T his article presents ASDEP, an expert system forr Idesigning a power plant's electrical auxiliary system,

implemented to demonstrate the feasibility of AItechniques for solving specific power system design

problems. Overall, ASDEP received positive commentsduring its evaluation. Specifically, Al techniques provedfeasible to address the particular design problem discussed.

Most design problems encountered in the electricalutility industry are complex and time consuming. Designersmust deal with interactions between alternatives,uncertainties, and important nonfunancial parameters inmost design phases. Typically, designers face thefollowing issues:

* Multiple objective functions;* Multiple (and often conflicting) constraints;* Complex system interactions;* The need for accuracy;* The need for trade-off, optimization, and "what-if'analyses; and

* Coordination of the decision-making process.

Presently, human experts solve design problems basedon experience, specialized knowledge, and engineeringjudgment, using the computer only for analysis. Conven-tional CAD programs build on the basic assumption thatfeasible solutions do indeed exist to solve designproblems; however, this premise does not always apply inreal-world design. Human experts frequently deal withdesigns not meeting all constraints and objectives imposedupon them.

Developers have successfully applied AI techniques tosome difficult engineering design problems, but little hasbeen applied to electrical power system design. In thisfield, the major design problem areas are generationplanning, transmission planning, substation design, andauxiliary-system design.

Generation planning. Generation planningdetermines the appropriate generation mix (such as nuclear,fossil, hydro, or solar) required to satisfy future customerneeds at minimum cost while providing adequate returns onstockholder investments. Customer needs encompassconcerns from reliability and quality of electrical supply toenvironmental, political, and geographical impacts. Theseconcerns often conflict, and are further complicated bynumerous constraints, uncertainties, and trends imposed onthe design.

Electric utility generation planning is a multiobjectiveproblem; generally, no single strategy exists to optimizeall objectives involved. Furthermore, many objectives areinherently difficult to quantify and are, therefore, notsuitable for combination into a single analytical functiond

Transmission planning. Transrnission planningdetermines how many additional power system transmissionfacilities are required to meet the design criteria atacceptable capital costs. Design criteria cover such issuesas reliability, security, dynamic stability,

0885-9000/87/0200-0056 S01.00O1987 IEEE56 IEEE EXPERT

Figure 1. Flowchart of design process.

and environmental impact. This problem is, amplified by itssize (that is, the combinatorial explosion of possiblechoices), the uncertainty of predicting the future, and howfar in the future to plan.

Substation design. Substations supply electricalenergy from high-voltage transmission systems to users atlower voltage levels. Electric loads fed by substations arefundamentally random in nature; therefore, we needprobabilistic measures to ascertain design quality. Duringdesign, many initial skeletal configurations can potentiallybe used that somehow must be ranked before selections canbe made.

Auxiliary-system design. Power plant electricalauxiliary systems supply electrical energy, either from theplant or from the transmission system, to electric loads(such as circulation coolant pumps or measurement andsecurity monitoring systems) required to operate the plant.An electric power generating plant can produce full poweronly if its auxiliaries are fully operational. When power islost to the auxiliaries, a generating unit may have to reducepower or shut down completely. Typically, auxiliary electricsystems cost five to 10 percent of total plant cost.2 Duringa large plant's long-term outage, due to the repair of majorauxiliary subsystem components, corresponding replacementenergy costs can exceed the total auxiliary system's capitalcosts; hence, the need to carefully design such auxiliarysystems.

Of the four major design problems described above,auxiliary-system design offers the least formidable challengeinsofar as Al techniques are concemed. Auxiliary-system

design does not present as great a dimensionality curse asthe other problems do; moreover, verification is fairlystraightforward to implement.

This article will address various Al techniques proposedand implemented to design auxiliary systems, discussASDEP's features, and present an evaluation of ASDEPcarried out by an independent engineering design group.While our research has established the feasibility of Altechniques for solving specific power system designproblems, additional work is clearly required to lift ASDEPto industrial design levels.

Present design methodology related to electrical auxiliarysystems evolves from engineers and technicians who, afterexamining a plant's load requirements, propose possibleconfigurations. They analyze each configuration, performingeconomic short-circuit, load-flow, and motor-start studies.Then, subjective evaluations are usually performed based oneach design's reliability, flexibility, maintainability, andexpandability. The designers select the design scheme bestmeeting design goals. After selecting the design scheme,they produce equipment specifications and obtain bids.Following equipment selection, they reexamine the finaldesign.

