Integration of Substation Data

M. Kezunovic

Texas A&M University, College Station, TX 77843-3128 USA (Tel: 979-845-7509; e-mail: kezunov@ece.tamu.edu)

Abstract: To improve reliability and security of the power system, operation data from all substation devices has to be integrated and useful information has to be extracted. Achieving data integration is a complex task and it is closely related to the interoperability paradigm. Interoperability is one of the most important and complex issues and it needs to be well understood and properly handled to assure the proposed concepts have long lived role through upgrading and expanding initial solutions. Having a standardized communication protocol facilitates integration of Intelligent Electronic Devices (IEDs) into systems, but it does not solve the problem of inconsistent and incomplete data formats and types. This paper describes means of achieving solution interoperability using Grid-Wise Architecture Council (GWAC) interoperability framework and it presents example applications.

1. INTRODUCTION

A modern substation’s intelligent electronic devices (IEDs) capture large amount of field data which are of interest to control centre and other enterprise applications. To collect this data, integrate it and extract useful information is not an easy task due to communication protocols, data models and data formats inconsistency. Achieving substation data integration is a novel paradigm and there is no standardized way of achieving it (D.S. Lah, et al 2005). Many utilities have poor communication resources, they use old technologies and they simple do not yet appreciate the business value of data integration. Utilities are concerned about cost of additional investment needed to improve data processing architecture in attempt to integrate substation data. EPRI and others have completed several studies about the positive impacts of data integration on efficiency and reliability of utility operations (M. Kezunovic 2010a). Unfortunately, it took large blackouts (particularly the northeast blackout in the USA in 2003) to recognize needs for improvement in disturbance reporting and analysis (UCPSOTF 2004). It appears that the requirements imposed by the North American Electric Reliability Corporation (NERC) after the northeast blackout can be easily met with the automated substation data integration and analysis. It is evident that utilities are coping with the data integration process in different ways. It is a common approach that different utility departments develop partial solutions that deal only with particular data creating “islands” of automation. However the full advantage of the automation can eventually be achieved if data is integrated across the whole system (M. Kezunovic et al 2004, M. Kezunovic 2010b).

Substation data integration can be defined as bringing

together data from different Intelligent Electronic Devices (IEDs) into databases at substation and control center level. This approach requires an architecture that supports open integration based on globally accepted standards, such as IEC 61850, IEC 61970, file naming convection for sequence data, COMTRADE, etc (IEC Std. 60255-24 2001; IEC Std. 61970-301 2003; IEC Std. 61850 2003; IEEE Std. PC37.232 2007). As a result of current situation, the problems faced by electric utilities in pursuing data integration are:

Lack of easy means of integration between legacy

and new applications Communication systems that do not exchange data

fast enough for practical uses Lack of standards for data models, data formats and

communication protocols To address the above issue, a comprehensive approach to data integration is needed. It should encompass not only the data integration problem but also problems associated with configuration data, data time synchronization, data archival, data visualization and applications that use new data to provide new benefits to the users. Illustrations of such comprehensive implementations have created experiences necessary to identify the problems discussed in this paper (P. Myrda, et al 2010). This paper discusses solutions and implementations for automated data integration based on Grid-Wise Architecture Council (GWAC) interoperability framework (GWAC 2008). The first part of the paper discuses data integration platform, the second part presents applications that benefit from integrated data, and then the new interoperability requirements are listed followed by conclusions and references.

