
using the most appropriate solutions for their requirements.
1.4.1 Smart Grid Maturity Model
The Smart Grid Maturity Model (SGMM) is a tool that provides the basis to help an
organization guide, evaluate, and improve its efforts to best select applications of
Smart Grid in order to achieve a proper transformation and modernization. From a
methodological standpoint, the model allows one to create a map defining the task
and technologies, to identify gaps in the strategy and execution, to support business
opportunities that promote Smart Grid projects, to delineate the organization vision
and strategy, and to evaluate alternative solutions and future goals that will help
guide the future of the electric network.
1.4.2 Benefits of using a Smart Grid Maturity Model
In today’s competitive world, the industry demands that organizations strive to
achieve sustainable improvements and repeatable and scalable procedures and to
promote improvements within an organization. Maturity Models were initially
intended to be applied in the software development industry, driven by the neces-
sity of evaluating various organizations under identical parameters. These models
gave the possibility of developing improved planning, engineering, and governing
practices to guarantee higher quality levels in both processes and results.
Many organizations approved the use of the Maturity Models in electrical uti-
lities, considering the successful experience in the software industry. It allowed then
one to determine the development level of networks and to visualize the gap between
the current and the future situation. From this the best solutions can be proposed.
Maturity Models must be combined with an entire work methodology to identify
the standards and technical solutions that will be considered in developing the Smart
Grid roadmap. Maturity Models also support the implementation of applications.
The methodology has three goals: first, to identify the entity’s current devel-
opmental state from an Smart Grid perspective and the desired state expressed as a
maturity level. Gap analysis is then employed to obtain a simplified list of required
steps; second, a cost–benefit analysis to determine which Smart Grid solutions are
financially feasible; third, to arrange and describe the user requirements with use-
cases based on the financial evaluations previously approved by the executives.
A robust model needs to recognize not only management activities being
carried out at the individual project level, but also those activities within an

organization that build and maintain a framework of effective project approaches
and management practices.
By undertaking a maturity assessment against an industry standard model, an
organization will be able to verify what they have achieved, where their strengths
and weaknesses are, and then to identify a prioritized action plan to take them to an
improved level of capability.
1.4.3 Genesis and components of an SGMM
The best known examples of Maturity Models are those developed by Carnegie
Mellon University and IBM. In this chapter, the SGMM, which is one of the most
accepted globally, will be explained.
The SGMM was originally proposed by four electrical utilities of the USA
(Center Point Energy, Progress Energy, Pepco Holdings and Sempra Energy);
DONG Energy from Denmark, NDPL from India; Country Energy from Australia;
and IBM and APQC. In 2009 with the support of the Department of Energy
(DOE), the development of the SGMM was given to Carnegie Mellon. That
University still is responsible for its administration and update. The SGMM is
maintained by the Carnegie Mellon Software Engineering Institute (SEI) as a
resource for utility industry transformation. Carnegie Mellon encourages utilities
to leverage SGMM to ensure that all aspects of transformation planning are con-
sidered, their options are prioritized, and their progress measured as the utilities
implement an Smart Grid structure.
The main organizations using Maturity Models are depicted in Figure 1.4.
1.4.4 Development process of an SGMM
The Maturity Model development process can be carried out with the following
steps:
1. Information gathering in the eight domains of the related organization: In this
stage, the consulting engineer must explore all organization characteristics
from a strategic point of view. Since the Navigator assists the organization in
comprehending the questions included in the evaluation, it is vital that he has a
full understanding of the model.
2. Smart Grid and SGMM concept awareness: The Navigator must be familiar
with the organization; likewise the organization itself must understand the
aspects to be evaluated. The Navigator must prepare the organization to
understand the concepts of the SGMM. Next, the criteria must be adjusted and
the evaluation process must be established.
3. SGMM application: In this stage, the Navigator researches the questions
included in the Maturity Model. The idea is to evaluate the current condition of
the organization as well as the desired future condition. It is vitally important
that the organization responds to questions in a critical, objective, and honest
manner. Also, it is important to involve individuals from the various areas of
the organization, since the model covers all aspects of the organization and
requires that answers are given with an exhaustive view of the problem. If this

