Design of A Knowledge Based Trouble Call System with Colored Petri Net Models

Transcription

1 2005 IEEE/PES Transmission and Distribution Conference & Exhibition: Asia and Pacific Dalian, China Design of A Knowledge Based Trouble Call System with Colored Petri Net Models Hui-Jen Chuang, Chia-Hung Lin, Chao-Shun Chen, Chi-Chun Yun, Chin-Yin Ho, and Chung-Sheng Li Abstract--A nowledge based trouble call system with colored Petri net (CPN) inference models is designed to identify the most robable faulted device for trouble call analysis (TCA) of distribution systems. The CPN model for inference engine considers two major arts: the traditional escalation method and the load comarison method. To identify the faulted device more accurately according to the outage reorts by service customers, the searching rocedures based on the imroved escalation method are included in the best first search of the CPN. The most ossible outage locations with corresonding blown out rotective device are determined by alying arallel-lie reasoning in the CPN to solve multile fault events simultaneously. One of the distribution systems in Taiwan Power Comany (Taiower) with customers is selected for comuter simulation to demonstrate the effectiveness of the roosed methodology to enhance the function of distribution outage management. Index Terms Trouble call analysis, Colored Petri net, Distribution automation system. I. INTRODUCTION With the advancement and alication of comuter control systems, unreliable ower suly can be extremely costly to electric utilities and their customers. To imrove system reliability and oeration efficiency, a distribution automation system (DAS) has been imlemented by Taiower since With TCA as one of ten functions, the outage duration of customers caused by system faults can be reduced by identifying the faulted device more accurately for reair crews to exedite ower restoration. Besides, the outage information can be retrieved by distribution system oerators so that roer load transfer can be taen for service restoration. With deregulation of ower industry, it becomes imortant for utility comanies to enhance service quality so that more customers can be et in the cometitive maretlace. With a fault on the rimary feeder of an underground distribution system in Fig. 1, the feeder circuit breaer will be tried by over-current relays. System disatchers can diagnose the contingency by SCADA system according to the status change of the circuit breaer and rotective relays at switches along the feeder. After detecting the fault H.-J. Chuang and C.-Y. Ho are with the Deartment of Electrical Engineering, Kao-Yuan Institute of Technology, Luzhu Shiang, Kaohsiung County 821, Taiwan C.-H. Lin and C.-S. Li are with the Deartment of Electrical Engineering, National Kaohsiung University of Alied Sciences, Kaohsiung 80709, Taiwan. C.-S. Chen and C.-C. Yun are with the Deartment of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung 80424, Taiwan.. location, the boundary load breaers of 4-way line switches are oened to isolate the fault section. The feeder circuit breaer is then closed to restore ower service of ustream customers. After that, the roer switching oeration lan is derived by considering the caacity reserve and oeration constraints so that the downstream unfaulted but out of service area can be transferred to the other feeders. With the DAS system, the fault detection, isolation and service restoration (IR) can be comleted within 3 to 5 minutes in Taiower. MTa D S Circuit breaer D S Fig.1. Feeder i Ii Power Fuse N.O. Power fuse Ij MTb Feeder j Lateral 1 3C#1XP SWi1 Four-way line switch To serve the load Four-way high voltage mold joint To serve the load Lateral 3 Lateral 2 Four-way line switch SWj1 Under 31A 3C500XP2 100~200A A tyical underground distribution system of Taiower. SWi2 50~100A 31~49A With more than 80% of faults in Taiower distribution system on the lateral or customer sides, the blown fuse at the source size of lateral or distribution transformers will interrut ower service of the affected customers. It is still not cost justified for system oerators to identify this tye of fault by DAS systems because so many fault indicators and communication systems have to be installed and the affected area is much serious faults on main feeders. After receiving hone calls from customers to reort the ower outage, reair crews are sent out to do the field chec to locate fault locations. It is very difficult and time consuming to identify faulted devices and comlete service restoration for an underground distribution systems. To solve the roblem, a geograhic based digital maing system has been created for the DAS system to include system networ connectivity and service customers with account number, N.O. 3C500XP2 Pad-mounted transformer Lateral 4 SWj /05/$ IEEE. 1

