 Okay, hello everyone, and thanks a lot for being here. My name is Javier Jorquera-Copierre. I am an energy analyst at the International Energy Agency, specifically at the Renovus Integration and Secure Electricity Unit, and I'm very happy to be the moderator of this event today with Olo. This event is called Electric Vehicles, Total Cost of Ownership and Grid Integration Tools, and we were exploring two different tools that IA produced in recent times. Before we begin, I will give a couple of important information for this event. First, I am showing here this slide of a disclaimer for interpretation. We will have today interpretation from English to French. And then you should know that in the questions and answers part of each presentation of the two tools we will present, we will have the opportunity to answer your questions. And these questions can be preferably in English, but you can also post them in French if that's better for you. Also, I would like to let you know that this session is being recorded. The terms of the data protection notice can be found in our website, where we have created a page for this event today. So, today we will begin with having opening remarks by Annika Berlin and Pablo Eviako. Annika Berlin is the Africa Platform Coordinator and also Program Management Officer of the Sustainable Mobility Unit, Industry and Economy Division of the United Nations Environment Program. And Pablo Eviako is the head of the Renovables Integration and Security Electricity Unit in the International Energy Agency, the IEA. After this, after their opening remarks, we will have a presentation of Shane McDonough, the Transport Analyst of the Technology Innovation Unit of the Energy Technology Policy Division of the IEA. He will present to us the Electric Vehicles Total Cost of Ownership Tool. Then he will have questions and answers section to answer all the questions you may have about his presentation. Then I myself will present the Electric Vehicle Charging and Re-integration Interactive Web Tool, and I also, after my presentation, will have another session to answer all of your questions. And then we will wrap up the event. We can go to the opening remarks. Annika, please, the floor is yours. Thanks Dr. Javier, and thanks especially to the International Energy Agency for organizing this exciting event and for presenting their tools. It's been a great partnership between UNEP and IEA to offer these sort of events. Just briefly as a reminder why we were talking about this topic. So, as most of you know in the webinar, I know the transport sector is increasingly moving towards electric vehicles for five main reasons. One being to reduce greenhouse gas emissions from transport, which continues to be a quarter of all energy-related greenhouse gas emissions globally. A second, and in many parts of Africa, most importantly to reduce air pollution, which causes respiratory diseases. Third, to reduce costs from increasing price of importation of fossil fuels. Fourth, increasing urbanization, which means that we need more efficient, cleaner and sustainable means of transport. And fifth, to create local value change around the assembly, manufacturing and maintenance of electric vehicles and green jobs. For example, also by using locally generated electricity that then can be used for vehicles instead of importing fuels. And that is of course also part of this webinar, how we can use and better integrate renewable electricity in grids and vehicles. It is estimated that by 2035 the main automotive markets, US, EU, Japan and China are going to be moving to all electric vehicle sales. And that means a few years later, we will see these vehicles on the main importing markets that are in Sub-Saharan Africa. And so why currently the number of electric vehicles in Africa is still low. The conditions are optimal to leapfrog to electric mobility by leveraging renewable energy resources that are abundant on the continent. And also from an economic perspective, the current rise in fossil fuel prices has given governments the urgency to move to more sustainable sources of energy in mainly importing markets. And under this background with funding from the global environmental facility, UNEP together with partners such as the IEA has established a global electric mobility program where we're working in over 50 low and middle income countries all over the world. To help with the shift to electric mobility. We're implementing runs from over 100 million US dollars and co-financing exceeding 500 million. The problem is active on the global level such as with global tools that we present here on the regional level with the Africa support investment platform that we are coordinating from Nairobi. And where we try to offer as much support as possible through trainings connecting with experts, financiers, and in general by establishing networks between people working mobility on the continent. And part of this work, the connection between the regional and the global level is this webinar. We're trying to bring the knowledge from the IEA to the region. And yeah, I'm very much looking forward to to an active exchange within this webinar. And with that, I'll hand over back to Javier. Many thanks. Thank you, Annika. Now, Pablo, please, the floor is yours. Thank you very much, Javier. And thank you so much, Annika Berlin, our colleagues from the United Nations Environment Program unit, and particularly to all of the colleagues that are joining us from different parts of Africa. It's really nice to be here speaking to you. And it's really nice. It's a pleasure to see how many participants we have from different places from the African continent. Today, Africa is a very important region in our work. We've been publishing several reports such as the African Energy Outlook 2022, as well as a vision for clean cooking access for all in Africa that are specifically focused on the continent. And we're about to launch a report on financing clean energy in Africa in collaboration with the Africa Development Bank Group at the Climate Action Summit taking place in Nairobi next week. And through all these projects, what we have been doing is collaborating with key partners in the region as well as discussing the size of the opportunities and challenges that African countries are facing in many topics related to energy and climate change. What we knew is that recently Kenya and Senegal have joined the IA family following in the footsteps of Morocco, South Africa and Egypt. And this means further focus and continuation on increasing our collaboration with partners in the region. We're aiming to support Africa in achieving its own energy climates and climate-related objectives, including of course universal access to modern energy, as well as clean energy development. In the context of today's webinar, electric mobility, we see it playing a central role. IA scenarios show that electric mobility can really enable deep decarbonisation of the global energy system in an affordable manner, which is really important and key. Every region has distinct opportunities and challenges to tackle the uptake of electric vehicles, and Africa is no exception in this case. One particular barrier that we've seen for electric mobility in Africa is of course the need to expand electricity access that today is only at an average electricity access rate