Why the Renewable Energy Industry is Going Digital

The renewable energy industry is witnessing an unprecedented amount of changes. Emerging policies, expanding investment interest, and advancing technologies are driving the growth of renewable energy across the globe. Interests in sustainable development and a global aim to drive policies to tackle climate change are pushing countries to speed up the adoption of renewables.

According to a report from IRENA, the global trend showcases a strong growth in renewable energy capacity which continued in 2018, with 171 GW added globally to the energy mix. 

Rising power consumption demands bring a great focus to optimizing assets and driving better metrics for operators. For most operators, downtime, operational inefficiency, and unreliable/inaccurate forecasting cost countless kilowatt-hours and impact revenue.

Asset downtime and under-performance have always been a challenge in the renewable industry. When a turbine experiences unexpected operational issues, farm operators need to dispatch engineers to diagnose and fix the issue. Anomalies often go undetected until they’re discovered in the course of scheduled maintenance. Farm operators inadvertently shave years off the lives of turbines and incur millions of dollars in losses because of the schedule-based maintenance process, which provides an incomplete assessment of asset health.

Absence of real-time information to perform preventative maintenance can lead to catastrophic failures that could easily be avoided. And a lack of data-driven forecasting leaves wind farms unable to adapt to changing weather patterns and grid demand.

As with any other industry, having a competitive edge depends on having a data-driven procedure to make informed business decisions and measuring risks. The same data-driven procedure implies managing renewable assets to operate new levels of productivity.

Data Analytics the way forward:

Industries are sitting on huge amounts of data that have the power to unlock way more value than is potentially being realized from existing assets and resources. Better planning with investment in the right technology can go a long way.

With advanced data analytics, farm operators can have a better understanding of the relationship between various signals and causes of failure. This identification of failures can now be done with good lead time, thereby improving operational efficiencies and reducing cost. Another aspect of improving operation and maintenance is to move from scheduled maintenance to predictive maintenance. This helps customers focus their attention on areas that need immediate help, with algorithms guiding the priority.

At Utopus Insights, our 'digital intelligence' leverages the power of advanced data science, machine learning, and artificial intelligence to unlock insights from vast amounts of IoT data including sensor, smart meter, and weather data, delivering software products that are descriptive (historic data and real-time visualization), predictive (energy and weather forecasting), and prescriptive (asset health for optimal maintenance and uptime).

Scipher.Vx Intuitive, interactive and customizable energy asset, data visualization and performance monitoring.

Scipher.Fx Renewable energy forecasting powered by advanced energy-specialized weather forecasting.

Scipher.Rx State of the art prescriptive analytics that enables proactive asset maintenance.

To know more about how Scipher™ can empower you with your data, drop a note to growth@utopusinsights.com and let our renewable energy analytics experts transform your Re assets.