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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Systematically introduces self-healing control theory for distribution networks, rigorously supported by simulations and applications * A comprehensive introduction to self-healing control for distribution networks * Details the construction of self-healing control systems with simulations and applications * Provides key principles for new generation protective relay and network protection * Demonstrates how to monitor and manage system performance * Highlights practical implementation of self-healing control technologies, backed by rigorous research data and simulations
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Seitenzahl: 387
Veröffentlichungsjahr: 2017
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Table of Contents
Cover
Title Page
Foreword
Preface
1 Overview
1.1 Proposal of Smart Grid
1.2 Development Status of China’s Power Distribution Network Automation
1.3 Development of Self‐healing Control Theory
2 Architecture of Self‐healing Control System for Distribution Network
2.1 Characteristics
2.2 Structure of Self‐healing Control System
3 Advanced Application Software of Smart Dispatching and Self‐healing Control for Power Distribution Network
3.1 Design Principles of Application Software for Smart Dispatching Platform
3.2 Overall Structure of Automation System for Power Distribution Network
3.3 Smart Dispatching Platform Functions
4 A New Generation of Relay Protection for Distribution Networks
4.1 Principles and Application of Network Protection for Distribution Networks
4.2 Adaptive Protection
4.3 Networking Protection for Distribution Network
5 Distribution Network Communication Technology and Networking
5.1 Introduction to Distribution Communications
5.2 Backbone Communication Network
5.3 Distribution Communication Technology
5.4 Communication Networking Method of Power Distribution
6 Detection Management System for Distribution Network Devices
6.1 Significance of Distribution Equipment Condition‐Based Monitoring and Maintenance
6.2 Distribution Network Device Monitoring System and Network Monitoring Management System
7 Implementation of Self‐healing Control Technology
7.1 Principle of Implementation of Self‐healing Control
7.2 Self‐healing Control Method
7.3 Implementation of Distribution Network Self‐healing
8 Pilot Project
8.1 Simulation Analysis
8.2 Pilot Application
9 Development Progress of Smart Grid in the World
9.1 Introduction
9.2 Current Situation of Chinese Smart Grid: China’s National Strategy
9.3 Current Situation of Foreign Countries’ Smart Grid
9.4 Energy Network
9.5 Opportunities and Challenges
References
Postscript
Index
End User License Agreement
List of Tables
Chapter 05
Table 5.1 Industrial and commercial Ethernet switch parameters
Table 5.2 Feature comparison of Bluetooth, Wi‐Fi, and ZigBee
Table 5.3 Comparison of communication technologies
Chapter 06
Table 6.1 Transformer failures and cause analysis
Table 6.2 Failures on transformer parts and analysis of their causes
Table 6.3 Oil chromatography gas composition
Table 6.4 Gases from different types of fault
Table 6.5 Coding rule
Table 6.6 Fault type identification
Table 6.7 Public monitoring variant
Table 6.8 Monitoring variant of characteristics
Table 6.9 Characteristics and parameters of broadband sensor
Chapter 08
Table 8.1 System state test items and results
Table 8.2 System management test items and test results
Table 8.3 Self‐healing control test items and results
Table 8.4 Simulation analysis test items and test results
Table 8.5 Test items and results of history query
Table 8.6 Line data
Table 8.7 Capacity of reactive compensation
Table 8.8 Typical profile data collected by system
Table 8.9 Loads of Pingshan substation
Table 8.10 Loads of Hongjiangtai substation
Table 8.11 Loads of Dongmen substation
Table 8.12 Jinniu substation load data
Table 8.13 Load data of Maji substation
Table 8.14 Load data of Liuhe substation
List of Illustrations
Chapter 01
Figure 1.1 Future intelligent power distribution network as described by ADA.
Chapter 02
Figure 2.1 Structure of self‐healing system.
Figure 2.2 How the self‐healing system is embedded in the dispatching automation system.
Chapter 03
Figure 3.1 Overall structure of automation system for power distribution network.
Figure 3.2 Schematic diagram of model management framework.
Figure 3.3 Schematic diagram of information interaction between automation system of power distribution network and external systems.
Figure 3.4 General configuration planning of analysis application software for power distribution network.
Figure 3.5 Schematic diagram of hand‐in‐hand simple fault: (a) overhead line; (b) cable line.
Chapter 04
Figure 4.1 Composition of distribution automation system.
Figure 4.2 System framework of networking protection for a distribution network.
Figure 4.3 Networking bus protection scheme.
Figure 4.4 Networking standby automatic switching scheme.
Figure 4.5 Logic Block Diagram for Automatic Switching Spare Bridge.
