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IEEE Transactions on Power Systems, Vol. 8, No. 3, August 1993
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ARTIFICIAL INTELLIGENCE IN ELECTRIC POWER SYSTEMS
A SURVEY OF THE JAPANESE INDUSTRY
Saifur Rahinan
Senior Meriibei
Virginia Polytechnic Institute & State University
Blacksburg, VA 24061-0111, USA
Abstract
The major work on the theory and application of artificial
intelligence (AI), which includes expert systems, is going on in the
United States, Europe and Japan. The Japanese electric utility
industry, manufacturers, universities and the government have taken
a focused goal-oriented approach in this regard. The author has
studied the Japanese involvement in this field and visited eight
Japanese R&D laboratories, where he discussed the AI and expert
system related activities (in the power industry). This paper provides
a comprehensive look at the combined Japanese effort. The current
topics of interest are: (i) AI and its application in power engineering;
(ii) problems in AI applications development and their solutions, (iii)
practical system examples; and (iv) AI applications to power systems
of the future. Out of the 97 papers cited in this paper, 10 were
produced by electric utilities, 10 by manufacturers, 17 by universities
and 60 were joint efforts. This shows the level and importance of joint
collaborative research among the Japanese researchers Even though
they are working on many theorectical aspects of the AI technology
including automated knowledge acquisition and verification, they still
use significant amount of theoretical work done in the United States for
successful prototyping of AI based tools. It is, however, safe to say
that the use of AI tools in the Japanese electric power industry is far
more widespread than what is seen in the United States or in Europe.
1.O Introduction
There has been remarkable progress in the development of
software and hardware for the analysis and design activities in power
system planning, operation and control. However, much still depends
on the judgment of human experts; i.e.. experienced planning and
design personnel capable of making intuitive and efficient decisions
on the basis of the comprehensive knowledge of the prevailing
circumstances.
Expansion of the power system, progress of
technology, high equipment reliability and the resulting shortage of
experience in dealing with faults have caused concern in the industry
that the expertise in the planning and operation of power systems may
be lost as staff retirements rise and replacements are slowed. It is
possible that artificial intelligence (AI) tools can fill this void between
the need for, and the availability of, experts in the future. Expert
systems are powerful AI tools using which the knowledge of experts
can be widely disseminated.
During the last five years there have been significant activities
in applying AI tools to power systems. A number of international
conferences have been organized to specifically address this issue.
The first one, Expert Systems Applications to Power Systems, was held
in Stockholm, Sweden in August 1988. The Second Symposium on
Expert Systems Application to Power Systems was held in Seattle.
Washington in July 1989. The third such symposium was held in
In addition, there was the First
Tokyo, Japan in April 1991.
International Forum on Applications of Neural Networks to Power
Systems, held in Seattle, Washington in July 1991
The major work on the theory and application of A I is going on
in the United States, Europe and Japan. The Japanese electric utility
indusiry, manufacturers, universities and the govel-ntnent have taken
a focused goal-oriented approach in this regard The author has
studied the Japanese involvement in this field and visited eight
Japanese R&D laboratories, where he discussed the research
activities related to the AI tool development for the power industry.
This paper provides a comprehensive look at the combined Japanese
effort. In addition to the eight papers/reports cited which repi-eseiit the
direction of research the Japanese powei- industry is pui-suing. 90
papers are referenced which represent all major expert system
related research activities in Japan. A review of these papet-s will give
the reader a detailed look at the Japanese electric power industry,
their research priorities, and above all, the people and corporations
involved in this research.
2.0 R&D in Japanese Electric Power Industry
According to Hiramaya [A-I]. “the R R D comniittee in Central
Electric Power Council, comprising Japan‘s nine utililies, the Electric
Power Development Company (EPDC. a wholesale power comp:tny)
and the Central Research Institute of Electric Power Industly (CRIEPI,
funded by utilities) play a major role in coordinating joint R&D and in
exchanging information on R&D plans arid strategies It also provides
advice on national R&D projects to tlie .lapaneso government (MITI 01the Science and Technology Agency) ”
He also states that, ”for electric energy RRD. the Japanese
government funds about 1,385 million dollars (US) per year (1990), with
almost the same amount provided by the utilities.
This large
government fund is obtained from a special tax paid by consumers as
a part of the electric tarrif, and is allotted to reflect natioiial and global
needs.”
The social concerns and technological advances have added two
new major areas to the utility R&D. One is the protection of the global
environment by using cleaner energy technology, and the other is the
application of information technologies such as artilicial intelligence
and expert systems to power systems, For example, expert systems,
neural network, and soflware development and assistance tools are
both short term and long term elements of major R&D themes in all
major Japanese electric utilites. Detailed discussion about the
application of AI tools to the Japanese power industiy is presented in
section 4.0.
A brief description of the visits to the Japanese
companies, R&D laboratories and a university is presented in the next
section.
3.0 Companies, R&D Laboratories and Universities
Visited
92 SM 397-0 PWRS A paper recommended and approved
by the IEEE Power System Engineering Committee of
the IEEE Power Engineering Society for presentation
at the IEEE/PES 1992 Summer Meeting, Seattle, WA,
July 12-16, 1992. Manuscript submitted January 28,
1992; made available for printing May 13, 1992.
