Ecoppia’s fully automated solar panel cleaning solution is on track to clean over 1GW of panels in the cutting edge Bhadla solar park by year end
Ecoppia, the world-leading developer of robotic, water-free photovoltaic solar panel cleaning solutions, announced today the completion of deployment of hundreds of its automated systems in the 2,255 MW Bhadla Solar Park in Jodhpur, Rajasthan India, in a site developed by Engie Solar India, subsidiary of energy multinational ENGIE Group.
Located in a vast desert area, Bhadla Solar Park is prone to frequent dust storms, which can reduce energy generation by as much as 40% in a matter of minutes.
Ecoppia is the only solution able to maintain peak energy production and restore panels post-storm in just hours – without water or external electricity consumption: with the deployment of Ecoppia across its site, ENGIE is expected to save over 1.5 billion of liters of water, and reduce its operating expenses drastically.
The subject project was won at record tariff, lowest in India at the time of bidding, hence it was indispensable to adopt an innovative and bankable technology like Ecoppia to ensure maximum plant productivity.
“We expect to harness Ecoppia’s revolutionary cleaning system to dramatically raise output and lower costs. This type of technological breakthrough not only benefits our own business interests, but the solar energy sector as a whole,” Engie Solar India commented. “We are proud to be one of the world’s first solar energy providers to adopt Ecoppia’s cutting-edge, autonomous robotic panel cleaning paradigm“.
Continuing Ecoppia’s commitment to cooperation with large multinational energy conglomerates and its specific focus on the Indian market, the company is expected to top 1 GW of deployments in Bahdla Park alone, and over 2GW across India.
Cleaning over 200 million solar panels to date, leveraging experience gained working with leading energy conglomerates like Adani Power, SunEdison and NTPC, Ecoppia cooperated closely with ENGIE throughout the design and deployment process to maximize rollout efficiency and optimize return on investment.
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