Figure 4.6 Frame diagram of communication network for distribution network.
Chapter 05
Figure 5.1 System security measures.
Figure 5.2 MTSP business process model as technical specification stipulated.
Figure 5.3 Network structure of EPON.
Figure 5.4 Signal transmission of EPON system.
Figure 5.5 EPON downlink transmitting principle.
Figure 5.6 EPON upstream transmission principle.
Figure 5.7 Structure diagram of power‐line carrier communication system.
Figure 5.8 Redundancy protection mode of backbone optical fiber.
Figure 5.9 Redundancy protection mode of OLT PON.
Figure 5.10 Redundancy protection mode of entire optical fiber.
Figure 5.11 Redundancy protection mode of OLT PON interface.
Figure 5.12 Hand‐in‐hand protection mode.
Figure 5.13 Distribution communication structure of EPON technology.
Figure 5.14 Architecture of TD‐LTE network deployment.
Figure 5.15 General framework of hybrid networking through multiple kinds of communication technology.
Figure 5.16 Primary wiring diagram of distribution network.
Figure 5.17 Structure diagram of hybrid networking of optical fiber and wireless.
Figure 5.18 Structure diagram of hybrid networking of many kinds of communication network.
Chapter 06
Figure 6.1 Schematic diagram of working principle of oil chromatography monitoring.
Figure 6.2 Commonly seen faults in hydraulic operating mechanism of breaker.
Figure 6.3 Waveform of multiple monitoring values as HV breaker opens.
Figure 6.4 Sequence diagram for opening circuit breaker.
Figure 6.5 Sequence diagram for closing circuit breaker.
Figure 6.6 Curve chart of electric life for some circuit breaker.
Figure 6.7 Curve relation between vacuum arc‐distinguishing chamber and AC flashing voltage.
Figure 6.8 Current circuit‐breaker structural schematic diagram.
Figure 6.9 Equivalent diagram for wideband sensor.
Figure 6.10 MOA full current monitor.
Figure 6.11 Equivalent circuit of MOA valve block under small current.
Figure 6.12 Principle of measuring MOA resistive three‐harmonic current.
Figure 6.13 Principle of monitoring MOA by dual AT.
Figure 6.14 Condition‐based monitoring system based on temperature measurement.
Figure 6.15 Equivalent circuit and phasor graph for lossy dielectric.
Figure 6.16 Wiring diagram for Schering bridge.
Figure 6.17 Schematic diagram of measurement method.
Figure 6.18 Zero‐phase sequence of time by comparison.
Figure 6.19 Equivalent circuit of current sensor.
Figure 6.20 Access method of sensor.
Chapter 07
Figure 7.1 Four controls for self‐healing system.
Figure 7.2 Flow chart for urban distribution network self‐healing control.
f
ex
,
f
re
,
f
se
, and
f
cr
are the limit values in the state of emergency, recovery, abnormal, and alarm conditions.
Figure 7.3 Flow chart of urban distribution network self‐healing control: (a) emergency control, (b) recovery control (c), corrective control, (d) preventive control.
Figure 7.4 Flow chart of self‐healing control based on distributed power and micro‐grid.
Figure 7.5 Islanding control diagram for micro‐grid power supply system.
Figure 7.6 Structural scheme of self‐healing control based on coordination control.
Figure 7.7 Flow chart for distribution network prevention and control.
Figure 7.8 Flow chart for optimal control and strong control: (a) optimal control, (b) strong control.
Figure 7.9 Flow chart of distribution network corrective control.
Figure 7.10 Flow chart for emergency and recovery control.
Figure 7.11 Flow chart of isolation control.
Figure 7.12 Layered frame system.
Figure 7.13 Relay protection device based on graphic logic programming software.
Figure 7.14 Simplified structure of WAMS.
Chapter 08
Figure 8.1 Simulation system information flow.
Figure 8.2 Wiring diagram for simulation case 1.
Figure 8.3 Wiring diagram for simulation case 2.
Figure 8.4 Wiring diagram for simulation case 3.
Figure 8.5 Installation and test site for on‐line supervision system of breaker.
Figure 8.6 System wiring diagram for test area.
Guide
Cover
Table of Contents
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Self‐healing Control Technology for Distribution Networks
Xinxin Gu
NARI Technology Co. LTD
and
Ning Jiang
Nanjing Power Supply CompanyChina
with
Kan Ji, Huiyu Li, Xinhong Qiu, Weiliang Li, Xuejun Ji,
Hongwei Du, Bingbing Sheng, Hai HuangNARI Technology Co. LTD
This edition first published 2017 by John Wiley & Sons Singapore Pte. Ltd under exclusive licence granted by China Electric Power Press for all media and languages (excluding simplified and traditional Chinese) throughout the world (excluding Mainland China), and with non‐exclusive license for electronic versions in Mainland China.© 2017 China Electric Power Press
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.