Along with their counterparts in the computer itidustry. who are
focusing on the fifth generation computer, researchers in lhe major
Japanese electric utifities and manufacturers are seriously pursuing
the AI technology - both its theory and application Correspondence
with several Japanese R R D organizations indicated that niiicli more
work is in progress there than is reported in major English language
journals. A large volume of the expert system development work i s
currently directed at the Japanese electric utility and tlie
manufacturing industry. In order to obtain first hand information about
these activities, the author visited several .Japanese R B D
organizations in November 1990 and in Api-il 1991.
These
organizations are listed in the following. DiSctJSsiOliS were held with
a total of 31 engineers and scientists during these visils.
0885-8950/93$03.00 0 1992 IEEE
1212
I. Hitachi Research Laboratory
Toshiba Corporation, Fuchu Works
2.
3.
Mitsubishi Electric Corp.
4.
Tokyo Electric Power Co..lnc.
5.
Kansai Electric Power Co.
6.
Kyushu Electric Power Co.
7.
Central Research Institute of Electric Power Industry
8.
University of Tokyo
This list includes three manufacturers, three electric utilities, a
major power research institute, and a major university. As utilities are
the primary users of AI tools in this industry, and these tools are
primarily produced by the major manufacturers in Japan, it was
decided to survey this select group. The list given above includes
three of the four largest electric utilities and the three largest
commercial developers of AI tools in Japan. A survey questionnaire
was mailed to these six organizations in advance of the visit. Written
and oral responses to this survey are summarized and presented in
this paper. The following section discusses the strategies and
practices of AI applications in the Japanese power industry.
include their desire to operate the system with smaller margins,
increase productivity, quicker fault clearing and service restoration,
better customer relations, and to provide the utility engineer with more
powerful design and planning tools.
In order to address this situation, the Japanese power industry
has embarked upon a large and concerted effort to employ AI tools for
improved system operation and planning. This work began in the
early 80's with the application of AI to simple problems closely related
to the daily activity the engineer/operator was involved in Most of
these early applications were in diagnosis arid operations support.
With the availability of advanced hardware and AI tools, atid the
greater number of personnel trained in such tools, the irange and
depth of applications have been broadened. This has resulted in an
increase of prototype systems as well as practical field applications.
Some of the areas where AI tools are now being applied are as
follows. Papers dealing with such tools are also listed for each
application.
1.
Nuclear power plant 149, 701
2.
Thermal power plant (8, 30, 40, 781
3.
Power transmission line [IO, 21, 36, 631
4.
Power substations [ I , 19, 20, 27, 28, 46, 56, 65, 871
5.
Power system operation and control 12. 7, 9, 11, 14, 15, 17,
22, 25, 26, 31, 32, 33, 34, 35, 37, 38, 39, 41, 42, 43, 47, 57, 62,
64, 66, 71, 801
4.0 Application of AI in the Japanese Power Industry
According to Tanaka et al. [A-61, the Institute of Electrical
Engineers in Japan (IEEJ) launched a research committee for AI
applications in power systems in June 1987. The goal was to
summarize the knowledge engineering environment around expert
systems in power systems. The Society of Electrical Cooperative
Research held an important discussion meeting entitled, "AI
Application to Power Engineering" in February 1988. The Sociely has
had a special committee for AI applications to power engineering
since July 1989. Researchers and engineers from Japanese utilities
have met and carried out a 2-year study on R&D in AI in power utilities.
This activity was completed in September 1990.
There are three platforms which Japanese power industry
researchers can use to promote AI applications. These are: (i)
Society of Electrical Cooperative Research, (ii) R&D Group for AI in
Power Utilities, and (iii) Institute of Electrical Engineers in Japan (IEEJ).
The fact that the power industry engineers are veiy active in AI related
R&D is well represented by their strong participation in relevant
conferences,
For example, the number of presentations on AI
applications at the IEEJ conferences have increased steadily: in 1988
it was 4, in 1989 it was 37, and 48 such papers were presented in 1990
The current topics of interest are:
I.
AI and its application in power engineering today:
2.
Problems in AI applications development and their
solutions;
3.
Practical system examples; and
4.
AI applications to power systems of the future
Additional information can be found in the paper, "Research and
Development on Expert Systems Applications to Power Systems in
Japan", by Tanaka, et al. [A-61. This paper is authored by six
individuals from the utilities, manufacturers, university and the central
power research institute in Japan. It, therefore, gives a sense of
common perspective among the developers and users of expert
systems in Japan.
4.f Need for AI Applications
The need for AI tools is very high in the Japanese power
industry. A combination of several factors, somewhat unique to Japan,
has caused this to happen. New engineers and plant operators,
employed in large numbers for the post-World War I1 reconstruction
of Japan, are now retiring. And due to the consistent efforts of the
industry over the last three decades, both the equipment and the
power grid have become very reliable.
As a result. the new
engineersloperators are not getting enough exposure to faults and
other related system problems This has raised concern among the
utility managers that the new engineers are probably not being
adequately trained to face the difficult task of operating a power
system in the event of a major fault. There are also several other
reasons for applying AI tools to power systeni problems. These
6.
Power distribution [12, 13, 16, 44. 48. 53, 54, 74, 77. 82. 881
7.
Power system planning [3, 4, 5, 6. 18, 23, 24, 67)
8.
Construction and civil engineering [58]
9.
Environment (291
IO. Marketing [E61
This list shows that the Japanese researchers have paid
attention to both the development of AI tools, and the widespread
application of such tools. Initial focus was placed on the repelitive
tasks of system operation, fault diagnosis and restoration Gradually,
with the development of advanced software tools and powerful
hardware, the applications are moving towat-ds the more complicated
task of power system planning.