2 telehone number, address and the distribution transformer connected. With so many rotective devices and voluminous customers involved in distribution systems, system disatchers have to identify the most robable rotective device out of service for disatching crews to fix the roblem. To exedite the searching rocedures, an efficient inference tool has to be develoed to suort TCA function by considering the nowledge base of distribution systems. Petri-Net (PN) is a owerful inference mechanism and has been successfully alied in the areas of service restoration scheduling [1] [2], fault section estimation [3], rule-based evaluation [4] and ower system rotection [5] [6]. With grahic reresentation, PN simulates the system oeration by including their timing and sequence of hysical objects. The nowledge and networ configuration of distribution systems can be exressed systematically through a structured model with arallelism and synchronization [1]. In this aer, the nowledge based trouble call system with colored Petri net (CPN) models is roosed to derive the TCA for Taiower distribution system. The CPN is alied to model the inference net to suort decision maing rocess by considering system toology and the change of feeder loading due to faults. When a ermanent fault occurs, the nowledge to identify out-of-service areas is obtained by the searching rocedures and system database. With the nowledge base and its arallel-lie inference engines, the CPN can find the most robable outaged devices for system faults. II. DESIGN OF THE KNOWLEDGE BASED TROUBLE CALL SYSTEM The nowledge base comrises the information retrieved from DAS database, system configuration by toology rocessor (TP), and searching rocedures. The DAS database stores the geograhic locations, attributes and connectivity records of distribution system comonents and customers. According to the connectivity records and dynamic statuses of switching devices, which have been retrieved from the real time SCADA system, TP is executed to determine system networ configuration for inference engine to rocess the trouble call analysis. The distribution system oeration rules are included in the heuristic search to suort deriving fault locations. The inference engine of high level CPN model is alied to find the most ossible faulted devices and their locations. With the distribution system configuration and customer database, the searching rocedures can estimate the switching devices which have been oerated for fault clearance according to outage reorts by the customer. The man-machine interface (MMI) rovides the tools for oerators to udate the database and oeration rules. A. Toology Processor Toology rocessor is to identify the networ configuration based on the attributes of distribution connectivity model and dynamic switch statuses in DAS database. By tracing the FROM and TO fields of connectivity table which oints to the ustream and 2 downstream devices of each comonent, the system networ configuration is determined and udated according to the oeration of switching devices. A distribution system comonent can be categorized as either branch or node. A branch is any device with two terminals such as line sections, switches, transformers, etc., while a node is the electricity oint that connects several branch devices together. The toology rocess is executed by starting from a given node or a branch and continues until either an oen tie switch is reached or all devices have been comletely traced. B. Searching Procedures for Trouble Call Analysis The searching rocedures for TCA are included in the colored Petri net model by considering the oeration rules to handle the customer trouble calls in Taiower. The TCA consists of the connectivity tracing stage (CTS) and load comaring stage (LCS). Since the triing of any ustream rotective device will result in service outage of all customers in the downstream service zones, the CTS is to identify all ustream rotective devices from the customers who have made the trouble calls. The LCS is to mae comarison of loading reduction of faulted feeder and the load estimation of de-energized service zones with trouble calls. To comly with the distribution system oeration regulation for TCA, the following heuristic search stes are exloited in the CTS rocess. Ste 1. Determine distribution system configuration by connectivity trace with a node-lin scheme as described in Section A. The results of connectivity trace are stored in the connectivity table with corresonding attribute of elements in the DAS database. The system is therefore reresented as a networ with tree grah to determine the scoe of