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55 IEEE Transactions on Power Systems, Vo1.6, No. 2, May 1991GUIDING A POWER SYSTEM RESTORATION WITH AN EXPERT SYSTEM

Daniel S.KirschenEmpros Systems InternationalMinneapolis, Minnesota

Abstract - Our civilization has become so dependent on a steadysupply of electric power that a blackout bears an enormouseconomic cost. Minimizing the amount of time needed to restore apower system helps reduce this cost and the public's resentmentover the interruption of service. An expert system can help theoperator achieve this goal by providing actualized restorationplans, dependable recommendations and a clear picture of thesituation.A hierarchical structure has been adopted for the prototype expertsystem described in this paper. This structure separates theselection of the next objective (strategic reasoning) from thedevelopment of a plan showing how this objective can be achieved(tactical reasoning). This separation enables the system to quicklyadapt its recommendations when a problem arises during theres toration.Planning connection paths through substations of widely differentconfigurations is greatly facili tated by the adoption of ahierarchical description of the topology of these substations. Thisknowledge representation scheme is the symbolic equivalent of theone-line diagrams used by the operators.

Terry L. VolkmannNorthem States Power CompanyMinneapolis, Minnesota

Many utilities have concluded that improvising a restoration planunder the stress of a blackout situation could lead to unacceptabledelays. After a careful study of their individual situation, theseutilities usually develop one or more written restoration proceduresreflecting the most effective ways of restoring the power system[6-121. Although it is commonly agreed that carefully preparedprocedures considerably simplify the restoration, these procedureshave serious limitations and the development of more powerfulmethodologies has been suggested [2].The main disadvantages of a written restoration procedure derivefrom its static nature. It is most likely that the status of the powersystem following the blackout will differ from the postulatedconditions used to develop the plans. Developing separateprocedures for different initial conditions alleviates but does notsolve the problem. Difficulties almost always arise during arestoration and it is clearly impossible to prescribe alternatives forevery conceivable problem. At some point, the operator in chargeof the restoration is thus likely to be forced to stray withoutguidance from the prepared plan. Such detours can be large or smallbut their preparation always takes time and their implementationincreases the probability of errors.

Keywords: power system restoration, power system operations,expert systems, knowledge representation. Another disadvantage of written restoration procedures is theamount of time required to reflect modifications in the powersystem. It is interesting to note that a review of 48 majordisturbances lists outdated procedures as the second leading cause ofI n t r o d u c t i o n restoration problems [2].Although electric utilities constantly strive to maintain thestability and the integrity of their power system, absolute securitycan never be guaranteed. A catastrophic sequence of events thatdefeats the preventive measures and overcomes the correctiveactions will occasionally unfold and cause a collapse of the entirepower system. If such a blackout does occur, electrical service mustbe restored as soon as possible to minimize the economic loss, theinconvenience to the public and the direct cost to the utility. Atthe same time, this restoration must proceed carefully to avoidendangering lives, damaging equipment or jeopardizing theprogress already accomplished in the re-energization.While performing the numerous operations required to rebuild thepower system following a blackout, the operator must be attentiveto many unusual voltage, line flow, stability and resourceconstraints. It is important to note that most operators haveprobably never had to work with the system when it is so farremoved fiom its normal state. References [l ] to [5] present veryinteresting descriptions and discussions of the problems whichcommonly arise during restorations.90 SM 341-8 P I P S A paper recommended and approved

The format of conventional restoration procedures also becomes ahindrance if the procedure cannot be followed as written. Textualinformation is intended to be read sequentially and does not lenditself to other modes of consultation. Following a written decisiontree forces the reader to jump back and forth in the text, querying awritten document is absurd, and switching to another level of detailis impossible.Finally, this textual format and the paper medium commonly usedto record these procedures force the operator to enter the restorationinstructions into the control computer. Transferring informationmanually is obviously a slow and error-prone process.Sakaguchi and Matsumoto [13] were the first to suggest that anexpert system could be used for planning switching operations.Since then this concept has been extended to the restoration ofdistribution systems [14] and generalized to the creation of optimalswitching sequences in substations [15]. Other authors [ l a . 171have proposed frameworks for the development of expert systemsapplicable to the restoration of high voltage networks. Reference[18] shows how a n expert system has been used to assist in theautomation of the restoration of a small power system.

by the I E E E Power System Engineering Committee-of theIEEE power Engineering Society fo r presentation at theIEEE/PES 1990 Summer Ivieetine;, Xnn eapo li s , Minnesota,Jul y 15-19, 1990. Manuscript submitted January 31,1990; made avai labl e fo r p ri nt in g June 21, 1990.