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2. DATA INTEGRATION AND INFORMATION EXCHANGE

Early substation automation developments were focusing primarily on providing additional operational data and enhancing functionality of Intelligent Electronic Devices (IEDs) enabling them to provide non-operational data in real time. In the last decade, some advancement have been made in enhancing the communications and data collection infrastructure, but there have been no significant work on using non-operational data for extracting useful information from it for real time applications. While the operational data tells the operators in the control centre what happened, non-operational data can explain causes of disturbances and reasons why particular equipment operation happened (P. Myrda, 2010; M. Kezunovic , 2010a). Proper operational and non-operational data integration is the main requirement to enable full IED data utilization. Fig.1. shows substation data integration conceptual diagram. Assuming that all devices are synchronized using Global Positioning System (GPS) time reference the first steps towards substation data integration are introduction of standardized file format-COMTRADE, and standardized IEEE naming convection. The COMTRADE standard defines common format for exchange of data files related to various types of fault, tests, or simulation data for electrical power systems. Standardized IEEE file naming convention for the time sequence data is used for more efficient and simple file management. The file naming solution, which contains unique information about an event (date, time, station, company, duration, location, etc.), can enable easier handling of large volume of files by allowing unique file identification. Without use of those standards manipulation and data integration is highly inconvenient due to data volume and variety of data designation nomenclature used by different utilities. The data from individual substation IEDs, such as Phasor Measurement Units (PMUs), Digital Protective Relays (DPRs), Digital Fault Recorders (DFRs) and Circuit Breaker Monitors (CBMs), etc. already provide useful information associated with standalone IED. However, to get a more relevant and versatile information about disturbance all IED data should be merged, information extracted and verified to be used by control centre applications or further information extraction. The data redundancy has important role in data integration and information extraction. It may be recognized that the topology data and associated measurements are changing dynamically as the substation operation takes place and that IEDs record data related to pre- post- and in-time-of-the-fault condition. To correlate those data and make it accessible to the applications located at the control centre level, extension of data modelling standard should be proposed. The existing data communication and modelling standards focus mostly on operational data.

Benefits of data integration across entire substation are many. First, IEDs record some of the same signals, creating an

Fig. 1. Substation data integration diagram

opportunity to utilize data redundancy for performing data consistency checks. Also, certain IEDs record signals are not recorded by other IEDs, which ads information. However, the main value of substation data integration is in speeding up the restoration of the system after loss of service. The proper use of integrated data allows utilities to increase efficiency of their personnel and meet disturbance reporting standards imposed by the regulatory bodies (NERC, FERC, etc.).

3. APPLICATIONS BENEFITING FROM DATA INTEGRATION

There are several groups of application that may benefit from substation data integration. Those applications may be located at control centre, substation or other enterprise level. The legacy applications that use SCADA data for computations may benefit from integration of IED data by several means. First, the SCADA system is not the most robust design possible; there may be errors in the readings because of some malfunction occurring in the CB auxiliary contacts, transducers, SCADA communication equipment or RTUs. Another performance issue with SCADA is its relatively slow scanning rate for measurements (1-10s). The SCADA systems are not capable of tracking dynamic changes occurring in the intervals shorter than the SCADA scan time. The limited SCADA capabilities can be extended with the view obtained from the data captured by IEDs. Besides this, new applications that use benefits of operational and non-operational data may be developed and understanding of system conditions may be further enhanced (M. Kezunovic et al, 2005b). The Optimized Fault Location (OFL) and Intelligent Alarm Processing (IAP) applications shown in Fig. 2 use benefits of both SCADA and IED non-operational data ( M. Kezunovic et al. 2007; M. Kezunovic 2010a). On the other head applications such as DFRA, DPRA and CBMA and report generator rely only on IED data (TLI 2003). The system architectures used for substation IED data integration depends on available communication infrastructure, utility policy, availability of substation PC, etc. The results of several applications have to be merged to

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achieve full event description. The data validity may be improved due to redundant measurements and comprehensive reports may be generated due to completeness of integrated data. The proposed data integration solution supports client/server architecture. The client part resides at a PC in the substation and the server is located at the control centre level. Report generation and pre-processing may be done either at substation or at control centre level. In the case of processing at substation level, see Fig. 2. , all IED data are automatically collected to centralized repository. After process of data verification, data are transferred to COMTRADE 99 format and renamed by sequence data naming convection standard. The time range between different timestamps is checked and if it is less than 5ms and other parameters in the file name are the same it is concluded that all files corresponds to the same event. Those data are than stored to the database (DB) at the substation site. Simultaneously, IED data are analysed by applications implemented for each type of device and results are stored into DB database. Using that information, report for protection engineers and information of interests for applications at control centre level are extracted and stored into database. Applications at control centre level, such as OFL and IAP, constantly monitor new data availability and after database is updated with new files, those data are retrieved and merged with SCADA data. This kind of processing is suitable for utilities with poor communication infrastructure between substation and control centre because size of the data that have to be transferred to control centre level is drastically decreased by pre-processing at substation level. In the case of pre-processing at control centre level only data validation is done at substation PC and all data are sent to control centre location where further processing is done. This solution is appropriate for utility that has good communication infrastructure between substation and control center and where security policy forbids storing and processing data outside the control centre location. The DFRA, DPRA and CBMA (where “A” stands for analysis) applications use intelligent techniques, such as fuzzy logic and expert system to extract information about fault location and correctness of device operation.

