Chinese wind turbine manufacturer Envision Energy is using an internet of things analytics platform to improve the efficiency of its wind turbines. The solution was provided by ParStream, a German startup that was acquired by Cisco Systems at the end of 2015.
Envision focuses on producing wind turbines and on the software business, which manages 13 gigawatts of renewable energy assets globally.
Renewable energy companies have experienced strong growth in recent years, but most of them face pressure to improve profitability and productivity as the industry scales globally. According to Envision, the energy business can no longer be differentiated just by mechanical engineering, but by the ability to monitor and maintain high performance over time.
Each of Envision’s wind turbines are built with more than 150 sensors that continually assess acceleration, temperature and vibration. Extracting data from their wind turbine sensors lets the Chinese company to see trends and create predictions for performance optimization to increase productivity and predictive maintenance to minimize downtime.
The company currently operates a network of more than 20,000 wind turbines worldwide, and the management of real-time data and the continuous monitoring of its wind turbine network is a complicated task.
By analyzing real-time sensor data from their wind turbines, Envision is able to identify actionable insights with potential business benefits. Two key use cases for Envision include performance optimization and predictive maintenance, which combined help to deliver a 15% improvement in productivity.
-Performance optimization: Envision uses sensor data to make decisions about altering the angle and speed of the turbine blades in order to optimize performance at any given time based on changing environmental conditions. “Through the use of real-time sensor data we can boost a customer’s total energy output by up to 15% from their wind farms,” said Guido Jouret, president of Envision Digital Innovation Center.
-Predictive maintenance: Envision’s sensor technology checks for any irregularities in operational performance for their 20,000 wind turbines, which allows the company to predict potential failures before they happen. They match real-time data against historical data to determine which parts need adjustments or replacements, reducing downtime.
“The platform’s unique ability to analyze terabytes of data with sub-second response times further improves our ability to generate significant value from our IoT applications,” Jouret added.
Envision selected ParStream’s IoT analytics solution, which allowed them to handle terabytes of data with sub-second response time, along with the capability to run distributed queries/edge analytics closer to the source of data. Envision wanted an integrated platform to continuously import and store large amounts of real-time sensor data with the ability to run fast and flexible queries.