4.2 Strategy to Promote AI Applications
Once the Japanese power industry R&D managers decided that
AI tools were potentially beneficial to the efficient operation of their
systems, they set out to find out more about activities in other
countries, particularly in the United States. For example, Uenishi [A-8]
of Kansai Electric Power Company reports on his visit to the United
States in December 1986 to study the then current developments
relating to Al. He visited 13 companies and research laboratories
where advanced AI research and applications development were
being carried out at the time. This experience proved useful for his
study o f technical developments related to Al.
Starting in the mid to late eighties there have been organized
activities in Japan to study the benefits o f AI tools. Activities of the
Institute of Electrical Engineers in Japan, the Society of Electrical
Cooperative Research, and CRlEPl in this regard have already been
discussed earlier in this section. These resulted in many collaborative
research and development activities among Japanese utility,
manufacturer and university researchers. In order to demonstrate the
activities of Japanese researchers, 101 selected papers by Japanese
authors are cited in the bibliography in section 8.0. These papers
represent all major power system ot-iented AI related research
activities in Japan.
4.3 Collaborative Research Activities in AI
Following the strategies and joint activities listed earlier, the
Japanese utilities, manufacturers, and universities have combined
their efforts to develop functioning AI tools. Utilities identify the
problem and provide the domain experts, while the manufacturers
provide the knowledge engineers, the software and the hardware. The
universities provide engineers and scientists with some training in the
field. They also conduct software testing and work on new concepts
and techniques.
In order to document the collaborative research activities o f
Japanese researchers, the citations in the bibliography (section 8 0)
have been coded according to the following
Code
Authors from
Electric Utility
Industry/manufacturer
University
Joint effort
10
10
17
60
Thus out of a total of 101 selected papers on expert systems 62 were
produced by joint efforts between electric utilities, manufacturers, and
universities. A majority of these however, represent joint efforts
between electric utilities and manufacturers only. Only about 10% of
the papers are produced separately by the manufacturer or the
electric utility.
-
Adoption of
real-time inference
Cases of faults troubles
are limited (Off-line
inference only)
Total
E
P
1213
I
Too much text in
guidance
[
I
More graphical
guidance
0
function
No on-line function
during training
Dual CPU System
4.4 Diversity in the Collaborative Research
Even though the Japanese researchers from utilities,
manufacturers and universities work closely in Ihe field of A I
applications, there are distinct characteristics of the approaches to
problems followed by each manufacturer and electi-ic utility. For
example, Toshiba Corporation uses a dedicated AI processor (AIP)
connected to their supermini computer implementing the SCADA
system [See Kunugi, A-31. The AIP is used as a backend processor for
execution of the expert system. In another area, Kansai Electric Power
Company has built an advanced power system analyzer consisting of
physical scale models of generators, transmission lines. transformers
and other elements. This is used to represent the dynamic behavior
of the electric power system by the analogous characteristics of its
components. On the other hand, Tokyo Electric Power Company, in
cooperation with Mitsubishi Electric Corporation, has built a real-time
digital simulator for power system analysis on a hypei-cube computer
[A-7). In building the real-time digital simulator, they have taken
advantage of the massive parallel computing capability of the
hypercube computer.
The Kyushu Electric Power Company, in
cooperation with Toshiba Corporation, has built a large scale SCADA
system with real-time knowledge based functions [A-01 for an
integrated control center of a power system. The knowledge based
functions include fault determination, restoration support. power
system security monitoring, and power systems operation planning.
Another example of diversity in collabol-ative research can be
seen from the view manufacturers take on this subject. In a recent
paper, Kunugi [A-31 has given the manufacturers’ viewpoint on the
current state of the art in Japan and the future trends in the field of
AI applications. He discusses the characteristics of expert systems (as
a way to apply AI tools), project management, AI hardware and
development environments, and the keys to pronioting practical
applications of these advanced tools. This paper shows that the
manufacturers’ viewpoints are somewhat diffei ent froin what are
expressed in utilities. This is especially true lor inaintaining the
knowledge base
El
during CPU
maintenance
1 1F H T l
I
I
f
I
User Oriented
Maintenance
Figure 1. Reflections from an Early
Expert System Application
use of dual-CPU is significant. because the operation of the expert
system cannot be suspended while it is in maintenance. Also, the
maintenance cannot be done efficiently and economically unless the
user is involved in the process. This resulted in the user oriented
maintenance systems.
5.2 Some Recent Activities
In the context of the difficulties encountered, and the
expectations unfulfilled, there have been some reorientation of the
approaches taken. The following includes some of the impollant ones,
Rahman [A-51.
1. Shift from operation support and diagnosis to scheduling and
planning. For example,
- Nuclear fuel transportation and scheduling system
- Optimizing cascading hydro operation.
- Planning support system for maintenance schedule
2. Incorporate AI programming methods into the conventional
computerized system. For example,
5.0 Problems and Promises of A I Tools
In the light of the AI related activities discussed in the previous
section, certain examples of the problems encountered in the
Japanese electric power industry are presented. Also discussed are
some of the remedies that have been applied to overcome these
difficulties, and prospects that lie ahead for AI tools in Japan. The path
traveled by Japanese researchers can give valuable insight to others
who are engaged in similar activities elsewhere.
5.1 Shortcomings and Unexpected Outcomes
Many prototype AI tools have been developed only for the
purpose of learning how they function and what they can possibly do.
