4 reasons why RESCO Model is the most successful way to expand solar installation in India

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Renewable energy in India has so far been dependent on subsidies given by the Government. But after Paris agreement, since India committed to setting up 175GW of renewable energy till 2022, we have seen the emergence of RESCO Solar model of PV installation. Factors such as frequent power cuts, increasing prices of conventional power, high irradiation and the falling costs of solar are driving the demand in Roof Top Market. Here are 5 reasons why RESCO Model in Solar would work in India-

  • Less Capital Intensive- RESCO Model is different from CAPEX model where the entire system is owned by the developer. Rooftop owners consume the electricity generated, for which they must pay a pre-decided tariff monthly. Thus, for consumers, it is a low-cost intensive option as compared to CAPEX model where the entire system is owned by the rooftop owners.
  • Continuous Ops and maintenance support from developers- Responsibility of O&M for the system lifetime in RESCO Solar model lies with the developer. Since it is done by the experts in the field, the system runs efficiently for longer duration and results in incremental generation as compared to CAPEX model
  • Government support- Central and State Government agencies provide subsidies to RESCO Solar developers on overall project cost. Currently 1GW Roof top capacity is installed in India. Government has targeted 40GW Rooftop Capacity till 2022. In order to meet the goal, in some special category states upto 70% subsidy is given to RESCO solar developers. Since the cost of solar panels fluctuates drastically due to uneven demand, customers are reluctant to opt for CAPEX model. With RESCO and attractive feed-in tariffs by the state regulators, consumers are less wary to get their piece of clean energy on their rooftops.
  • Better Monitoring of load and consumption with energy data analytics- Developers under RESCO model provide monitoring system to the owners where they can see their load pattern and take necessary steps to reduce their day time consumption. Thus resulting into reduction in consumption backed by data analytics.