Optimising Value

Utilities look at cloud-based solutions for asset management

Power management and the ability of utility companies to react to near-real-time operational data remotely is becoming more critical and represents an improved and strategic approach to work and asset management. For the assets themselves, operational data such as maintenance records, performance anomalies and equipment stock data are collected and analysed by machine learning (ML) algorithms targeted at predictive, preventive and prescriptive maintenance of utility assets. Utilisation of data through asset management efforts can improve the performance and extend the life of assets such as renewable and traditional generation systems, substations and transmission lines.

Cloud-based asset management applications can make access to data in the field easier via mobile devices, helping maintenance crews and linemen perform their jobs more efficiently, leading to quicker outage restoration times and better operational safety. With cloud-based asset performance management, utilities can optimise the value of asset during its life cycle, starting with acquisition and construction – including predictive maintenance, repair  and inspection – and can also manage purchasing and inventory.

Key applications of cloud computing for asset management

Predictive maintenance: Predictive maintenance is the failure inspection strategy that uses data and models to predict when an asset or piece of equipment will fail so that maintenance can be planned well ahead of time in order to minimise disruption. Predictive maintenance can cover large areas, from failure prediction, to failure diagnosis, to recommending mitigation or maintenance actions after the failure. The best maintenance is advanced forms of proactive condition-based maintenance. The combination of cloud, ML and maintenance applications, leveraging IoT data to deliver more accurate estimates of equipment failure, the range of positive outcomes and reduction in cost, downtime and risk, is worth the investment.

Asset health indexing: Extending the life of an asset can be a low-cost alternative to capital replacement. With many utility assets nearing their end of life, asset health indices can provide a safe and reliable solution to extend the asset’s life as well as satisfy regulatory demands for proof of compliance and justify rate cases/budgets. ML, through cloud, can improve asset health indexing methodologies, empowering utilities to make defensible asset investment decisions. Even with a limited budget, asset health indexing software is being leveraged to automate the analysis and ensure sustainability of the process.

Video and image interpretation: Thermal imaging has become a core predictive maintenance tool in any ongoing inspection programme. It is widely used for substation surveys and safety checks before the planned maintenance work. This helps avoid costly service interruptions and equipment losses. Cloud-based data management could be used to spot the patterns of images by identifying transformers and transmission lines, thereby speeding up the time process.

Smart meters: With the increasing use of smart meters in homes, energy companies can now tap into the data provided by IoT to give a more accurate picture of supply and demand by gaining more insights into individual habits. Measured data can be sent and consumed by cloud services at short intervals.

Distributed energy resources management: The intermittent nature of renewable energy such as wind and solar, the rise of behind-the-meter distributed energy resources (DERs) including battery and storage, and the rise in electric vehicle loads have increased the need for greater visibility, predictability and remote operational control of these assets. The high penetration of DERs and renewables is also increasing the need for data such as electricity demand, temperature, sunlight, wind speed and generation output to feed next-generation load and forecasting engines. Access to near-real-time data sets collected from sensors is critical for power and utility teams managing DERs and renewables. Cloud capabilities allow for better collaboration and quicker, more informed decision-making across departments within a power or utility company, while managing and operating DERs and renewables.

Challenges and the way forward

Several factors such as interoperability issues, reliable communication, cybersecurity and capacity building are some of the biggest challenges for implementing cloud-based asset management solutions. As the industry digitally transforms and increases its cloud capabilities and the deployment of connected devices on field assets, power and utility companies are looking closely at risks and strategies related to cybersecurity and physical security. Therefore, strategic planning, assessment of the existing infrastructure, identifying gaps and establishing benchmarks are required. In sum, cloud-based asset tracking will help utilities make informed decisions with respect to further purchases and distribution. Cloud-based asset management not only assists in utilising assets and resources to the fullest and reduce wastage but also improves efficiency.


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