Figure I (excerpted from a preliminary draft of the IEEEP666 Standard) provides a task organization flowchart of thedesign process, indicating approximate times required tocomplete each step. No provisions are made for feedback, or

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to answer various "what-if' questions, until the end of theprocess.

Past experience reflects the adequacy of utility industryauxiliary-system designs. However, the following areas needimprovement:

* Clearly stated design and system performance criteriaare often not properly formulated, in writing, beforethe design.

* Typically, individuals with little formal trainingperform power system analysis.

* Few analysis programs supporting auxiliary-systemdesign are available.

* Most "what-if' questions are not explored because theywould delay the design process (note the lack offeedback loops in Figure l's flowchart).

* Due to the large staffs involved, overall systemobjectives can become unclear and conflicting.

* Insufficient reference material exists to supportsystematic auxiliary-system design.

Can knowledge-based systems alleviate some of thesedeficiencies?

The goal. ASDEP seeks to design good (as opposed tooptimal, since optimality is awkward to define related toelectric power designs) electrical auxiliary systems meetingoperational requirements. We measure design quality againstoperational performance, reliability, maintainability,flexibility, expandability, and cost. Consequently, weconceive ASDEP to be truly design-oriented.

Objectives and limitations. ASDEP evaluates howstate-of-the-art AI techniques can be applied to powersystem design, using practical and physical examples.Primary issues are to (I) evaluate AI potential, and (2)

implement existing AI techniques. This research does notattempt to produce a problem-free expert system, but ratherseeks to evaluate the feasibility of using general AIframeworks for such designs.

Since our research focused on demonstrating feasibility,we imposed the following additional limitations on ASDEPto highlight major concerns during its construction:

* Functional boundaries of the auxiliary system to bedesigned (for example, the switchyard) must be clearlydefined beforehand.

* Low-voltage systems are not explicitly considered(that is, less than 1000 volts); however, low-voltageloads are implicitly considered as lumped loads atintermediate voltage levels.

* We designed ASDEP to handle only single-unit powerplants.

* ASDEP's final output, not intended as a detailedengineering drawing, describes the auxiliary system'sfundamental topology.

We based our research on existing AI techniques;therefore, ASDEP's evaluation phase was very important asit might have been determined that Al techniques cannotadequately address problems related to power system design.We will specifically address evaluation in due course.

Observations incorporated in ASDEP. Trans-cribing problem-solving expertise from human experts tocomputer programs is at the heart of expert systemdevelopment.3 Design engineers rely on the followingobservations when designing auxiliary systems:

* Using little or no backtracking, they follow an orderlyprogression from initial designs (containing littledetailed information) to detailed designs.

* They use general problem-solving techniques in

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conjunction with analytical methods during designdevelopment.

* They generally use analytical methods that arerelatively simple mathematical formulations relatingkey design parameters to targeted constraints.

* They cannot satisfy all constraints initially imposedon the design.

* They primarily seek satisfactory (as opposed tooptimal) solutions.

* They articulate preferences during the entire designprocess, called for by intermediate design results.

ASDEP embeds these six observations.

Let's consider ASDEP's general methodology, concen-trating on AI issues faced during its implementation. Latersections will briefly discuss an actual design and review anevaluation of an auxiliary-system design generated byASDEP.

Figure 2 illustrates ASDEP's organizational flowchart.Major features of the flowchart's basic blocks follow.

Block 1: Language processor. Designers use aproblem-oriented language, relying on a user-oriented andfixed vocabulary, to (1) conveniently input and display dataand (2) select and apply the appropriate rule group whenprompted by the program to do so.

Block 2: Input procedure. We must provideASDEP with specific design information before design canbegin. We sort this information into three parts: (1) loadand system data, (2) equipment inventory, and (3) goal andconstraint data. A major problem frequently encountered isthe lack of accurate information regarding load andequipment components. We use default rules in the know-ledge base to reasonably approximate missing load andequipment information, and can later modify this infor-mation as desired during design.