The restoration of a power system is often described as a two-phaseprocess. During the first phase, a skeleton network linking thegenerating stations and the main substations is re-energized. Thisenergization is then expanded to the rest of the network andcustomers are reconnected as power becomes available.This paper describes the Restoration Assistant, a prototype expertsystem designed to reduce the amount of time required to complete

0885-8950/91/0500-oS58$01.0001991 IEEE

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the fi s t phase of the restoration of a large power system. Thisreduction is achieved by:

presenting restoration plans that reflect the actual stateof the power system to the operator;relieving the operator from the more mundane tasks ofthe restoration to let him or her concentrate on morecomplex activities and on tasks which require humaninteractions;providing a clear picture of the status of the restorationto facilitate the decision-making process.

This expert system was developed on the basis of the newly-definedrestoration procedures of Northem States Power Company and mayreflect some of this utility's restoration philosophies. Inparticular, these procedures do not call for the simultaneouscreation of several restoration "islands" as is practiced by otherutilities. Consequently, the problems related to the existence ofseparate islands have not yet been studied in detail. However,every effort has been made to keep the architecture flexible and therules generic to ensure the applicability of this system to a widerange of situations.Description of the SystemIn artificial intelligence terminology, the restoration of a powersystem is classified as a planning problem. These problems havetraditionally been solved by determining a goal state and searchingheuristically for a sequence of actions leading from the current stateto this goal state [19, 201. This sequence of actions constitutes theplan. If a problem surfaces during the execution of a plan, which isvery likely in the case of a restoration, it must be discarded and thetime-consuming planning process must be repeated. This approachis thus not practical in situations where the environment isunpredictable and uncertain.However, the restoration can be decomposed into a set of goals orobjectives. Examples of objectives which must be achieved duringthe fi st phase of the restoration include the supply of crankingpower to each generating station and the creation of backup linksto each of these stations. It is then preferable to plan only as fa r asthe completion of the next objective. Using this approach, theamount of planning which must be repeated is much smaller if aplan fails at execution. Furthermore, if the expert system detectsthat, due to the current conditions, no feasible plan can be found fora given objective, this objective can be temporarily replaced byanother.This decomposition also creates a clear and useful separationbetween strategic and tactical matters. At the strategic level, theexpert system suggests to the operator which objective appears tobe the most urgent and broadly outlines the different ways ofreaching it. At the tactical level, the expert system prepares adetailed plan showing How a given objective can be achievedfollowing a given approach. In the remainder of this paper,strategy thus refers to the decisions which influence the globaloutcome of the restoration while tactic pertains to the decisionswhich affect only the success of a particular objective.Once a plan has been reviewed by the operator, the expert systemcan take care of issuing the commands necessary to implement it.If a problem develops during the execution of these commands, theexpert system will notify the operator and suggest an altemative.The expert system consists thus of three modules (strategicplanning, tactical planning and execution control) and a graphical

