Pathways to Round the Clock RE in India | ft. Irfan Mohamed

[Podcast intro]

Welcome to the season five of the India Energy Hour podcast. This podcast explores the most pressing hurdles and promising opportunities of India energy transition through an in depth discussion on policies, financial markets, social movements and science. Your hosts for this episode are Shreya Jai, Delhi based energy and climate journalist and Dr. Sandeep Pai, energy transition researcher and author. The show is produced by 101 reporters, a pan India network of grassroots reporters that produces original stories from rural India. If you like our podcast, please rate us on Spotify, Apple Podcasts or the platform where you listen to our podcast. Your support will help us reach a larger audience.

Having committed to the ambitious target net zero by 2070 and 50 per cent energy from green sources, India would need transition planning across sectors. The most important planning would be in the electricity sector which would need to decarbonise faster than any other sector. This transition would depend on India’s ability to produce round-the-clock clean energy, or 24/7 carbon free energy (24/7 CFE), at cost and scale to meet the country’s rapid economic development. But it faces the challenge of grid management and conducive energy planning which would integrate renewable energy across the power systems of the country.

To understand one such model of 24/7 CFE, we spoke with Irfan Mohamed, South Asia Analyst at climate analytics nonprofit TransitionZero to delve into the concept of 24/7 CFE and why, according to TransitionZero’s modelling, 24/7 CFE planning and procurement is a ‘no regrets’ option for India’s energy planners, grid operators, and corporates. Irfan is an energy modeller and analyst with multiple years of experience in modelling electricity markets. Before joining TransitionZero, Irfan worked at the Department for Energy Security and Net Zero developing decarbonisation policies for the UK.

[Podcast interview]

Shreya Jai: Hello and welcome to the India Energy Hour Irfan. Thank you so much for joining us here. We have discussed, we have spoken over email in the past about some of the work that you do at Transition Zero. So good to have you here and listen to you, not just talk about yourself, this report and all the other work that you do. So thanks again for joining us here today.

Irfan Mohamed: No, it’s great to be here. Thank you for having me on this podcast.

Shreya Jai: Thanks. Before we, you know, delve into the complex issues of India’s energy sector, let’s just first start with you. Can you tell our audience a little bit about yourself, what all sectors, segments you are interested in as a researcher, writer? How did you get into it? What did you study? Where are you from?

Irfan Mohamed: Yeah, sure. So I’m an energy systems modeler. And what this means is basically simulating and modeling power and electricity systems. So typically this includes things like forecasting into the future of what a power sector would look like, answering questions like, what is the cost optimal mix to achieve a 50% reduction in emissions by 2040, for example? Or what would happen if solar is 20% cheaper than it would be expected by 2030? So, you know, questions like that. And it’s a lot of creating mathematical models, but it also combines some data work, desk research, working with stakeholders to gather data and really get a sense of, you know, is what is coming out of a model something that makes sense? Because rarely modeling, yeah, rarely does modeling provide something that’s unintuitive, like solutions and scenarios that come out of the models should often make sense to people and be grounded in reality. So currently I work for Transition Zero, as you’ve already mentioned. I’m the main modeler for the South Asia region. And Transition Zero is a non-profit organization. It’s aiming to make energy transition planning more open and accessible. And we’re doing this through providing data and tools that will make it easier for no-code analysts and policymakers to make better energy decisions quicker. So we’re trying to make sure that, you know, policymakers and analysts aren’t locked behind, you know, quite expensive software or expensive consultants when they’re trying to make these kinds of decisions for the energy transition planning. And yeah, we do that providing a lot of tools that make it a lot more accessible for people to get into answering these kinds of questions. So then a bit about myself, I’m originally from Malaysia. My family moved to the UK when I was quite young, so I did most of my high school here in the UK. I originally studied engineering, civil engineering specifically, and I was a civil engineer for quite a few years before I moved into the UK civil service. And I was in the civil service that I started my kind of energy systems modeling career. So I looked at the UK power system, did a lot of analysis about, you know, forecasting to 2030, 2050, how to achieve net zero by 2050, looking at, you know, specific policies such as nuclear policies or renewable auctions, things like that. And that’s, yeah, that’s where I really got started with energy systems modeling. And then I moved into transition zero, doing pretty much the same stuff, but across other countries and geographies, instead of just being focused on the UK. And it’s, yeah, it’s a really nice mix of being able to use the kind of a technical background that I have from engineering, along with math skills. But combined with the obviously very, very exciting energy sector and energy transition sector, there’s just kind of so much to look at in this space. There’s so much space for innovation. And of course, you know, there are lots of consequences of what we do for us as humans in terms of our energy consumption, energy needs, and what the next 10, 20, 30 years looks like for us. So yeah, that’s pretty much myself, what I do now and how I got into it.