of 57%. Another aspect is linked to affordability and the need to develop affordable vehicles as well as their operation. Despite these barriers, what we see is a great potential for an expansion of the electric vehicle market in the region. And with the government's interest and efforts towards remission and regulations to support the uptake of electric vehicles in various African countries, this is a very strong path forward. To assist countries with the uptake of electric mobility, we have developed the IAA two interactive tools under the GIF program, the Global Environment Facility Global E-Mobility Program. And during this workshop today, we're going to be presenting these tools as part of a series of regional dissemination events that began in April this year. The first tool is a total cost of ownership tool, which allows to compare cost of owning and operating fossil fuel and electric vehicles, and that helps understanding under which conditions an electric vehicle can be more affordable to own than a fossil fuel based vehicle. And the second tool is the electric vehicle charging and green integration tool, which allows to understand the impacts that different fleets and behavioral profiles can have on the power grids by simulating several charging strategies in fleet behavior. And this, of course, is going to be of higher relevance for the development of the African power grids. To present these tools, I am very happy to introduce my colleagues, Shane McDonough and Javier Jorqueda. During this workshop, we're really looking forward to any questions and feedback from colleagues that are participating. We hope that the workshop today will contribute to supporting electric mobility deployment in Africa and our continued cooperation and collaboration with the region. Thank you so much. And I'm looking forward to the discussion and the comments that we received today. Thanks. Thanks Paolo and Anika for your great opening remarks. Now I will hand over the floor to Shane to begin his presentation. Thank you Javier. Good afternoon everyone. So I just need to share my screen so bear with me if things are a little bit messy at the start. I hope they're a little bit smoother thereafter. Okay. Nice. So just a very, very brief presentation to get started to give some context. So my name is Shane McDonough. I'm an energy analyst here at the IEA, specifically looking at transport and also coordinating our work with the Global Environmental Forum, the e-mobility project. So working group one specifically looks at light duty vehicles. We hope to expand the TCO tool and other tools into other areas in the future. So the focus is quite firmly on that light duty vehicle segment. So we're talking about passenger vehicles and small advance. We don't right now have a focus on two and three readers. And but again, this is something we hope to expand into because we know it's particularly relevant for Asian and African colleagues. My email address is there on screen. I really encourage anyone who has any questions related to the presentation or even if they're somewhat tangential. So if you have any questions about transport and you think that the IEA and our Jeff coordinators might be of help, please feel free to reach out to us at that email address. I'll also show at the end of my presentation. So just really quickly, and what we have here is a map of all of the countries that are participating in the Jeff 7 project. So this iteration of the Global Environmental Forum. And what we're trying to do is promote an extra mobility in these countries and you can see that they cover pretty much every part of the world, north to south, but there's a focus on developing economies. And we can see that the use cases in these countries are obviously going to be quite quite different. Our projects focus on a range of issues from policymaking to trying to reduce the cost to try and increase access. We look at, like we said, passenger vehicles and buses. So again, if you have any questions, please feel free to reach out and understand that the Jeff deals with a really wide variety of subjects with respect to electric mobility. Again, working group one, we're looking at like 2D vehicles. That's myself. And then working group four, which is Javi and Pablo are looking at grid integration. So we have to essentially look at what is the most suitable vehicle? When is an electric vehicle more suitable than a fossil alternative? And then how best do we charge that? How do we integrate it into the existing electricity system? And with respect to this tool, what we're trying to do is number one, make it applicable to a really wide range of users. So again, the Jeff participants are quite diverse, even within Africa, they're very, very diverse. So we want to make this tool available to a really wide range of users. We don't want anyone to need technical expertise to be able to get some lessons from the tool. And we want to provide lots of learning opportunities. So again, people who are not very technically adept or people who are new to the subject should be able to come to this tool and get some really meaningful learnings from us. We need to understand the effect on policy. So many of us here are maybe, you know, tangential to policy. So we might be talking to policy makers at some stage. We might be asked to inform policy making, but it's also super important that we understand the most effective ways to try and influence and to try and increase the uptake of mobility. So for example, if we had the choice between subsidizing a vehicle or, you know, investing in electricity infrastructure, we should understand the effects of that has and specifically to kind of our use case. We want to make people aware that the technology is improving. So if we perform a calculation or model some analysis as of today, we know that the potentials for fossil fuel technology and for electric technologies are different, you know, fossil fuel technologies are very mature and therefore they're unlikely to get very much better than what they are today. Whereas with electric technologies, we understand that they're relatively immature. And there's lots of opportunities to try and improve them and to try and integrate them into the systems a little better. So the bulk of my presentation will actually be a demonstration of the tool itself. It works. You might just let me know that people can still see my screen. Yes, we see your slides. The slides or the TCO tool? The slides at this moment. Okay, right. So I might have to just stop sharing and then reshare to make sure. Now, you can see. Yeah, perfect. Yeah. So, thanks. So this is the TCO tool as it is available on the website. So we can share the link and maybe if we want to even put it in, if someone wants to put it into the chat. And when you visit the webpage, this is exactly what you will see. And what we have is lots of information about number one, what a TCO is. So a total cost of ownership analysis. What that does is it tries to calculate all of the different costs of, for example, purchasing the vehicle and buying fuel or charging the vehicle, you know, maintenance. If you have to take out some finance or a loan to purchase in the first place, puts all of those costs together and produces a single figure. And that can be in terms of the, you know, for example, dollars per kilometer driven