Exelon/PECO EPCOR Tokyo Electric
Shanghai
Municipal Electric
Power Co.
Alliander
EDF (UK)
DONG Energy
ERDF (France)
Union Fenosa
NDPL (India)
Zhejiang Energy
CLP (Hong Kong)
Energy Australia
Country Energy
CPFL (Brazil)
EDP (Brazil)
AusNet
CELPE (Brazil)
Enexis
(Netherlands)
Integral Energy
Hydro Ottawa
Exelon/ComEd
VELCO
Allegheny Power
Dominion Power
First Energy
AEP
PHI
Exelon
Duke Energy
SCANA Corp.
East Miss EPA
Ameren Illinois
Ameren Missouri
NB Power
PGN Carolina
PGN Florida
Manitoba Hydro
BC Hydro
Bonneville Pwr.
Portland Gen.
Salt River Proj.
Sempra
Austin Energy
CoServ
CFE
Entergy
Glendale WP
Detroit Edison
Integrys
PGE
Toronto Hydro
Tucson Electric
Power
Xcel Energy
Software Engineering Institute
Burbank Water
Power
Carnegie Mellon
Figure 1.4 Some organizations that use the SGMM (taken from the Carnegie Mellon Software Engineering Institute)

is not the case, key points will be missed and efforts may be focused on irre-
levant aspects. It is recommended to reevaluate after the first model attempt.
4. Final results: Results are obtained regarding the actual condition of the orga-
nization and the future condition. The results help identify gaps that must be
filled in order to reach the desired condition. The cost and time required to do
so should be carefully analyzed to assure the viability of the project. If the gap
is large, a viable economic solution may be to extend the time or reduce the
scope of the future vision.
1.4.5 Levels and domains of the SGMM
The characteristics and capabilities of an organization can be determined with the
help of the Definition Matrix of SGMM as proposed in a document entitled
“SGMM Model Definition. A framework for smart grid transformation” Version
1.2 of September 2011 of the Software Engineering Institute of the Carnegie
Mellon University. The Definition Matrix of SGMM is composed of six levels in
eight maturity domains.
1.4.5.1 Maturity levels of SGMM
The SGMM has six maturity levels that represent well-defined states. Each one
describes the capabilities and the characteristics of the organization to achieve the
Smart Grid vision regarding efficiency, automation, reliability, energy savings,
interaction with the user, integration of distribution energy resources, and access to
new opportunities of the business.
The lowest level (level 0) represents the default position of the organization
when the study starts. An organization operating in a traditional way without
modernization will be at this level. It is important for an organization to evaluate its
condition to establish the future vision in a predefined time interval. Since level 0
represents the starting condition, the model does not have precise characteristics for
this level.
● Level 1: It shows that the organization is in the starting process and exploring
the Smart Grid technologies. At this level, the organization has a vision but
does not have a clear strategy. At this level, the organization is capable of
communicating its vision to the community and industry.
● Level 2: It shows the organization has a defined strategy and that it is already
investing to attain the modernization of the electrical network. At this level,
tests are performed with the business case already implemented, to assess the
changes in the organization.
● Level 3: The organization integrates its Smart Grid program with the operating
departments. The procedures should be made repeatable and the information
should be shared within the whole organization.
● Level 4: The functionality and benefits of Smart Grid can be assessed. The
organization performs analysis and makes corrections on real time.
● Level 5: The organization is on a permanent innovation state, develops stan-
dards, and improves procedures. The organization becomes a leader of the

