The evolution and deployment of smart grid technologies has transformed the nature of the asset management challenge for energy companies. The smart grid creates entirely new and more complex asset classes, such as hardware, firmware, software, communications systems and storage capabilities. And, as the pace of smart technology deployment quickens and swathes of projects result in millions of intelligent endpoint devices (IEDs) across the grid, the volume of assets to be managed is unprecedented.
Meanwhile, smart grid data, which energy companies must be able to capture, store and visualize, has become an asset class in its own right. Collecting large amounts of new data from intelligent endpoint devices is just the start. To get the true return on smart grid investment, energy companies need to be able to create actionable insight from data, develop advanced asset control algorithms and leverage machine learning principles to track asset cost, performance and risk.
In short, the dramatic and growing impact of smart grid technologies on facilities means energy companies must now add more and increasingly complex assets to their asset management portfolio. As a result, many now need to consider implementing more complex asset management systems.
Managing smart grid assets
As energy companies rise to the challenge of managing smart grid assets, new trends and approaches are beginning to emerge:
- Integrating 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, new asset integration approaches are emerging. The integration of legacy utility equipment (breakers generators, transformers) with new electronic control and monitoring devices (bushing power factor, DGA, etc.) means utilities need to manage multi‐aged assets with varying depreciation rates. As a result, they are beginning to build new capability to defend rate cases and overcome the challenge of operating and managing multi-aged assets. This includes, for example, the addition of Network Operating Centres (NOCs) to manage communications in addition to standard System Operating Centres (SOCs) to manage switching operations.
- Managing an increase in asset volume: The introduction of AMI, smart distribution line sectionalising switches, automated capacitor banks, transmission synchrophasers and other intelligent endpoint devices could double the number and value of utility assets within the next 10 years. As a result, companies are increasingly revaluating existing asset management hierarchies, systems of records and overall asset methodologies to accommodate the volume change.
- Collecting and storing smart asset data: Utilities now need an enterprise-wide, integrated work and asset management system that allows them to define, collect, store and analyse physical, operational and maintenance data from assets in real time and across various 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. In some organisations, asset financial and operational performance is being combined with overall risk analysis and mitigation to develop whole asset life cycle costing.
- Deploying asset management analytics: More data from more sources is challenging utilities to integrate, automate and analyse various forms of new asset data. Understanding how to analyse 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 can improve total uptime, reduce asset maintenance costs and improve overall asset health.
Is your organisation up to speed?
As asset management becomes increasingly complex, a key strategic question for utilities is how to ensure they have the right asset management infrastructure and cross‐enterprise strategies in place. Developing an effective strategy is likely to include some of the following steps:
- Realigning asset groups: To facilitate performance analysis, asset groups should incorporate assets with similar characteristics such as life cycles and maintenance activities. So, for example, electromechanical assets, such as the capacitor bank, should be separated from electronic assets, such as the capacitor bank’s electronic controller, as they have different asset lives.
- Realigning depreciation rates: Realigning depreciation rates will enable organisations to adequately account for variable life spans in the realigned asset groups.
- Creating a centralised asset health centre: This involves defining what physical, operational and maintenance history data is necessary to create an overall view of each asset’s health, condition and performance. Utilities that take an integrated asset health approach will have a foundation for plugging multiple new smart grid assets into the organisation more easily.
- Making a holistic asset data strategy: The data strategy should combine multiple data sources across new and existing systems. In addition, the right data analytics and business intelligence tools to facilitate asset cost, performance and risk analysis must be implemented.
- Developing a proactive asset strategy process: The strategy for new electronic asset groups should include proactive maintenance, upgrading and replacement.
Lastly, although smart grid technologies, infrastructure and data are making asset management more complex, utilities should ensure that, whatever asset strategy they deploy, it supports overall asset management strategy in terms of life cycle management, risk management and financial and operational performance.