CMERI installs massive solar tree, claims it is the 'largest in the world'

The Central Mechanical Engineering Research Institute (CMERI) based in West Bengal’s Durgapur has developed a massive solar tree at its residential complex.

Speaking to DH, CMERI Director Professor Harish Hirani said that it is the largest solar tree in the world with capacity of generating more than 40 to 45 kilowatts hour per day, which is significantly higher than the current estimated highest capacity of 40 kilowatts hour per day. CMERI is a Central government institute working under the Council of Scientific and Industrial Research (CSIR).

“It has the annual capacity to generate 12,000-14,000 units of clean and green power,” said Hirani. He also said that the solar tree has 35 photovoltaic solar panels which are designed in a manner to ensure maximum exposure of each panel to sunlight and least shadow area beneath the structure.

Unlike conventional roof mounted solar panels, these can be adjusted as per requirements. This feature makes it suitable for large scale use in the agricultural sector such powering equipment like e-tractors, high capacity pumps and e-power tillers.

“These, Solar Trees can be aligned with Agriculture for substituting price-volatile fossil fuels. Each Solar Tree has the potential to save 10-12 tons of CO2 emissions from being released into the atmosphere as Greenhouse Gases when compared with fossil fuel fired energy generation,” said Hirani. He also said that the surplus power can be fed to the energy grid.

The electricity generation can be monitored either on real-time or daily basis.

Hirani said that each of the solar trees costs about Rs.7.5 lakhs.

“Interested MSMEs can align their Business Model with the Pradhan Mantri Kisan Urja Suraksha evem Utthan Mahabhiyan (PM-KUSUM) Scheme for farmers, for developing a Renewable Energy based Energy Grid,” stated a release issued by CMERI.

It also has features such as round-the-clock CCTV surveillance in agricultural fields, real-time humidity, wind speed, rainfall prediction and soil analytics sensors.