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Protecting Smart Grids and Critical Infrastructure Are Top Concerns for Energy and Utility Firms

As the energy market transforms and utilities use machine learning to be more efficient, they must also keep their guard up against cyberattacks.

Rising energy demands, fluctuating oil prices, renewable integration, aging infrastructure and changing regulatory requirements are all challenges facing the energy industry today.

While multiple approaches exist for addressing these realities, one constant remains — technology will be at the heart of the majority of solutions. Whether it’s sensors and cameras monitoring utility and oil and gas assets, drones that perform high-risk inspection operations, or machine learning tools that identify energy efficiency opportunities, technology innovation is critical for the future of the industry.

The shift to smart electricity grids and digital oil fields does not come without risk. The technologies proliferating in the energy industry are also endangering it — opening up critical systems to cyberattacks. Shoring up utility and oil and gas infrastructures will become ever more urgent in the coming years — and tech will again be a central player.

What are some of the key IT trends facing the energy industry as it undergoes another transformation in the years ahead?

Cybersecurity Is a Constant Concern

How vulnerable is the country’s utility system? America’s power grid suffers a cyber or physical attack once every four days, according to a USA Today investigation.

The Industrial Internet of Things (IIoT) aims to improve power delivery by using predictive analytics to ensure greater grid resiliency.

However, the IIoT also introduces new security vulnerabilities as the devices and machines connected to the cloud provide digital doors to control systems. The increased risk was clearly evidenced by the 2015 BlackEnergy malware cyberattack that took down a Ukrainian power grid. While compliance with reliability standards provides some protection, utilities need to take a more active approach to thwarting cyberattacks. Multiple layers of defense need to include proven security strategies that look at risk assessment, asset monitoring, data encryption and employee training.

Cybercriminals can gain network access using malware delivered to a trusted employee via spear-phishing emails. Access may require only the click of a malicious link or attachment. As cybercriminals grow bolder and attacks more frequent, energy firms need to implement multilayer IT security in conjunction with effective protocols and training to prevent human nature from becoming human error.

Using IoT for Asset Management

The Internet of Things has its upsides, though, and can help utility companies with asset management, which continues to be a challenge as energy firms balance an aging infrastructure with new smart-grid technology.

Increasingly, IoT-enabled devices are helping assess the health of multiple types of equipment, ranging from traditional substations and switches to newer assets like smart meters and solar arrays. Sensors, cameras and other embedded technologies can feed valuable performance data in real time, allowing utilities to conduct preventive maintenance before a problem occurs.

As utilities look to be more predictive and less reactive about their networks, the market for asset management and condition monitoring devices and solutions is expected to grow. Navigant Research predicts global revenue will rise from $2.6 billion in 2016 to $6.5 billion in 2025.

Machine Learning Has Numerous Uses

To be truly data-driven, utilities need to make use of advanced analytics capabilities made possible with machine learning — a subset of artificial intelligence which uses algorithms to detect patterns, and then can predict outcomes and potentially operate autonomously.

Identifying patterns found in immense amounts of collected utility data is especially effective for improving customer engagement through personalization. Machine learning can help utilities tailor programs to different customer types based on specific energy usage. Additionally, it can examine energy efficiencies and make specific recommendations that reflect a homeowner’s habits and actions.

Machine learning can tie weather patterns together with customer behavior so predictions can be made about future usage. And it can monitor call center conversations to make future interactions between customers and sales associates more effective. In a competitive marketplace, machine learning can go a long way toward helping utilities better understand their customers so they provide a superior experience.

Protecting SCADA Systems from Cyberattacks

Meanwhile, data-streaming industrial supervisory control and data acquisition (SCADA) systems can be processed in real time for a clear view across the value chain. These insights add value by boosting productivity and informing faster decision-making.

Yet, without the right cyber safeguards in place, hackers with malicious intent can potentially access connected SCADA systems to gain control of equipment or even halt operations. Due to inherent weaknesses in legacy equipment and a rising number of network access points, control system cyberthreats are on the rise. According to Tripwire, 82 percent of oil and gas operations reported an increase in successful cyberattacks over the past 12 months. Oil and gas other data-centric industrial enterprises need to act now to protect vulnerable SCADA systems from growing cyberattack threats.

Read more about where the energy and utilities tech market is going in this CDW report

ThinkStock
Feb 03 2017

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