ASIATODAY.ID, JAKARTA – WindESCo, the leading wind plant optimization company, announced that it has signed a multi-year agreement for its Swarm solution with UPC Renewables for the 75 MW Sidrap project in Indonesia.
WindESCo Swarm is estimated to increase annual revenue between $7,000 and $9,000 per MW for the wind plant.
Turbines within a plant continue to operate in isolation to other turbines. This is costing the industry billions of dollars in lost revenue. WindESCo’s Swarm enables turbines to communicate and learn from one another, leading to more optimum plant performance.
As part of the Swarm system WindESCo will be installing its patented Edge device in the turbines along with a Swarm Server located centrally in the wind plant. The system will be optimizing the plant in real time using its co-operative closed loop control program.
UPC Renewables is one of the largest independent renewable energy companies in the Asia Pacific region with over 1 GW of assets in operation and construction. Based on the success of WindESCo’s Find-Fix-Measure solution that has been providing value to Sidrap since 2019, UPC decided to sign a multi-year contract for Swarm.
“The wind industry has been talking about wake steering and other plant level optimizations for many years now. WindESCo has pioneered not just a retrofit wake steering solution, but have also included multiple other applications that will benefit our wind project. WindESCo’s innovations providing attractive returns for our projects is the reason why UPC continues to work with WindESCo,” UPC Renewables CEO Brian Caffyn stated, to asiatoday.id, Friday, August 26, 2022.
Mo Dua, WindESCo’s Founder and CTO, noted, “UPC Renewables has been a long term customer of WindESCo. Our engineering team has been doing R&D on Swarm for over 4 years now. We are very happy that UPC continues to trust our solutions and look forward to applying our Swarm technology to their Sidrap project.”
WindESCo launched Swarm in early 2022 as the world’s first solution for autonomous, co-operative control of wind turbines in a plant. (AT Network)