distribution systems. The node reduction rocess has been executed to minimize the size of system model. Ste 2. With toology rocess in Ste 1, a binary integer matrix LR is created to reresent the connectivity of rotective devices and service zones. A samle system in Fig. 2 is used to illustrate the rocess of determining the elements in the matrix LR. Based on the radial networ structure and locations of rotective devices, the entries of matrix LR can be determined as (1). P1 P2 P3 P4 P5 P6 P7 SZ SZ SZ LR = SZ SZ SZ SZ where SZ and P are the set of service zone grous and the set of rotective devices, resectively. For the element LR ij with value 1, the trouble call from customers in service zone SZ i will be made if the jth rotective device P j is oerated. On the other hand, for element LR ij with value 0, the oeration of rotective device j will not cause the ith service (1)

3 zone SZ i to be de-energized. Therefore, LR can reflect not only the connectivity between the rotective devices and service zones, but also the color settings of Petri net models for trouble call analysis. Ste 3. According to the trouble calls made by outaged customers, the most ossible fault location is estimated by searching customer geograhic locations and tracing the networ connectivity. The common oints of connectivity in the ustream ath from the locations of the callers will rovide the ossible rotective devices for several crews to chec and reaired. With the structure of matrix LR in (1) for the samle distribution system in Fig. 2, trouble calls from service zones SZ 5 and SZ 7 will result in the tracing rocesses by the escalation method as follows: Set1= {SZ 5 P 5 P 3 P 2 P 1 } Set2= {SZ 7 P 7 P 4 P 3 P 2 P 1 } FCB i Main Feeder i Fig. 2. SZ 6 D S Substation MCB 1 MCB 2 Lateral P 1 P 2 P 6 SZ 1 SZ 2 SZ 5 P 5 P 3 From the above escalation aths, the intersection oeration is imlemented on sets Set1 and Set2 to identify the common ath for ustream rotective devices as follow. P 3 P 2 P 1 The robable outage device is suggested as P 3, P 2, or P 1 Ste 4. To deal with trouble calls for multile outage roblem, the outage escalation method is used to search the location of each caller until the first common rotective device is reached. The multile ossible faulted devices will be the combinations of robable outage devices instead of the first common rotective device. For the above examle, the tracing rocesses are reeated by the escalation method as follows: Set3= {SZ 5 P 5 P 3 } Set4= {SZ 7 P 7 P 4 P 3 } By investigating Set3 and Set4, the ossible outage devices are determined as combinations of (P 5, P 7 ) and (P 5, P 4 ). Ste 5. For any additional trouble call, the rocesses in Ste SZ 4 P 4 SZ 3 P 7 Samle underground distribution system. FCBj Main Feeder j SZ 7 : Four-way switch : Service zone : Protective device 3 and Ste 4 are reeated until the most ossible fault oint has been identified. By this way, the confidence level of faulted device can be imroved with sufficient number of trouble calls. In order to determine the most ossible outage device, it is necessary to estimate the load current of associated service zones connected to each ossible outage device. It is very tedious and imractical to solve the load estimation by conventional load flow analysis because of so many combinations of all associated service zones involved. The quic load estimation SL of service zone i by (2) is alied in this aer by assuming the conforming loads for all customers. TCi SLi = I = a,b,or c hase N TCi i=1 where I : actual feeder hase loading before outage, (2) TC : total rated caacities of transformers within i service zone i for hase, N: total number of service zones. The following heuristic search stes are alied in the LCS rocess. Ste 6. Sum of load estimations of service zones for the ossible outage device is calculated for each hase, I SLi = n i= 1 Ste 7. Retrieve hase currents of feeder loading before and after trouble call from the SCADA system for the calculation of current change in (4). aft bef (3) I = I I (4) Ste 8. Solve the mismatch of loading estimation by (5). a a ( ) 2 b b ( ) 2 c I I + I I + ( I I ) c 2 LD = (5) Ste 9. Select the device i which will result in the minimum mismatch as the most ossible fault device. III. THE INFERENCE MECHANISM OF THE COLORED PETRI NET MODEL In this aer, a high-level CPN model [7] is used for the determination of the most ossible outage device. The lace nodes (PL) reresent the conditions and the transition nodes (TR) reresent the events for state transitions of the study system. The CPN inference is erformed by the toens and colors assing from the system initial state to the final state. The TR node will be activated if the guard function of the enabled TR node is evaluated to be true. The toens are then assed from the entering laces to the outgoing laces. For CPN inference mechanism, many toens and colors may exist to result in the activation of several TR nodes at the same time. Therefore, these toens and colors assing can be rocessed simultaneously to achieve arallel-lie inference mechanism. The CPN inference models have been roosed [8] by 3