or dollars per year. And what that does is it allows you to compare different cars of different characteristics. And it also allows you to compare them across different use cases. And when I say use case, I might mean whether you drive 10,000 kilometers per year or 25,000 kilometers per year. And if you use the vehicle, for example, for commercial purposes, if you're a taxi, or if it's just for personal use. So TCO was a way to fairly compare different power trains. I won't go into too much detail on what's written on the page. What we have is some really useful context and some explainers. Firstly, what we have are some, I would call them lessons or kind of helpful user guides. And I encourage everyone to use these because again, the purpose of this tool is not necessarily to really accurately model anyone's situation. It's to impart principles and for the users to be able to understand what affects the costs of an electric vehicle. So I wouldn't necessarily come to the TCO tool, trying to say how much would my vehicle cost if it was electric, how much would it cost if it was petrol. It's capable of that. But what's more important is that we understand the circumstances and the scenarios in which one might be more suitable than the other. And at what point in the future, that kind of that change might happen. So maybe electromobility is more expensive than the fossil alternative today, but in the not too distant future will be cheaper. And by playing with this tool, we'll also be able to understand, you know, what levers and how we can improve the, you know, the competitiveness and the affordability of electric options. So our lessons here are, for example, you know, we're looking at a cumulative cost curve because this is important to understand how the results are shown. And we're looking at, for example, we have vehicle A, vehicle B, and we can see the point at which these lines intersect or cross over. That's when one becomes essentially cheaper than the other. And with an electric vehicle, for example, we can understand that they're more expensive up front. So to purchase the vehicle is more expensive. But because it's generally cheaper to charge an electric vehicle than it is to refuel a fossil fuel vehicle, there is a point in the future at which those costs, you know, intersect again. And so we can say, in this example, you know, if we buy our car in 2022 by about 2029, vehicle A will be more expensive than vehicle B. So it's more cheaper to buy. It's cheaper to buy at the start, but by 2029, that has changed. So there's some dynamics happening here. And this is with respect to financing. So it gets a little bit complicated. That's why we have these lessons here. And again, I encourage anyone using the tool to go and check these out. Well, I'll briefly go to what we have with our basic version. And what we have number one is a list of example regions or countries in which the analysis performed. When we change these, when we select different countries on the list, what happens is it changes the default values for, for example, a vehicle cost. So vehicles cost in general to different amounts of money in different countries. These are just examples. If you don't see your country there, that's no problem. What you can do is you can choose this custom option. And with that custom option, you can model any country you want. So for example, if you're in, I heard Kenya mentioned earlier, and you want to model the difference between electric mobility and perhaps diesel, that's possible using our custom option. We have two time horizons today being the relative or the kind of average cost of the vehicles today and also around 10 years now. So we say around 10 years now because again, this isn't the aim of this tool is not to explicitly model any one situation, but to give us good ideas of how costs change over time and what effect that has on our total cost of ownership. We can change things like our driving distance. We have different vehicle types, small, medium, large pickup trucks, SUVs, and we also then have again our powertrains. So powertrain, we mean how is the vehicle duals, where does the power come from? We have diesel, petrol, petrol hybrid. Petrol hybrid here is a mild hybrid. So essentially, we cannot plug this in. All of the energy ultimately comes from petrol. And people might be familiar here with the Toyota Prius, which is maybe the most famous hybrid car. And then we have a plug-in hybrid where there's a small battery on board that you can charge from a socket or a charging station on the road. And then we have battery electric, which is fully electric. I might just at this point say if people have questions throughout the presentation, it's perhaps more beneficial if you pull up your hand and you ask now, there is a Q&A session at the end of this. But if you have a question now, feel free to ask because it's better to answer it such that you understand the rest of the presentation rather than moving forward with maybe some of the people a little bit confused about something specific. But so the tool here, we have a couple of ways of showing our results. So we talked about that total cost of ownership. We have dollars per kilometer, dollars per year. The cumulative costs. So this is, you know, we've purchased our vehicle and, you know, perhaps through financing. So we have a down payment of perhaps 10%. And then each year we spend money on things like maintenance and fuel until we reach a point in which our loan is paid off. So we're no longer paying the loan, we're just paying maintenance and fuel. And you can see here that the lines continue to change. We also have the breakdown of our total cost of ownership. And that's essentially gives you what chunk of the total costs our fuel purchase, our maintenance, our financing. And if we go to the battery electric option, we can see here that the vehicle cost is much, much greater than it is in the petrol. But then if we look at, for example, you know, we have financing, again, because a battery vehicle is more expensive. It's more expensive there. But what we have then is a large chunk of our costs are liquid fuel purchase or petrol in this case, or gasoline, sorry. Well, I'll switch back to this, because one thing that's really beneficial about this tool is that it calculates in real time. We don't have to change all of our inputs and then wait for results. What we can do is, for example, try and drag out those lessons, those important lessons. So the green line here is our battery, battery electric vehicle. Our purple line is our petrol vehicle. If you hover your mouse over any points, you'll get the exact numbers. And what we see is if we're driving just 7000 kilometres per year, the petrol vehicle has a much, much lower cost because it's cheaper to buy. Even though it's more expensive to run, we're not running it very often. And so the total costs of a petrol vehicle are much lower if you run a very small number of kilometres per year. But if we change this, if we go up to someone who drives an average of maybe, we can say, quite high, you know, if you were doing a taxi job, 30,000 kilometres per year, you can see that that changes very significantly. And because the lines now intersect, because they cross over, we can see that actually within seven years, our battery electric option would have a lower total cost of