human interface. A detailed description of each of these modules ispresented in the following sections.Strategic PlanningThe identification of an internal or external source of power is thefirst step in restoring a power system. Once t h i s source has beenactivated, through a blackstart or an agreement with a neighboringutility, it is used to supply the auxiliaries of other power plants andmake possible their restart. Backup paths between the energizedstations must also be established to reduce the probability of acatastrophic set-back.For the purpose of strategic planning, the expert systemdecomposes the creation of this skeleton network into a set ofobjectives. Each of these objectives corresponds to the creation ofan energization or backup connection between two stations. Whilethe list of objectives is given, the order in which they are achievedis not imposed. Except for the fi s t two or three steps followingthe activation of the initial source of power, there are usuallyseveral objectives that can be reached directly and often severalways of reaching them.The expert system keeps track of which stations have beenenergized and which backup paths have been established. Thestrategic level module also relies on a predefined set of paths whichhave been determined through engineering studies as being suitablecorridors for the restoration. A path is either a single line or aseries of lines and minor substations linking two majorsubstations. Once a substation has been energized, the paths thatemanate from it become feasible. If such a feasible path leads to ade-energized substation, the energization of this substationbecomes a reachable objective. If this objective was alreadyreachable, the newly feasible path is recorded as an alternative wayof reaching this objective. Similarly, if a feasible path links twoenergized substations, it provides a way of creating a backup pathbetween these two stations. A path is not considered to be feasibleif it comprises a faulted line. a substation whose communicationsystem has failed, or a substation that has been disabled by a majorincident (e.g. a fire.)The predefined paths are not a detailed description of how aconnection can be established between two substations. They arede fi ed solely in terms of lines and stations and their sole purposeis to avoid having to consider too many details when searching fora possible approach to an objective.The feasible paths and the corresponding objectives are displayedon a high level diagram of the power network. The operator canthus decide which objective will be undertaken next based on a cleardisplay of the options. If a problem arises in the execution of anobjective, the operator can temporarily abandon it, return to thehigh-level diagram and select a substitute objective.If the restoration is managed from a central location, all thereachable objectives cannot be worked on at the same time and themost urgent one must be selected. The relative urgency of thevarious objectives depends in part on their intrinsic importancewhich can be assessed off-line. However, this urgency is alsoaffected by time-dependent factors which can change drasticallyduring the restoration. For example, the priority assigned to thereenergization of a particular station may be high until theexpiration of the deadline for a hot restart. On the other hand, thepriority given to the supply of auxiliary power to a nuclear plantwould increase dramatically if the emergency generators of thisplant were to fail. Upon request from the operator, the strategicplanning module will reassess the time dependent factorspertaining to each reachable objective and combine them withtheir static importance to establish a list of priorities. While all

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the reachable objectives are shown to the operator, the most urgentobjective is brought to his or her attention through a specialhighlighting. The knowledge encoded in the expert systemcurrently is capable of only a rudimentary priority assignment.More knowledge must be acquired to refine these recommendations.The final decision as to which objective to pursue and which pathto use rests with the operator and is communicated to the expertsystem by pointing and clicking on the graphical representation ofthe objective. The strategic planning module records the selectedobjective and the chosen path and passes this information to thetactical planning module which is thus assigned the task ofestablishing a detailed list of actions which must be carried out toachieve this objective. Possible actions include opening andclosing breakers, checking the value of a measurement or callinganother human operator to request the execution of a particularoperation.It must be emphasized that at the strategic level, the expert systemreasons only about abstract concepts (such as objectives and tasks)and high level objects (such as stations and paths).Figure 1 illustrates the type of information provided by thestrategic planning module. In this example, several objectives canbe reached from the substations already energized. Energizing thestation BDS is recommended by the expert system as the mosturgent objective. However, the operator could instead choose toenergize the stations BLL, HBR, ASK or WH T or to create a backupconnection between the substations RRK and IVH via thesubstation CGR.

XR D GRC B E NG-G-0

RO C0 Deenergized Substation=Energized Substatione =Path Substation

@ =Objective Substation@ =Most Urgent Objective

-- Energized Line- - - - =Path Line L ine11501

Figure 1. An Example of Strategic Information andRecommendations Provided by the Restoration Assistant.

The expert system suggests two paths for the energization of BDS.The fist goes through IVG and PKN while the second eoes through

KCH, WPC, FIS and BRV. Once the energization of BDS isachieved, the path which was not chosen will be recommended for abackup connection. The path between BYN and BDS is notsuggested by the expert system because a fault on the line betweenLKM and WEF makes it infeasible.Figure 1 is a black and white approximation of one of the dynamiccolor displays that have been designed for the expert system. Onthe actual displays, the user can switch to another display, trigger aplanning task, or start the execution of a plan simply by pointingand clicking at the appropriate location.Tact ical PlanningThe tactical planning module is responsible for translating into alist of actions the tasks defined by the strategic planning module.A task usually prescribes the connection of two stations via a path.A path is either a single line or a sequence of lines and intermediatesubstations connecting the two stations. Each task is decomposedinto subtasks, one for each substation affected by the connection.Each subtask thus prescribes the creation of a connection betweentwo points within a single substation. These two points are:

the incoming and outgoing lines for an intermediatesubstation;the outgoing line and the energized bus closest to thisline for an energized station;the incoming line and the auxiliaries bus for adeenergized station.

