Renewable Energy Integration in India: Big Aspirations, Bigger Challenges

Jun 09, 2020

Among the countries with Fulbright programs, India presents one of the most interesting case studies of a modern energy infrastructure. Its exploding economy (and ballooning electrical demand), coupled with the central government’s aggressive renewable energy goals make for a rapidly transforming electrical landscape. My nine months immersed in this research community showed me first-hand the incredible pace and promise of wind and solar development throughout India, but it also highlighted the brand-new challenges these technologies present to a struggling electrical grid. 

My nine months immersed in this research community in India showed me first-hand the incredible pace and promise of wind and solar development throughout India, but it also highlighted the brand-new challenges these technologies present to a struggling electrical grid

The headline solutions to climate change are now part of everyday language: swap out your incandescent bulbs for LEDs, drive a Prius, and, most importantly, vehemently lobby your government to adopt renewable energy and divest in fossil fuels. This last strategy is often showcased as an economic solution. You have likely seen plots of the plummeting costs of Chinese made solar panels. Given that the variable costs of weather-based electricity generation are zero (the fuel is free and endless) and taking into account the added bonus of large subsidies and tax incentives, it’s only a matter of time that renewables become more cost-effective than fossil fuels. The market should solve the problem, right? In fact, the cost of generating a kilowatt-hour of electricity (this is the standard unit you see on your electrical bill) with a wind turbine or solar plant is already on par with coal and natural gas, and sometimes even lower. This is true in many parts of India, and it is certainly encouraging.

The problem is one of control. Treating the electrical infrastructure in the economic terms described above is helpful in many ways, but it belies the fact that electricity is unlike any other commodity. Electrical energy flows from a steam- or wind-driven generator, through a network of transmission lines, out of your wall outlet and into the coils of your hair drier at nearly the speed of light. Kilowatts can’t be housed in a distribution center and sent out just in time for your evening beauty routine; they have to be generated at the very instant they are consumed. For this reason, variable generation (the technical term for that subset of renewable energy technologies, mostly wind and solar, that cannot be controlled), leads to a less stable and dependable electrical grid. A new field of energy research concerned with “renewable energy integration” has blossomed in recent years, and it is in this field that the US-India Educational Foundation (the Fulbright organization in India) helped me launch my career.

India has some incredible renewable energy integration challenges in its immediate future. In the Paris Climate Accord of 2015, Prime Minister Narendra Modi committed his country to generating 40% of its electricity from renewable sources by 2030. Even prior to Paris, Prime Minister Narendra Modi targeted 100 gigawatts (GW) new solar, and 65 GW new wind energy by 2022. Even if they operate below 20% of their rated capacity (more on this percentage later), 165 GW is enough to power roughly 250 million average Indian households (or 25 million average American households) and still send a DeLorean or two back to the future.

In order to predict how the Indian power system will manage all of this new wind and solar, the National Renewable Energy Laboratory (NREL) recently conducted a high-level integration study, using a least-cost optimization model. I dedicated my Fulbright grant to supplementing the results of this model. Their goal was to determine the lowest-cost mix of resources needed to supply electrical demand in future years. To predict wind and solar output, they used satellite-based weather data. Ideally, this would be used in conjunction with actual energy data from existing wind and solar plants, but high time-resolution data of this nature is hard to come by. By periodically visiting government offices in person, however, my advisor and I got access to some actual, historical wind energy production data.

We used a simple metric called capacity factor to characterize the data and compare it to NREL’s model results. Capacity factor (CF) is calculated by dividing the actual energy produced by a power plant by its maximum rated capacity. For instance, if a coal-fired plant runs at full steam for 6 months, and half-output for 6 months, it has a yearly CF of 75%. But steam boilers can be fully controlled with valves, buttons and switches. The capacity factor of wind and solar plants, on the other hand, measures the consistency of the weather resource. Not surprisingly, the CF of solar energy is always less than 50% (usually close to 20%), though wind capacity factors have been steadily rising over the years. (The US has seen capacity factors increase from 25% in 1998 to 42% in 2016.)

Averaging over our seven-year dataset, we found the wind CF in the southern state of Karnataka during the monsoon (the windiest time of the year) to be 34.7%. By contrast, NREL’s model predicted an 81% monsoon capacity factor. Why such a discrepancy? We suspect it has a lot to do with hub height assumptions. Our study found that the wind CF is very sensitive to the height of the wind turbines, and this makes sense; wind speeds become stronger and more consistent at higher altitudes. NREL assumed a single hub height across all the wind sites, and while this is likely accurate for new turbines, the historical data comes from a mix of old (shorter) and new (higher) turbines. Still, the model provided a fantastic overall picture of how the future grid might be operated.

There is a lot of room in the field for independent researchers like Fulbright Fellows to support these larger modelling efforts with spot analysis

Of course, much more research and testing must be done throughout India’s energy transition. NREL (where I now work) is in it for the long haul. We have strong relationships with grid planners and operators across several states, as well as in the central government’s Ministry of Power. We continue to revise our models as new policies come out, and we perform analyses on all scales with many different scopes. Still, there is a lot of room in the field for independent researchers like Fulbright Fellows to support these larger modelling efforts with spot analysis. In the words of statistician George Box, “all models are wrong; some are useful”. Every study in this field makes assumptions and simplifications, and they all trade off between scope and detail. Every model benefits from “ground truthing”, or validation with actual measured data.

The integration of this much renewable energy is unprecedented, and the timeline very aggressive. Climate change is, by definition, an international problem; it can only be solved with international cooperation. The Fulbright program’s core tenet is international exchange and cooperation, so a Fulbright Grant presents a great opportunity for immersive energy research in foreign nations. We need all the help we can get!


Marty Schwarz is a model engineer in the Strategic Energy Analysis Center at the National Renewable Energy Laboratory, where he works on renewable integration in India and North America. He completed his Fulbright Fellowship at the Indian Institute of Science in Bangalore, India from 2018 – 2019. Please email him with any questions about renewable energy in India (! If you’d like to explore this topic in more depth, a paper with the results summarized above will be published shortly.

Francisco Zubeldía is a Chemical Engineer from the UNMdP in Argentina. He has postgraduate degrees in physics and energy and is now a Fulbright scholar getting an MSc in Engineering Management at Trine University in Angola, Indiana. He is the Content Manager for the 'Energy Inputs' series of research articles on Fulbrighter.

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