ownership than our petrol option. So this is just one example of how we can change different parameters and see how it affects the costs. If you go to a petrol hybrid, we can see here that it actually becomes, you know, that the costs are very, very similar to a battery electric. But because an electric vehicle is more efficient, it uses less, it spends less money on fuel, it would actually be better than a petrol hybrid in this circumstance. Likewise, we can look at plug-in hybrids, we can look at diesels. One thing that's important with the plug-in hybrid is we also need to know, because a plug-in hybrid has the ability to run on purely electric or on petrol or a mix, and you need to know what share of your journeys are being covered by the pure electric mode. And you can see here, this is the difference maybe between someone who lives quite close to work, to school, to the shops, where most of their journeys can be run on that small battery, or if they do a lot of motorway driving, and it's quite different. So we can see here, there's lots of ways to change. We can also change, for example, the electricity costs. You know, it makes a lot of sense if the electricity cost is much higher, it makes our battery electric vehicle less competitive. Likewise, if our liquid fuel costs are higher, we can see that it has a huge effect on the competitiveness of our fossil option. So I hope that all makes sense. And I use the word play with the tool. I mean that the best thing to do is to play around with the options, and then you start to understand the effect that different changes have. So I think it makes sense to everybody that if the fuel costs are higher, for one rather than the other, that will have an effect on competitiveness. But by playing with these sliders here and inserting different values that might be kind of more relevant to your country, you can see what kind of effect that would have. Really quickly then I'm going to show you the advanced version. So these are the simple inputs that we give to users. And we expect most of them to be able to use this version without much technical know-how. But in our advanced version, we offer much, much more control over the specific kind of circumstances that you model. So you can put in specific vehicle costs. What we have here is before taxes, you know, and this allows you to, for example, if you're testing different policies, you know, what might it be better to reduce the purchase taxes or to reduce the fuel taxes. And you can play around with those different things there. So we have import tax, registration, CO2. What we do here is we compare vehicles on a 10-year basis. Because petrol, diesel, electric all have different lifetimes, it can be different to compare them kind of evenly and fairly. So what we did was we took it a 10-year timeframe because this is about the upper end of what we expect first generation battery electric vehicles to operate for. After this, what tends to happen is not that they get less efficient as what happens with fossil fuel vehicles. What happens then is that the range reduces. So if your new battery electric vehicle can run for, for example, 400 kilometers on one charge, after 10 years, that figure might be as low as maybe 250 or 300 kilometers. Second generation and maybe more expensive battery electric vehicles, that reduction is much, much lower. And there are new regulations in place to kind of limit how, how small or how big of a drop that is after a number of years. But in general, we expect battery electric vehicles to have a lower range after 10 years. Whereas we expect petrol and diesel vehicles to consume more fuel and require more maintenance after 10 years. So you can change the, what we call the residual value. This is how much we expect the vehicle to be worked out for 10 years. You can change that here. It doesn't really have a large effect. Because, excuse me, relative to the cost of a new vehicle, we understand ourselves that you generally only get about 10 to 15% of the value of the car back when you sell us, especially after you've driven for 10 years or more. With respect to operating costs, then we have lots and lots of different parameters here. I won't go through them all, but some of the most important ones, again, are fuel costs, you know, and how much of that is tax that changes significantly by country, particularly in Africa. We have the fuel efficiency. So the liters of fuel required per 100 kilometers, or in the case of electric vehicles, the number of kilowatt hours per 100 kilometers. So if we met our electric vehicle really inefficient, we can see here the change. If we met our fossil fuel vehicle much more efficient, we can see the change. We have things here like the share of day charging, share of night charging. It's a small bit more complex, but again, what I do is I invite anyone here to play around with the tool. And then if you have specific questions, reach out to us at our email address and we can help you. Something really important to understand, again, particularly with respect to that kind of policy making element is the effect of financing. So if you are borrowing money to purchase an electric vehicle, even though the operating costs are lower, so the operating costs, and we have these kind of like information bubbles throughout. So if you get stuck for information, you can click on any of these. The operating costs is the sum of fuel maintenance, all these things. Is that someone there, sorry? No. And what we can see is if you're paying a lot of money on interest rates for your loans, that can wipe out a lot of the savings due to lower operating costs from a battery electric vehicle. So if I was a policymaker and I was playing with this tool, one of the things that I would hope I would take home is that rather than offering subsidies on the cost of the vehicle and the alternative option might be cheap financing. And so, for example, I'm looking here at my battery electric auction. If I had a low interest rate, we can see that it has a huge effect on the competitiveness. You know, so arguably the interest rate of the loan has a much greater effect on the cost than, you know, the fuel efficiency of the vehicle, or even often the cost of the fuel, you know. And likewise, if I was saving, I was making a commercial decision, so if I wanted to purchase a taxi, maybe I was writing Uber or something like that. If I had a lot of money saved up, and rather than taking it alone, I just paid a higher deposit, we can see that it has a big impact on the costs. So paying for your vehicle in cash can actually save you more money than, for example, buying a more expensive vehicle that has a lower energy requirement. Hopefully a lot of this makes sense. If not, I know we were responded behind time, so I'm happy to jump into the Q&A session right now and fingers crossed is a couple of questions. So I'm maybe going to leave my screen as is or have any of you can tell me what you prefer. Well, I'm happy to start taking some questions now. Yeah, thanks. You can leave it there if you want. Thank you. Maybe Jason or someone, is someone maybe moderating this that they can own new people? It would be great if people could ask a question because I'm not sure that if one person has a question, I'm sure many people do. Yeah. We'll start with the question from Kevin. Okay, thank