Tactical planning consists therefore primarily of determining theswitches that must be opened or closed to connect two points of asubs ation.The knowledge base used for tactical planning is complete if itcovers all substation configurations and any pair of points in anysubstation. Furthermore, the presence of malfunctioning breakersor faulted busses may not prevent it from producing a feasibleconnection plan if such a plan exists.A tactical plan is correct if it is equivalent to what an experiencedoperator would do under the same circumstances. In general, thisimplies avoiding the energization of unrelated lines andminimizing the number of switching operations. However, thisminimization is not carried out with a short term perspective.Some extra switching operations are often performed before theyare actually needed to facilitate future connections and reduce thenumber of operations needed in the long run.In addition to the traditional criteria of completeness andcorrectness, the tactical planning module must also be efficient. Itis indeed likely that the expert system would be rejected by theoperators if it took more than a few seconds to construct a plan.The development of an expert system which satisfies theserequirements has been greatly facilitated by the design of a newknowledge representation scheme. The topology of a substation iscommonly defined for algorithmic applications by specifying thecomponents to which each device is directly connected. For expertsystems, this approach is not practical because it does not providea global view of the substation. Planning a connection path basedon this information requires a search analogous to finding one'sway in a city by relying strictly on the street signs at the end ofeach block. Such a search is feasible [I51 but very different fromthe mental process used by an operator to plan a connection path.It is easier and more intuitive to rely on a "symbolic map" of the

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561substation. A hierarchical knowledge representation scheme hasbeen designed to provide this map to the tactical planning module.The main features of t h i s scheme will be explained using thesimplified diagram of the RRK substation shown on Figure 2. Thisstation is divided into two levels separated by transformers (RRK-345 and RRK-115). Each level consists of busses (e.g. 115-TOPand 115-BOT for RRK-115. 345-TOP and 345-BOT for RRK-345)and branches (A, B,C. E and F for RRK-345,'E.F. G. H, I, J and Kfor RRK-115). A branch is defined as one, two, or three switchesconnected in series. Branches belong to different classesdepending on how many switches they contain and whether or notthey include a transformer. For example, C is a three-switch branchwhile E is a two-switch-transformerbranch.If both ends of a branch are in the same level, the branch is anintemal branch of this level (e.g. A ,B and C for RRK-345, G, H, I,J and K for RRK-345). If the ends are at different levels (e.g. E, F)it is an extemal branch of each level. A branch is also extemal ifone of its ends is connected to a line.Several attributes are defiied for each branch. For example, thedefinition of branch J is:

from-end 115-TOPto-end: 115-BOTfirst-switch J1first-midpoint: Esecond-switch: 12second-midpoint: RRKCGRthird- sw ch: J3

Similarly, the definition of branch E isfrom-end: 345-TOPto-end: Jfirst-switch Elfirst-midpoint: TR-1second-switch: E2

The line RRK-CGR has the following definition:from-station: RRKto-station: CGR

(a bus)(a bus)

(a breaker)(a branch)(a breaker)(a line)(a breaker)

(a bus)(a branch)(a breaker)

(a transformer)(a disconnect)

(a station)(a station)from-end J (a branch of RRK)

to-end: Z (a branch of CGR)Some operations which must be repeated often when determining apath through a substation become very simple using this scheme.For example, the definition of line RRK-CGR indicates that thisline has a terminal at station RRK and that this terminal is onbranch J. The definition of branch J shows that this terminal isseparated from bus 115-BOT by only one breaker. 115-BOT is thusthe "closest bus" to line RRK-CGR at station RRK and theenergization of this line will usually require the energization ofthat bus.This scheme is applicable not only to breaker-and-a-half typesubstations but also to ring-bus and other types of substations.Since a unified representation of all substations is now available, asingle method can be used to plan a connection path between twopoints in any substation. This method proceeds as follows:

If the two points are in different levels, the problem isfirst decomposed into the selection of an extemal branchlinking the two levels and the planning of a path in eachlevel.

The location of the endpoints of each path are thenpinpointed using the branches where they are located andthe closest busses.Using this information, the type of connection isdetermined. For example, if the two endpoints areclosest to the same bus, a connection will be establishedalong this bus. Otherwise, a more complex connectiontype is suggested. The rule base is organized in such away that the most desirable types of connection areconsidered first. If a path would involve a faulted bus ora breaker that is blocked open, it is rejected and anotherpath is determined.Finally, a list of all the switching operations required tocreate this path is constructed on the basis of theselected connection type and the status of thesubstation.