industry. The vision and strategies of the organization fulfill national, regional,
and local interests.
The organization will be in a higher maturity level when the implementation of
changes starts. Each organization has to establish its own target maturity levels
based on its own operating system, strategy, and timeline. It is obvious that higher
levels of maturity in the model indicate a successful adoption from its grid mod-
ernization efforts. The target level is not the same for each organization. So
achieving any level could be appropriate to an organization but not to other.
1.4.5.2 Domains of the SGMM
The SGMM has eight domains, the description of which is presented in the fol-
lowing paragraphs:
The Strategy, Management, and Regulatory (SMR) domain establishes the
internal procedures of performance and government of the organization and
encourages support relationships with the groups responsible to implement the
vision and strategy.
The Organization and Structure (OS) domain represents the capabilities and
characteristics that allows an organization to plan and operate in order to achieve an
Smart Grid in place.
For the transformation efforts to be successful, the organizational structure
must promote and reward the planning and operation in various functions. This
domain focuses on changes in communications, culture, structure, training, and
education within the organization. Maturity in this particular domain evidences an
increased organizational proficiency to develop their decision-making initiatives
focus on fact-based decision to meet its Smart Grid goals. Additionally, it exhibits
the general vision of individuals committed to reach the Smart Grid goals.
The Grid Operations (GO) domain represents the functional practices that
support reliable, safe, and efficient electric network operations. The organization
employs new automation and communication solutions to improve key network
elements view and decrease control action response time. The information gathered
from implemented Smart Grid solutions provides organizations, which have suc-
cessfully achieved high maturity levels, with valuable information for automation.
Additionally, this enables managing of power flows to reduce losses and maximize
generation at reduced costs. It also allows higher levels of automation and a larger
view of the entire system. On the other hand, response times improve in commu-
nications and control avoiding cascading failures throughout the system. The ben-
efits of such capabilities allow for larger grid improvements to reach the goal of
serving customers with high-quality power, diversified generation, maximized
asset utilization, and efficient operations.
The Work and Asset Management (WAM) domain represents the organization
capabilities in managing assets and personnel. Maturity in the domain reflects
improvements in predictive and reactive maintenance resulting in improving relia-
bility, safety, and efficient operations. Advances in this domain represent an incre-
mental ability to utilize information obtained from Smart Grid implementations to

reduce causeless maintenance and out of service time, identify failure origin and
indicate corrective actions, identify failures beforehand, minimize problem identi-
fication and solution time, and improve personnel resources and planning results.
The Technology (TECH) domain focuses in utilizing IT infrastructure that
serves as a base to develop and supports services that open new markets. It reflects
compliance with relevant standards and integrating a strategic technology to
connect and support various data sources and users (applications, systems, and
persons).
Advances in the technology domain represent compliance with industry and
government standards and integration of applications in Smart Grid with over-
whelming data. The utilization of the IT structures promotes new business solutions
and promising new markets.
The transformation to Smart Grid provides benefits to the organization that
requires efforts beyond the acquisition of new Smart Grid technologies that can
provide a positive or negative support to the organization’s efforts to materialize
their Smart Grid plans. Smart Grid involves several technologies like wide-area
monitoring, two-way digital communications, and advanced control. This com-
prehensive technological platform developed through advanced engineering and
organization business initiatives requires processing large data sources and control
systems that comprehend current Smart Grids and future applications.
The Customer (CUST) domain represents the organizational capabilities and
characteristics that enable customer participation toward achieving the benefits of
the Smart Grid transformation. The participation could be passive (the utility
manages customer loads and select the power source) or active (provides tools to
customer allowing them to manage the usage, sources, and energy cost based on
cost and available options in the market).
Achieving important levels of maturity in the CUST domain represents big
benefits for customer allowing them to decide and manage power usage selecting
from different sources and energy cost, maintaining network security, and pro-
tecting customer privacy. Additionally, exemplifying high levels of maturity in the
domain represents organizational ability to fulfill utility, regional and network wide
goals, with the use of modern Smart Grids, in regards to grid stability, energy
efficiency, peak load reduction, green energy integration employing distributed
generation while minimizing the usage of foreign resources.
The Value Chain Integration (VCI) domain exhibits the utility potential to
advance in reaching the goals set to successfully capitalize the Smart Grid initiatives
by integrating the different utility departments with the production and delivery of
energy demands. Smart Grid automations go beyond traditional boundaries (substation
automation) offering innovation in load management, distributed generation, and
market operations. Smart Grid serves as a platform for planning, implementing, and
energy management from generation to final user consumption.
As a result of environmental concerns and the need for increased efficiencies,
market forces and regulatory bodies will again force the industry to change, pro-
viding new opportunities for organizations with Smart Grid competence and
causing new value chains to emerge. Automation will extend beyond traditional