you. Thank you so much, Annie Kenshin. So my question will be okay. In terms of total cost of ownership, whereby you showed us the graph, the point of parity, can this be the point where you know that now is time whereby a reader can, like us we do a leasing model, point of parity, can it be the point where a reader can be the owner of the bank now and as consider it, it's a point where we should have now the total cost of returns in terms of the way the investment costs. Thank you. I think that's a really good question. And I think the easiest way to think about that crossover point with that point of parity is, is the year in which the costs of the both power trains equal, right. And if one is increasing faster than the other. So, for example, and the costs of a fossil fuel vehicle tend to increase more rapidly than a battery electric because petrol and diesel tend to be more expensive than electricity. And you can say, if I own my electric vehicle for that many years, that's how many years I need to drive it for it to pay itself off. You often hear that term. So basically, at that crossover point every year thereafter, I'm saving money driving an electric vehicle compared to a fossil fuel. I hope that makes sense. So that the parity or the crossover point is the year in which the total cost of ownership is equal. And then if you look at the trends, basically every year after that, I'm saving money compared to the alternative. So what I would do is, for example, if that crossover point didn't happen until year 15, I would probably look at a battery electric vehicle and I would say, and I need to drive this for at least 15 years before I save money compared to petrol. I don't think this car will last that long. The other way to look at it then is if that crossover point is at year four, for example, you can say, OK, my electric vehicle should last at least 10 years. So for six of those 10 years, I'm saving money compared to my fossil fuel vehicle. Does that make sense? I hope it does. Maybe I could share my screen again and it might, you know, seeing an example might be helpful. So I hope people can see again. So what we're looking at here is in year three, you know, the costs of the petrol vehicle become greater than the costs of the battery electric. So for every year after year three, I'm saving money compared to if I bought an electric car. Now, if I drive much fewer miles, you know, that doesn't happen until year six, you know, so the savings will be much, much lower by the end of year 10. And if I if I drive even fewer kilometres, these lines don't intersect. And so I basically am driving enough kilometres in a year to enjoy the benefits of an electric vehicle. And again, guys, if you have any more questions or if that doesn't make sense, I encourage you, number one, to play around with the tool to mess with the different things like costs and number of diameters per year and then come back to us with questions. Yes, yes, yes, yes. Hi, can we take one more question from Brian? Yeah. Yes, I will take the question from Brian. You're muted Brian, so perhaps you need to unmute yourself and then ask aloud. Hello, sorry, Shane, you can hear me now. I can. Thank you. I'm quite a good presentation and I love the tool, though I have one suggestion in future iterations, could you possibly consider incorporating local currency as well? Because the way I look at it, the information is more beneficial to the end user. So they'll have much more confidence when they can compare like for like. Yeah, this, that's a great question and this is something that we grappled with when we were building the tool. And we can install an API that would kind of automatically, I would say, convert from one currency to the next. But the issue we had was kind of finding data for those countries that was quite difficult. Excuse me and then converting say vehicle costs in particular became an issue. So we decided that in order to keep it simple and to make sure that the lessons were not lost. And again, the most important part of this tool is that we understand, like for example, I talked about how favorable financing conditions so lower interest rates higher down payments actually does more to reduce the cost of your electric vehicle. Then for example, if somebody gave me a purchase subsidy or offered me 15% lower fuel costs, you know, so these kind of tradeoffs and policy implications were the main focus of the tool. So we included currency exchanges, which we weren't, you know, very confident about, and the changes in vehicle costs, all this started to make it a little bit more complex. And so we decided not to include it for this version. But if we can think of a way to include currency conversions make it more relevant to the specific users. I think we'll do that in the future. Thank you. So Shane, we have two questions in the question journey box because you can be addressing as well. Okay. Yeah, so I'll just answer it. Sorry, I did poho if I if I'm getting that right or I didn't push you. I'll get your question just a second but how this user asks how long do the batteries of electric cars last and can they be replaced once they failed to hold charge long enough. And this is, you know, what, let's go on again. The short is the batteries don't tend to fail. You know, what we do is we experience a reduction in range over the years. And that is tends to be for first generation cars around seven years, which, you know, when someone's driving an average of 20,000 kilometers per year. It doesn't mean that the car fails. It just means that, you know, if you were to fully charge your electric vehicle and drive it all the way until the battery runs empty, that you'll have covered fewer kilometers than you would have in year one. We can also replace individual cells. So the battery is not just one big solid battery it's made up of lots of individual small batteries. Rather than them all fail at the same time, what tends to happen is individual pieces fail and currently they can be replaced. It's not very, very easy on older electric vehicles, but newer electric vehicles are being manufactured to make that process more easy. And as I said, newer regulations are in place to try and make the life of those batteries even longer. So if we looked at, if you asked me that question seven or eight years ago, and the answer could have been as little as five years, you know, and after five years, the battery would have been, you know, not very good. It would have been difficult to live with, but technology is improving so quickly that, you know, an electric vehicle lasting for 10 years plus is going to be a regular occurrence going forward. I actually didn't get a chance to read the second question. But maybe a little bit more on that is just we expect that you can replace, you'll be able to replace the battery in an electric vehicle somewhat similar to replace the engine in your fossil fuel vehicle. You know, it's the most expensive component. But once you replace it, you have close to a new vehicle. So anyone with a hand up, I can take one more question for sure. I don't want to go too far over time. Hello, good afternoon, everybody. So thanks for the presentation sharing and the tool is just a wonderful tool to actually look at. But I'm at the podium calling from speaking from Nigeria, and I'm actually looking at the context of