Block 3: Initial design procedure. The initialdesign proposal is an inherent part of most designprocesses. Fortunately, due to the nature of many powersystem design problems, a simple initial design can beproposed meeting some (but usually not all) design goalsand constraints. We can use two extreme methodologies toautomatically propose an initial auxiliary-system design, ahighly reliable but high-cost design, or a less reliable butlow-cost design.

Using the first approach, ASDEP would modify theinitial design by tearing it down to achieve lower cost whilestill meeting stated constraints. Using the second approach,ASDEP would modify the initial design by building it up, orby changing the proposed design's structure, to produce ahigher cost design meeting stated constraints. Humanexperts take an approach resembling the second method.

Figure 3. The initial design procedure.

ASDEP generates an initial design based on the secondapproach as well, intending to use top-down refinements toproduce a satisfactory design.

Figure 3 presents ASDEP's initial design procedureflowchart. The following additional comments areappropriate. The system

* Divides all loads into two broad groups, emergency (orvital) loads, and nonemergency (or nonvital loads),based on information obtained in Block 2;

* Creates the load buses simply based on load goals andon the related switchgear's kVA rating (buses are large,electrical conductors enabling electrical loads andsupply feeders to be connected);

* Distributes the loads on the buses, balancing the kVAloading on similar buses;

* Selects load bus voltage ratings based on rulescontained in the system's knowledge base;

* Determines the kVA load on each load bus by addingall loads connected to each bus; and

* Automatically proposes a radial distribution systemconnecting most load buses to the main generator andthe switchyard.

In an effort to remain at a preliminary stage, the initialdesign may not be fully connected. As will be seen, thedesign will be fully connected progressively as provided forin Block 6 (dealing with "critics") and in Block 7 (dealingwith design refinements). We use this approach, resemblingNOAH's underconstrained method,4 to avoid backtracking.

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Figure 4. An example of default rules.

Figure 5. An example of a design change rule.

Block 4: Knowledge base. The knowledge base isan expert system's heart. KnYowledge acquisition is mostdifficult, frequently constituting a bottle-neck during expertsystem construction.3 How knowledge is acquired,represented, and organized represents a central issue for allexpert systems.

Most of ASDEP's application-specific knowledge isrepresented using production rules. ASDEP employs thefollowing rule language structure based on the Backus-Naurform:

<RULE> ::= (IF <ANTECEDENT> THEN <ACTION>)

where ANTECEDENT is a Boolean expression composed ofpreconditions that must be satisfied before a rule can beactivated, and where ACTION is a Boolean expression thatwill either change a design, select another rule group, orchange a design parameter.

We use a rule-based formalism to capture human expertknowledge and experience, and to store that expertise in theknowledge base. Knowledge base rules diverge into twomajor groups: equipment default rules, and design changerules. Whenever ASDEP calls the knowledge base, thesystem selects the appropriate rule group by usingmetarules.5 Next, ASDEP checks each rule's preconditionsand (if valid) performs the appropriate binding between rulevariables and the specific design. Due to the subjectivityinherendy attached to knowledge base rules, users must havethe option to add, delete, or modify all knowledge baserules. Figures 4 and 5 exemplify rules found in each majorgroup, using Lisp computer language code.

During any design's initial stages, users frequently lacksome information needed to start the design process.Typically, human experts supply their estimates of missinginformation based on knowledge and prior experience.Likewise, knowledge base default rules (intended to capturehuman knowledge and experience) will supply most missinginformation regarding load and equipment data.

Figure 4's first rule will supply the missing kVA motorrating, if required. In addition, a decision must be made forany design as to appropriate voltage levels; indeed, voltagelevel selection is a most significant factor in power plantauxiliawy-system design. Several factors affecting systemvoltage selections6 are

* Load magnitude,* Distance from the main power supply,* Utilization device availability (as a function of voltageratings and limitations),

* Safety,* Codes and standards,* Cost of utilization and service system equipment, and* Future load growth.

Figure 4's second rule exemplifies a voltage selection rule.Figure 5 gives a design change rule related to a

switchgear's continuous current limit violations. Designchange rules typically will not undo the effects ofpreviously triggered design change rules, an approach oftencalled "nonchronological backtracking."3

Since auxiliary-system design progressively articulatespreferences, metarules play an important part in selectingappropriate design change rules. Each rule group selectionwill depend on a particular condition and the particulardesign stage.