Thus their effectiveness and feasibility have not been sufficiently
examined. In many cases the requirements for practical use of these
tools are very strict, and it is rather difficult for ordinary operalors to
handle such tools. Since the AI technology is still immature, some of
the systems do not have sufficient capabilities in the areas of
knowledge acquisition and representation, inference mechanism,
processing capacity and time, and user interface. Some reflections
from the first expert system application at the Kansai Electric Power
Company [A-21 are given in figure 1. Obviously there were difficulties
during both the operation and maintenance of the software tool. Some
of the countermeasures that were taken are shown. In this regard the
- Alarm processing system incorporated into the central control
board of a thermal power station.
3. Select practical themes, and limit the diversity of functions
example,
For
- Oil-filled equipment diagnostics by analyzing the dissolved gas.
- Support system for developing greening
plan.
4. Combine AI tools with innovative computer technology.
example,
For
- Layout design of restaurant electrical kitchen appliances.
- Decision support system for choosing household electrical
appliances.
The net result of A I related activities is now evident in the
following three areas.
The number of persons farniliar with AI tools has increased;
The areas where AI tools can be used has expanded; and
There has been a tremendous increase in the number of
prototype systems.
1214
For example, at the Kansai Electric Power Company IA-51, the
application of AI tools can be classified as shown in figure 2. Even
though network control is the largest application, there are many other
uses of AI tools The current approach to the AI application in the
Japanese electric power industry can be described in the flow chart in
figure 3. This shows both the actors for, and pi-ocesses of, effectively
using AI tools.
.,
9
- O/,.-
Nuclear Power
I-
0Thermal Power
9
The equally important roles played by the universities. manufacturers
and utilities can be represented as shown in figure 4. The collective
efforts of these three groups can result in more robust and broader
based AI tools like the two expert systems shown in this figure. Sets
of knowledge based packages can be developed as a result of the joint
collaboration. The featut-e of easy addition and deletion of rules will
facilitate the development of application oriented knowledge bases
from a central pool of such knowledge. Once such specific knowledge
bases are available, inference engines can be designed to use the
knowledge in expert systems. Then there will be several expert
systems dealing with specific applications.
Transmissiod'ransformer
4 yo
1 2%
1- (
Network Control
@ Civil Engineering
14%
-
Construction
0Environment
34%
I Manufacturers I
1
I
Development of Knowledge
Base with Easy Addition
I and Deletion I
I
I
S
Knowledge
B Power Distribution
Ol
Service support
Sets of Knowledge Base Packages (KBP)
Figure 2. Classification of the Application of AI Tools
(\
The prototype systems have increased
Translation of KBP for Each Application
Only few practical applications
Inference
Engine A
U
--
Expert System A
Inference
Engine B
Expert System B
Needs
Figure 4. A Generalized Approach
to Developing Expert Systems
t
Continuation of R&D
in each Department
*Development based upon
needs in each Department
*To select specificjobs for
system Application
*To establish concrete plan
for system Application
Fundamental research on
AI tool developement
I
*FundamentalR&D work in
the following areas:
*Knowledge acquisition
I
*Fuzzy application
-Qualitative Reasoning
I Implementation of Practical Systems I
Figure 3. R&D Approach to the Application of AI
5.3 Promises of AI Tools
On the basis o f the experience gained so far, certain specific
goals and expectations have emerged. These can be classified as
follows.
I. Using AI tools for both faster prototyping and cost savings.
2.
Providing built-in enhancement features such that users can
easily modify the rules.
6.0 Conclusions
The Japanese electric utility industry, manufacturers,
novernment
R&D laboratories and universities have taken a focused
~.
approach to developing AI tools for addressing operation and planning
problems related to the power system. This action precipitated from
the need for automation, and to maintain a highly reliable and high
quality power system. They have developed the necessary R&D
infrastructure to provide both guidance and funding for the
development of such tools. The areas of concentration appears to be
in knowledge acquisition, fuzzy theory application, and qualitative
reasoning. The area of contention between the developer and the user
The user (i.e.,
of the system appears to be knowledge maintenthe electric utility) is still concerned about the cost and difficulty of
maintaining the knowledge. The developer (i.e.. the manufacturer or
the university) is working on automated knowledge acquisition and
verification on a high priority basis to make the AI tool more widely
usable. The developers of Japanese AI tools still use a significant
amount of theoretical work done in the United States for their
successful prototyping. It is however, safe to say that the use of AI
tools in the Japanese electric power industry is far more widespread
than what is seen in the United States or Europe.
a-
7.0 Acknowledgements
The author acknowledges with thanks the assistance and
information provided by the engineerdresearchers from the eight
organizations he visited. This survey was made possible by a grant
from the National Science Foundation-Divison of International
Programs. Grant No. INT-9017799.
1215
8.0 Bibliography
9.
A. Citations used in this paper
1.
Hiramaya, T., "Electric Utility R&D in Japan", /€E€ Power
Engineering Review, June 1991, pp. 8-11, [I].
2.
Ito. S.. "Practical Applications of Expert Systems in Power
Systems and Future Trends - A User's Viewpoint", Third Symp. on
Expert Systems Application to Power Systems, Tokyo-Kobe, April
1991, 17p, [ I ] .
3.
Kunugi, M., "Practical Applications of Expert Systems in Power
Systems and Future Trends - A Manufacturer's Viewpoint", Third
Symp. on Expert Systems Application to Power Systems.
Tokyo-Kobe, April 1991, 5p, 121.