Sandeep Pai: Amazing. Do you want to just quickly share with us what kind of model has transition zero, you know, created, especially for India? Is it a supply demand model, CG? Is it integrated assessment model? So, and if you can share what your model is in the context of all the other models out there.

Irfan Mohamed: Yeah, certainly. So I’ll talk about kind of the models we do transition zero first, and I’ll talk about the India model, and then I’ll try to compare that against the other models out there. So at transition zero, we typically do two kinds of models. One is capacity expansion models, which you may know by different names, but it’s basically long-term studies understanding kind of what power systems or power sectors will have to build in terms of nuclear, solar, geothermal, et cetera. In order to meet anticipated supply in future years. So that’s, it’s a cost, it’s an optimization model. And I’ll take an inputs like, you know, this is your electricity demand in 2030. These are the costs of your different technologies. This is what your demand profile looks like. Now solve what is the right combination of technologies to build in order to meet that demand in 2030, 2040, 2050. So those are capacity expansion models. We also do a lot of kind of dispatch models, which again, you may know about other names, dispatch models is looking much more detailed, at a much more detailed level. So we’re looking at hourly dispatch of the power sector and power plants. So instead of looking at kind of say like a long-term forecast from now to 2050, typically we’ll look at one specific year. And, you know, in the study, we looked at 2030, for example, and we look at each hour. We look at specifically things like what’s the solar generation profile in each hour? What’s the wind profile in each hour? What is the demand in each hour? And we look at the different grid zones. So in India, we looked at the five different transmission grid zones. And it’s a lot more detailed. So we’ll consider things like how fast can a coal plant, for example, increase its generating capacity? Or, you know, if we’re looking at the really detailed level, we’ll model things like, okay, if the coal plant has switched off, it will take four, eight, 12 hours before it can switch on again, because of all the necessary downtime and uptime maintenance that’s required. So that’s our second kind of set of model to do. It’s a dispatch model, hourly granularity. And we really look in detail at every single power plant. And we look at how that contributes to meeting the demand that’s required at each hour. For the model of India that I did in this study, again, this is a dispatch model. So it’s looking at the year of 2030. And the spatial granularity is looking at the five transmission grid zones. So India North, Northeast, Southwest, and East. So all the demand is kind of attributed to one of these five grid zones. And similarly, all the supply is attributed to each of these five grid zones. And we look at data sources from government data sources, transmission grid operators, discoms. And we essentially built up a database of all the power plants that we found in each of these five grid zones. And we modeled them. And we basically let the model look at what is the cost optimal way to meet the supply. And what it does is it basically it plots what’s known as the merit curve or the dispatch order. So typically what that would look like is coal is kind of the first to dispatch. It’s probably got one of the lowest costs. In India, typically the costs for coal actually are much lower than in other countries. So it will be much lower in America. So dispatch first. And then you’ll have other sources that will come up. Gas is very high. Gas in India, you know, is very expensive. So it typically comes up much higher in America. Solar, wind, they’re cheap. Obviously, they’re intermittent. So you can’t control when they come into America. So, yeah, we basically model the power sector. And we look at what proportion of each technology dispatches at what time. And it is just as a model of the power sector. So in contrast, there’s some other models, like integrated models. It doesn’t look at, say, water consumption needs or kind of like the hydrogen economy, both of which are pretty big, pretty big considerations. India specifically, you know, we’ve got the national green hydrogen emission. And, you know, water consumption is obviously a big question when we think about things like data centers. So it does look at power system, power sector specifically. It also doesn’t look at kind of the transport sector or other non-power sector needs. So you’ve obviously got kind of increased electrification when transport moves from, say, like gas to electrified transport. But until that happens, this power sector model doesn’t really look at kind of oil or gas consumption in the transport sector or other sectors that aren’t strictly limited to electricity consumption and generation. So, yeah, those are the two main models, two sets of models we do in Transition Zero. That’s kind of the model we did for India. And it’s, I think it’s fairly similar to the two other models I’ve seen done for India in terms of dispatch models. So off the top of my head, I know Terry, the Energy Resources, Energy and Resources Institute India, have done similar dispatch and capacity expansion models. I know the government uses capacity expansion models to plan things like the, I think, what was the publication called? The 2029 to 2030 optical supply mix. So it’s very much the same kind of techniques and same models that academia and governments would use to plan power sector expansion. Yeah.

