Why a Well-integrated OMS is Crucial to Reliability of Today’s Energy Utility

puzzle with a piece missing

For energy utilities that have invested in the automation of outage management, their implementations have paid off by enabling them to improve productivity, improve customer service, and handle system growth with greater efficiency. Automation of operational systems organization-wide has also positioned utilities to further leverage their investments by integrating the historical real-time data embedded in these automated systems to optimize asset management. By combining and analyzing historical event information, utilities can improve the operations, maintenance and design of distribution network systems and components, which in turn can lead to a reduction in outages and increased reliability overall. 

Evolution of Automation within Utilities

Utility automation is an evolutionary process that often takes place in four phases and culminates with the application of real-time sensors to manage the grid optimally from an energy efficiency perspective (Green), improve reliability, and to improve asset management. Most utilities will find themselves somewhere within the first three phases of automation. The operational benefits of achieving each phase are compounded and equate to increased reliability, safety, compliance, and profitability for the utility.

Phase One: Digital Transformation

The first phase of utility automation begins with digital transformation – installation of computerized systems for the management of substations, customer information, work orders, mobile work forces, geospatial information, automated metering infrastructure (AMI) and other critical operations. A major aspect of further automation has included the implementation of intelligent electronic devices such as digital relays and digital fault recorders to feed real-time event information through SCADA systems from the substations to a control center. 

These systems have given personnel instantaneous access to status information relating to components and sub-systems throughout the distribution network. Alarms and monitors put breaker positions, fault distances, load measurements and dozens of other digital and analog data points at the fingertips of personnel as events occur. Whether this real-time information is streaming in from the substation or from the FCIs along a feeder, operations personnel are better equipped to monitor the current operating condition of the distribution system.

Stand alone systems provide workforce automation for specific job types: service orders, construction work orders, maintenance orders and trouble orders.

Phase Two: Optimizing Workforce via Systems Integration

The second phase of utility automation has involved the integration of two or more automated systems. In many cases, automation and integration can be carried out simultaneously. Achieving enterprise-wide access is the driving force behind this approach. By linking outage management (OMS), customer information (CIS), interactive voice response (IVR), work management (WMS), mobile workforce management (MWM), SCADA, AMI and geographic information systems (GIS), utilities can create operational threads that share real-time data and provide all personnel in the organization with access to information on the overall health of the distribution network. 

This sharing of real-time information has further enhanced the ability of personnel to make faster and smarter decisions that get customers back online more quickly or to provide a good picture of what has been restored and what needs to be restored still a couple days into a major storm event. 

A good example of this level of automation within utilities is bringing AMI data into the control center for the OMS to use as part of its outage prediction and automated outage restoration verification processes.

This phase of automation addresses the need to optimize the utility workforce by integrating the independent crew and work management systems to provide a view of current service orders, maintenance orders, construction work and same day emergency trouble work that allow scheduling engines to schedule short duration, long duration, filler jobs and same day interruptions including integrating with the utility’s automated call-out roster system.

While many electric utilities have been investing in both the underlying energy delivery business systems and their high-value integrations for decades, gas utilities are just starting to invest in operational business systems such as AI powered incident management systems and gas outage management systems and integrating them with dashboard technology to bring the same level of operational awareness and customer service that has been enabled by electric OMS deployments.

Phase Three: Operational Performance Analysis Improving Asset Management

Not only has enterprise-wide information allowed personnel to schedule and perform work more efficiently, it has also enabled them to maintain the assets more effectively by planning equipment upgrades and squeezing longer lives out of aging components. This transition from enhancing personnel performance to optimizing assets will push automation into its next phase of evolution – integration of real-time data archives to support outage trend analysis, power quality issue analysis and feeder reliability analysis. 

Until now, the automation of systems has successfully revealed what is happening in the distribution network. The information that can be obtained from the integration of historical real-time data stored in data archives embedded within automated systems can tell personnel why specific events happened and aid in forecasting when they may occur by integrating with simulation software and AI powered threat analysis. 

Emerging analytic functionality can also help identify parts of the network that are at the greatest risk of potential failure. There has been research and development efforts that can forecast when a device will fail based on its digital footprint historic signatures. Such heads-up information can aid utilities to proactively replace and/or reinforce weak links to reduce the probability of unplanned events. This knowledge will yield benefits far beyond those now offered by operational automation and integration. 

Data Repositories – Building Blocks of Operational Intelligence

For many utilities, data repositories of the real-time measurement and event data recorded by automated systems were installed during automation implementation, and they have been archiving irreplaceable system performance information ever since. This means utilities may already have decades of historical system performance logs available for integration and analysis.