Figure 6 shows the basic design change rule structure inthe knowledge base. Presently, the knowledge base containsover 150 rules formulated using Lisp. Of these, 60 aredefault rules and 90 are design change rules.

Block 5: Design storage. Intermediate designspecifications are stored in three major sections: load data,branch data, and bus data. The load data section lists allloads with their associated specifications. The branch datasection lists the buses connected to each branch, in additionto each branch's associated kVA rating. The bus data sectionlists the loads connected to each bus, in addition to eachbus's associated kV rating.

Block 6: Critics. Realizing designs from the goalsand constraints imposed upon them is difficult. Notsurprisingly, many initial designs don't satisfy all goals andconstraints. We must evaluate designs to verify adequateperformance levels, and to determine appropriatecorrections.

ASDEP uses two critics to evaluate designs. The firstcritic (PCritic) ascertains whether physical constraintsimposed on designs are satisfied. The second critic (RCritic)evaluates overall design reliability.

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Using critics to evaluate designs resembles the Hackerprogram philosophy.7 To a large extent, Hacker's criticshelp correct plans containing conflicts among theirsubgoals. Both PCritic and RCritic are written in Pascal, inview of Lisp's limited numerical handling capabilities.

PCritic. PCritic examines a design's physical con-straints to determine (1) which are violated and (2) optimalequipment selection for switchgear and transformerimpedances. The violated constraints will vary depending onequipment selection, making the problem difficult even forsimple cases. For example, the continuous current limit of a4.16-kV switchgear can vary from 1.2 to 3.0 kA; its short-circuit current can vary from 49 to 88 kA, while its closing-latching current can vary from 19 to 78 kA.

In addition, it is usually impossible to satisfy allphysical constraints, bringing on a new problem: How todetermine which constraints must be satisfied, and whichcan be somewhat violated. The set of constraint violationswill be used later to modify the design during the designchange phase.

PCritic contains three stages. Stage I minimizes thenumber of constraints violated. Stage 2 optimizes designparameters subject to the set of satisfied constraintsdetermined in Stage 1. Stage 3 classifies all constraints intothree sets: satisfied constraints, aimost-satisfied constraints,and violated constraints.

During Stage 1, PCritic addresses the following fiveconstraints:

* The continuous current limit,* The interrupting current limit,* The momentary current limit,* The steady-state voltage limit, and* The starting voltage limit.

PCritic applies each constraint to every load bus,consecutively. These five physical constraints are appliednot only to each bus, but also to each mode of plantoperation (start up, and normal running mode, for example).Based on the number of constraints violated, PCritic selectsthe worst-case mode for evaluation.

Since designers are normally not interested in findingoptimal solutions, precise analytical results aren'tnecessary. Designers are usually interested in findingsatisfactory solutions or a "satisfactum."8 A satisifactum is anacceptable design: that is, any design within acceptableparameters. This concept is fortuitous when designingauxiliary systems because conventional analytical methods9such as load-flow and short-circuit programs cannot beapplied to partial designs that are not fully connected, asmay be the case for the initial design. However, usingsimplified mathematical formulations, PCritic can break theproblem into noninteracting subproblems for each load bus.

RCritic. RCritic evaluates design reliability. Electricalauxiliary systems supply energy to motors, such as thosedriving circulating water pumps for coolant systems andcirculating fans for combustion systems. Power plants

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Figure 6. The knowledge base structure.

require other auxiliaries providing noninterruptible powerfor computers, instruments, and vital loads that must alwaysfunction, even when main generator and switchyard suppliesare not available. The reliability of these systems must beevaluated to quantitatively understand trade-offs betweensupply reliability and cost.

RCritic's basic reliability techniques rely on the mini-mal-path approach to determine minimal-cut sets.10 Forauxiliary systems, RCritic applies conventional reliabilityindices to each load bus. Basic load bus indices are (1) ex-pected failure rates, (2) average repair times, and (3) ex-pected annual outage times.

Block 7: Design refinements. Using knowledgebase design change rules and critic evaluations, users cancorrect the current design. In addition, they may changesome constraints previously imposed on the design (anoption called "articulation of preference").8

ASDEP's basic design change strategy partitions designchanges into the following four subproblems:

(SPI) Physical constraint satisfaction,(SP2) Load bus connection to satisfactory supply buses,(SP3) Reliability satisfaction, and(SP4) Determination of the appropriate grounding

system.