the tool in application to the multiple variations, you know, that is so frequent that we have the cost of a petrol and also in terms of the local currency exchange rates. You know, yes, advantage might be to those that have stable currency in terms of dollars, but looking at the local currency where we cannot determine prices, most especially for imported products. How best can this guide our actions, you know, in the procurement of batteries, and also is this is a question I've also been asking all the way from Africa, that is the only country in Africa, or any author told us ever use a battery for seven years. How long do we know that this battery is going to last us for seven years. I was looking at the electric vehicle, one of the most important part of it is the battery, and mostly in terms of cost. So I don't know how your tool can actually help or guide us in this in relation to the cost. Thank you. Right, I apologize if I may be misinterpret your question but there's two things here is about that currency and informing decisions. The first tool is primarily a way to compare different power trains. And so whether you're comparing them in US dollars, or you know, South African Rand. And if one is better than the other, and then you convert from US dollars into Rand, for example, one will still be better than the other. So if you, if you start off using this tool as a way to compare, you know, diesel versus petrol hybrid, and you find out that diesel is better in the situation that you models. Well then, when you convert those both into local currency, diesel will still be better, you know, and then if you compare diesel to battery electric you might find that battery electric is better. I totally understand that looking at answers in US dollars might not ring so many bells or it might be difficult. But if you start and try and find which option is best for you and then just convert your your winning option into your local currency. That's maybe a good place to start with respect to how it informs decisions on batteries. So, for sure, the battery cost is is the largest part of the vehicle cost with respect to battery electric vehicles, in the same way that the engine and the drivetrain are the most expensive component of a fossil fuel vehicle. I think really, as an individual purchasing batteries or purchasing a battery electric vehicle, there's not a huge amount you can do to influence those costs. What you can do is look at the cost of the vehicle you're looking at. You can look at the energy efficiency. So how many kilowatt hours per 100 kilometers it uses, use that information to feed into the tool, and then compare us to, you know, your petrol option, which will again have a cost. And have a liters of fuel per 100 kilometers. And by taking those real world values. So, for example, if I looked at, you know, I'm going to say a Ford focus. And I took the values from the electric option and from the petrol option and I fed them into the tool. I can get a good idea of which one would cost me more money over time. And what I do then is we have some other tools coming in the future about life cycle assessments with dig deeper specifically into that battery cost and maybe the life cycle assessment kind of nature of it. So if you want to write your questions down in the email and send it to me, I can give you a more detailed response and maybe point it towards some reports we've done in the past. Thank you, Shane. Would you be okay because I see that there are some more open questions but we are a bit late schedule so would you mind maybe questions you find appropriate and you can answer answering them written in the Q&A box. Sounds good. Okay, thanks very much. Thank you guys. Thank you Shane for the great presentation and also for the questions to all of our audience members. So now I will share my screen. Just bear with me for a second. Okay. Can you see my screen? There. Can you see it? Perfect. So as said before, the same format as Shane had, I will present a brief overview of the tool and some background of some important topics on the aspect of EV electric vehicle charging and grid integration. So if you have a pressing question that you think is making you very difficult to understand and follow the rest of the presentation, please raise your hand but otherwise please write the questions in the Q&A box and I will answer them after I finish my demonstration. So yeah, thanks again for joining today. As I will say, my name is Javier Jorqueraco-Pierre. I'm an energy analyst at the Renewable Integration and Security Electricity Unit and I will present to you the electric vehicle charging and grid integration tool which was developed under the collaboration of the International Energy Agency with the Global Development Facility Project, specifically under the working group 4. And I also left there my email so that you can contact me as in case of any question or also if you have any suggestion or idea that you think would be good to improve this tool. So the other one for this presentation is first I will discuss a bit about grid integration of electric vehicles based on our report, our team published in 2022 which is a manual for policymakers on how to better make use of the opportunities that the grid integration schemes provide. Second I will give some context of the electric vehicle charging and grid integration tool and I will also do a live demonstration of it and then I will follow suit with the questions and answers session. So first, a bit about what the goal of this manual is and also why grid integration is an important topic that we should be talking about regardless of whether a country or even on a sub-national level, a city, if it has a lot or very little amount of opportunities I think throughout all of the stages of development this is very important to take into account. So the goal with this report that was the manual for policymakers and grid integration of electric vehicles was to help policymakers to make sense of all the information around grid integration of electric vehicles and also to create a step by step guide that can also help policymakers and also the broader public to understand how to prioritize policies according to their own local context. We think this can be useful to countries in all stages of electric vehicle deployment, regardless if they have just a couple of electric vehicles in their fleet or already a large scale deployment. And that's why we think this is a very important report to present to you today as context. So grid integration can be understood as the process of adapting power system operations to accommodate the entry of new energy technologies such as electric vehicles, always trying to maintain cost effective operation that is to make sure that they are integrated to the power system, minimizing the costs as much as possible. So why is it important to ensure an adequate integration? This is because excessive demand of electricity can cause several issues, I will name just a couple. For example, we could have power outages or blackouts in certain parts of the network, if the electricity demand at a specific moment is too much for the local network infrastructure to manage to handle. Second, also we see that potentially because of additional electricity demand costs by electric vehicle charging, this could translate into a possibly