In case of OFL application, once the disturbance records are obtained from the DFRs, two processing steps are taken to obtain phasors from the samples of recorded analogue signals:

Removal of high-frequency noise by low-pass filtering

Use of an improved Fourier algorithm to effectively remove decaying dc-offset component and obtain the pre-fault and during-fault phasors of voltages and currents.

Fig. 2. System Architecture

Fig. 3. Optimal Fault Location Application

Fig. 4. Intelligent Alarm Processing

The pre-fault phasor can be calculated using initial cycles of the recorded waveform. The during-fault phasor can be calculated using any fault cycle following the fault inception and prior to fault clearance. The fault inception moment is determined by DFRA from waveforms recorded by DFR. Fig. 3 shows information extraction for OFL application.

It is possible to select different fault cycle from the different DFR recordings to calculate the during-fault phasors. This may introduce fault location error, especially for the arcing faults during which the fault resistance is changing. Under this situation, selecting different fault cycles means experiencing different impacts of fault resistance.

In case of IAP application files generated by DPR and CBM have to be pre-processed and information of interest has to be extracted. That information consists of relay pick up values,

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Fig. 5. Interoperability Framework

relay trip status and circuit breaker status. This information is used to verify SCADA system measurements for the same event (See Fig.4). 4. NEW INTEROPERABILITY REQUIREMENTS

The interoperability is defined as “the capability of two or more network, systems, devices, applications, or components to exchange information between them and to use the information so exchanged” (EICTA 2004). Informational interoperability covers the data content, semantics and format (syntax). The proposed GWAC interoperability framework organizes concepts and terminology to identify interoperability problems. The framework recognizes that interoperability is only achieved when agreement is reached across many layers of concern. These layers cover the details of the issues involved to link systems together, to achieve the understanding of the information exchanged. Fig.5 summarizes the layered interoperability categories according to the technical, informational and organizational groups of issues.

To achieve communication interoperability between the systems or devices, data extraction, data exchange and data storage protocols have to be predefined and synchronized between the systems as shown in Fig. 6.

The description of each layer from the GWAC interoperability framework follows:

The basic connectivity presents digital exchange of the data between the systems and the establishment of the communication path. It is communication specification that explains communication medium, low level data encoding and rules for accessing the medium. This layer presents physical and data layer of the standardized communication Open System Interconnection (OSI) model.

The network interoperability presents mechanism of exchanging messages between multiple systems across a variety of networks. It means that agreed upon protocols are independent of the information that is transferred. This layer presents network, transport, session, and application layers of the standardized communication OSI model. As seen from Fig. 7, commonly used communication protocols for

Fig. 6. Interoperability between two systems

Fig. 7. Network Interoperability

Fig. 8. Syntactic Interoperability

substation and control centre levels are IEC 61850 and IEC 61970.

The Syntactic interoperability presents description of the format and structure in the messages exchanged between the systems. This layer includes the application and presentation layers of the standardized communication OSI model (See Fig. 8.)

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Fig. 9. Semantic Understanding

The Semantic understanding gives definition of the concepts contained in the message data structure. This layer governs the definition of the things, concepts, and their relationship to each other as shown in Fig. 9. Commonly used standards are IEC 61850 and COMTRADE at substation level and IEC 61970 at control centre level.

The Business Context presents business knowledge related to a specific interaction. It refers to restricting and refining the aspects of an information model relevant to a specific business process in question. It acts a bridge that transitions the more general semantic understanding with the needs of the specific business procedures. The Business Procedures define alignment between operational business processes and procedures. Effective information interoperability between business organizations requires that the involved organizations have compatible processes and procedures across their interface boundaries. The Business Objectives presents strategic and tactical objectives shared between businesses. It implies that strategic and tactical objectives across the systems have to be compatible. The Economic/Regulatory Policy presents national, state and local governance. Interoperability between the systems requires regulatory alignment for proper environment to build business relationship. The following are some of the issues recognized in attempt to achieve interoperability between substation and control centre systems (M. Kezunovic et al. 2005; O. Preiss et al. 2006 ):

It was shown shows that the published CIM version cannot meet the requirements of developed applications. The CIM model is very comprehensive and focused on modelling of operational data and some substation components. The CIM does not provide models for non-operational data, COMTRADE data format and some IEDs, such as CBM and DFR. It also does not allow for representation of dynamic data such as autoreclosing sequences.