Example 1:Suppose that it has been decided to energize the station CGR fromthe station IVH and through the substation RRK. A plan showinghow to connect the points labeled IVH and CGR on Figure 3 mustbe developed. These points being in different levels, the expertsystem begins by identifying an extemal branch linking these twolevels, Branch F is chosen because it links directly the bussesclosest to the endpoints. The problem is thus decomposed intothree subproblems: closing all the switches of branch F.connecting branch F to the line to CGR and connecting branch F tothe line to IVH. The first subproblem is trivial. For the second, itis determined that the connection should be made on the bus 115-BOT while for the third it should be made on the bus 345-BOT.Figure 3summarizes the operations required to create this path.Example 2:Suppose that a connection between the same two endpoints isdesired but that it is known that breaker F1 is blocked open. Theexpert system determines that branch F cannot be used and thuschooses branch E to link the two levels. The line to IVH musttherefore be connected to the bus 345-TOP. This path is inferior tothe one constructed in the First example because it requires theenergization of the line to PRI. Figure 4 summarizes theoperations required in substation RRK to create this path. Thesystem also determines which breakers must be opened in stationPRI.Figures 3 and 4 are only black-and-white approximations ofdynamic color displays. On the actual displays, the operator canmodify a plan simply by pointing and clicking on the desiredswitches. If the planned connection involves a neighboringstation, clicking on the name of that station brings up a similardiagram which highlights the operations required in that station.It must be emphasized that the knowledge used to develop thetactical plans is purely generic. It reflects only standard operatingprocedures and does not include any information specific to aparticular substation. Therefore, the knowledge base does not needto be updated each time the configuration of a substation ismodified.

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562TLK AFT RFS E PRI ASK

RRK-345 LevelMAX BCK STY CGRRRK-115LevelFigure 2. Description of the SubstationRRK using the Knowledge RepresentationScheme of the Restoration Assistant.

TLK AFT RFS E PRI ASK

Figure 3 . Tactical Plan for the Condition of Example 1.

TLK AFT RFS E PRI ASK

MAX BCK STY CGR

Figure4.Tactical Plan for the Condition of Example 2.

e vsy =C o ~ & o nPath=Unaffected breaker

0 =Breaker to be opened or kept open. =Breaker to be closed or kept closed.=Breaker blocked in open position.11502

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Execution Control563

C o n c l u s i o nOnce a plan has been reviewed and approved, the operator has theoption of letting the expert system take care of its execution.Performing switching operations manually is indeed a slowprocess. The one-line diagram of each substation must bedisplayed, the cursor must be positioned on the appropriate switch,the switching command must be issued and confirmed. Asubstantial amount of time can clearly be saved by automatingthese manual operations.If the responsibility for implementing the switching commands isdelegated to the expert system, the amount of time required to issuean extra command is very small. The expert system can thus beused to execute commands that might be neglected when theswitching is performed manually. For example, issuing an "open"command to a breaker which is already open resets the automaticreclosure mechanism which might have been activated by a relayduring the system collapse. If this mechanism is not reset, thebreaker may close automatical ly when one of its sides is energizeddepending on the last breaker operation which took place beforethe blackout. This closure could reconnect a significant amount ofload and cause a major set-back in the restoration.In order to properly schedule the execution of the switchingoperations, the expert system monitors the completion of thecommands which have already been issued. If the event processorof the SCADA system indicates that a command did not produce theexpected result, the expert system b r i g s t h i s fact to the attentionof the operator and attempts to develop an alternate plan. If thefailure is due to a switch blocked in the closed position, a smallmodification to the plan can usually be found. On the other hand, ifthe failure is due to a switch blocked in the open position, theentire plan may have to be modified.

