Pune, May 04, 2022.
Mr. Lakshmanan Subashchandra Bose, CEO, RENOM Energy Services Pvt. Ltd., was recently awarded ‘India’s Most Powerful Wind Leader’ by Wind Insider 2022. The honour was conferred upon RENOM for being India’s first and only Independent Service Provider (ISP) to manage wind turbines of all the five technologies. RENOM Energy Services, is the Energy arm of the business conglomerate Sanjay Ghodawat Group and is one of a kind operation and maintenance company; established with a basic philosophy to deliver quality services through innovative practices.
Today RENOM is maintaining 13 brands and 24 models of wind turbines, with a total portfolio of 1500 MW across 7 states and 55 plus locations in India. RENOM has various Global and Indian IPPs like Acciona Energy, Apraava Energy (CLP), Atria Power, Leap Green Energy, NSL Power, Hero Future Energies, Tata Power, and other corporate and retail customers. RENOM also has its own in-house state-of-the-art Electronic Repair Service (ERS) Centre in Pune to service all types of PCBs, SRBs, and controllers with less turnaround time.
Thanking the team of Wind Insider for the award, Mr. Lakshmanan, says, “We are honoured and delighted that Wind Insider recognised our contribution in the space of Wind Energy. This would not have been possible without the support of our well-wishers, stakeholders and partners.”
Speaking about future expansion, Mr Shrenik Ghodawat, Founder & Director – RENOM, says, “With a vision to be the most preferred ISP for the customers in the global renewable energy market space, we aim to provide premium quality & value-added services to customer assets at affordable cost. We are the only ISP that has developed SCADA (RESCA) with a single-window dashboard, to view all makes, models of wind turbines for remote monitoring and controlling of assets.”
RENOM also owns a Digital Twin (DT) platform developed along with ATOS. DT builds a digital replica of the physical assets. The platform computes the failure analysis for various components of the wind turbines by using data analytics. It is the prediction model which predicts the remaining useful life of the wind turbine components and provides the yield prediction.