The right of Xinxin Gu and Ning Jiang to be identified as the authors of this work has been asserted in accordance with law.
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Library of Congress Cataloging‐in‐Publication Data
Names: Gu, Xinxin, 1952– author. | Jiang, Ning, 1965– author.Title: Self‐healing control technology for distribution networks / Xinxin Gu, Ning Jiang.Description: Singapore ; Hoboken, NJ : John Wiley & Sons, 2017. | Includes bibliographical references and index.Identifiers: LCCN 2016038230 (print) | LCCN 2016054149 (ebook) | ISBN 9781119109334 (cloth) | ISBN 9781119109358 (pdf) | ISBN 9781119109365 (epub)Subjects: LCSH: Wireless communication systems–Quality control. | Wireless communication systems–Automatic control. | Computer networks–Management. | Self‐organizing systems.Classification: LCC TK5103.2 .G79 2017 (print) | LCC TK5103.2 (ebook) | DDC 004.6–dc23LC record available at https://lccn.loc.gov/2016038230
Cover Design: WileyCover image: Michael Siward/gettyimages
Foreword
This book has its origin in an R&D project designated by the Science and Technology Department of the State Grid of China – that is, the self‐healing control system for urban power grid – and draws on our experience in the process of research.
The idea of a self‐healing project began in late 2006, when final conclusions and reflections were made after the first trial of distribution automation. Many attempts have been made at large‐scale pilots of Chinese distribution automation, from the end of the last century to the start of this century. Owing to the undeveloped nature of technologies, the successful cases were few. So, domestic electric power enterprises have not been motivated to carry out distribution automation, and all chose to reflect on and watch the development trend. This was a low‐tide period for the development of distribution automation, and R&D on automation technologies and products remained stagnant.
However, during the 11th Five‐Year Plan, as China’s economy grew rapidly, there were increased demands on power load intensity, complex power supply modes, and reliability. The demand for electricity could not be satisfied, due to the development level of the distribution network at that time.
The Technology Department of the State Grid Corporation of China, with the support of head office, implemented urban network planning and renovation, in order to promote coordinated development between power grid and cities, aimed at exploring solutions to problems existing in the distribution network and automation system, and with a new direction for distribution automation – especially for urban power grids.
During the project research, China suffered a serious and rare natural disaster in 2008 in the form of the Sichuan earthquake, which covered large areas of China, lasted for a long time, and caused great losses. In areas worst hit by the disaster, towers of the backbone transmission lines fell over and the lines broke, leading to water and power outage across nearby cities. The problems that the power grid faced suggested defects existing in the urban network back then. Once there is a breakdown in large‐scale power grid under extreme weather conditions, power outage will spread across an entire area. Urban power grids bear most of the power loads of cities, so national political and economic security are involved, as well as the lives of hundreds of thousands of households. Once large‐scale power failures occur in an urban power grid, many areas will be affected and suffer from great losses. The grid structure, power source structure, and corresponding distribution automation are essential, and research on self‐healing systems has become increasingly important.
Research on a self‐healing control system project for urban networks was ended at the time the State Grid Corporation of China launched the smart grid in 2009. So, the members of the research group had the opportunity to participate in smart grid research, and this book was written with the aim of offering a platform for smart grid research and discussion both at home and abroad, exploring self‐healing theory and methods in practice.
Our thanks go to the State Grid Corporation of China and the State Grid Electric Power Research Institute for their involvement and support.
Following expert advice, this English version of the book has added Chapter 5: Distribution Network Communication Technology and Networking (invited contribution by Mr. Hai Huang) and Chapter 9: Development Progress of Smart Grid in the World.
Xinxin Gu
Preface
China currently has the world’s biggest energy network and energy utilization terminal, and the next two decades will witness a rapid development of industrialization and urban sprawl. Demand drives the development of the Chinese smart grid, as well as new developmental patterns such as energy peak‐load regulation, new energy storage systems, and cyclical utilization of resources, smart management of energy utilization terminals, and intelligent network services.