Implementation and TestsThe prototype has been implemented as a rule-based expert systemon a Symbolics 3675. Its knowledge base was developed using thePROTEUS expert system shell [21] and currently containsapproximately 350 rules. A significant portion of the NorthernStates Power system has been modelled to validate the expertsystem.Each module was first tested separately. In particular, the tacticalplanning rules were checked on different substation configurations.A large number of paths were generated within each substation andverified by comparing them to standard operating practices. If theexpert system was informed of the unavailability of some devices,it generated alternate paths which were carefully examined andfound acceptable.The various modules of the expert system were then integrated tosimulate the restoration of the NSP system. If no equipmenttrouble was introduced, the expert system produced a plan identicalor equivalent to the written procedures.Planning the energization of a sta tion along a path which crossesthree large substations typically takes about five seconds. Aparticularly complex connection or the presence of knownequipment problems may require a slightly longer time. Planning arestoration path on-line is therefore not only theoreticallyfeasible, but can also be done in a sufficiently short time to bepractical and acceptable to an operator.

Reducing the amount of time required to restore a power systemfollowing a blackout is the ultimate goal of the expert systemdescribed in this paper. Each of the following features of thisexpert system contribute to th is reduction:

.The plans generated by the expert system reflect thecurrent configuration of the substations, the true statusof the power system, and the known equipmentproblems.Some operations which are usually performed manuallycan be delegated to the expert system. The expertsystem not only performs these tasks faster than theoperator, but the time saved can be used by the operatorfor more complex duties or for functions requiring humaninter actions.Since the plans generated by the expert system arealready in an "electronic" format, the amount ofinformation which must be manually entered is minimaland the probability of error is considerably reduced.The expert system reasons and interacts with theoperator at both the system level and the equipmentlevel. This feature allows the operator to separate minordifficulties from major decisions.

Experiments with the prototype system have shown that it iscapable of preparing and displaying complete and correct tacticalplans much faster than an experienced engineer could point on asubstation diagram to the breakers that should be operated.The Restoration Assistant is intended to supplement, not replace,the design of a restoration strategy for each utility. A significantamount of knowledge is acquired from the results of these studiesand implicitly incorporated in the expert system under the form ofrestoration objectives, paths, and priorities. Inserting thisknowledge explicitly in the expert system would further increaseits power and flexibility.

ReferencesM. M. Adibi et al. "Power System Restoration - A TaskForce Report," IEEE Transactions on Power Systems,Vol. PWRS-2, No. 2, pp. 271-277, May 1987.M. M. Adibi et al. "Power System Restoration - TheSecond Task Force Report," IEEE Transactions on PowerSystems, Vol. PWRS-2, No. 4, pp, 927-933, November1987.M.M. Adibi, D. Scheurer, "System OperationsChallenges: Iisues and Problems in Power SystemRestoration," IEEE Transactions on Power Systems,Vol. PWRS-3, No. 1, pp. 123-124, February 1988.W.A. Johnson et al., "System Restoration - Deployingthe Plan," IEEE Transactions on Power Apparatus andSystems, Vol. PAS-101, No.11, pp. 4263-4271,November 1982.U.G. Knight, "Aids or the Emergency Control of PowerSystems," CIGRE Electra, No. 67. pp. 101-134,December 1979.

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R.J. Kafka, D.R. Penders, S.H. Bouchey, M.M. Adibi,"System Restoration Plan Development for aMetropolitan Electric System." IEEE Transactions onPower Apparatus and Systems, Vol. PAS-100, N0.8, pp.3703-3713. August 1981.R.J. Kafka. D.R. Penders. S.H. Bouchey. M.M. Adibi,"Role of Interactive and Control Computers in theDevelopment of a System Restoration Plan," IEEETransactions on Power Apparatus and Systems, Vol.PAS-101, No.1. pp. 43-52, January 1982.D. Scheurer, "System Restoration at PhiladelphiaElectric Company". paper presented at the IEEE PESWorkshop on Real-Time Monitoring and Control ofPower Systems, Montreal, Canada, October 10-12,1984.S. Peach, "Hydro-Qutbec System RestorationSynthesis." paper presented at the IEEE PES Workshopon Real-Time Monitoring and Control of PowerSystems, Montreal, Canada, October 10-12, 1984.P.F. Arnold, "Summary of System Restoration Plan forthe Pacific Northwest Power System," paper presented tothe Power System Restoration Task Force at the 1982IEEE Winter Power Meeting.E.J. Simburger. F.J. Hubert, "Low Voltage Bulk PowerSystem Restoration Simulation," IEEE Transactions onPower Apparatus and Systems, Vol. PAS-100, No.11,pp. 4479-4484, November 1981.E. Mariani. F. Mastroianni, V. Romano, "Fieldexperience in Reenergization of Electrical Networksfrom Thermal and Hydro Units," IEEE Transactions onPower Apparatus and Systems, Vol. PAS-103, No.7. pp.1707-1713, July 1984.T. Sakaguchi, K. Matsumoto, "Development of aKnowledge Based System for Power SystemRestoration." IEEE Transactions on Power Apparatus andSystems, Vol. PAS-102, No.2, pp. 320-329, February1983.C.C. Liu, S.J. Lee, S.S. Venkata, "An Expert SystemOperational Aid for Restoration and Loss Reduction ofDistribution Systems, " IEEE Transactions on PowerSystems, Vol. 3, No. 2, pp. 619-626, May 1988.Z.Z. Ban g, G.S. Hope, O.P. Malik, "A Knowledge-based Approach to Optimize Switching in Substations,"IEEE Transactions on Power Delivery, Vol. 5, No. 1,January 1990.