Shreya Jai: Yeah, thanks. Thanks for explaining the model and the report, the recent report on India, which is looking for, which basically we have done modeling for how to provide 24 by 7 or as we call it in India, round the clock, carbon free or renewable energy electricity in India. Can you tell us the findings? And interesting that you mentioned, Terry, and how the government of India does modeling on the basis of capacity expansion. And the report seems to has come at a very opportune time. The government has declared that 50 percent of our electricity generation comes from non-fossil fuel sources. However, that does not translate into round the clock green energy availability. So some very interesting numbers in your report, but I’ll let you, you know, brief us on that. What are the findings? What does the scenario looks like in the time period that you have analyzed?

Irfan Mohamed: So, yeah, you got it exactly right there. Just because we have more renewables coming on the system doesn’t necessarily lead to emission savings or cost savings. And essentially what our report looked at was just this very question. So, like I mentioned, we have this model of India in 2030. We assume that India meets its NDC commitments and its 500 gigawatts non-fossil fuel capacity target by 2030. And we have that kind of as our base scenario. And what we do is we take a portion of the total demand in 2030. And in this case, it was 5 percent. And we imagine, oh, not imagine, we remodeled what happens if that 5 percent either does kind of nothing. It just sources electricity as it usually would from the grid. And then we look at what happens when it goes under, when it tries to do annual matching. So this is what most corporations do typically right now. If they consume, say, 100 units of electricity throughout the year, they’ll buy 100 units of clean generation to match their total consumption with their total supply. So we model what happens when this demand does annual matching. And then we model what happens when this demand, this sector of demand, goes for around the clock rather than annual matching. And, yeah, the key point that we’re trying to understand is when the CNI consumers, so commercial and industrial consumers, when they move from annual matching to round the clock, what are the impacts on the system? So the greatest whole, what are the impacts on them as a CNI consumer in terms of costs, in terms of capacity builder? What are the impacts on emissions? And what other interesting things do we see? And really what we find is that India by 2030 is likely to be approaching a state where there’s lots of renewables. There’s a high renewable penetration share. And just adding more renewables on top of that without really paying attention to the timing or where those renewables are deployed is not the best way to keep. To keep generating emission savings, to keep generating cost savings. What you need are things like round the clock matching to make sure that renewables are paired with things like battery storage to ensure that the renewables come on the systems, come on the system at times which are most beneficial for the system. And what we found that 70% round the clock matching. So by that would mean that the CNI consumers are matched with clean energy 70% of the time. We find that 70% is actually cheaper for the grid than annual matching. And the reason that is, is because it’s all about this timing of the renewables and this pairing of solar and batteries. So for example, if a CNI consumer did annual matching, they’ve just bought a lot of solar power, for example, the cheapest renewable option out there at the moment. But all that solar power is likely going to be generating in the middle of the day. And it’ll be generating at the same time as all the other solar plants out there in India. And it’ll be what typically would happen is that you have this phenomenon called self-cannibalization where because all these solar plants are generating at the same time. Now, you’ve got this surplus of renewable generation and the surplus power, and you either have to end up curtailing it. So you’re just wasting renewable energy. But the more clever thing to do or the better thing to do is to store that energy in batteries and deploy it at other times of the day. And that is exactly what CNI consumers do when they have this round the clock matching machine. So we find that I’m just going to look at some of the numbers. We find that when this 5% of demand goes under annual matching, that costs the system about 25,000 crore per year. When they go to 70% CFE, that’s 17,000 crore per year. So that is a 8,000 crore saving, which is pretty significant. And the reason why that’s coming about is because A, you’re building less capacity because you’re being a bit more clever about, okay, I don’t need to build a huge amount of solar. I need to build the right amount of solar paired with the right amount of batteries, which means that I have more clean energy available throughout the day. The second reason why you have those cost savings is because you can sell excess clean energy back to the grid. So again, having batteries means that you can sell clean energy back to the grid at times when it’s most valuable. So for example, when you have a lot of coal generating on the system right now, or a lot of gas generating on the system, if you have solar and batteries, that can displace the expensive gas and that can save grid operators money because you don’t have to burn expensive fossil fuels essentially. Yeah, so we’re finding that solar and batteries are kind of the key to a successful kind of round the clock matching regime. There is a role for onshore wind because onshore wind isn’t as cheap as solar, but onshore wind is less intermittent than solar in that it can generate throughout the day and night. You know, it’s not limited to daily hours. It can be windy at night, obviously, which means that it does have a role to play in generating round the clock clean energy. So that’s the, yeah, that’s a mostly solar batteries that have been up onshore wind. And the final bit is that there are a lot more emission savings on the round the clock clean energy matching rather than annual matching. Again, for the same reasons that we’ve already talked about, because you’re deploying these renewables, batteries at the right times during the day, you’re displacing coal, you’re displacing gas, which means you’re reducing emissions. emissions. As opposed to under annual matching, you’re just adding more and more solar power at the, you know, the day or hours, which may not actually be displacing fossil fuels. So you’re seeing limited returns when you just indiscriminately add renewables to the system.

