by Scott Sidney and David Groarke, PA Consulting
When asset management first became popular as a utility business model back in the late 1980s and early 1990s, it was focused on expensive, long-life assets such as substation transformers and circuit breakers. Even the advances in asset management competencies tended to focus on these same types of assets. Although most U.S. utilities still deployed basic run-to-fail (even with good maintenance) asset strategies, the core asset focus remained unchanged.
As smart grid technologies began to be deployed rapidly at utilities through the last parts of the 2000s in the predominant forms of advanced metering infrastructure (AMI), distribution automation (DA) technologies and control room software such as distribution management systems (DMS), few companies understood that adding those assets to a companywide asset management strategy portfolio would be as important as it now is.
This new paradigm continues to manifest itself in several ways for utility asset management approaches:
- New types of assets to manage. Along with the classic asset groups (breakers, transformers, switches, meters, poles, etc.), with smart grid assets there are entirely new and more complex asset classes: hardware, firmware, software, communications systems and storage capabilities. For example, smart grid communications infrastructure (RF mesh, cellular networks, power line communications, etc.) that enables two-way digital control may be as costly and complex as the equipment it networks.
- More assets to manage. Not only must original assets (line vacuum switches, for example) be managed, as the pace of smart technology deployment quickens across the industry with swathes of projects resulting in the proliferation of millions of intelligent endpoint devices (IEDs) across the grid, the volume of assets to manage is becoming unprecedented.
- Increase in smart grid data. Effectively managing smart grid assets and the data they create requires the ability to capture, store and visualize data pertaining to asset status, performance and real-time risk. Thus, smart grid data becomes a new asset class in its own right and in need of managing.
- Evolving asset management analytics. Collecting large amounts of new data from intelligent endpoint devices is one step to realizing smart grid asset management. Being able to create actionable insight, develop advanced asset control algorithms and leverage machine learning principles to track asset cost, performance and risk and maximize new infrastructure and assets is where the smart grid return on investment resides.
Utilities should consider more complex asset management systems (as defined by PAS 55 and ISO 55000/1/2) to deal with the impact of new smart grid technologies on facilities. Looking at the main areas of impacts, we see several key smart grid asset management themes and approaches:
- Integration approaches for new asset types. Because new smart grid asset groups have shorter life spans, different depreciation rates, more complex maintenance requirements and different operating scenarios, we are seeing the need to define new asset integration approaches. The integration of legacy utility equipment (breakers generators, transformers) with new electronic control and monitoring devices (bushing power factor, DGA, etc.) is creating the need to manage multiaged assets with varying depreciation rate issues. As a result, utilities are beginning to build new capability to manage multiaging assets to defend rate cases and overcome challenges to operate and manage assets. Take, for example, the addition of network operating centers (NOCs) to manage communications in addition to standard system operating centers (SOCs) to manage switching operations.
- Management of an increase in asset volume. The introduction of AMI, smart distribution line sectionalizing switches, automated capacitor banks, transmission synchrophasers and other intelligent endpoint devices can potentially double utility assets in numbers and dollars within the next 10 years. As a result, utilities are increasingly revaluating existing asset management hierarchies, systems of records and overall asset methodologies to accommodate the volume change.
- The collection and storage of smart asset data. There is a need to have an enterprisewide, integrated work and asset management system that allows utilities to define, collect, store and analyze asset physical, operational and maintenance data in real time and across enterprise systems (WMS, OMS, MDMS GIS, etc.). This includes the ability to enable plug-and-play architectures and access real-time field data to make effective asset decisions and provide regulatory justification for expenditures to prove smart grid business cases. We are seeing asset financial and operational performance being combined with overall risk analysis and mitigation to develop whole asset life cycle costing.
- Deployment of asset management analytics. More data from more sources is challenging utilities to integrate, automate and analyze forms of new asset data. Understanding how to analyze the data (distributed analytics: real-time operations, predictive capabilities, trigger alarms and actions) will be the proving ground for many smart grid asset management business cases. For example, by deploying predictive asset maintenance analytics that increase the quantity and quality of maintenance schedules, utilities are improving total uptime, reducing asset maintenance costs and improving overall asset health.
Given these industry themes and as asset management complexity increases, a key emerging strategic question for utilities is how can they ensure they have the right asset management infrastructure and cross-enterprise strategies to effectively manage asset cost, performance and risk? Here are a few suggestions:
- Realign asset groups to incorporate similar characteristics such as life cycles and maintenance activities to facilitate performance analysis. Separate electromechanical from electronic assets (for example, separate the capacitor bank from its electronic controller because they have different asset lives).
- Realign depreciation rates to adequately account for variable life spans in the realigned asset groups.
- Create a centralized asset health center. Define what physical, operational and maintenance history data is necessary to create overall views of asset health, condition and performance. Utilities that take an integrated asset health approach will build a foundation by which multiple new smart grid assets can be plugged into the organization more easily.
- Create a holistic asset data strategy that combines multiple data sources across new and existing systems while working to implement the right data analytics and business intelligence tools to facilitate asset cost, performance and risk analysis.
- Develop a proactive asset strategy process to deal with these new electronic asset groups, including proactive maintenance, upgrading and replacement.
Last, although managing smart grid technologies, infrastructure and data is increasing asset management complexity, make sure that whatever asset strategy you deploy supports your overall asset management strategy in life cycle management, risk management and financial and operational performance.
Scott Sidney is an asset management expert with PA Consulting Group. He has worked with more than 100 utilities on five continents to help senior utility managers rebuild their asset management competence levels according to PAS 55 and ISO 55000 requirements and industry best practices.
David Groarke is an energy utilities expert at PA Consulting Group. He has worked with utilities and organizations across Europe, Australia and North America. His project experience spans the entire energy value chain, including transmission and distribution, customer service, meter-to-cash and enterprise services with a focus on smart grid, AMI initiatives and utility business transformation.
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