Getting the Most Out of Data: The Key to Successful Electrical Utility Application Integration

DGetting the Most Out of Data: The Key to Successful Electrical Utility Application Integration

Lawrence J. Kuhl
VP – Partnerships & Business Development
Coherent Networks, Inc.
1 Adler Drive
East Syracuse, New York 13057

Abstract

The electric utility industry is experiencing increased merger activity, more sophisticated competitors, more stringent regulatory demands, and customers with expanding menus of energy choices. These are just a few of the factors that drive utilities to look for new operating solutions. Corporate mergers often require integration of different operating systems. All utilities strive to implement operational enhancements that involve the integration of existing systems. When systems are integrated, the data that drives these systems must be migrated and integrated, too. But the required data integration is not always a success. In fact, 75 percent of respondents in recent IT surveys report significant problems as a result of defective or poorly integrated data. Before the processes that draw on this data can be trusted and counted on, the data itself must be verified as accurate. This article will examine issues associated with data accuracy, data sources, target applications, typical errors, and the need for new Operations Support Systems. It will explore techniques for verifying and validating data to ensure that it is accurate and complete. Architectures and methods for integrating applications using advanced gateways, messaging bus, and point-to-point solutions are outlined. Finally, the benefits of combining integration of technologies are discussed.

Paper

Introduction
The electric utility industry is experiencing re-regulation, the introduction of new more sophisticated business entities, more stringent regulatory demands, and customers with expanding menus of energy choices. These are just a few of the factors that have resulted in increased merger and acquisition activity and that drive utilities to look for new solutions to improve operational efficiency and meet constituency expectations. Corporate mergers result in having different operating systems that address the same basic need. In many cases, to achieve the anticipated benefits of the merger, consolidation or integration of information systems is required. Business expectations drive the need for operational enhancements, improved reliability, increased customer satisfaction, and cost reduction. In some cases, these are conflicting goals.

The merging of different business entities typically requires the merging of different business processes, inevitably leading to the integration and replacement of existing systems. When systems are integrated, the data that drives these systems must be migrated and integrated, as well. But the required data integration is not always a success. In fact, according to PriceWaterhouseCoopers, 75 percent of respondents in recent IT surveys report significant problems as a result of defective or poorly integrated data. Before the processes and corresponding applications that draw on data can be trusted and counted on, the data itself must be accurate.

This paper briefly explores the issues of data accuracy and consistency, the impact of quality data on Operations Support Systems, and the corresponding need for operational applications targeted for the electrical utility industry. Techniques for verifying and validating data to ensure that it is accurate and complete are reviewed. Methods of integrating applications using messaging bus and point-to-point solutions are discussed. An example of how the combination of technologies can be leveraged to benefit utilities is also presented.

Data – Sources, Targets and Errors
10:18 AM 12/17/2003 There are many sources of data needed by end-use Operations Support System (OSS) applications. Many of these systems rely on a geospatial representation of network assets. Meter reading and other customer load information, real-time network element status, analog energy flow, network connectivity, crew, customer status, construction, cost and other basic information is essential to maximizing the performance of these systems. For electric-based OSS applications, detailed physical asset attribute and configuration information, customer-to-facility relationships, phasing, electrical connectivity, structural integrity, are mandatory components. Typical source systems include CAD, GIS, CIS, AMR, SCADA, Distribution Automation, Asset Management Systems, and Graphical Design Estimation. The data from these systems, in turn, drives Outage Management (OMS), Work Management (WMS), Distribution Management (DMS), Energy Management (EMS), and Engineering Analysis packages. The conjunction of data from such a wide range of sources opens the door to data omissions, conflicts, gaps and errors.

What are the types of data errors that can impact an OSS and where do the errors come from? Data errors can result from data migration and data integration efforts if these projects are not properly monitored and controlled. Here, incompatible data formats, incomplete data, and duplicate data from two or more sources can offer stiff project challenges above and beyond what may have been inaccurate to start with. However, most errors result from a lack of proper data-entry business processes and data ownership. Typically, these errors arise due to limited error checking at various stages in the data management process. Another contributing factor is the inability of personnel who rely on the data to easily make corrections. Other error sources are often beyond the control of the utility. For example, when performing restoration efforts after a major storm (ice, hurricane, etc.), the primary focus is to get power back to customers, not to accurately report how the network was altered. Data-capture problems during these emergencies are compounded by the use of “foreign” crews who are not familiar with the local utility’s data-capture procedures.

The following represents the situation encountered after performing an initial assessment on a typical sample data set:

1	Anchor Text Outside of File	(39 of 7,992)
2.	Linear Objects (Primaries, Secondaries, Services) with 1 vertex	(1,582 of 26,682)
3.	Construction Spans w/o phasing 30 missing phasing 102 missing phasing, node ids, and circuit ids	(132 of 3,174)
4.	Fuses/Switches/Reclosers w/o conductors 102 not aligned w/ conductor or Open/Close status unset	(348 of 348)
5.	Primary Conductors node id unset	(6 of 20,513)
6.	Network connectivity issues 75 logical connectivity (node id attribute) problem 57 graphical connectivity problem	(132 of 3,193)

On a percentage basis, these problems may not seem extreme, but their on various systems can be very significant.