4
Moriguchi, S., Taniguchi, T.. Kunugi, M., Shirnada, K. and Suzuki,
K.,
"A
Large-scale
SCADA
System With
Real-Time
Knowledge-Based Functions" , Second Symposium on Expert
Systems Application To Power Systems, Seattle, Wash., July 17-20,
1989, (41.
5.
Rahman, S., "Artificial Intelligence in Electric Power Industry - A
Survey of the Japanese Industry", Virginia Polytechnic lnstitufe
and State University, Final Report submitted to the U.S.National
Science Foundation, September 1991, 118 p.
6.
Tanaka, H., et al., "Research and Development on Expert Systems
Applications to Power Systems in Japan", Third Symp. Expert
Systems Application to Power Systems, Tokyo, Apr. 1991, 19p. (4).
7.
Taoka, H., lyoda, I., Noguchi, H., Sato, N. and Nakazawa. T.,
"Real-Time Digital Simulator For Power System Analysis On A
Hypercube Computer" , /€€€/PES 1991 Winter Meeting, New York,
N.Y., February 3-7, 1991, paper no. 91WM 158-6 PWRS, (41.
8.
Uenishi, K., "Observations on the Development of Artificial
Intelligence (AI) in the United States", Internal Report, Kansai
Electric Power Company, 1986, 16p, 121.
B. Selected papers on AI tools and applications by
Japanese authors
1.
2.
3.
4.
Abe, T., Goto, H., Mitzutori, T., Matsuki, N., "An Expert System for
Generating Switching Sequences at Substations" , lnternafional
Workshop on Artificial lntelligence for Industrial Applications,
I f f € , 1988, 141.
Akimoto, Y., Tanaka, H., Ogi, H. Taoka, H. Nishida, S. and
Sakaguchi, T., "Autonomous Distributed Network Architecture For
Control System", Distributed Computer Control Systems. 1988. pp.
21-28, 141.
Akimoto, Y . , Tanaka, H.and Yoshizawa, J., Klapper, D.B., Price,
W.W., Wirgau, K.A., "Application of Expert Systems To Transient
Stability Studies", Second Symposium On Expert Systems
Application To Power Systems, Seattle, Wash., July 17-20, 1989,
pp. 211-217, 141.
Akimoto, Y., Tanaka, H , Ogi, Hiromi, Taoka, H and Sakaguchi, T I
"Distributed Simulator For Power Systeni Analysis Using a
Hypercube Computer" , Proceedings of fbe Tenth Power S y s t e m
Computation Conference. Graz. Austria, 19-24 AugiJst 1990, 141.
5.
Akirnoto, Y. and Tanaka, H., "Towards Development of the Smart
Systems for Power Systems Planning and Operation" , Symposium
on
Expert
Systems
Application
To
Power
Systems,
Stockholm-Helsinki, August 22-26, 1988, pp. 18-16- 22, [ I ] .
6.
Akimoto, Y., Tanaka, H., and Yoshizawa, J., Klapper, D.B., Price,
W.W., Wirgau, K.A., "Transient Stability Expert System", lEEE
Trans. on Power Systems, Vol. 4, No. 1. February 1989. pp.
312-320, 141.
7.
Aoyagi, K., Tanemura, K., Matsumoto, H., Eki, Y , and Nigawara,
S., "An Expert System for Startup Scheduling and Operation
Support in Fossil Power Plants" , International Workshop on
Artificial lntelligence for lndustrial ApplicationsJEEE, 1988, (4).
8.
Aoyagi, K., Sano, I., Matsumoto, H., Iba, D.,and Nigawara. S., "A
Scheduling Support System Based on Fuzzy Iiiference lor Startup
of Fossil Power Plants" , Seminar on Expert Systems Applicafions
in Power Plants, Sponsored by Electric Power Research Institute,
Boston, Massachusetts, May 27-29, 1987. (41.
Arikuni, K., Misawa, K., Ueyama, S., Nishijima. A., and Nakarnura,
Y., "Use Of An Expert System Applied To Power Requirement's
Fault Diagnosis", Third Symposium O ~ Experf
J
Systems Application
To Power Systems, Tokyo-Kobe, Japan, Api-il 1-5, 1991, pp.
602-608, [ I ] ,
10 Choi, K., Nishiya, K., and Hasegawa. J., "Fuzzy Decision Making
of Deicing Countermeasures Against Snow Accretion on
Transmission Line," Third Svmoosium On Exoert Svstems
Application To Power Systems, fokyo-Kobe. Japan, April 1-5, 1991,
pp 433-438, (31
11 Choueiry, B.Y., Sekine, Y., "Knowledge Based Method for Power
Generators Maintenance Scheduling", Symposium on Expert
Systems Application to Power Systems, Slockholin-Helsinki,
August 22-26, 1988, pp. 9-7-14, (31.
12 Fudo, H., Egawa, S., Sanga, K., Inoue. H., and Imaniura. Y., "An
Expert System for Restoration Of Distribution Network". Third
Symposium On Expert Systems Application To Power Systems,
Tokyo-Kobe, Japan, April 1-5, 1991, pp. 695-700, (41.
13
Fujii. Y., Miura, A., Hata, Y., Tsukamoto, J , Youseff, M.G.. Noguchi,
Y.. "On-Line Expert System For Power Dislribution System
Control", Third Symposium On Expert Systems Application To
Power Sysfems, Tokyo-Kobe, Japan, April 1-5, 1991, pp. 701-707,
141.
