Predictive Maintenance Key to Enhancing Safety and Productivity of Power Sector

A new report looks at how predictive maintenance is becoming key to the power sector as it extends the operational life of infrastructure, while also enhancing safety & productivity

Predictive maintenance is becoming integral to the power sector as it extends the operational life of field equipment and infrastructure in order to improve organisational 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, according to a new report by GlobalData.

The report, ‘Thematic Research: Predictive Maintenance in Power’, explores which power companies have begun incorporating predictive maintenance tools. For instance, 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 optimisation. Furthermore, E.ON created technology that utilises artificial intelligence (AI) to notify potential power failures prior to their occurrence.

Sneha Susan Elias, senior power analyst at GlobalData, said that Duke utilised Genpact’s Lean Digital approach, to re-evaluate its O&M processes, putting into effect the Genpact Data-to-Action Analytics framework that included intelligence into operations, statistical predictive models, and successfully tackled its business needs and challenges.

The report further added that 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.

“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 percent. In addition, InspecTools’ SolarAMS solar asset inspection system has also been selected by SMA Solar Technology, a major solar energy company, for analysing its solar module condition data,” Elias explained.

Incorporating predictive maintenance tools has provided power utilities with more effective ways of monitoring and assessing their assets and undertaking a 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.