T. Kojima et al. "Restoration Guidance System for TrunkLine System." IEEE Transactions on Power Systems,Vol. 4, No. 3. pp. 1228-1235, August 1989.I. Takeyasu et al. "An Expert System for Fault Analysisand Restoration of Trunk Line Power Systems." inProceedings of the First Symposium on Expert SystemsApplications to Power Systems, Stockholm-Helsinki.August 22-26, 1988, pp. 8-24 to 8-31.L.R. Blessing, C.K. Bush, S.J. Yak, Automated PowerSystem Restoration Incorporating Expert SystemTechniques," in Proceedings of the Second Symposiumon Expert Systems Applications to Power Systems,Seattle, July 17-20, 1989. pp. 133-139.R.E. Fikes,N.J. Nilsson, "STRIPS: A New Approach tothe Application of Theorem Proving to ProblemSolving." Artificial Intelligence, Vol. 2. No. 3/4, pp.189-208. 1971.E. D. acerdoti, "Planning in a Hierarchy of AbstractionSpaces," Artificial Intelligence, Vol. 5, No. 2, pp.115-135. 1974.C. Petrie, D. Russinoff, D. Steiner, "PROTEUS: ADefault Reasoning Perspective". in Proc. 5th GenerationConference, National Institute of Software, October1986.

~

Daniel S. Kirschen received the Electrical and MechanicalEngineer's degree in 1979 from the Universitt Libre de Bruxelles.Belgium. He received the Master's and Ph.D. degrees in ElectricalEngineering from the University of Wisconsin-Madison in 1980and 1985 respectively. He has been working for the EMPROSdivision of Control Data Corporation since 1985.Terry L. Volkmann received the Bachelor of Science degree inElectrical Engineering from the University of Minnesota in 1978.He has been employed by Northern States Power Company since1975. He presently is the Superintendent of OperationCoordination with the responsibility of technical support to theSystem Control Center in the area of transmission operation. Inthis capacity, he lead the team that developed the knowledge baseof NSPs Intelligent Alarm Processor. He has been working on thedevelopment of NSP's restoration procedures since 1986.

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D scussi onH. M. AD BI Appl i cati on of expert systems f orassessi ng t he st atus of di st r i but i on syst emsand deter m ni ng t he appropr i at e sw t chi ngoperat i ons f ol l ow ng maj or di st urbances hasbeen expl ored i n [13,14 & 151 and the authorspaper i s a si gni f i cant contr i buti on i n t hi sarea. The r estart and rei nt egr at i on of bul kpower suppl y however, requi res a combi nat i onof expert systems and anal yti cal t ool s so t hatduri ng t he "st r at egyf 9 nd l l t acti cal *f l anni ng,t he f ol l ow ng concer ns woul d be properl yaddressed [3,16 & 171:1.

2.

3 .

4 .

5.

The

energi zi ng l arge sect i ons of t ransmssi onl i nes w t hi n t he accept abl e t r ansi ent andsustai ned over vol t ages w t hout t he r i skof generator sel f exci t at i on,l oad pi ck-up i n l arge i ncrement s w t houtt he ri sk of f r equency decl i ne andrecur r ence of out age,mai ntenance of st eady st ate and t ransi entstabi l i t i es as system i s bei ng rest oredand when i mpedances are l ar ge,reduct i on of st andi ng angl es when cl osi ngl oops t o f i r mup tr ansmssi on pat hs, andcoordi nat i on of t her mal pl ant st ar t - upt i m ngs w t h l oad pi ck- ups t o bri nggenerators t o thei r st abl e mni mum l evel sand w t hi n the range of maj or anal ogcont rol l ers.exi st i ng anal yti cal t ool s are l ar ge,compr ehensi ve and i nef f i ci ent f or on- l i nest rategy and t acti cal pl anni ng. Does t heaut hors approach consi der t he above and ot herpower syst emconst r ai nt s and what exi st i ng ornew anal yti cal t ool s ar e used i n pl anni ng t he"skel etont 1net work?