Sandeep Pai: Fantastic. So I just want to ask you kind of one big picture question. So for 2030, you know, your modeling clearly shows that like daily matching is better than the annual matching. But given that India wants to achieve a net zero by 2070 and like in the long term, I mean, you need like India is like unlike any other country, you need like not just wrong the clock, but you need everything at every time. You know, if I can say that like, I mean, we’re talking about thousands modeling studies of thousands of gigawatts of solar. Yeah. So I mean, given the short term is clear, but in the long term, given that India does need everything, could India not do both? I mean, yes, obviously Indian policymakers are sort of embracing battery storage paired with solar and wind and so on. But could they also not do both? But could they also not do both pairing given, you know, like build out solar indiscriminately, even if you have to curtail, even if, you know, there is a little bit of savings loss. So I don’t know if you have any thoughts on that. Just thinking about the big picture in the long term.

Irfan Mohamed: Yeah, that’s a good question. I think from my experience looking at other countries and looking at India, the message of the energy transition is fairly consistent in that. If you want to reach net zero by any year, whether that’s 2070, 2050, you have to pursue all avenues. You have to do everything within your power to decarbonize, essentially. And I think in that respect, you’re right. So short, medium term, yes, pursuing round the clock energy and making sure that, you know, it’s cost optimal for C&R consumers and cost optimal for the grid. But the longer term, I think you’re right. If there is, like, if the pathway to building a lot of solar and India obviously has such great solar resources available to it, it’s like the Indian geography is very fortunate in that regard, especially, you know, you saw the heavy states like Rajasthan, Tamil Nadu, I think Gujarat and Karnataka. You know, they have such great solar resources. It makes sense to pursue that solar resource as much as you can. And, you know, the benefit of that is you get supply chain reduction, cost reduction because, you know, the solar chain is built out. You can build out your domestic, your domestic industry with solar panels, solar resources. And, you know, another key point is not just kind of the manufacturing supply chains and the raw materials, but it’s building that local talent, building that local expertise to be able to, you know, build out your domestic supply chains and your power sectors quite, you know, independently and not having to be hugely dependent on, I guess, you know, foreign expertise, foreign imports in order to reach your decarbonization goals. Yeah.