ASDEP addresses these subproblems sequentially, SPIthrough SP4. It solves subproblems SP2, SP3, and SP4using knowledge stored in the knowledge base. It solvessubproblem SPI in the same way; however, a progressiveordering triggers the rules. Initially, rules yielding onlyminor design changes (least expensive modifications) aretriggered. Next, rules yielding more drastic design changes

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Based on observations by human experts who designelectrical auxiliary systems and who generally carry out anentire design process before seeking critical evaluation, wedecided not to incorporate backtracking methods in ASDEPand designed the knowledge base accordingly. Thevalidation procedure, to be discussed next, proved this basicassumption valid.

This section will clarify the function of each of theseven blocks and the role the user plays in the designprocess.

Figure 7. The design change strategy.

(expensive modifications) are triggered progressively in thehope that all physical constraint violations can bealleviated.

Figure 7 shows ASDEP's design change strategy. Thefigure contains four categories of rules.

(1) Bus-PCI, Bus-PC2, and Bus-PC3 rules generatedesign change proposals to alleviate any physicalconstraint violation (subproblem SPI).

(2) Sort rules generate design change proposals toensure the auxiliary system's full connectivity (subproblemSP2).

(3) Reliab-ruleOl, Reliab-ruleO2, and Reliab-ruleO3generate design change proposals to improve the auxiliarysystem's reliability characteristics (subproblem SP3).

(4) Grounding rules generate design change proposals tosize the auxiliary system's appropriate grounding system(subproblem SP4).

Evaluation criteria. ASDEP is prototypical.Evaluation at this stage will demonstrate that AI techniquesare applicable for designing a power plant's electricalauxiliary system. We will not demonstrate full expert levelperformance or implement a production grade program.Furthermore, evaluation at this stage is informal. A morestructured approach will be taken when appropriate at a laterstage of development.

We solicited and obtained the assistance of recognizedhuman experts from Southern Company Services,Incorporated. It was agreed that Southern Company Serviceswould select a particular power plant auxiliary system, forwhich a design had already been completed, and provide thedata required for ASDEP to generate its version of the sameauxiliary system. An evaluation of the ASDEP design wasthen to take place. That evaluation was to address thefollowing issues:

* Load groupings,* Bus voltage selections,* Equipment selections, and* System topology.

Additional comments from Southem Company Servicesdesign engineers were also encouraged.

Problem statement. Southern Company Servicesengineers selected a single-unit, 990-MVA fossil powerplant. They considered only medium voltage loads.Furthermore, they allowed no generator circuit breakers orgenerator power switches in the design. Our referencesprovide all relevant design data and criteria provided bySouthern Company Services.U'

ASDEP's results. Rather than stepping through adetailed computer trace of dialogue between the user andASDEP, we will provide the design evolution and majorreasons for design changes. ASDEP completed the design infour steps. Figures 8a-c summarize the first three designsteps. Figure 9 shows the final design in more detail. MSUstands for main-step-up transformer, SST stands for station-service transformer, and UAT stands for unit-auxiliary

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Figure S. (a) Design DO, (b) Design Dl, (c) Design D2.

SPRING 1987 63

Figure 9. The final design.

transformer.Fossil plants employ two basic modes of plant

operation: start-up, and running. Running, the more severemode, was the mode considered for evaluation; however,ASDEP can model both modes.

Mainly, the load data provided by Southem CompanyServices contained categories and quantities of each loadtype plus related horsepower and kVA. We relied upondefault rules to provide the considerable missing data, inthis case intentionally omitted, to exercise the default rules.

ASDEP first generated a primitive initial design (DesignDO). Table I lists the PCritic evaluation of DO for loadbuses 20 and 21. The system then triggered design changerules in the knowledge base to alleviate the current andvoltage violations. This action split the loads on buses 20and 21. Figure 8b illustrates the resulting design.