Each data repository, in addition to OMS, contains valuable information relevant to the system that recorded it:

  • OMS archives the time, duration and cause of outages, customers impacted by the outage, actual operating network configurations, and switching logs.
  • WMS maintains a history of all work orders pertaining to maintenance and installation of various distribution facilities and construction crew productivity.
  • MWM keeps records of preventative maintenance performed on equipment and infrastructure in the field as well as personnel productivity.
  • CIS maintains billing and load data and tracks trouble calls made by customers as well as levels of customer service response they have experienced.
  • ERP records the financial investment in each component and its current book value.

Although most automated systems are installed by the vendor with built-in data repositories developed specifically to archive data for that problem domain, SCADA systems are the exception. Because these systems can communicate with dozens of meters and intelligent electronic devices of various makes and brands, most SCADA installations do not include data repositories for both control and device operating histories. Instead, this type of information is captured in a separate system component often referred to as a ‘historian’ or SCADA Historian. 

Historians capture data such as breaker position, recloser operations, equipment and environment temperatures, relay status, load measurements and other substation conditions. SCADA data repositories are designed specifically to handle large data files sizes and to perform time-series evaluations of real-time data. 

Data repositories provide great insight into distribution operations. For instance, analysis of historical work order logs can reveal which transformers have been particularly troublesome and may require refurbishment or replacement. Review of ERP archives enables utilities to determine revenue generated from individual infrastructure components, a valuable calculation when replacement or upgrading is under consideration.

Realizing the Operational Analysis Solution for Utilities

The next step is to analyze these data archives as cohesive units, a logical consideration since these automated systems work together within the context of utility operations. However, the stumbling block to analyzing these data sets in an integrated fashion has been the lack of a bringing in all the digital data being generated in the field on a continuous basis to take advantage of its information from an asset management point of view and a product designed to handle disparate data sources. 

The solution to this problem lies in the GIS, a system that many utilities already have in place. Within the utility, the GIS is typically used as a live map of the distribution network and all its components. The GIS ties these individual components and systems to a land base, which links them to a real-world coordinate system. The architecture of the GIS is perfectly suited for integration of data repositories because it is designed to accept inputs of different data sources and relate them to each other for thematic analysis.

The power of the GIS resides in its ability to pinpoint the location within the network model where events occurred or are projected to occur, and to be able view an aggregated network set of related facilities. This enables engineers to begin associating events by location and time. By layering these associated data points in the GIS, utilities can identify the multiple smaller events that occurred (or at risk of occurring) leading up to a major event such as an outage. Utilities can look at how well subsets of their electrically related circuits performed as a unit. This electrical related grouping is a unique feature the GIS brings to the reliability analysis domain over some of the other business intelligence (BI) technologies.  Incidents that once seemed unrelated suddenly appear as understandable trends through the view of the GIS.

Once the data has been integrated and georeferenced, the GIS can feed the composite view to operational dashboard views configured to measure system performance and predict infrastructure reliability. The asset management benefits provided from this analysis will impact operations, maintenance, and design programs.

Operational Analysis Dashboard Benefits

Predictive Maintenance

By integrating and analyzing archived real-time and operational data, utilities provide their personnel, specifically the engineering staff, with valuable system performance and reliability information that can result in more productive use of assets. This information will enable the utility to better understand where future investments should be focused in the replacement, maintenance and upgrading of facilities.

Optimized Demand Response

In terms of daily operations, for example, engineering planners can combine ADMS and AMI data to visualize load flows during peak demand events. With this realistic performance information, the engineer can create what-if scenarios in the modeling tools to determine how asset modifications might improve the distribution during peak times. The changes can be prioritized by how well they enhance performance and reliability so that equipment modifications offering the best return on investment can be included in the following year’s capital improvement program.

Performance-based Maintenance

Maintenance operations can expect similar advantages. Personnel would have more accurate details of how each sub-system and component performed under actual operating conditions, especially during peak loads. Based on this information, the utility can prioritize where funding should be allocated to better maintain the infrastructure that really needs attention and defer work on equipment that is performing above specifications.

Cost Effective System Design

The cost savings will flow into system design work as well. Planning engineers seek to optimize automatic sectionalizing and conductor materials in the design of new installations. With real performance and reliability information available to them, they can model the impacts of scaling material quality up or down. The planners will then have a more accurate and cost-effective view of what quality materials should be used in a specific installation, saving money by not over-building the equipment.

Getting Started

For most utilities, the main pieces of the data repository integration puzzle already exist. Data archives in the OMS, WMS, MWM, CIS, ERP, AMI and SCADA need to be linked with the GIS to feed integrated data to an engineering analysis tool. This integration process can be accomplished on a fast track if the automated components are in place.

Connect with us to learn more about OMS integration and supporting operational performance and reliability analysis with a Feeder Sentinel™ dashboard solution.

Tom Helmer headshot

10 years at UDC / 32 years in GIS

Tom Helmer

Executive Solution Architect for UDC and SAFe® 4 Certified Agilist (SA), Tom has extensive experience designing and integrating utility solutions around GIS and related technologies, including advanced metering infrastructure and smart grid solutions.