Shreya Jai: Yeah. One interesting point in the report, among others, is also about the discussion or the mention that you have about energy storage capacity that India would need to build, you know, for achieving this goal. My question is around the cost estimates. India remains a very price sensitive electricity market. Coal is still cheaper, though in some of the new thermal contracts, we’re seeing the price inching up. Yet the battery plus solar would invariably at current rates be costlier than coal. So is there any cost estimates that you have provided, you know, in terms of the savings that can be made or the cost that will cost comparison with the current conventional technology? If you can shed some light on that.

Irfan Mohamed: Yeah. So what we found in our study was that if this 5% of demand wants to meet 70% CFE, you need to be building another 17 gigawatts of batteries or 34 gigawatt hours if you want to do it from a storage. Sorry, if you want to look at gigawatts hours instead of gigawatts. So 17 gigawatts of batteries at 70% CFE and 100% CFE, you need to build about nearly four times that much, 60 gigawatts of batteries. And it’s hard for that to compete with coal, I think. Coal is just very cheap. And if you’re trying to, if solar and batteries are trying to compete, if C&I consumers are trying to compete with coal, purely in a cost basis, solar and batteries, I don’t think, you know, with the current prices that will work very, very well. I’m not sure. I, my, yeah, I don’t have a hugely detailed insight into kind of the, the, the policies, but this is my lived understanding. Like, you know, C&I consumers are not, they’re going for these, rather clock tenders and the solar and battery tenders,  because they’re cheaper than grid tariffs. But, you know, that doesn’t necessarily mean that the grid tariff is representative of the core price. If you know what I mean, you know, the discounts are charging these tariffs, that have a lot of, you know, extra subsidies piled up on top. And what I’m trying to get at here is that solar and batteries don’t necessarily need to compete with coal directly. They can compete on the basis of kind of the price of the levelized cost of energy. So the price of solar batteries and coal is directly, but then you also have to consider the,, the infrastructure around it. so how easy is it to get energy from thermal power plants to your C&I consumer, as opposed to getting it from solar and batteries. When, you know, a lot of the time, if you’re a small consumer, you can maybe even do solar batteries behind the meter. You can build it on site and that is probably a lot easier, a lot quicker than trying to procure energy from, or even building a coal power plant on your backyard, which obviously isn’t going to happen. so I think you have to look at more than just the price of coal, and look at kind of the wider enabling system, the wider power grid. and then if you have things like, you know, a carbon price market, obviously tip the scale in favor of batteries and solar and the battery industry in India, from my understanding is, you know, kind of on the up and up it’s, it’s getting bigger. It’s getting better. from our conversations with stakeholders, when we were doing the study, they, they were not so optimistic on a lot of technologies, but the one technology that they were using, they were consistently optimistic on was battery storage. And I think that’s reflected in a lot of the recent tenders that are coming out. Now the, the big challenge I think is kind of going beyond that 77% CFE, right? So I said, do you need 17 gigawatts of batteries for 70% CFE? And then 60 gigawatts for a hundred percent CFE. If you’re just using conventional lithium ion battery storage, what really needs to happen is if you want to reach the a hundred percent decarbonization, a hundred percent round the clock, you need to be able to deploy long duration energy storage. And that’s one of the biggest challenges. And I think that industry seems to still be quite new and not that developed, not just in India, but, you know, across, across the world. Like you’ve got so many contenders, you’ve got kind of liquid energy storage, you’ve got, liquid,  sorry. You’ve got, hydrogen storage, you’ve got compressed air storage. You’ve got so many different long duration storage carriers, but there doesn’t seem to be any kind of like one front runner and definitely not one that can compete cost wise right now. So I think that’s the other big thing that needs to become more competitive for solar and renewables and batteries and storage to be able to outcompete against thermal and especially dispatchable power. Cause that’s the big thing, right. You know, I’m dispatched on power. That’s kind of something you can’t really put a price on a lot of the time, having dispatched on power versus intermittency.