Energy and the environment lie at the heart of world challenges in the 21st century. To respond to such challenges, it is a common choice for all countries to seek to tap and utilize renewable resources. Against the current backdrop, the power industry came to realize that new energy access is getting more and more difficult if it is based simply on traditional and conventional technologies and measures. The Chinese power industry faces new challenges, and the contradiction between electric power development/resources and the ecological environment is increasingly serious. China will stay committed to reaching the twin goals of non‐fossil energy accounting for 15% of primary energy consumption and emissions of carbon dioxide per unit reducing by 40–45% by 2020 compared with 2005, and further seek to develop green energies such as hydroelectric energy, wind power, and solar energy. Smart grid is the only solution to the large‐scale development of resources, such as wind power and solar energy, and ensures the large‐scale access, transmission, and absorption of renewable energies over long distances, distributing energy nationwide in a more efficient way.
The Ministry of Science and Technology, in its 12th Five‐Year Plan for the industrialization of major science and technology, has demonstrated clearly that its overall goal is to make great breakthroughs in core technologies, such as large‐scale intermittent new energy grid‐connection and energy storage, smart distribution and utilization power, large‐scale grid smart dispatching and control, intelligent equipment, establishing a technology system and standard system for intellectual property protection, establishing a complete production chain, basically completing a smart grid featuring informatization, automation, and interaction, and upgrading the Chinese power grid to be efficient, economic, clean, and interactive. During the timescale of the 12th Five‐Year Plan, China established a UHV backbone structure covering the main energy bases and load centers. At the same time, China worked to promote intelligence in all aspects of a smart electric power system and build a comprehensive and smart service network covering most areas of China.
Self‐healing technology is one of the core technologies of smart grid, and has been the subject of intensive interest in the field of world power systems. This book was written based on the authors’ own experiences from a self‐healing control system project for an urban distribution network, and experience and practice in the study and construction of smart grid. The book is being published to advance the research and establishment of China’s smart grid and to provide a reference for researchers, developers, and technicians on the subject.
Ju PingHohai University
1Overview
1.1 Proposal of Smart Grid
Since the 1980s, great changes have taken place in computer, information, and communication technologies. With the continuous penetration of new technologies and materials, the electric power system – which is considered a traditional field of technology – is now facing great changes. The great change that is going to take place immediately is generated by the demand of users, national security, and environmental protection. On July 8 and 9, 2003, more than 200 experts from American Electric Power Industry Equipment manufacturing company, academia, industry organizations, national laboratories, federal and state government agencies met for the National Electric System Vision Meeting in Washington D.C.
The topics below were discussed in the meeting:
goals for the years 2010, 2020, and 2030 to achieve the vision;
challenges that may be faced in achieving the above goals and vision;
research, development, and demonstration needed for facing challenges;
time schedules for research, development, and demonstration.
At that time, the challenge for the American electric power supply was that the aged power grid and electrical facilities failed to meet the demand for economic development and held the economy back. Particular attention must be paid to this serious problem.
Power transmission and distribution play a significant role in electric power supply, and the market and America’s economy (to a value of 10,400 trillion USD) are greatly dependent on a secure and reliable electric power supply. With the ever‐increasing requirements of users for electric power supply, considering national security, environment protection, and energy policies, it is necessary to set out a strategy for power grid reformation: integrated approaches for market, policy, and technology; electric power system research, development, and demonstration; policy analysis and modeling; and coordination between federal, regional, and state departments. The aim is to form a competitive North American electricity market through plan “Grid 2030,” providing sufficient, clean, efficient, reliable, and affordable electric power at any time and in any place, leading to the world’s most secure electrical service.
All the above services are provided, based on:
Power backbone network – to achieve power exchange between the US East Coast and West Coast.
Regional Internet power grid – a strong supplementary to the power backbone network.
Regional power distribution network – to implement power distribution.
Final US power grid – including communication and control systems.
The conference proposed combining the technology of power grids with up‐to‐date communication, control, and electronic technologies in order to establish a more intelligent electric power system and thus achieve a real‐time self‐healing power grid by 2030 [1, 3].
1.2 Development Status of China’s Power Distribution Network Automation
The pilot work of power distribution network automation that started during the upgrading of urban and rural power grids at the beginning of 2000 lasted for about 2 years. As power distribution network automation equipment and communication technologies are immature, most systems failed to achieve as expected, and the development of power distribution network automation was still not clear.
With the rapid development of China’s economy, however, problems such as high load density of power supply, complex power supply modes, and increasing requirements for reliability of power supply occurred in major cities. Urban power distribution networks have the most concentrated loads, which is of concern for the security of state politics, the economy, and every household; therefore, reliable and safe power supplies are required, especially in major cities. Once an accidental power failure occurs in a major city, great losses will be felt.
