Predictive maintenance is becoming integral to the power sector as it extends the operational life of field equipment and infrastructure in order to improve organizational profitability, while also enhancing safety and productivity. Therefore, a number of power companies have begun implementing the tools across the operational value chain, including operations and maintenance (O&M), power generation, and transmission and distribution (T&D) areas, to monitor critical infrastructure and equipment, says GlobalData, a leading data and analytics company.

GlobalData’s report, ‘Thematic Research: Predictive Maintenance in Power’, explores which power companies have begun incorporating predictive maintenance tools. For example, Duke Energy, a major power utility in the US, dealt with cost over-runs involving wind turbines and other equipment using predictability along with asset optimization. Furthermore, E.ON created technology that utilizes artificial intelligence (AI) to notify potential power failures prior to their occurrence.

Sneha Susan Elias, Senior Power Analyst at GlobalData, comments: “Duke utilized Genpact’s Lean Digital approach, to re-evaluate its O&M processes, putting into effect Genpact Data-to-Action Analytics framework that included intelligence into operations, statistical predictive models, and successfully tackled its business needs and challenges. E.ON’s technology is now deployed by Schleswig-Holstein Netz’s medium voltage grids, and has increased the chances of detecting any faults in their power grids prior to their occurrence.”

A number of crucial partnerships have also evolved as a result of predictive maintenance such as Framatome and IBM, and Enel Green Power North America and NarrativeWave. Framatome, a company engaged in the design and construction of nuclear power plants (NPP) and research reactors, partnered with IBM Watson’s IoT platform, to provide a data analytics solution for the nuclear power sector.

Susan Elias adds: “Together the platform brings in crucial operational enhancements for NPPs, aiding to decrease asset failures and unexpected outages, prioritize O&M expenses, and improve reliability and reduce costly downtime.”

Vestas leads when it comes to offering predictive maintenance solutions. The company reinforced its wind turbine predictive maintenance offerings through its partnership with InspecTools, a major asset inspection company. Vestas will employ InspecTools’ WindAMS throughout its global service business units.

Elias explains: “WindAMS will enable the enhancement of predictive maintenance and aid in alleviating serious issues such as leading-edge erosion (LEE) that can decrease annual energy production by approximately 5%. In addition, InspecTools’ SolarAMS solar asset inspection system has also been selected by SMA Solar Technology, a major solar energy company, for analyzing its solar module condition data.”

Incorporating predictive maintenance tools has provided power utilities with more effective ways of monitoring and assessing their assets and undertaking few of the regular maintenance tasks in an automated way. Some of the technologies that have the potential to enhance utilities’ O&M include machine learning for predictive maintenance, and robotic drones.