4 the authors to solve the roer switching oeration for distribution system fault restoration. A totally different CPN model has been designed with new searching algorithm to assist the trouble call analysis function by considering the relationshi of customer service zones and rotective devices. A. The Colored Petri Net Model for a Service Zone The roosed CPN model for a service zone of distribution systems is illustrated in Fig. 3. There are 3 PL nodes (P1, P2, and P3) and 1 TR node (T1). P1 reresents the connectivity between the service zone and each rotective device. The color setting of P1 is determined by matrix LR in the heuristic search Ste 2. The color setting of P2 is defined by outaged customers in a service zone. The TR node is embedded with oeration rules to decide the status transfer of P1, P2, and P3. The inference mechanism for transition nodes and lace nodes is illustrated in Table I. The inference of transition mode 1 is to ass the color setting and toen of P1 to P3 with the trouble calls of customers in the service zone. Mode 2 is alied to ass a non-calling color setting to P3 if no trouble call has been made by customers in the service zone. The non-calling color setting is ONE if all the row elements for the service zone in matrix LR are 1. P1 P2 T1 B. The CPN Inference Model for Searching the Most Possible Outage Devices Fig. 4 shows the CPN inference model for searching the most ossible outage devices. The color settings of PL nodes (S a1 ~S an ) with service interrution reorts are determined by the inference of CPN model for a service zone in Table I. To solve the intersection oeration in Ste 3, the AND oeration is executed for color settings of S a1 ~S an of all service zones in the feeder as defined by (6). S a1 S a2 L S an (6) S a1 T a1 T 1 T n T c1 T cm P 1 P n CP 1 CP m Goal lace nodes Fig. 4 The CPN inference model for searching the most ossible outage device For the CPN inference model in Fig. 4, all color settings of S a1 ~S a7 are ONE excet SZ5 and SZ7 in Table II. The common rotective devices are determined as follows: S an I 1 I n CO 1 CO m Fig. 3. The colored Petri net model for a service zone TABLE I THE INFERENCE OF THE CPN MODEL FOR A SERVICE ZONE Transition mode Pre-action color settings P3 Post-action color setting P1 P2 P3 1 S(T) C S(T) Descrition with trouble call in the service zone w/o trouble call in the 2 S NC ONE service zone S: The color setting of each service zone. (T): Toen C: with trouble call within the service zone. NC: w/o trouble call within service zone. Suose there are two customers to reort the service outages for the samle distribution system in Fig. 2, customer 1 in service zone SZ 5 and customer 2 in service zone SZ 7. The inference of CPN model for 7 service zones is illustrated in Table II. TABLE II THE INFERENCE OF THE CPN MODEL FOR THE SAMPLE DISTRIBUTION SYSTEM Service The re-action color The ost-action color Transition zone settings of lace nodes settings of lace nodes mode P1 P2 P3 P1 P2 P3 SZ NC NC SZ NC NC SZ NC NC SZ NC NC SZ (T) C C (T) 1 SZ NC NC SZ (T) C C (T) 1 4 P 1 P 2 P 3 P 4 P 5 P 6 P By executing the intersection (AND) oeration and activating the TR node T 1, the candidate outage devices (the color settings of PL nodes I 1 ~I n ) in common ath are determined. Besides, multile device outages are also considered in the CPN model. In Ste 4, the combinations of ossible outage devices (the color settings of PL nodes CO 1 ~CO m ) are obtained by escalating from the location of each caller to the first common rotective device after intersection oeration. In the examle, the ossible outage devices are P 1, P 2, and P 3 and the combination of (P 5, P 4 ) and (P 5, P 7 ) are considered for the ossible multile outages. In Fig. 4, the PL node reresents the feeder with trouble calls. The most ossible outage device is determined by comaring the load estimation of service zones to the change of feeder loading in Ste 8. The PL nodes (I 1 ~I n or CO 1 ~CO m ) which has the minimum mismatch will activate its corresonding TR node among T 1 ~T cm and ass the toen to the corresonding goal PL node. IV. PRACTICAL SYSTEM STUDY To demonstrate the effectiveness of the roosed methodology to enhance trouble call analysis, an underground distribution system served by Tzyou Substation of Taiower is selected for comuter simulation.