In order to change the situation of power distribution networks lagging behind, the State Grid Corporation of China (SGCC) organized and launched 31 major power distribution network projects and an international consultation for Nanjing and Qingdao power distribution networks. These projects are intended to speed up the pace of power grid construction combined with urban development and optimize power grid structure, build a robotic power distribution network, and increase the capacity and reliability of power supply.
Since 2003, we have been studying the application of project “Grid 2030” and new technology in traditional power industries, and what we can learn from this to promote the development of China’s electric power, especially Advanced Distribution Automation (ADA) as researched by the US Electric Power Research Institute (Epri) R&D team, led by Frank Goodman.
ADA is the future development goal of power distribution network automation. It mainly studies and aims to solve the following problems:
improving reliability and power quality;
reducing operating costs;
researching the integration of power distribution networks and distributed power supplies;
researching the coordination between power distribution systems and demand‐side systems;
shortening the time of power outage and recovery;
providing more options for subscribers.
The fields of technology involved in the project include:
design of new intelligent electronic devices (IEDs);
research on low‐cost and multi‐functional static switchgears, sensors, monitoring systems, fault prediction, etc.
Figure 1.1 shows the future intelligent power distribution network described by ADA. The automation system is composed of a synchronous satellite, communication, sensors, intelligent electronic devices, a control substation (local agent), and a distribution control center. The power distribution system is composed of a distribution substation, FACTS, IUT, and DER. It is an ideal, controllable, and adjustable distribution network with a complete system that provides industrial, residential, and commercial consumers with secure, reliable, and high‐quality power supply [2].
Figure 1.1 Future intelligent power distribution network as described by ADA.
1.3 Development of Self‐healing Control Theory
Can the faults of an equipment system, if any, be controlled or eliminated by itself during operation?
Are the faults able to self‐heal like human or animal diseases?
Under the guidance of system science, the “self‐recuperating” treatment principle of modern medicine, including immunization, defense, compensation, self‐healing, and self‐adaptation, can be used as a guideline for research on equipment self‐healing and its application.
Following the self‐healing control principle of an equipment system that aims at prevention and elimination of faults, the electric power system is constantly summarized, perfected, and improved in practice to create a self‐healing control theory of electric power systems.
Modern equipment is becoming increasingly large, high‐speed, automatic, and intelligent. In particular, high‐speed turbo‐machinery, industrial pumps, fans, compressors, centrifuges, and other major equipments that are widely used in the petrochemical industry, metallurgy industry, electric power industry, non‐ferrous metallurgy industry, and other process industries are closely linked to the process of production, and thus form a great system. Should a failure occur in such a system, major accidents and great economic losses may be caused. Since the 1960s, the international engineering science and technology circle has developed equipment monitoring and diagnostic technology; predictive maintenance and intelligent maintenance are gradually being introduced to industrial enterprises and an emergency stop interlock system is widely used, which has played an important role in ensuring safety in production and achieving practical results.
The purpose of self‐healing control research is to change the traditional methods that depend merely on emergency stop and manual maintenance and troubleshooting. Different from device diagnostic technology and predictive maintenance technology, this theory and method focuses mainly on how to provide the equipment system with a fault self‐healing function and the ability to eliminate faults by itself during operation rather than employing manual troubleshooting with a mere emergency stop. Project practice has shown that the occurrence of most failures is a gradual progress, except for a few sudden failures. This means that equipment faults can be prevented by prompt and appropriate actions, once they are found at an early stage.
The occurrence of equipment failure is a gradual process. If the equipment is not designed with monitoring at important links, or it lacks intelligence, we may miss the opportunity to monitor and detect hidden dangers and these hidden troubles in the equipment will develop into failures.
Similar to an equipment system, an electric power system would first trip through the action of relay protection, followed by manual handling in the event of failure. An electric power system is a complex multi‐device system and tripping can often cause multi‐point disturbance; the possible consequences include large areas of disturbance or instability, such as splitting and generator tripping.
The concept of electric power system self‐healing was first proposed in the Complex Interactive System Joint Research Project launched in 1999 by EPRI and the US Department of Energy. Later, the research projects Intelligrid of EPRI and Modern Grid Initiative of US Energy Laboratory both took self‐healing as the main research objective, and deemed it the core technology for ensuring quality of power supply. The self‐healing function has been a hot topic recently.
Self‐healing refers to one function of a power grid that takes advantage of an advanced monitoring system to perform continuous on‐line self‐assessment of power grid operating conditions and takes preventative control measures so as to achieve timely detection, rapid diagnosis, rapid adjustment or isolation, with little or no human intervention. Remove the hidden danger and adjust the operating mode so that the failure can be isolated promptly upon occurrence, and the reconfiguration can be accomplished quickly and automatically; in this way the normal power supply would be unaffected, or affected as little as possible. Like the immune system in our human bodies, the self‐healing function makes it possible for the power grid to protect against various internal and external damages (faults) to ensure secure and stable operation of the power grid and high‐quality electric power.
