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Managing Assets on the Electric Grid

June 26, 2017
One of the hottest topics in the power-delivery industry is how utilities are managing assets.

When the average manager, engineer and maintenance technician hear the words asset management, their typical response is less than positive. Tell them they have to go to an asset management meeting, and one would think they had been sentenced to the most arduous task imaginable. After all, the term asset management is really bean-counter speak for accounting work, or is it? Not really. Whether they realize it or not, non-accounting utility personnel have been using asset managing information for longer than most people have been working in the industry.

Utility personnel do not typically think of T&D equipment in abstract terms such as assets, but rather circuit breakers, transformers, reactors, lines, circuits, structures and such. The T&D system has been providing information from these electrical apparatuses for a long time. And utilities have been doing this through devices common to the grid such as relays, supervisory control and data acquisition (SCADA), distributed control systems (DCS), meters and remote terminal units (RTUs), to name a few.

Utilities use intelligent digital components to monitor their operational parameters and the parameters of the systems they make up. Now this data can be sent for analysis to centralized digital asset management platforms through the Internet of Things (IoT) or standard communications channels, and be used by utilities to improve their internal processes. In the following pages, several utilities share their experiences with digital asset technology. But first, it is important to understand the changes that have taken place in asset management since the introduction of the smart grid.

Digital Technology

When smart grid technology came along, it started changing the T&D grid into an interconnected system with devices that communicated data. The smart devices contained sensors, monitoring systems, self-diagnostic systems, mini cameras and many other digital technologies. This triggered a massive flood of big data that produces real-time situational data critical to understanding the equipment’s condition. In other industries, these devices are connected to the internet, but the power-delivery industry has not yet embraced IoT because of cybersecurity issues and competition among utilities.

The big story in managing assets today is digital technology. Several of the technology drivers such as information technology (IT), operational technology (OT), big data, cloud-based computing and IoT are modernizing asset performance systems. When combined, these schemes provide utilities a different vantage point for managing their assets with real-time condition monitoring using correlation processing.

Globally, many utilities are interested in the convergence of IT and OT data for asset managing software, and this interest is not coming exclusively from large corporations. Small- to mid-sized utilities have determined enterprisewide asset management systems make sense for them, too. Interestingly, some utilities are working with manufacturers on customized products, while others are using standard out-of-the-box

Some utilities also are using standardized products but integrating them with their existing customized systems. Developers of this digital asset technology are facing an interesting challenge. Some of the standardized asset managing platforms utilities use are ABB’s Ability Ellipse on Microsoft Azure, GE’s Predix, IBM’s Maximo, Schneider Electric’s EcoStruxure and Siemens’ MindSphere, to name a few.

Digital asset management systems can be tailored to fit a utility’s requirements, but it helps if the utility knows what it expects the platform to provide and has a detailed specification of what those requirements are. Typically, utilities are looking for out-of-the-box features like asset life-cycle management, condition-based maintenance scheduling, inventory management, asset risk trade-off management, organizational cooperation between departments and integration of business processes.

Utilities also are interested in improvements to their data analysis, easy integration with other systems (for example, SCADA and DCS) and user-friendly software for their employees. Another feature gaining popularity is the ability to incorporate the enterprise asset managing system with environmental, health and safety systems.

Expanding Systems

National Grid has several million customers for gas and electricity delivery in the UK. It uses most of the components of ABB’s Ellipse enterprise asset management system, but National Grid has developed its own data collection system for field personnel to use. Over the years, the utility’s infrastructure grew beyond the capabilities of its existing end-of-life mobile system. The utility needed a state-of-the-art system that could operate on both Microsoft Windows and Apple iOS platforms from laptops, tablets and other leading-edge devices. Nearly 2000 field personnel would rely on the system for field engineering and inspection processes.

Working with ABB and AMT-SYBEX, National Grid extended the existing Ellipse system to its field personnel using Fieldreach for data collection. This project united the National Grid mobile processes into a seamless system that could be accessed by Windows and iOS devices through a single sign-on. It is now possible for field personnel to access asset managing data such as maintenance history and asset condition directly on their mobile devices. National Grid’s management noted, with this asset managing expansion, “Everyone wants an iPad now.”