5 Fig. 5 shows the artial diagram of the system with 3 main transformers, 18 rimary feeders, 328 laterals, 379 service zones, and 362 rotective devices to serve customers. To reresent the distribution system by the roosed CPN model, 1827 PL nodes, 1035 TR nodes and 2534 directed arcs are created. In this aer, a comuter rogram is written in CLIPS and run on a ersonal comuter Pentium-III 800 MHz to simulate the trouble call analysis with the roosed CPN model. Case 1: Single Fault A fault event is assumed to occur on the rotective device P611 of Fig. 5 and two customers in service zones Z572 and Z609 have reorted the service outage. Fig. 6 shows the locations of the above two customers with the associated candidate rotective device sets and the intersection of these two sets generated by the roosed CPN model. It is found that there are two ossible oerated rotective devices (P611 and P613) in the intersection set for the single fault. Besides, ten combinations of [(P607,P578)(P607,P560)(P607,P576)(P607,P574)(P607,P5 73)(P610,P578)(P610,P560)(P610,P576)(P610,P574)(P610, P573)] are considered for the multile oerated rotective devices. By comaring the load estimation of service zones for the ossible outage devices and the change of feeder loading (searching stes 6~9 in Section II-B) in Table III, the mismatches of loading estimation for rotective devices P613 and P611 are 16.5 and 14.6 resectively. With such a small difference of LD, both P613 and P611 will be selected as the most robable faulted devices. According to the restoration rules in Taiower, the downstream rotective device P611 will be checed first for fault identification. Case 2: Multile Faults For a large scale ower outage of distribution systems caused by flood or storm damage, many trouble calls will be made by customers within 8 service zones in Fig. 7. The most ossible faulted devices derived by both traditional TCA algorithm and the roosed method are resented. By the traditional escalation algorithm, the outage location will be escalated to fuses P578, P611, and P613. However, the roosed method as shown in Fig. 7 will reort the outages at their lower levers of distribution system with four indeendent outages (fuses P560, P580, P583, and P586). The incorrect identification of outage devices with over-escalation by the traditional algorithm may cause time delay to locate the faulted device for service restoration. On the other hand, the roosed CPN algorithm can redict the faulted device more effectively by considering system networ connectivity and the comarison of load estimation of ossible outage service zones and loading change of the faulted feeder. B1 MT1 Tzyou BF1 B2 Fig.5 CB The one-line diagram of Taiower distribution system. CB52 CB53 CB

6 Z617 TABLE III MISMATCH OF LOADING ESTIMATION OF SERVICE ZONES AND FEEDER LOADING CHANGE FOR POSSIBLE OUTAGE DEVICES Switchgear Room Protective device ΔLD GD9690 P GD9692 P BD1466, GC2100 P607, P BD1466, FB9285 P607, P BD1466, EB9300 P607, P BD1466, FA4761 P607, P BD1466, FA6600 P607, P BD1690, GC2100 P610, P BD1690, FB9285 P610, P BD1690, EB9300 P610, P BD1690, FA4761 P610, P BD1690, FA6600 P610, P P618 P615 Z614 P616 Z639 P642 P635 P638 Z623 P627 P629 Z628 Z626 P60 P613 To higher level feeder circuit breaer Customer 1 escalation ath Z596 P599 Z598 P597 P595 Z594 P611 Z558 P592 Z591 Customer 2 escalation ath Intersection ath P608 P607 P610 Z609 Z606 V. CONCLUSIONS In this aer, a nowledge