boundaries and across the entire value chain to provide opportunities for innovation
and efficiencies in load management, distributed generation, and market structure.
As utility matures, the cooperative planning, implementation, and management of
electricity from the sources of production to end-use consumption will optimize
profitability and improve performance of the utility’s value chain. Networked IT
and data sharing, aligned with value chain business units’ requirements, are critical
for success.
Finally, the Societal and Environmental (SE) domain represents the organiza-
tional capabilities and characteristics that allow contributing to meet social goals
associated with reliability and safety of the electric network infrastructure, type of
energy sources employed, and the environmental impact and quality of life.
Proper application of these social initiatives benefits the organization and
solidifies the connection with users and regulators. Efficient operation enabled by
enhanced Smart Grid solutions represents higher profits while reducing environ-
mental impact. Continued prevention and risk mitigation of network security events
is an important part of Smart Grid implementations.
1.4.6 Results and analysis obtained by SGMM
Once the results of the Maturity Model are obtained (the actual state and the desired
future), a gap analysis is needed to determine what actions to take. Figure 1.5 helps
one to illustrate an example of results obtained by applying the SGMM.
It is important to mention that establishing a high future condition is not pre-
cluded by a low present rating. On the other hand, not aiming for a level of 5 in a
particular domain does not mean that the organization is not focused on the Smart
Grid technology. It is possible for a business model not to involve all aspects in the
domain or for the organization not to consider it profitable to improve their level in
Strategy,
Management,
and Regulatory
5
4
3
2
1
0
Organization
and Structure
Grid
Operations
Work and Asset
Management Technology
Desired state in X years
Desired state in X years
Current maturity level
Customer
Value Chain
Integration
Societal and
Environmental
Figure 1.5 Example of results obtained from the SGMM (taken from the Carnegie
Mellon Software Engineering Institute) [1]

that domain. Similarly to the software industry, where ideas are born from Maturity
Models, some organizations consider an optimization condition acceptable in the
processes in a domain.
1.4.7 Example case
The previous methodology was applied to the evaluation of a real utility, which has
around 500,000 users. This utility has a vertical integration as it handles generation,
transmission, distribution, and energy marketing. The results presented refer to
some of the questions used in the SEI-SGMM model, which correspond to the GO
domain and the answers given by the utility.
GO-1.3
Do you have proof-of-concept projects and/or component testing for grid
monitoring and control underway?
(A) No
(B) To some extent, not directly for Smart Grid
(C) To some extent, for Smart Grid
(D) To a great extent (i.e., numerous evaluations underway or completed)
GO-2.3
Aside from SCADA, are you piloting remote asset monitoring of key grid assets
to support manual decision-making?
(A) No
(B) In documented plan including committed schedule and budget
(C) Piloting
(D) Pilots complete or technology being deployed
GO-3.4
Have smart meters become important grid management sensors within your
network?
(A) No
(B) In documented plan including committed schedule and budget
(C) Moderately (40% of a grid is using meters as management sensors)
(D) To a great extent (40%)
It can be observed in the questions above that the degree of difficulty increases
with the levels. At the end, a score is obtained indicating the maturity level of the
organization. Figure 1.6 shows the results from this organization. The redline
indicates the required limits to satisfy the requirements of each level. For the case
of the example, the values are established by a certification institution by using
particular standards.
It is assumed that the criterion of the certification institution to pass the first
three levels establishes a score minimum of 0.6 for each one. After the third level,
higher score is required to approve (level 4 specifically requires at least 0.7 and
level 5 requires 0.8). Once the score gets below one of the defined limits at a level,