Table 2 shows the PCritic evaluation of Dl for bus 20only. For buses 21, 22, and 23, the PCritic evaluationsrelating to the five physical constraints are similar. Allconstraint violations have been updated to Good with theexception of the Voltage-start constraint (now at the Poorlevel). The system triggered design change rules in theknowledge base to alleviate the Voltage-start constraint.ASDEP then selected a lower motor start voltage level of 85percent, changing the Poor status to Good.

Next, RCritic evaluated the design. Since this concerns afossil plant, reliability was not as vital as it would havebeen for a nuclear plant. However, RCritic did supervise theuser in combining two-two winding transformers into one-three winding transformers.

Finally, ASDEP triggered the grounding rules andselected a resistive grounding system for both the maingenerator and the unit auxiliary transformers. Figure 9shows the final design.

Evaluation. The Southem Company Servicesengineers delivered an overall evaluation of "positive." Ourreferences give their comments and recommendations." Inpart, they reported that

The basic system developed by the expert system[ASDEP] was one of the arrangements originallyevaluated for the subject plant. This scheme was rejectedas a result of an economic evaluation. This fact does notdiscount the validity of the expert system designs, butpoints out the need for an economic evaluator in theexpert system. Presently, ASDEP does not evaluatedesign economy explicitly, nor does it evaluate thecomparative economy of design decisions.

The following summarizes Southem Company Servicescomments for each of the four points in the evaluationcriteria and lists the necessary corrective actions to betaken:

* Load groupings were "good overall." However, twoloads "need to have redundant supplies, but this factorwas not specified by us [Southem Company Services]in the original data package . . ." RCritic can readilyhandle this point. No action need be taken.

* Bus voltage levels were identical to "one of the

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Table 1. PCRITIC evaluation for buses 20 and 21.

Physical constraints

Bus= 20Bus-load = Too many to listBus-voltage = 6900VSWGR = 9Continuous-current = ViolatedInterrupting-current = ViolatedMomentary-current = ViolatedVoltage-Start s ViolatedVoltage-reg = Good

original systems we [Southern Company Services]evaluated."However, Southern Company Servicesengineers selected a dual operating voltage level of4.16 kV to better handle small motors. By expandingthe knowledge base's voltage selection rules andincorporating an economic evaluator, ASDEP shouldarrive at similar decisions.

.Equipment selection had mixed reviews. However, theonly major difference was in switchgear selection.ASDEP properly selected switchgear selections for twoof the four load buses. The other two were improperlyselected due to a misinterpretation of switchgear dataprovided by Southem Company Services. Using correctinput data, ASDEP correctly calculated the generatorneutral resistor and correctly selected all fourswitchgears.

* Circuit topology for the running system was good.However, reliability of the starting system wasconsidered poor. Swapping buses 20 and 22 wouldremedy most reliability deficiencies. Presently, ASDEPdoesn't examine starting-system reliability in the samedetail as it does the running system. Expandingknowledge base reliability rules to better handle thestarting system should correct this problem.

Most of this commentary can be readily integrated intoASDEP'S next version. The major addition needed toenhance ASDEP's performance is an economic critic withappropriate economic rules in the knowledge base.

A SDEP incorporates the following Al techniquesand concepts:

* Default knowledge,* Underconstrained initial design,* A knowledge base,* Plan refinement,* Critics,* Metarules, and* Skeletal plans.

Bus = 21Bus-load = Too many to listBus-voltage = 6900VSWGR =9Continuous-current = ViolatedInterrupting-current = ViolatedMomentary-current = ViolatedVoltage-Start = ViolatedVoltage-reg = Good

Table 2. PCritic evaluation for bus 20.

The methodology used to implement ASDEP is notlimited to auxiliary system design. Indeed, both substationdesign and distribution design resemble auxiliary systemdesign. In all three cases, we must deal with strictly radialstructures where simplified analysis techniques can besuccessfully applied to subsets of the entire system.However, while auxiliary system design application islimited to relatively few new power plant constructions,substation and distribution designs have broad and frequentapplications. In this latter direction, ASDEP methodologywill demonstrate its full applicability. The fact remains thatthe methodology used in ASDEP will probably not bereadily extendable to transmission system planning becausepiecewise and local analysis techniques, used in the ASDEPcritics, are invalid for the highly meshed structures found in

all modern transmission networks.

AcknowledgmentThe authors wish to sincerely thank William E.