increased power generation from fossil fuel based plants such as a coal fired power plant. This would lead, in many cases, the electricity costs to increase in that system, and also in turn it could lead to higher carbon dioxide CO2 emissions. All of this can have a negative impacts on both the system but also very importantly on consumers of this area. So these are some reasons why we believe that grid integration is a very important topic that we should be thinking very carefully and working doing it properly. So in the report, we have a summary of four steps that policymakers should follow to successfully integrate electric vehicle storage systems. First, one of the steps is for the electric mobility transition. This relates to engage electric mobility stakeholders, so not only ministries of energy should be involved but also for example all of the ministries that oversee a lot of the government agencies that oversee infrastructure development, like for example in cities or even at a national level, also transport entities should be involved. And that way, through all of the collaboration and information sharing of all stakeholders, the silos can be broken, both in planning and also in policy making. A second aspect is very important, regardless as I was saying if there's little or a lot of electric vehicles to assess the power system impacts that electric vehicles could have. So first, many countries have defined an electric mobility strategy. For example, in many cases they set targets of how many electric buses or electric cars they could have in a certain year. And this can give an idea of where the country is heading to, under which idea that the country can prepare for. Then also the country can gather data and develop insights, for example, collect data to understand what are the driving patterns of different type of users, for example, truck drivers or also a private car drivers. And combining all of this, the countries can assess the grid impacts on their various mobility scenarios. For example, they could do several scenarios to assess. If there, what happens to the grid, if there's more, like let's say 1000 electric buses in a city or what happens if there's 2000 and 1000, and what these differences mean in terms of planning. Third, policy makers can deploy measures for grid integration. For example, they can ensure to accommodate all types of charging solutions. For example, a smart charging of different ways. I will explain a bit more on this later. But the idea that we suggest is that whenever possible, they should always aim to deploy smarter or more flexible ways of charging electric vehicles. Then, policy makers can also facilitate aggregation by enforcing standards and interoperability, for example, ensuring that the type of charger, the adapter is common so that the same user can use several different charging locations to charge their vehicle. Also to value the flexibility of electric vehicles in terms of flexibility they can provide, for example, by changing when they charge and therefore modifying the demand of the system. And also, policy makers could benefit from, for example, coordinating EV charging with renewable generation and incentivizing smart readiness. For example, making sure that the technologies to facilitate smart charging are in place increasingly in the country. And lastly, we think that policy makers could also benefit from improving planning practices, for example, conducting proactive grid planning that is not waiting to see when a several large fleet of electric vehicles connect, but rather to try to anticipate when this could happen and to which extent. And also to fully reflect the value of electric vehicle charging by, as I was saying, trying to recognize the value, for example, of flexible charging under various smart charging schemes. So also very important to mention is that continuing to the point that every country will have a bit of a different starting point and also different opportunities and challenges. So in the estimates we see that various countries have widely different fleets. Nowadays of all vehicles including electric vehicles and non-electric vehicles, but also in the electric vehicle fleet specifically they also show differences. And also we see that in Vietnam, a large share of the vehicles, both in all vehicles and also only electric vehicles correspond to two wheelers. And then the minority of the other vehicles, the rest of the vehicles are just the minority over the total share. For example, we see in Africa, both in Africa and South Africa, we see that a passenger light duty vehicles or simply cars. They play a bigger role than in other countries such as India and Vietnam. With also some role played, like for example, two wheelers such as scooters or motorcycles, for example. And then also there is a share of medium and heavy duty trucks and vans. Now talking about EVs, at least this is an estimate that we have for a recent year. In the case of Africa, we see that despite that we see that in total vehicles, there's a more distributed share between different types. In the case of EVs, the deployment up to this day has been mostly regarding cars and also in some cases to vans, which is light commercial vehicles. So we see at least temporarily a difference there and a shift compared to the overall fleet, which also would include non EVs. So this is important because different vehicle types and segments imply different opportunities for electric vehicle deployment and charging solutions. And therefore, it's very important for policymakers to be aware of where the country starts from, for example, the thinking of the all vehicles segment. But then also to combine that information with understanding what is the current status of electric vehicles to have an idea of what actions should be carried out now. But also how the EV electric vehicle fleet could evolve in the near and longer term. So I will go just very quickly with this. In this report we provided a great integration of electric vehicles to help policymakers prioritize the measures to deploy it. And this is based on the electric vehicles that you currently have, your network conditions and also how the policymakers would like them to interact. So, for example, we see that some countries could be in phase one where the current electric vehicle fleet maybe is not enough to cause a significant impact in the power system at a local or national level, for example. So, in that phase, for example, countries could encourage a higher vehicle uptake through incentives and also through public electric vehicle charging stations deployment and then it could be good that countries coordinate where to allocate these charging stations, both on the demand for in terms of transport configuration, but also considering the capacities of the distribution. Because, for example, in some cases the without even without electric vehicles in some cases that we could be already very stressed. So it's very important that policymakers take into account, which are the points that could sustain even more demand if electric vehicles were to charge there. Then a phase two would be when countries start to see a more noticeable demand of electricity due to electric vehicle charging, but still without a big flexibility demand of electricity. So this is for example what we see in Norway where we