Sandeep Pai: Great. Let’s talk about savings. Irfan. maybe you could explain like how you calculated the savings and what your big picture is. And yeah. Like, how do you, like, how are you planning and what,  is it based on policy? Is it based on like just least cost? Yeah. I’d love to hear how you’ve calculated.

Irfan Mohamed: Yeah. So, the way we calculated savings in the grid is  yeah, we, our model was, I would go back to our modeling setup just briefly. So our model was a least cost model and it’ll build out the required renewables, battery storage, etc. So our model is a lot more capacity at least cost in order to meet the constraints of meeting 70%, or 80%, or 90% CFE for BC and our consumers.  or annual matching even, sorry. So the way we calculate these savings is under annual matching, we see how much is built in capital expenditure and how much is saved in operational expenditure. So what’s built in capital expenditure is the costs you can attribute to,  more solar plants, more onto wind plants, building up batteries. Your operational expenditure savings are your savings from, when your renewables displace expensive fossil fuels. So you get better savings from that because you don’t have to burn so many,  so much fossil fuels. So we look at the capital and operational expenditure changes and we compared that under the case of annual matching to CFE 70, 80, 90, 95, etc, a hundred. and yeah, what, what we found was that compared to annual matching, you need to build about 10% less, sorry, it’s 10% cheaper in terms of the capital expenditure to build CFE 70 compared to annual matching. And again, that’s because of,  like this combination of well-planned solar and battery is actually cheaper cost-wise than just building a lot of solar to match your total consumption with your total supply. And supply the second thing is that you have about double your operational cost savings in CFE 70 or 70% around the clock compared to annual matching. And again, that’s because, you know, like I said, your timing, your renewables better and you’re creating more value to the grid and more value to value to consumers. Because you’re getting that cheap renewable energy throughout the day, not just, you know, during their hours.  and like I said, what that amounts to is a saving of about,  8,000, crore rupees, annually when you’re moving from annual matching to CFE 70, and that’s about, yeah, $1 billion, US dollars. So, you know, it’s not,  a small number. Yeah.

Shreya Jai: You have a similar analysis, if I can use the word similar analysis on emission savings as well. mostly aimed at, you know, corporate buyers who would be, who would be major beneficiaries from around the clock renewable energy. can you talk a bit about that as well?

Irfan Mohamed: Yeah, definitely. so the first point is, you know, under annual matching, you can never, you can never reach 100% emissions reductions. Kind of the, the concept of annual matching, as a theoretical basis can never let you decarbonize 100%. It’s just, it just doesn’t work. You need that granular accounting, you need the around the clock clean energy matching in order to reach zero emissions. So if a C&R consumer wants to reach zero emissions, they have to go for some form of around the clock matching scheme or granular accounting scheme. and again, what that means in practice is that when we compared around the clock or CFE, 24/7, CFE to annual matching, we found that again, at 70% CFE, you are already,  you’ve already got, more emission savings than under annual matching.  and again, and again, this is for very much the same reasons that we’ve been discussing. You are timing your renewables better. You’re pairing with storage. It’s available throughout the day, which means you are, can displace, fossil fuels throughout the day. And you’re basically, yeah, like I said, you’re just being a bit more clever about how you are using your renewables and kind of the, the side effect of this is. The cost of emissions or the cost of carbon abatement. and what I mean by carbon abatement costs is, you know, how much does it cost to reduce say one ton of CO2 in the system? That carbon abatement cost is about, I think three times cheaper. If I remember correctly. Yes. Three times cheaper under a round the clock matching regime than under annual matching. So what that means is for every rupee you are spending in trying to, you know, reduce your emissions through around the clock energy, that is three times more effective than an equivalent rupee spent, under an annual matching regime. And again, same reasons it’s because you’re using your renewables a lot more effectively. You are pairing with battery storage. I’m saying all the same things here, but it’s all, it’s all the same thing. Like compare, combining your solar and a bit of wind with your batteries means you can spread it throughout the day and get clean energy throughout the day. And you can displace fossil fuels much more effectively. And you’re doing so at a cost that’s cheaper to consumers and cheaper, to, the grid up to a point. So, obviously I mean 80, 90% is more expensive. but for now 70% seems to be that sweet spot. Yeah. 