Off-Line Testing

Data can be separated into two general classifications: off-line and on-line. Off-line data is used typically for retrospective analysis, while on-line data is used for real-time interactive analysis. Most utilities have a combination of these two asset data classifications, and the challenge is how to integrate both forms of data into useful asset health information for decision making and risk reduction.

On-line data is generated by all the intelligent smart grid devices and monitoring systems installed on a utility’s T&D infrastructure. Off-line data is produced from field maintenance records, lab results and diagnostic testing reports.

Several years ago, Austin Energy announced plans to work with Doble Engineering and OSIsoft to address this issue. The utility installed the dobleARMS asset management platform, which has an OSIsoft PI server. All of Austin Energy’s data is fed into the PI system through SCADA to collect, store, organize and distribute data. The dobleARMS system combines the on-line and off-line data in an all-inclusive asset risk system running on servers in Doble’s data farm.

The asset managing system compares the Austin Energy data with industry databases. The resulting analysis performs a failure mode review along with health and risk indexing, which provides Austin Energy with asset information to assist the utility in making asset decisions. 

Down Under

TransGrid is a transmission network provider that connects distribution utilities and industrial companies with power stations across the state of New South Wales, Australia. It has roughly billions of dollars’ worth of assets to keep track of and to keep in top working condition. The challenge for TransGrid is to provide safe, reliable, efficient transmission services to meet customer demands and regulatory requirements with these assets as they age and more are added to the system. That is why the utility is always looking for better ways to manage and improve the health of its assets.

In 2013, TransGrid completed the deployment of an enterprise asset management system using ABB’s Ellipse platform. TransGrid reports the software provides it with asset life-cycle, maintenance scheduling and business processes. Since going into service, the Ellipse system has become very valuable to the utility for collecting all the details about its assets and has made it easy to schedule maintenance.

Ellipse also houses the utility’s human resource (HR) data and enforces common costing rules across the organization. The system enables TransGrid to plan the construction of new assets and connect that information to its supply, finance and HR functions.

Born from the Storm

Hurricane Ike devastated CenterPoint Energy in 2008 when it left 1.9 million consumers in the dark because of storm-related outages, some of which lasted for weeks. As a result, CenterPoint filed for a US$200 million Department of Energy stimulus grant to improve the reliability of the Houston power grid. CenterPoint used $150 million of the grant to accelerate the installation of smart meters. The remaining $50 million of the grant was used for the automation of 31 substations; the installation of 866 intelligent-grid switching devices on more than 200 distribution circuits, and distribution line monitors with remote terminal units. A wireless radio-frequency mesh telecommunications network was also built across the utility’s coverage area.

In 2016, this work was tested by another severe storm with wind, lightning and widespread flooding. More than 240,000 customers experienced interrupted service. The storm required more than 600 overhead line fuses and 650 transformers to be taken out of service, which resulted in extensive outages. Swift restoration by the field crews was also hampered because of road closures across Houston, Texas. This required handling a large amount of data on the power outages, to understand the situation, prioritize actions and deploy resources quickly.

The heart of CenterPoint’s intelligent grid platform is ABB’s Network Manager advanced distribution management system. The utility uses information from 2.4 million advanced meters and field sensors to enable real-time grid monitoring and control. The system was also integrated with ABB’s Service Suite mobile workforce management software and an advanced outage analytics package to tie it all together.

CenterPoint reported it can quickly identify, isolate and restore power, reducing outage times. In addition, the utility said the smart meters combined with data analytics provide immediate insight into a situation, so the right crews with the right equipment are dispatched to the affected areas so power can be restored quickly to the customers.

Asset Health Monitoring

American Electric Power (AEP) estimates 33% of its power transformers are at least 50 years old and approximately 18% are 60 years old or older. As a result, in 2013, AEP partnered with ABB to develop a systemwide analytical tool called the Asset Health Center.

Phase one was deployed enterpriswide in 2016. This stage relies on real-time performance data generated by vital station equipment. Initially, AEP decided to monitor its new transformers and retrofit extra-high-voltage (EHV) transformers. The system monitors parameters such as gas leaks, temperatures, fan currents, bushing health, partial discharge and dissolved gas.