14 Fukui, C. and Kawakami, J., "An Expert System for Fault Section
Estimation Using Information from Protective Relays and Circuit
Breakers", /€E€ Trans.On Power Delivery, Vol PWRD-1. No. 4,
October 1986, pp. 83-90. 121.
15
Fukui, C. and Kawakami, J., "Fault Section Estimating Method
Based on Knowledge and Physical Objective Model". Electrical
Engineering in Japan, Vol 107, No. 6, 1987, pp. 32-41, translated
from Denki Gakkai Ronbunshi, Vol. 107C. No. 2, February 1987, pp.
181-188, 121
16
Fukui. C. and Kawakami, J., "Switch Pattern Planning in Electric
Power Distribution Systems by Hopfield-type Neural Network ,
International Joint Conference on Neural Network. Washington,
DC, 1990, (2)
17 Fushimi, T., Matsumura. S., Koi, T., Momoeda, K., Kaniiya, A.,
"Turbine-Generator On-Line Monitoring and Diagnostic Expert
System". Symposium ori Expert Application to Power- Systems,
Stockholm-Helsinki, August 22-26, 1988, pp. 11-14-19, 141,
18. Haida, T. and Akimoto, Y , "Voltage Optimization Ry Using Genetic
Algorithms", Third Symposiurn On Expert Systems Application To
Power Systems, Tokyo-Kobe, Japan, April 1-5, 1991 [ I ] .
19
Hamamoto, K., Osada, M.,Oue. H., Yamada. K., Takoaka, Y., and
Higashiyama. F., "275 KV Substation Operation Support System System Under Field Test", Third Symposiuni On Expert Systeriis
Application To Power Systems, Tokyo-Kobe, Japan, April 1-5, 1991
141.
20
Hara. H. and Tsugio, H., "Development of An Expert Systein For
Generating Switching Sequences At Suhstations", Third
Symposium On Expert Systems Application T o Power Systems,
Tokyo-Kobe, Japan, April 1-5, 1991, pp. 315-322, [4]
21
Hasegawa, J., Nishiya, K.. Matsunami. S., "Expert System
Assisting
Power System Operators to Decide Deicing
Countermeasures for Snow Accretion of Transmission Lines",
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Systems, Seattle, Washington, July 17-20, 1989, pp. 359-365, (31.
22
Hatta, M., Satoh. H.. Serizawa, Y., "Application of the Expert
System to the Determination of the Operational Coordination of
Switch Gears and Power Fuses for Short Circuit Protection",
Symposium on Expert Application fo Power Systems,
Stockholm-Helsinki, August 22-26, 1988, pp. 6-27-34, (31.
23
Hayashi, Y. Iwamoto, S., Matsuda, S.. and Akimoto, Y.,
"Introduction of Neural Network Theory to Newton-Raphson Load
Flow", Third Symposium On Experf Systems Application To Power
Systems, Tokyo-Kobe, Japan, April 1-5, 1991 141.
24
Hiyama, T., Sameshima, T., and Lim, C.M., "Fuzzy Logic Stabilizer
with Digital Compensation For Stability Enhancement for
Multimachine Power System". Third Symposium On Expert
Systems Application To Power Systems, Tokyo-Kobe, Japan, April
1-5, 1991 141.
1216
25. Inoue. N.. Fujii, T., Shinohara, J., Mochizuki, K. and Kajiwara, Y.,
"An Expert System for Intelligent Alarm Processing in EMS and
SCADA Systems" , Second Symposium on Expert Systems
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89-95, 141.
26. Inoue, T., Tanaka, Y., Tsukiyama, H., Suzuki, T., Wada, N., and
Hiramatsu, H., "Power Plant Maintenance Scheduling Expert
System", Third Syniposium On Expert Systems Application To
Power Systems, Tokyo-Kobe, Japan, April 1-5, 1991, pp. 574-578.
(41.
27. Ito, S., Hata, I., Hasegawa, T., Amano, M., and Maruyama, A.,
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Power Systems, Tokyo-Kobe, Japan, April 1-5, 1991, pp. 405-412,
[41.
28. Ito, S., Hata, I, Maruyama, A. and Kawakami, J., "Application of
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30. Kaneko, T., Tsuzuki, N., Sato, M., Maruyama, F., Tamaoki, H.,
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31. Kakimoto, N., Emoto, M., Hayashi, M., "An Application of Artificial
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Ill.
34. Kobayashi, N., Okamoto, H., Yokoyama, A.. and Sekine, Y., "Power
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45. Matsumoto, K. Sakaguchi, T., "An Approach to the Dynamic
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51. Mori, H., Tsuzuki, T., "Power System Topological Observability
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Electric Systems, Study Committee 39, Meeting in Tokyo, Japan,
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55. Muto, S., Sekine, Y., "Modality Based Inference lor Power
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17-20, 1989, pp. 267-275, [4].
56. Muto, S., Matsuda. T., Yamagata, Y.. Kawakami, Y. and Tanaka,
Y., "Supervisory System For Substation With Expert System". Third
Symposiunr On Expert Systems Application To Power Systenis,
Tokyo-Kobe, Japan, April 1-5, 1991, pp. 413-418, [4].
57. Nagasawa, T., Humano, M., Shimano, S., Fukui. C., and Fujikawa,
T.. "Development of Restoration Guidance For Control Center",
Third Symposium On Expert Systems Application To Power
Systems. Tokyo-Kobe, Japan, April 1-5, 1991. pp. 479-486, [2].