Under St rategi c Pl anni ng i t i s stat ed t hat t he"st r ategi c l evel modul es" r el y on a predefi nedset of pat hs whi ch have been det erm nedt hrough engi neer i ng studi es. Thi s cont r adi ct st he statement under I nt roduct i on t hat t he"st at us of t he power system f ol l ow ng t hebl ackout w l l di f f er f rom the postul atedcondi t i ons used t o devel op t he pl ans". Coul dt he aut hors cl ari f y these two apparent l ycont radi ctory st atement s?I n order t o avoi d l osi ng cri t i cal t i mes suchas hot rest ar t of t hermal pl ant s and t o t akeadvant age of several sources of bl ack st artcapabi l i t i es wi t hi n t he power syst emgeneral l y t wo or more subsyst ems ar e rest oredi n paral l el . Coul d t he authors cl ari f yNort hern Stat e Power' s phi l osophy i n adopt i ngsequent i al rest or at i on?Whi l e rest orat i on procedure has a def i ni t ebegi nni ng, i t s compl et i on i s not so cl ear cut .Theref ore, mni mzi ng t he r estorati on dur at i onas the goal i s not as meani ngful as maxi mzi ngt he restorati on of servi ce mega-watt - hour asshown i n [21. The curves are r eproduced heref or conveni ence. I t can be seen t hat bothscenari os or st r at egi es reach the 1600 Mw l oadl evel 10 hours af t er t he st art of r estorati on.

565However , dur i ng t he 10 hour s, Scenari o Iserves 17. 4 GWH or 42% more t han 12.3 GWH f orScenar i o 11. Woul d t he aut hor s comment on t heef f ect of change i n goal on thei r st rat egypl anni ng?

Mega- Watt-Hours Restored2500

2000LI.3 1500*g2.3 1000

G

"-l

*TV

500

0 0 1 2 3 4 5 6 7 8 9 1 0 1 1 1 2Restoration Duration - HoursScenario 1 . cenario 11

M a n u s c ri p t r e c e i v e d J u l y 2 7 , 1990.

D.S. Kirschen, T.L. Volkmann: The interest that Mr. Adibishows for our work and his encouraging comments are verygratifying. His remarks highlight some of the areas which we willhave to investigate in more details as we continue the developmentof our expert system. In particular, it is clear that the use of someanalytical tools would increase the confidence of the operator n therecommendations of the Restoration Assistant. At this time, webelieve that streamlined versions of the analytical tools will be usedto check the plans developed by the expert system. Considering theuncertainty about the value of some parameters and the questionablevalidity of the traditional models during a restoration, simplifiedcomputationsmight be sufficient.The contradiction between the design of the Restoration Assistantand the introductory statement concerning the uncertainty as to thestate of the power system after a blackout is only apparent. If thisstate was totally predictable, prepared plans would be effective andthere would be little need for an expert system . If it was totallyunpredictable, the expert system would have to have completeflexibility to adapt to any situation and would thus be extremelycomplex. In practice, the uncertainty is such that the expert systemmust have some flexibility but does not have to invent a newrestoration strategy for each case. It has thus been designed todevelop reconnection plans based on a choice between paths whichhave been shown to be viable alternatives through engineeringstudies.

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566Although a parallel restoration of two or more subsystems couldtheoretically shorten the restoration, the implementation of such anapproach is difficult when the control of th e power system iscentralized as is the case for Northem States Power. The operator incharge of the restoration would have to split his or her attentionbetween two areas and it is doubtful that the end result would bebeneficial. Manuscript received September 27, 1990.

Mr. Adibi is entirely correct to point out that restoration Strategiesshould be compared on the basis of the amount of energy deliveredto the customers. It is clear that the choice of restoration objectivesshould be guided by this criteria.