Sandeep Pai: I know it was a modeling exercise, but I’m, I’m just curious if you looked at even in a qualitative sense, if not in a quantitative sense, the policy landscape and whether actually. They’re going to get it, like the Indian planners are planning in the round of clock way or it’s in the annual way. And like, what, what do you see likely happening? Not in a, if, if then scenario, like a model, but you know, in case what’s happening in reality and where do you see that?

Irfan Mohamed: Yeah. So we did a bit of studies into this mostly through conversations with stakeholders on the ground, trying to understand, you know, are the results sensible things like that. And what we found is that when, when we back calculated the tariffs that we were getting out of our model, they are roughly comparable to, car tariffs are being discovered. So FDRE tenders right now, so and dispatchable renewable energy tenders are, I think in about the range of about four to six rupees per kilowatt hour. And that’s about the range that we were getting with our CFE, studies. So I think it, it’s, it’s mimicking reality, which is just comforting as a modeler. It’s always terrible when you’re modeling something and then you get results that make no sense. And it indicates that you have to go back and change some assumptions. so that, that’s one aspect. So the, the tender prices look, they look about right.  but in terms of kind of the policies on the ground, again, I’m not a policy expert, but what my understanding is that it’s kind of a, it’s kind of a, there’s, there’s a couple of considerations. On the one hand, you know, we know India is amongst the world leaders in increasing renewable energy share. kind of just last year, I think it was how much 20, 25 gigawatts of soda was added to the system in 2024, which is a significant amount. but I think what also has been recognized is India is also one of the world leaders in, clean energy tenders. So, you know, from the early iterations of the RTC tenders, so the round of clock tenders, to the current iteration of FDRE tenders and similar tenders. That’s not something you actually see in many other countries. You know, these tenders have very specific rules about load following, about what percentage of energy has to come from clean sources, very specific rules about off peak and peak hours. So there’s a lot of promise in that regard in, you know, in the policy landscape, in terms of these tenders, because these, these tenders and these policy rules and  policy stipulations is what is, incentivizing, you know, these, solar and battery projects. And kind of my non modeling, non highly educated opinion is that, you know, federal and state governments in India need to continue this push creating and mandating and, you know, spreading these tenders that require around the clock clean energy. now on the other hand, the current REC system, so the renewable energy certificate system in India, as I understand it, could see some improvements. So I think right now there’s not a lot of detail about, about the certificates you’ve got, I think, solar and then non solar in terms of the certificates you can buy. It’s mostly for compliance purposes, not really for emissions reduction purposes. And,  it doesn’t have, you know, the really key information you need for granular accounting and round the clock, clean energy matching, which are things like, you know, specifically, where was the energy,  generated and what hour of the day was it generated? what was the energy generation source, you know, things like that. So, kind of an improvement of that REC system mandating kind of, time-based, time-based RECs and making sure that it’s accessible and freely available to CNI consumers, will also help, you know,, improve this push towards rather clean energy matching. Yeah. And, yeah.

Shreya Jai: No, no, thanks. Thanks for answering that in such detail. I hope this report and your insights catch the attention of the people who would actually provide round the clock renewable energy here in India. But, overall, thanks. Thanks. Yeah., but thanks again. Thank you so much for joining us here at The India Energy Hour.  It was a great conversation. Energy sector modeling is something that we have, we have not much covered.  We did discover, we did discuss, we have discussed in the past about climate modeling,  and everything, ahead of COP, I think, two seasons back. But this was something new and very interesting. so thanks again for being here and explaining it so lucidly.

Irfan Mohamed: Thank you. Yeah.

Sandeep Pai: Thanks. It was a pleasure talking to you.

Irfan Mohamed: And a pleasure having this conversation.                                        

[Podcast outro]

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