based outage management system with the associated CPN inference model has been develoed to enhance the trouble call analysis. The most ossible faulted devices are identified efficiently so that the ower service of affected customers can be restored with less outage duration. By executing the toology rocess, the system networ configuration is identified and udated according to the oeration of line switches and rotective devices. With the networ connectivity and CPN inference model, the roosed methodology can locate the faulted devices by considering the loading estimation of service zones and the change of actual feeder loading. The searching rocedures have been included in the CPN model for inference mechanism so that the trouble call analysis can comly with the oeration regulation. By the searching rocedures with arallel-lie inference caability, the CPN has been alied successfully to imrove the identification of ossible outage rotective devices for fault isolation and service restoration of distribution systems can be enhanced. To demonstrate the effectiveness of the roosed CPN based trouble call analysis, a ractical distribution system in Taiower has been selected for comuter simulation. It is found that the trouble call system can identify the outage location very efficiently by the CPN inference mechanism for both the small and large scale outage roblems. Z637 P583 P578 P586 Z585 Z617 Z582 P580 Z579 Z584 Z571 Z577 Z575 Fig.6 The customer locations and the ossible candidate oerated rotective devices P618 P615 Z614 P616 Z639 P642 P635 P638 Z623 P627 P629 Z628 Z626 P60 P613 Z596 P599 Z598 P611 P560 Z572 P573 P574 P576 Z569 P562 P564 Z563 Z561 To higher level feeder circuit breaer P597 P595 Z594 Z558 P588 z587 Correct identification of outage devices by roosed algorithm Incorrect identification of outage devices by traditional escalated algorithm Service zone with service interrution reort VI. REFERENCE [1]. Jaw-Shyang Wu, Chen-Ching Liu, Kan-Lee Liou, and Ron F. Chu, "A etri net algorithm for scheduling of generic restoration actions, " IEEE Trans. on Power Syst., vol. 12, no. 1, , Feb [2]. Jaw-Shyang Wu, "A etri-net algorithm for multile contingencies of distribution system oeration, " IEEE Trans. on Power Syst., vol. 13, no. 3, , Aug [3]. C.L. Yang, A. Yooyama, et al., "Fault section estimation of ower system using color time etri nets, " Proc. of Exert System Alication to Power Systems, , [4]. K. Tomsovic, "Evaluation rule-based systems, " Proc. of Exert System Alication to Power Systems, , [5]. L. Jenins and H.P. Khincha, "Deterministic and stochastic etri net models of rotection schemes, " IEEE Trans. on Power Delivery, vol. 7, no. 1, , Jan [6]. F. Wang and J. Tang, "Modeling of a transmission line rotection relaying scheme using etri nets, " 96 WM PWRD, IEEE/PES Winter Meeting, Jan , 1996 Baltimore, Maryland, USA. [7]. K. Jensen, Colored Petri Nets-Basic Concets, Analysis Methods and Practice Use, Berlin, Germany: Sringer-Verlag, 1992, vol. 1. [8]. Chao-Shun Chen, Chia-Hung Lin, and Hung-Ying Tsai "A rule-based exert system with colored Petri net models for distribution system service restoration, " IEEE Trans. on Power Syst., vol. 17, no. 4, , Nov P583 P578 P586 Z585 Z582 Z571 P560 P588 Z577 P576 Z575 P574 Z572 P573 P592 Z591 P608 P607 P610 Z609 Z606 Z637 P580 Z584 P562 Z561 Z579 Z569 P564 z587 Z563 Fig. 7 The service interrution and candidate oerated rotective devices for case 2. 6