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Energy/Utilities


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Image shows an abstract representation of solving problems using artificial intelligence to increase reliability and reduce losses and accidents during the transmission of electrical energy.

Energy Asset Performance Management to Take on Automation

Asset monitoring isn’t new to IoT-based energy management. The maturing products are becoming more predictive, with sights set on automating operations.
  • Written by Rich Castagna
  • 28th December 2019

Laiq Ahmad, chief technology officer and chief architect of digital energy for GE Power, points out that the majority of their customers already have ample sensor implementations collecting operational data. “Customers want to take advantage of real time data,” said Ahmad, but typically they need help analyzing that sensor-generated data. 

But it goes beyond just ferreting through mountains of data, as each utility is likely to have specific requirements. “Based on the data points received from sensors, we can figure out what the customer needs,” said Ahmad, and then make any necessary tweaks to their asset management application.

Scaling and Communications

Growth is another concern for APM users. The ability to scale the application to meet future needs is a key priority, according to Mohsen Mohseninia, vice president of market development, Europe for Aeris, an IoT communications technology provider. “Scaling has two aspects: one is scaling within a geography and the other is scaling outside a geography,” Mohseninia noted. “So typically they start with one or two markets and then as that market gets saturated, they need to find new markets, and typically new markets mean new geographies.” 

Remote access may also be at the top of a utility’s APM wish list. “If their business model is to supply energy to their customers on a pay-as-you-go basis, then the priority is to make sure that they have remote access to their devices anytime, anywhere, any place,” explained Mohseninia.

APM to Move from Reacting to Acting

By far, the most promising development — and among the greatest needs of users — is the ability of APM applications to use advanced AI/ML-based analytics to create models that indicate that maintenance is required before obvious performance degradation or even failure.

GE’s Ahmad has a clear vision of the necessary development of APM systems. Today, Ahmad noted, APM can react with relative ease when a component or process dips below expectations. Those expectations may be based on a combination of criteria such as operational history of the device, industry specs, user-defined baselines and so forth.

Ahmad said that the developmental path for GE’s IoT energy management and diagnostic tools is “reactive to predictive to prescriptive,” but right now the industry is still centered around the “reactive” part of that development scenario. “Leveraging technologies like ML/AI to collect and interpret data can lead eventually to automated responses — essentially maintenance or component adjustments occurring without manual intervention,” Amhad said.

For an industry that’s feeling an expertise pinch as veteran utility administrators retire, the prospect of being able to confidently turn over some operational responsibilities to an automated system is compelling.

APM Integration with Biz Apps and Safety Systems

The data that fuels APM systems is often also useful to other parts of the business, according to consultant Feblowitz.

Beyond sensors, APM apps could potentially integrate with other business systems such as GIS, work and management applications, ERP and other enterprise management systems. 

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Tags: Asset tracking Oil and gas Smart grids Energy/Utilities Other Content Features

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