The connectivity and phasing problems discovered would have severe impact on the operations of an OMS or an engineering analysis package. Inaccurate data can create a multitude of problems—wrong assumptions about which device has operated to clear a fault, sending crews to the wrong location, over or under designed facilities, and false facility loading predictions that can lead to shortened facility life and potentially dangerous situations.

Other errors are associated with switching updates, loads, construction types, conductor sizes, consistency in device information like regulator settings, and customer-to-facility (usually the transformer) linkage. These data errors can also pose problems for a variety of applications. So, the question that remains is how do we detect and fix these errors?

With any approach to correcting errors, if procedures are not put in place to keep the data correct, then the effort will be in vain as the data will quickly become incorrect and thus waste resources. One approach involves performing a complete field audit. This approach is a very effective. It is also expensive. In some cases, this approach cannot be avoided. Another approach involves the implementation of advanced data gateways to limit the amount of fielding required. Advanced data gateways detect errors, automatically correct many of the errors, provide reports on what was fixed, and provide the tools for highlighting and fixing the remaining errors that cannot be automatically corrected. This approach allows the utility to target the areas that need to be fielded, thus reducing the overall expense.

Data/Application Integration Strategies

Three strategies for integrating applications come immediately to mind: Point-to-point, bus, and hub-and-spoke architectures. Point-to-point interfaces are common throughout the industry. They can be set up in either a batch or a transaction-based mode. They can be implemented as custom interfaces, gateways, by embedding components using COM technology, or by a combination of these technologies. There are a variety of information-bus technologies on the market from TIBCO, Vitria, IBM and others. They offer an excellent means to transport data from one application to another if you assume the data is accurate to start with. Bus architectures hide the messaging. Technology from SISCO takes the bus architecture for utilities one step further through the utilization of a Common Information Model (CIM) that has been defined for transmission and is well on its way for distribution asset information. However, data validation for the target systems cannot be completely addressed by this approach. Many utilities are finding their source system data is not accurate enough to support their OSS and have turned to gateway technology to maximize the performance of their applications.

Each approach has advantages and disadvantages. I will not debate the merits of these architectures. Instead, I will focus my attention on the need for accurate data regardless of the transport mechanism or integration architecture. For each architecture alternative, an interface or adapter is required. This interface or adapter can either be a simple translation mechanism or an advanced data gateway.

A gateway, configured to do more than simply transport data, is a unique technology that offers several advantages over an application interface. Advanced gateways focus on the data content needed by target applications. They provide not only a mechanism to fix data ambiguities and deliver the correct data in the exact format needed by the target application, but also the ability to return corrected information back to the data source or sources. Gateways for OSS applications have a state-of-the-art geospatial data viewing & editing environment, advanced data modeling to handle any target application and standard representations like the CIM, and pre-configured data exports including a direct link to message bus data transport technologies. They are compatible with any geospatial source.

Sophisticated gateways provide a means to integrate data from a variety of source systems for delivery to specific target systems. Source systems contain data needed by your target system. However, typically, the data is not in the form or of the high quality required by the target system to operate at its full potential. Gateways provide automated routines (mini-applications) that not only indicate where the problems are, but also correct many of the problems automatically. This technology also automatically integrates, constructs and validates the data attributes and relationships needed by specific target systems. In addition to the automated features, a high-performance graphical user interface for data viewing and editing fast and easy correction of any problems requiring operator attention. Making the process “fast and easy” requires an extensive set of flexible tools. For example, when a “verify” routine has been executed, a list of discrepancies is displayed. When the user selects one of the discrepancies, the user interface automatically navigates to the highlighted object in question, provides a description of what is wrong and opens the tool needed to fix the problem. Once the simple operation to correct the situation is performed, a re-verify can be executed to make sure the problem has been corrected.

For the specific integration task at hand, the gateway provides:

access to any geospatial data source
linkage between GIS Model and Network Element Tags (monitoring points)
validation and verification of network data against model requirements
identification and correction of data discrepancies

Example of Benefits Associated with the Combination of Integration Technologies
By combining several technologies (gateway, COM/ActiveX, and PI capabilities) along with direct access to real-time data sources, the utility can leverage existing assets to increase operational efficiencies and, ultimately, improve customer satisfaction. Taking advantage of the information already in CAD or GIS allows the utility to eliminate redundant graphics & data and associated with data-entry activities.

Combining historical network status and network configuration information provides the ability to replay specific events to more accurately analyze root causes of network disturbances. With the more accurate data, studies to place capacitors, regulators and sectionalizers/reclosures will generate more accurate results. Real-time displays can be made available to anyone in the utility.

Operations personnel can take advantage of having detailed asset information along with real-time data to operate the network more closely to design limits. This information will also facilitate dynamic feeder profiling, verification of load reduction in reaction to timeof- use (TOU) rate signals, and enhanced load balancing. Using dynamic network representation capabilities, network operations personnel can quickly take action so overload situations can be avoided which, ultimately, extends the life of existing facilities and prevents certain types of customer outages.

With access to up-to-date network information and real-time data from Operations, system planners can enhance protection coordination, develop solutions to lower line losses, and defer the construction of new facilities.

And that’s just scratching the surface. The real power of combining these technologies to integrate this data has yet to be realized. The network engineers, planners and operations personnel will determine how their current capabilities will be enhanced which will drive new and improved business processes and associated new Operations Support System applications. One of the keys to achieving new levels of operational efficiency is consistent, accurate and up-to-date data. Using the right mix of information technologies will ensure this key to success can be achieved.