Optimising Performance: Turning to predictive analytics to reduce risks and improve reliability

Turning to predictive analytics to reduce risks and improve reliability

David Thomason, Industry Principal – Power Generation at AVEVA 

Power generation companies are facing a growing number of challenges, from increased market complexity and demand, to regulatory compliance, sustainability objectives and uncertainty spurred by Covid-19.

The pandemic forced the industry to switch remote working, and deal with maintenance gaps created by supply chain disruptions. It highlighted the need for operational resiliency and agility in order to ensure the delivery of power. Gartner has reported that resilient delivery is one of 2021’s top utility trends given the industry’s underlying belief that volatility will continue.

Power plants are becoming ever more digital with the combination of assets with connected devices. Most importantly, the data captured from these assets supports the sector’s growing focus on resilience, agility and reliability.

According to Gartner, 50 per cent of the utilities will have advanced their use of internet of things (IoT) technology to build dynamic capabilities, optimise processes and improve decision-making by 2024. In addition, 40 per cent of new monitoring and control systems in this sector will be using IoT to enable intelligent operations by 2025.

Resilience and reliability are more important than ever in the power generation and utility sector. As organisations look to digital transformation to reduce risk, they are discovering the benefits predictive analytics can bring to their operations.

Benefits of digital transformation

The use of artificial intelligence (AI) and machine learning (ML) enables organisations to have full visibility of operations. It also provides insights that can help overcome some of the sector’s most disruptive challenges.

The amount of big data produced by power generation companies means that forward-thinking businesses are investing in monitoring and predictive analytics tools that help leverage this data to its full capacity. Navigant Research, for example, estimated that almost $50 billion will be spent on asset management and grid monitoring technologies by 2023.

By supporting agility, organisations can respond to change more quickly. Predictive maintenance allows the power industry to identify malfunctions before they happen, ensuring the reliability of their operations. This better positions them for growth in uncertain times ahead.

What does predictive analytics offer?

Predictive analytics enables the operations and maintenance personnel to be more proactive. In addition, the reliability and performance of assets are improved through early warning notifications and diagnosis of equipment problems days, weeks or months before failure. It can help forecast the remaining useful life of assets to provide deep insights into operations and maintenance risks.

Through predictive analytics, companies are able to implement asset strategies designed to avoid unplanned downtime for their most critical assets, while also deciding which preventative or corrective asset strategy is the best option for less vital equipment.

The benefits of predictive analytics go far beyond optimising maintenance schedules to ensuring reliability of operations. As risk assessment becomes more exact, prioritisation of capital and operational expenditures can be optimised. Companies can also realise financial savings by avoiding costs related to loss of power and/or productivity, replacement equipment and additional man hours accrued during a fault.

Tangible business benefits

A great example of the benefits of predictive analytics in the power sector is Tata Power. Tata Power turned to predictive analytics as a means of avoiding asset failures and reducing downtime by monitoring the health and performance of equipment fleet wide and in real time. By moving from reactive to proactive maintenance, the company was able to receive early warnings of potential faults – on one occasion saving an estimated $27,000. It also improved equipment reliability and performance, and helped capture knowledge of equipment failure modes.

Knowledge capture and transfer

Knowledge capture and transfer is another key benefit of predictive analytics, an area of huge importance to a sector that is seeing many of its experienced staff reaching retirement age. Accumulated knowledge stays available to new staff as they join the business, ensuring that best practices, operating procedures and maintenance processes are passed on to the next generation, thus reducing risks and improving reliability.

Staying competitive in today’s changeable times

The power generation and utility sector is grappling with a world that is more volatile and complex, but demands greater speed, agility and resilience. In response, it is undergoing a digital transformation that enhances the way power is produced and delivered. Predictive analytics has a key role in this transformation as it enables organisations to become more resilient, reliable and efficient by moving from a reactive to a proactive way of working.

As more power generation companies embrace this technology, we will see reduced risks, speedy crisis response and improved resiliency, which will help organisations remain competitive and profitable in a more uncertain “new normal”.