Underwood for his time and valuable commentary. Inaddition, we thank Lowell Brothers, Tom Higgens, andBippen Patel of Southern Company Services for their effortin providing a test case and for their professionalcommentary.

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Physical constraInts

Bus= 20Bus-load = PAF, IDF, CHS, GRF, VCP, PSW, BCW, PLV,

PRE, PULBus-voltage = 6900VSWGR = 1 1Continuous-current = GoodMomentary-current = GoodVoltage-Start = PoorVoltage-reg = Good

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References1. D. Geraghty et al., "Strategic Planning: Why Do We Need It?",IEEE Trans. Power Apparatus and Systems, WM064-2, IEEEService Center, 445 Hoes La., Piscataway, NJ., 1984.

2. R.N. Allan, R. Billinton, and M.F. DeOliveira, "ReliabilityEvaluation of the Auxiliary Electrical Systems of PowerStations," IEEE Trans. Power Apparatus and Systems, IEEEService Center, 445 Hoes La., Piscataway, NJ., Sept.JOct.1971.

3. D.B. Lenat, D.A. Waterman, and F. Hayes-Roth, Building ExpertSystems, Addison-Wesley, Reading, Mass., 1983.

4. E.D. Sacerdoti, "A Structure for Plans and Behavior," Tech.Report 109, Al Center, SRI Int'l, Menlo Park, Calif., 1975.

5. W. Gevarter, 'Expert Systems: Limited but Powerful," IEEESpectrum, Aug. 1983.

John J. Jansen is an assistant professor of electricalengineering at the Virginia Polytechnic Institute and StateUniversity. From 1983 to 1985, he worked as a graduate researchassistant at the Georgia Institute of Technology, developing anexpert system to design portions of a nuclear power plant. From1979 to 1983, he was a design engineer at the Duke PowerCompany in Charlotte, North Carolina, and was involved in thedesign and control of several nuclear power plants.

Jansen received his BS and MS degrees in electrical engineeringfrom the University of Florida in 1977 and 1979, respectively. In1985, he received his PhD in electrical engineering from theGeorgia Institute of Technology. His primary research interestsfocus on Al, robotics, and energy. A registered professionalengineer in North Carolina, he is a member of the EEE.

His address is the Dept. of Electrical Engineering, VirginiaPolytechnic and State University, Blacksburg, VA 24060.

6. D. Beeman, Industrial Power Systems Handbook, McGraw-Hill,Hightstown, N.Y., 1955.

7. P.R. Cohen and E.A. Feigenbaum, Handbook ofArtificialIntelligence, Vol. 3, Addison-Wesley, Reading, Mass., 1986.

8. A. Goicoechea, D.R. Hansen, and L. Duckstein, MultiobjectiveDecision Analysis with Engineering and Business Application,John Wiley and Sons, New York, N.Y., 1982.

9. J.R. Neuenswander, Modern Power Systems, IntemationalTextbook, Scranton, Penn., 1971.

10. R. Billinton and R.N. Allan, Reliability Evaluation ofPower Systems, Plenum Press, New York, N.Y., 1984.

11. J.F. Jansen, Application ofArtificial IntelligenceTechniques to Power System Design, doctoral dissertation,School of Electrical Engineering, Georgia Inst. of Technology,Atlanta. Ga.,1985.

Hans B. (Teddy) Piittgen has been an associate professor ofelectrical engineering at the Georgia Institute ofTechnology since 1981. From 1976 to 1981, he was a facultymember of the Califomia State University at Fresno, where he heldprimary responsibility for the electric power program. He hassupervised research projects funded by Lockheed and Thomson-CSFand by such agencies as the Califomia Energy Commission, NSF,EPRI, and TVA.

In 1972, he received his MSEE from the Swiss Federal Instituteof Technology. In 1974, he completed graduate studies in businessadministration at the University of Lausanne. He received his PhD inelectrical engineering (electric power option) in 1976 from theUniversity of Florida. His present interests involve the design andanalysis of electric power systems and intelligent electric motorcontrollers. He is a senior member of the IEEE, and a member of theTau Beta Phi, Eta Kappa Nu, and Phi Kappa Phi honor societies.

His address is the School of Electrical Engineering, Georgia Inst.of Technology, Atlanta, GA 30332-0250.

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