the total is then calculated with the summation of the scores obtained up to that
level, including the score of the last one.
The GO domain for this organization indicates a maturity around 1.4, which
indicates that the organization manages higher levels of operations automation and
network optimization processes. The example shows that the current condition (blue
bars) only reaches the redline in the first level with a 0.85 score (minimum is 0.6),
and in the second level only 0.55 is achieved. Since the second level is the first level
that does not approve the objective, the equivalent level will be the score summation
up to this point (1.4). According to the results shown in Figure 1.6, this organization
can reach at the most for the GO domain, the third level in 5 years, which could be
acceptable for that company. In that case the total score would be 3.1, which is
calculated from the results of the table (0.98 points for the first level, 0.85 for the
second level, 0.75 for the third level, and 0.5 for the fourth level). The organization
aims to improve its current condition by 1.7 points in a 5-year term for a total of 3.1.
This demonstrates that the organization currently has instituted Smart Grid
initiatives where technologies and equipment have been elected for pilot testing, some
of which may have concluded, and implementations are in process. For example, the
Distribution Automation and the interoperable data system employ tools like CIM.
Once current and future state results have been obtained for the company under
review, an analysis is conducted to evaluate what efforts must be made to reach
such condition. It can also be defined based on the conditions the model expects for
the particular level. For the particular example, efforts to reach the desired level
must focus on the following:
● The organization must have functional-level approved business cases for
improvements in the employee resources and Smart Grid assets in order to
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
1 2 3
Levels
4
Future level
Current level
5
Figure 1.6 Example of results in Grid Operations (GO) domain

determine necessary changes in abilities of management personnel and assets,
guaranteeing increased productivity, and better prediction of events. They are
designed to reduce maintenance due to faults and optimization of life cycle
costs, ensuring availability. For the expected level, the business cases do not
need to be integrated with the rest of the organization.
● In the asset management area, the organization must have finalized the remote
supervision usage evaluation. Remote monitoring offers more than the basic
control using SCADA. This implies that a dual real-time communication
channel must be established to obtain detailed asset information, in contrast
with previously used performance reports that provided support to conduct
corrective actions.
At this level, the organization must have completed equipment and field
personnel assessment along with focusing assets on the Smart Grid vision of
the organization. This evaluation includes the geospatial equipment to connect
assets with their geographical location. An example would be the field crew
integration with the remote monitoring communication system.
● The organization should invest in technologies to support asset monitoring and
field crew performance. A documented plan must be established to explore Smart
Grid capabilities in order to create inventories and provide for event record
keeping and asset follow-up. The equipment history should include tendencies
and profile information based on actual data. Asset supervision must be devel-
oped by trial testing, and an integrated view of the GIS, state, and connectivity.
● Additionally, the organization should develop a strategy for field crew opera-
tions with the aim of generating a significant impact on the organization. It
means that the organization has recognized the need to optimize mobile assets
with specific performance objectives. Ideally, the field crew strategy must be
interconnected with smart networks for higher performance.
● The organization should have started implementing Smart Grid solutions with
asset management and field crews to employ the information available.
● The organization must have performance data, tendency data, and event con-
trol for at least 25% of individual components. Computer systems are SCADA
and Remote Terminal Unit (RTU); physical elements include breakers, trans-
formers, meters, etc. that support generation, transmission, and distribution.
● A maintenance plan must be implemented for a small percentage of equipment
(smaller than 25%) to pilot the maintenance and replacement plans that will be
developed based on real-time data obtained from an asset supervision program.
This allows equipment capacity prediction and prevents damage to the system.
It is important to integrate remote asset supervision with asset management
while they are both in the planning stages. Integration at this level might be the
ability to automate the order being processed and to relocate the crews based
on the requirements in the network. GIS integration with the asset supervision
system may be conducted based on location, state, and interconnectivity in
order to improve the visual operability in at least one type of asset.
● The organization must make an effort to have a follow-up process with some
level of automation for a small percentage (around 1%–25%) of assets from