There are inconsistencies between SCL/LN models defined in IEC61850 and IEC61970 data models and those models cannot be easily matched. The main inconsistencies can be classified on three levels: (a) per type representing a concept, (b) per relations between conceptually similar types, and (c) per presence or absence of attributes of conceptually similar types.

5. CONCLUSIONS

This paper focuses primarily on one aspect of smart grid implementation, namely data integration. It has been pointed out that:

The main value of substation data integration is in improving system reliability and security by speeding up the restoration of the system after loss of service.

Moreover, the proper use of integrated data allows utilities to increase efficiency of their personnel and meet reporting standards imposed by the regulatory bodies.

To take full advantage of data integration system the interoperability must be achieved. However, it brings many challenges in terms of technical (syntax), informational (semantic) and organizational (pragmatics aspects.

ACKNOWLEDGEMENTS

The work reported in this paper was funded by many parties including Electric Power Research Institute, Department of Energy and several utility companies: CenterPoint Energy, First Energy, Hydro One, American Electric Power-Texas and TXU Delivery. Many graduate students contributed to the results: B. Matic Cuka, Ce Zhang, O. Gonen, P. Dutta and Y. Guan.

REFERENCES

D.S. Lah, J.A. Mendonca (2005) "Measuring the impact of data integration in cooperative utilities," Rural Electric Power Conference, IEEE Cat. No. 05CH37644

EICTA (2004) Interoperability white paper” European Industry Association, Information Systems Communication Technologies Consumer Electronics.

GWAC (2008), GridWise Interoperability Context-Setting Framework,” [Online]: www.gridwiseac.org

IEC Std. 60255-24 (2001)”Common Format for Transient Data Exchange (COMTRADE) for Power Systems” First Edition 2001-05, International Electrotechnical Commission.

IEC Std. 61970-301(2003) “Energy Management Systems Application Program Interface-Part 301: Common Information Model (CIM) Base”, International Electrotechnical Commission.

IEC Std. 61850 (2003) “Communication Networks and Systems in Substations”, International Electrotechnical Commission.

IEEE Std. PC37.232 (2007), Recommended Practice for Naming Time Sequence Data Files.

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M. Kezunovic, A. Abur, A. Edris, D. Sobajic (2004) “Data Integration/Exchange Part II: Future Technical and Business Opportunities,” IEEE Power & Energy Magazine, pp 24-29.

M. Kezunovic, T. Djokic, T. Kostic (2005a) "Robust Topology Determination Based on Additional Substation Data from IEDs" PowerTech, St. Petersburg, Russia.

M. Kezunovic, A. Abur, (2005b) “Merging the Temporal and Spatial Aspects of Data and Information for Improved Power System Monitoring Applications,” IEEE Proceedings, Vol. 9, Issue 11, pp 1909-1919.

M. Kezunovic, E. Akleman, M. Knezev, O. Gonen, S. Natti (2007) "Optimized Fault Location," IREP Symposium 2007, Charleston, South Carolina.

M. Kezunovic, Yufan Guan, (2008) “Intelligent Alarm Processor” ERCOT Final Report.

M. Kezunovic (2010a) "Multiple Uses of Substation Data," EPRI Technical Report.

M. Kezunovic (2010b) "Substation Fault Analysis Requirements," IEEE PES Conference on Innovative Smart Grid Technologies, Washington, DC.

P. Myrda, M. Kezunovic, S. Sternfeld, D.R. Sevcik, T. Popovic (2010) “Converting Field Data to Information: New Requirements and Concepts for the 21st Century Automated Monitoring Solutions,” CIGRE General Session, Paris, France.

O. Preiss, T. Kostić (2006) “Unified Information Models in Support of Location Transparency for Future Utility Applications” 39th Hawaii International Conference on System Sciences.

TLI, (2003): “DFR Assistant - Software for Automated Analysis and Archival of DFR records with Integrated Fault Location Calculation”, [Online]. Available: http://www.tli-inc.com

UCPSOTF (2004) “Final Report on the August 14, 2003 Blackout in the United States and Canada: Causes and Recommendations“ US-Canada Power System outage task force, Available: http://permanent.access. gpo.gov/websites/ reportsenergygov/reports.energy.gov/ BlackoutFinal-Web.pdfM.

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