The power transmission network is designed for a looped network and multiple feed structure, so that one or more components out of service won’t affect the normal power supply of the system. Hence, the self‐healing function on the one hand can achieve on‐line monitoring of electronic equipment and find/remove potential faults by the removal of fault components in time through relay protection and on the other hand can perform on‐line assessment of safety and warning/control so as to avoid widespread blackouts caused by power grid instability.
The power distribution network is user‐oriented. Generally, power is supplied in a radiation mode. Any distribution network fault or power quality disturbance will have an effect on the quality of the power supply. Therefore, the self‐healing function of a distribution network has some characteristics different from that of a transmission network. Self‐healing functions of intelligent distribution networks include: firstly, reducing the duration and frequency of power failures, especially to avoid the problem of short‐time unexpected power failures present in current power grids and increase the quality of power supply; secondly, optimizing the quality of power energy, especially restraining sudden drops in voltage; finally, effectively improving the ability to prevent disaster and damage.
It is necessary to note that the self‐healing function is not a totally new concept in terms of definition and technology; relay protection and automatic safety devices both belong to it. The self‐healing function is developed on the basis of traditional relay protection and automatic safety devices, but is more advanced. Its ultimate goal is to provide an uninterruptable power supply without human intervention.
The research and development/application and dissemination of self‐healing control technology play a significant role in the construction of a smart grid and the improvement of power supply quality.
2Architecture of Self‐healing Control System for Distribution Network
2.1 Characteristics
The self‐healing control system marks great new progress in the fields of network protection and control, and is designed to strengthen the abilities of self‐prevention, self‐adjustment, and self‐recovery. It has two distinctive characteristics:
Preventive measures are taken to detect, diagnose, and eliminate potential failures in time. On‐line monitoring technology is one such important measure.
There is a fault ride‐through (FRT) capability.
Supported by the rich and comprehensive data available by real‐time measurement and monitoring, the self‐healing control technology motivates the power grid to operate through control measures, such as simulation technology, computation of short‐circuit currents, protection‐setting coordination, type identification, and load forecasting. Preventive control technology, used in the case of exceptions, prevents the system from failure and ensures the reliability of the system; the global control technique, during a fault, strives to avoid any power outage or shorten the outage coverage and time needed to restore power; the emergency control technology, in an emergency, would enter protection‐acceleration procedures, initiate standby power, and turn the device from cool standby to heat standby. An emergency control pre‐plan is a series of schemes arranged in several defense lines. The first scheme is carried out when the system is subject to the smallest disturbance; plans are worked out to prevent the system from entering into a fault state.
The final line of defense in emergency control is to recover control for the distribution network by self‐healing control and relaying protection for the distribution network. Large‐scale blackout will be prevented by improving the power output, cutting off part of the load, or even separating the whole distribution network into several temporary islands of power supply. The following technologies may be used:
A configuration and algorithm for optimum operation under normal conditions. When abnormally operated, the failure can be judged from the abnormal conditions or defects detected by an on‐line measuring system of the equipment and distribution network. Later, the system will form a precaution strategy and take preventive measures. It needs to modify fixed values to relay protection on‐line and check/simulate the modified values before the distribution network can enter a healthy state.
An algorithm and technology of prevention and control, an algorithm and technology of pre‐reconfiguration for distribution networks. In case of failure, emergency control measures will be taken, including isolating the faulty areas, reducing the blackout area and time, and reconfiguring the network to accelerate failure recovery.
A strengthening of the coordination among primary, secondary, and automation systems – applying the self‐healing control technology to enhance the reliability of the distribution network.
A self‐healing control system created all‐round through coordination among global digital control, equipment on‐line monitoring, relay protection for the distribution network and switchgear, and embedding advanced applications for self‐healing control into the dispatching system. The self‐healing control helps to ensure continuous power supply by reducing faulty areas and shortening any blackout time.
2.2 Structure of Self‐healing Control System
The self‐healing system consists of a self‐healing control function, data interface, SCADA platform, and system platform, as shown in Figure 2.1. The self‐healing system is embedded in a dispatching automation system by installing an additional self‐healing control data server, system server, and workstation, as shown in Figure 2.2.
Figure 2.1 Structure of self‐healing system.
Figure 2.2 How the self‐healing system is embedded in the dispatching automation system.