58. Nakamae, E., Nishita, T.. Fujii, K., Tanaka, H. and Noguchi, T., "The
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Mexico City, Mexico, November 1987, 141.
1217
59. Nara, K., Satoh, T., and Maeda, K.. "Maintenance Scheduling By
Expert System Combined With Mathematical Programming". Third
Symposium On Expert Systems Applicatiori To Power Systems,
Tokyo-Kobe, Japan, April 1-5, 1991, pp. 385-390, [4j.
76. Suzuki, H., Kawakami, J., Kunugi, M., Tanaka, H. and Sekine, Y.,
"Experiences of Expert Systems For Power System Analysis In
Japan" , Symposium on Expert Systems Application to Power
Systems, Stockholm- Helsinki, August 22-26, 1988, pp. 1-1-1-7, 141.
60. Nara, K.. Satoh, T., and Kitagawa, M., "Distribution Systems Loss
Minimum Re-Configuration By Genetic Algorithm", Third
Symposium On Expert Systems Application To Power Systems,
Tokyo-Kobe, Japan, April 1-5, 1991, pp. 724-730, [4].
77. Takeyasu, I., Fukuta, T., Kunugi, M.,Shinohara, J. and Nagata, J.,
"An Expert System For Fault Analysis And Restoration Of Trunk
Line Power Systems" , Symposium On Expert Systems Application
to Power Systems, Stockholm-Helsinki, August 22-26, 1988. pp.
8-24-31, 141.
61. Niimura, T.. Nakanishi, Y.. Yasuda, K., and Yokoyama. R.,
"Multi-Machine Voltage-Reactive Power Control Baased on
Approximate Reasoning", Third Symposium On Expert Systems
Application To Power Systems, Tokyo-Kobe, Japan, April 1-5, 1991
141.
78. Tamura, Y., Yazawa, S., Hosaka, J., "A New Method of On-Line
ELD for Thermal Power Plants", Symposium 011 Expert Systems
Application to Power Systems, Stockholm-Helsinki, August 22-26,
1988. pp. 10-1-8, [3].
62. Ogi, H., Takeshima, Y., Shinohara, J. and Haruki. K., "An Expert
System with Cognitive Model for Power System Outage
Scheduling", /E€€. CH 2747-4/89, pp. 179-184, [4].
79. Tamura, Y., "How To Revisit And , Review Interdisciplinary
Domains in KE and AI Environments", Third Sympoiiurb On Expert
Systems Application To Power Systems, Tokyo-Kobe, Japan, April
1-5, 1991, pd. 757-763, (3).
63. Okada, K., Urasawa, K., Kanemaru, K. and Kanoh, H..
"Knowledge-Based Fault Location System For Electric Power
Transmission Lines with OPGW" , lnternational Workshop on
Artificial lntelligence for lndustrial Applications, /€€E, 1988, pp.
52-57, [4].
64. Okada, K., Yokoyama, R., Sasaki, H., "Knowledge-Based System
for Real-Time Load Frequency Control in Multi-Area Power
System", Symposium on Expert Application to Power Systerns,
Stockholm- Helsinki, August 22-26, 1988, pp. 11-20-27, 131.
65. Oki, M., Nishimori, T., Hiyoshi. M., Takaoka, Y., "Substation
Operation Support
System Which . Allows
Event-Driven
Processing" , lnternational Workshop on Artificial lrifelligence for
lndustrial Applications, IEEE, 1988, pp 64-69, 141.
66. Osaka, S., Amano, M., and Kawakami, J., "An Expert System For
Power Generation Scheduling", lnternational Workshop on
Artificial lntelligence For Industrial Applications, /€E€, 1988, pp.
557-562, 141.
67. Osaka, S., Kono, Y., Fujiwara, R. and Yamanishi, A., "Development
Of The Expert System For Operation Planning Of Power System",
lnternational Workshop on Artificial lntelligence for lndustrial
Applications, IEEE. 1988, pp. 545-550, [4].
68. Sakaguchi, T., Tanaka, H., Uenishi, K., Gotoh, T. and Sekine, Y.,
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Cascais, Portugal, 31 August-4 September 1987, pp. 71-82, 141.
69. Sakaguchi, T., "Future Prospects of AI Technology for Friendly
Interface and Software Development", Syntposium on Expert
Systems Application to Power Systems, Stockholm-Helsinki,
August 22-26, 1988, (2).
70. Sakuda. H., Fujii, S., Kondo, S., Muto. K., Toriumi, Y., Tani. M.,
Masuda, Y., and Fujita, Y., "Operator Suppoit System For
Japenese PWR Nuclear Power Plant", Third Symposium On Expert
Systems Application To Power Systems, Tokyo-Kobe, Japan, April
1-5, 1991, pp. 521-525, [4).
71. Sasaki, H., Gurita, H., Yorino, N., Ohnogi, Y., "An Expert System
Assisting System Security Control". Symposium on Expert
Systems Application to Power Systems. Stockholm-Helsinki,
August 22-26, 1988, pp. 14-1-7, [3].
72. Sasaki, H., Kawahara, K.. Takasaki, N., Yorino, N., Yokoyama, R.,
Kitagawa. M., Sugihara, H., "A Novel Scheme for Validation and
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on Expert Systems Application to Power Systems, Seattle,
Washington, July 17-20, 1989, pp. 416-422, [4]
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"Monitoring and Control Strategies of Voltage Stability Based on
VIP1 (Voltage Stability Proximity Index)", Symposium on Expert
Systems Application to Power Systems, Stockholm-Helsinki,
August 22-26, 1988, [3].