when they leave the factory until they reach their destination. The follow-up
must include information like asset location, usage state, scheduled main-
tenance date, and end-of-service date. Bar code and radio frequency identifi-
cation are among the available technologies to accomplish this.
● The organization must have a documented plan to develop an asset investment
model for key components based on Smart Grid data that allows integration
and developments in asset control.
Table 1.1 summarizes the maturity level in each of the domains discussed in the
model for this example, and Figure 1.7 shows a graphical representation of this
score. Based on the results obtained, an analysis will identify the gaps to be
improved. The distance from actual to future in the evaluated conditions represents
Table 1.1 Example of results after applying the SGMM
Domains Current maturity level Future maturity level (5 years)
SMR 2.2 4.7
OS 2.6 3.6
GO 1.4 3.1
WAM 1.3 2.7
TECH 1.5 3.5
CUST 2.2 3.2
VCI 1.6 2.5
SE 1.5 3.5
Mean maturity level 1.80 3.36
0.0
1.0
2.0
3.0
4.0
5.0
SMR
OS
GO
WAM
TECH
CUST
VCI
SE
Future maturity level (5 years)
Current maturity level
Figure 1.7 Graphical example of results after applying the SGMM

the efforts required to reach the desired future condition. The larger the gap
between actual and future conditions (radar chart area differences), the more
aspects need to be improved. Based on the estimated time and budget, necessary
efforts must be defined and the probability of success evaluated.
1.5 Prioritization in Smart Grid projects
The decision of which projects have to go first is hard making inside any utility.
Cost–benefit analyses are the most popular methods for making these decisions,
which is discussed in the next section. Nonetheless, these methods are difficult to
use when social and environmental impacts play an important role while evaluating
projects. A list of different techniques is shown in the following pages.
Smart Grid evaluation system for the modernization of the electrical systems
explained in this section considers the structure of the SGMM.
The structure of the Smart Grid decision problem considered in this paper
consists of eight criteria and four subcriteria. The number of alternatives can vary,
though it is recommended not to be greater than ten due to the number of pair
comparisons needed.
The list of criteria for Smart Grid decision problems is based on the domains of
the SGMM developed by Carnegie Mello University mentioned in the previous
sections as shown in Table 1.2.
The list of subcriteria for Smart Grid decision problems is based on the type of
benefits related to the Smart Grid, presented by the US Department of Energy
(DOE) (Table 1.3).
Table 1.4 illustrates some of the alternatives needed to develop an integral
Smart Grid into any utility. These alternatives are an example of some projects that
must be evaluated in accordance with the SGMM results. Each alternative will be
explained briefly afterward.
A1. Vision and strategic planning
Utilities must identify their needs and set their roadmap for the sequential
implementation of new Smart Grid processes and technologies, based on a
Table 1.2 Criteria for prioritizing Smart Grid projects by using the AHP
Item Criteria
C1 Strategy, Management, and Regulatory (SMR)
C2 Organization and Structure (OS)
C3 Grid Operations (GO)
C4 Work and Asset Management (WAM)
C5 Technology (TECH)
C6 Customer (CUST)
C7 Value Chain Integration (VCI)
C8 Societal and Environmental (SE)

strategic and comprehensive vision that includes an understanding of the cur-
rent state, resources, and future status to be achieved.
A2. Business architecture
A structured approach that will allow each company, from a strategic point
of view, to understand and meet the needs of the Smart Grid project from an
integral perspective, considering the business domain, data, planning, appli-
cations, and technological infrastructure.
A3. Assets and work force management
Represents the organizational capabilities and characteristics that support
the optimal management of assets and work force resources.
A4. Physical and cyber security
Security must be inherent in the development of intelligent networks
throughout their life cycle to ensure the integrity of the system. The data security
has the privacy, integrity, and reliability of the same, and the access to the net-
work refers to the authentication and identification of resources and users.
A5. AMI
Electricity meters that use two-way communication to collect use data of
electricity and deliver information to customers. It allows utilities to balance
Table 1.3 Subcriteria for prioritizing Smart Grid projects
Item Subcriteria
C11 Economic benefits
C21 Power quality and reliability benefits
C31 Environmental benefits
C41 Security benefits
Table 1.4 Alternatives proposed for reaching the objectives of Smart Grid
projects
Item Alternatives
A1 Vision and strategic planning
A2 Business architecture
A3 Assets and work force management
A4 Physical and cyber security
A5 AMI
A6 Two-way communication
A7 Energy efficiency
A8 Advanced distribution automation
A9 Microgrids
A10 Distributed generation
A11 Energy storing
A12 Demand site management
A13 Transmission automation
A14 Smart mobility
A15 Smart street lighting

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