According to the security protection requirements for electric power, the electric power system is divided into four zones in order of importance of security. The self‐healing system is at zone I and II, and interconnected with other systems by a physically isolating equipment and network firewall.
3Advanced Application Software of Smart Dispatching and Self‐healing Control for Power Distribution Network
3.1 Design Principles of Application Software for Smart Dispatching Platform
The smart dispatching platform for a power distribution network (namely the automation master station system of the power distribution network) is the main carrier satisfying various application needs in the operation, dispatching, and management of the power distribution network. It is structured with standard and general software and hardware platforms, and is properly provided with various functions based on the scale, practical demand, and application infrastructure of the power distribution network in each region. Meanwhile, the advanced system architecture is certainly proactive, so should be set up based on the principles of standardization, reliability, availability, safety, extensibility, and advancement, following the development direction of the smart power grid.
As one of the core technologies for smart dispatching of the power distribution network, the self‐healing control software includes mainly the following application functions:
optimal operation control strategy in case of normal operation;
preventive control strategy in case of abnormal operation;
global control strategy in case of failure and coordination with relay protection;
emergency control strategy in case of emergencies (including the islanding strategy).
The application software of the automation master station system for the power distribution network is designed mainly on the following principles.
Standardization
Compliance with related international and national standards of software and hardware platforms, communication protocols, databases, and application program interfaces, etc.
Provision of an open system architecture and an open environment, suitable for stable operation on multiple hardware platforms and in such operating system environments as Unix and Linux, etc.
Compliance with IEC 61970 and IEC 61968.
Reliability
The software and hardware products incorporated in the system should be tested by the industrial certification authorities, to be assured of reliable quality.
The key system equipment should be deployed in a redundancy configuration, and a single point of failure should not cause any loss of system functions and data.
The system should be able to isolate the faulty nodes, fault removal should not affect the other nodes in normal operation, and the point of failure should be quickly recovered.
Availability
The system software and hardware and the data information should be easy to maintain, with complete tools for testing and maintenance and diagnosis software.
Each functional module should be flexibly configured, so that their addition and modification do not affect other modules in normal operation.
The human–machine interface should be user friendly, with rich interaction means.
Safety
Compliance with the requirements specified in the regulations on the Safety Protection of Electric Secondary System (SERC No. 5 Order) and the General Planning for Safety Protection of Electric Secondary System.
There should be a complete rights management system to ensure information safety.
There should also be a data backup and recovery system to ensure data safety.
Extensibility
The system capacity should be extensible, to be added on‐line with power distribution terminals, etc.
The system nodes should be extensible, to be added on‐line with servers and workstations, etc.
The system functions should be extensible, to be added on‐line with new software functional modules.
Advancement
The system hardware should consist of mainstream products suitable for the industrial application trend, and meet the development demand in the power distribution network.
The system support and application software should follow the industrial application trend and meet the development demand of application functions in the power distribution network.
The proactive system architecture and design thinking should meet the development demand in terms of the smart power grid.
The supporting platform for the system software should comply with related industrial/international standards; for the master station of a larger system, the server should use the Unix/Linux operating system; the network model should be the ISO‐OSI 7‐layered network reference model, and the network protocol should be TCP/IP‐based.
The real‐time database and the commercial database are combined together, which not only satisfies the real‐time demand on the electric power system, but also reflects the superiority of the commercial database in the management and application of mass data. Standard API interfaces are provided for data access to multiple LANs/WANs, and for data interaction with other information systems (PMS, CIS, GIS, etc.).
Open functions on the application layer only involve those application programs that will not modify the original system configuration when the user’s business process changes. With application extensions added to the parameter configuration, normal use of existing application programs and stability of system functions will not be affected.
3.2 Overall Structure of Automation System for Power Distribution Network
Besides providing the basic functionality for data interaction between the SCADA of the power distribution network and the superior dispatching automation system, the master station software of the automation system for the power distribution network should also satisfy actual demands in terms of the automation master station for the power distribution network, the application of related information management systems, and the automation research and development for the power distribution network, so as to build the application software functions stepwise in order when conditions permit. The overall structure of the automation system for the power distribution network is shown in Figure 3.1.
Figure 3.1 Overall structure of automation system for power distribution network.
The automation master station system for the power distribution network is of a layered component structure, in which the distribution application can be completed on the heterogeneous platform through the bottom operation in the shielding layer of the application middleware. All the software modules must be designed in accordance with such international standards as IEC 61968, IEC 61970, IEC 61850, etc. to realize the standardization of data interaction and sharing with external systems and the plug and play of software products from third parties.