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on lnformation Technology for Organizational Systems. Athens,
Greece, 16-20 May, 1988, pp. 886-891, 141.
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"CSES: An Approach To Integrating Graphic, Music And Voice
Information Into A User-Friendly Interface" , /€E€ lnternational
Workshop on Industrial Applications of Machine lntelligence and
Vision (MlV-89), Institute of Industrial Science, Toyko, Japan, April
10-12, 1989, [ I ] .
87. Ueda, T., Maruyama, A., Mori, E., Yamagiwa, T., Nakayama, N.,
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MI.
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Y., "An Expert System Applied To The Dislribufion Automation
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Stockholm-Helsinki, August 22-26, 1988, pp. -0-1 to 0-4, 131.
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Saifur Rahmnn (IEEE 5-75, M-78. SM-83) is a professor of electrical
engineering at Virginia Tech. He also directs the Energy Systems
Research Laboratory at VPI. He serves on the System Planning and
Demand Side Management subcommittees, and the Long Range
System Planning, the Load Forecasting and the Photovoltaics working
groups of the IEEE Power Engineering Society.
1218
DISCUSSION
P.K.
Kalra and S . C .
Srivastava
(Indian
Institute of Technology, Kanpur.
India).
W e congratulate author for his contribution iri
presenting
t h e recent developments
in tho
field of Expert System Applications to Power
System. Author's
reepose to the following
comments will be appreciated :
Author has been involved in development
of Expert System for Power System apylication8 for considerable
long period.
if
It would
enhance .the information,
some kind of comparison among approachetl
used in U . S . and Japan for promoting A.I.
applications can b e provided.
A r e there any projects in Japan which a r e
instruction for
dealing with AI Based
power
eystem operation, control
and
planning?
S o m e data of conversion of prototypes
to
actual systems will add t h e information
for t h e future application in this field.
Does author
feel that similar social
advancements a r e possible in developing
countriee in Power Sector if t h e same
approach of promoting A.I. technology is
f ol lowed?
Manuscript received July 30, 1992.
Saifur RAHMAN (Electrical Engineering, 340 Whittemore Hall,
Virginia Tech, Blacksburg, VA 24061-0111) The author appreciates
the interest shown by Profs. Kaka and Srivastava in the process of
identifying Ai applications in many parts of the world. Their
comments and questions are addressed in the order presented in
their discussion.
(A) The Japanese electric utility industry, manufacturers,
government R&D laboratories and universities have a taken
focused approach to developing AI tools for addressing
operation and planning problems related to the power system.
The Japanese approach to this is summarized at the beginning of
section 4.0 in the paper. The approach followed in the United
States is, on the other hand, is rather dispersed and individualistic.
The AI related activities in the US electric utilities started based on
the individual engineer's interests on the topic and their curiosity
to find out what AI and expert systems can do to help. These
activities have resulted in many prototype expert systems, several
of which have been deployed and tested. In conjunction with
the electric utility industry, the academic community in the United
States has also spent considerable amount of time and resources
to define the role expert systems can play, and build prototypes.
In the later stages, the Electric Power Research Institute has
attempted to provide some leadership in defining the need and
potential for expert systems in power system planning (Rahman
and Lauby, 1991).
(B) There are several AI based instructional projects which deal
with power system operation, control and planning. One of them
is the CRlEPl (Central Research Institute of Electric Power Industry)
developed system known as "An Advanced Educational System
of Nuclear Power Plant Operators". The objective is to assure
easier understanding of plant changes during abnormal events,
test the operator's knowledge about certain aspects of the
nuclear power plant's operation, identify gaps of knowledge on
the part of the operator, and provide relevant information to him
so he can learn more about the area where he is deficient in.
Additional information about such and other systems can be
found in Rahman (1991).
(C) According to Tanaka, et al (6), the power companies and
manufacturers in Japan identified 48 examples of expert systems
at various stages of development; 24 were in power system
control and the rest in substation equipment management. Out
of those, 63% (in system control) and 83% (in equipment
management) have reached the stage of practical system
development, field testing or practical use.
(D) One of the major reasons for promoting AI in Japanese
power industry is the realization that soon there will be a large
scale loss of experienced engineers and operators due to the
approaching retirement of many who started their career during
the fast growth period following the second world war. It is.
therefore, crucial to provide fast and effective training
mechanisms to expose the new engineers and operators to the
intricacies of the system, and train them to deal with the
unexpected events. In developing countries, the lack of timely
maintenance and adequate repairs (caused largely by the
shortage of trained technicians) are significant contributing
factors for the shortage of electricity. The opproach followed in
Japan can work for developing countries if such a focused effort
is undertaken. One concern, however, is the limited training and
technical sophistication of system operators in many of these
countries. This might hamper their ability to absorb the
sophisticated technologies like Al. Technical universities in many
developing countries can play a major role in overcoming such
difficulties.
REFERENCES:
1. S. Rahman and M. Lauby, "Expert Systems and Their Role in
Power System Planning", Roc. EPRl Conference on Expert
Systems Applications for the Electric Power Industry, Boston.
MASS, September 1991, 19 p.
2. S. Rahman, Artificial lntelliaence in Electric Power Industrv A
Survev of the J a mnese Industrv. Report submitted to
National Science Foundation, grant no. INT-9017799.
September 1991, 118 p.
Manuscript received September 1 4 , 1992.