The next phase is expected to include pilots for 138-kV power transformer monitoring, underground cable monitoring and capacitive voltage transformer monitoring.

This system is designed to move AEP from time-based maintenance to condition-based maintenance. The asset health system integrates equipment-based operational technology and enterprise information technology. In addition, the software package leverages operational and diagnostic expertise contributed by AEP to reduce the consequences of equipment failures and outages using asset condition data, predictive analytics and risk modeling.

AEP’s asset health system has prevented the failure of three EHV power transformers, saving the utility an estimated $15 million to $20 million. In addition, AEP reported it has discovered a partial-discharge signature in its review of monitoring data, which has led to a new ultra-high-frequency partial-discharge alarming scheme for personnel safety.

End-to-End Managing

Several years ago, CLK Energy, the largest electric utility in Turkey, began a program to modernize its system and give it a true end-to-end enterprise management system. The project is estimated to be more than 80% complete to date, and the results have been better than expected. To give a perspective of CLK Energy, it distributes and sells about 46 TWh of electricity per year to approximately 10 million customers in 11 cities across four different regions. CLK Energy has four retail companies and four distribution system operators, so it was not an easy undertaking.

CLK Energy’s goal with the project was to be more efficient by using the latest technologies and taking advantage of a fully integrated IT/OT operating structure to unify all its business processes and technical solutions. Since the onset of the project, CLK Energy has brought components together primarily from ABB, Esri and Oracle to produce a state-of-the-art enterprisewide asset managing system across the group’s eight operating companies.

Because of the project, a real-time network control and management solution from ABB was deployed that included ABB’s Network Manager SCADA, distribution management system and outage management system as well as outage life-cycle management systems for all four distribution regions. This implementation included SCADA human machine interface, single-line diagrams and network controls from transmission substations to service transformers. This project represented a significant milestone, as it was one of the first SCADA implementations in Turkey’s electricity distribution market and the first global implementation of ABB’s outage life-cycle management system.

A complete end-to-end asset managing system requires the business side of the utility to be included, too. The CLK Energy project used Oracle’s Enterprise Asset Management business suite and ABB’s Service Suite mobile workforce management system. Oracle’s Utilities Customer Care and Billing suite was applied to CLK Energy’s four regions. Also, Oracle’s E-Business Suite enterprise resource planning modules were implemented for HR, finance, logistics, procurement and projects. They also used Oracle’s Utility Analytics, Data Warehouse and Oracle’s E-Business Suite business intelligence applications.

The system also needed data from a geographic information system (GIS), so Esri’s ArcGIS was selected for asset mapping and network modeling. Esri’s network models and field automation equipment provided GIS mapping and asset coding, which included customer indexing and GIS-enabled network modeling for each of the four regions. The modeling included mapping of the mid-voltage and low-voltage circuits from the substation to the customer’s meter.

The utility elected to use integrated GIS mapping for the entire network model and included asset hierarchy. This is a master data repository of network assets and their status, providing operations, maintenance and planning access to the assets’ condition and situation.

These engineering and analytics tools have been described as a connected asset life-cycle management system with the capability to reduce failures. The platform also offers a switch from the age-old calendar-driven approach to maintenance to a more efficient condition-based maintenance program, enabling CLK Energy to prioritize maintenance and replacement decisions, optimize asset investment strategies, and improve productivity and safety. This implementation combined key elements from ABB, Esri and Oracle to create an end-to-end asset performance management system that has improved CLK Energy’s ability to operate more efficiently, reduce outages and meet regulatory requirements.

Asset Management Landscape

These examples of utilities integrating asset managing systems into the enterprise are showing a sneak preview of the digital utility of the future. By integrating IT and OT data together, and adding IoT technology and cloud-based computing with data storage, it will be a utility different from anything seen before.

These platforms are moving beyond connected systems that simply gather data, filter it and predict trends from it to determine the health of an asset. Essentially, they are using cognitive computing to make sense of the massive amounts of data being produced from the interconnected network of the smart components and assets to make decisions.

To paraphrase an old saying, “You can’t avoid risk, but — with today’s correlation processing and deep learning tools — it can be minimized.” It is going to be a technological adventure working with this smarter grid. ♦

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