The supporting platform layer is the center of the entire system structure, the design rationality of which directly affects the structure, openness, and integration capability of the entire system. Through further analysis, it can be classified into three layers: integration bus layer, data bus layer, and public service layer. The integration bus layer provides a standardized interaction mechanism among various public service elements, application systems, and third‐party software; the data bus layer provides the proper data access service for them; the public service layer provides various services for all application systems to complete, such as graphic interface and alarm service, etc.
3.2.1 Supporting Platform Layer
3.2.1.1 Integration Bus Layer
Compliant with open international standards such as IEC 61970 and IEC 61968, the integration bus layer provides a standardized interaction mechanism among public services, application systems, and third‐party software, and is the integration basis between the system internals and third‐party software.
The integration bus layer complies with the component principles specified in IEC 61970, and adopts advanced distributed object technology. The distributed object technology, represented by CORBA, innovates the software design method, as it allows objects to collaborate with each other and consequently constitute an organic integrity in the distributed object and heterogeneous network environments. Considering that the CORBA technology is characterized by supporting the heterogeneous systems, various programming languages, and integration legacy systems, it is the core of the integration bus layer for achieving the independence of software and hardware platforms of the integration system, independence of programming languages, position transparency, and ease of modification, maintenance, and migration, etc. The integration bus layer can support components of different granularity, which means that a component can be as large as a whole system, as medium‐sized as an application system, or as small as a service element. Therefore, the integration bus layer not only supports integration with other independent systems from third parties and integration of third‐party applications into the system, but also applies to integration among internal components in the system, so that all kinds of component are organically integrated into an entire system.
The integration bus layer also complies with IEC 61968 and establishes an information‐based exchange mechanism. The integration targeted by IEC 61968 applies to independent application systems not internal system components, as it defines the interface reference model among systems and a complete set of message formats and modes. With the message broker and transfer functions implemented by the message middleware among different application systems, a loose coupling mechanism is provided for the independent application systems in a heterogeneous environment.
In conclusion, the integration bus layer plays a key bonding role which not only provides a standardized interaction mechanism between working service elements inside the system and various application systems and an effective mechanism for close integration of third‐party software into the system, but also finds a reasonable way for the system itself to be integrated with other third‐party independent systems.
3.2.1.2 Data Bus Layer
The data bus layer is composed of a real‐time database, commercial database, and corresponding data access middleware. The commercial database is to store non‐real‐time and accidentally synchronized data and provide an historical data service. It is characterized by high reliability, big capacity, standard interface, and good safety. Relying on the bottom integration bus layer, it constitutes a distributed real‐time database to ensure synchronization of real‐time data.
3.2.1.3 Public Service Layer
The public service layer refers to various kinds of tool providing display, management, and other services to the application software. The public services focus on the general tools, whereas the application software focuses on the business solutions. Various kinds of application demand are sufficiently analyzed and summarized during the service design in order to set up a public service layer meeting all kinds of application demand.
Graphic tool: Provides graphic display/editing and graph–model–library integration functions.
Report tool: Provides a function for preparing various kinds of statistical report for applications.
Rights service: Provides the functions of rights management and assignment by the system administrator to all system users, and offers precise assurance methods for system rights management via a multi‐level management mechanism consisting of functions, roles, users, and groups.
Alarm service: Processes various kinds of alarm/event and sends out the alarm information in a certain way as defined. Meanwhile, it separately records, saves, and prints out all the events, and provides retrieval and analysis services.
Web service: Provides an aII‐area web service, completely maintenance free.
System management: Includes system process management, redundancy configuration management, parameter management, resources management, operation monitoring, etc., providing a complete set of management service mechanisms to help application systems implement their functions instead of self‐implementing their own management mechanisms.
Analysis application service for power distribution network: Provides such analysis application component services for the power distribution network as network modeling, network analysis, power flow calculation, path searching, and load transfer.
Process service: Includes graphical process customization and drive engine of the business process flows.
Form customization: Provides a description of the individual business forms.
The process service and form customization mainly serve the dispatching and operation management of the power distribution network, so that the dispatching and operation management subsystem of the power distribution network can be realized based on the process drive and free form customization.
3.2.2 Application System Layer
The application system layer includes multiple external interfaces for SCADA, FA, GIS data conversion, and other advanced applications, all of which complete their own application functions with the support of integration buses, data buses, and public services, and are also organically integrated together as a whole system.
3.3 Smart Dispatching Platform Functions
3.3.1 Supporting Platform
The supporting platform provides a uniform, highly available, and highly fault‐tolerant environment for the application software. The functions of supporting software include the integration bus layer, the data bus layer, and the public service layer. The supporting platform provides a standard development environment for users.
Database management.