already see that electric vehicles can be impacting more the grid. But still because these countries have a lot of renewables and a lot of flexibility in their system, this is not yet affecting too much. So in that case, some passive measures, namely measures that the users themselves can take, it's not the grid forcing them to do. Such as, for example, time of use tariffs, which define a different price of electricity through every hour, for example, they can help to try to accommodate EV charging on the moments of the day in which it could be best for the network. And then we have a phase three and four, which relates to places in which countries could already have a more significant electricity demand due to electric vehicle charging. At the same time, in these cases, there could be measures in place to have that electricity demand because of charging being more flexible. So in this case, if we could see, for example, that countries could begin to implement some active measures, for example, active refers to measures where the charging is controlled. So there's an agreement to, for example, so the users that the system of charging to control when they charge. So in this case, this can be beneficial to try to match the charging to whenever the devour system demand is lower and therefore to reduce the gain. All of these recommendations, you can read them in more detail in the report, which is called the grid integration of electric vehicles and websites. So I will now, before I go to the tool, I will have a mental question for you. So please go to mental.com and use the code that I'm showing there. Okay, so the question is the global electric vehicle electricity demand as of 2022 equals to total national electricity consumption of which of these four options. Okay, so we have some people that say it's eight times Ethiopia, which would be 110 terawatt hours per year. Some people say it could be same as the United Kingdom, 300 terawatt hours. And at least until now, no person thinks it's the same national consumption. Well, now one person thinks that it's equal to Japan. Up to now, nobody thinks it's one third of South African demand. I will give a bit of time for you to reply and then I will reveal the answer to this question. Okay, yeah, due to the time, I will just answer the question now. So actually the majority here of the respondents got it right. Maybe the Africa reference because we put an African country as the correct answer gave us away, but yeah, according to estimates of 2022, the global electricity demand due to electric vehicle charging amounted to 110 terawatt hours, which is eight times the demand of Ethiopia. Okay, now I will continue with the TV charging tool and I will give some context and I will also do it. Let me explain the motivation. The idea of this tool is to be a companion of the manual I just explained about, and the idea of this tool is to in practice help policy makers, but also for example pilot project developers, general public academics, industry members and whoever could be interested to make the link between electric vehicles and also what electricity demand they could have. And this could enable whoever is using this tool to assess the impact of electric vehicles on power systems. So this tool has three main goals and motivations. The first one, which is the base model would be to assess the impact of charging on the power system. And this is done computing a simulation of the electric vehicle charging behavior, which has as an output the weekly electric vehicle charging demand profile. And third models actually were under development and for this event are already available in our website. So you can also use and simulate with them whenever you want. Number two, it refers to assessing the effects of measures for mitigating the electric vehicle charging impacts. So basically, with this we try to understand which methods we would use to reduce the impact of, for example, peaks of electricity demand created by electric vehicle charging. So this is done by a simulation of different profiles when we use managed or we could also say smarter charging. And the third model, which as I was saying was also just released in the tool is aiming to calculate or estimate the CO2 emissions that are directly attributable to electric vehicle charging. So basically, the tool simulates an electricity mix or a power system and then with that, and with the electricity demand profile estimated because of the electric vehicle fleet, it calculates which are the emissions that are specifically due to the charging of electric vehicles. So now I will go to the tool and show you a first through the results, what it gives and then I will show you how to get there and also to show a lot of examples. Here. Okay. As I was saying what we simulate with this tool is a weekly electricity demand profile, and this goes in five minute intervals so it has a very high resolution so that you can have a lot of detail in your simulation. And this shows what demand is caused directly by electric vehicle charging. So here I am in the link that I showed but also you can Google the electric vehicle charging and grid integration tool and you will find the here this link in the website. So here I'm starting with the results tab just to show you where we will get that and then as I was saying I will show you how to get there. So this tool shows the weekly demand profile. This can be seen for example in several charging locations. So for example we can have a charging location that relates to charging at the workplace, charging at home, charging at the roadside for example in a public parking lot that has charges. So this can allow the users to see for example the hourly profile by location and also if you have different fleets you can see it by segment here in this tab. You can see the emissions there which I will show at the last bit of my presentation. And also you can assess indicators such as for example the maximum peak in that week of power demand in this case it will be 101 kilowatts. The average demand over the week how much energy it consumes over the week and an estimate based on that for the year. And you can also here download the data if you want to do some further analysis with it. That's also a possibility. With this you can make several use cases for several stakeholders for example potential users can be policymakers and utilities who would like to know whether the grids in capacity or the generation capacity needs any upgrade. For example in the transformer capacity or even in the power plant capacity to accommodate a certain number of vehicles. And policymakers and academics can also study trade offs between different charging schemes and fleet behavior. Also for example pilot project developers can use it to provide a preliminary assessment of electricity demand curves that could be associated to the test system and that way they could have an idea of if the network location where they plan to allocate the charging station is enough has enough capacity for their fleet or if they maybe could need to ask for an upgrade in for example the transformer capacity in that. I'll go back to this slide. So I will first begin with some context and then I will show a bit more how to get to that resolution. There are several types of charging locations and I will go through them just very quickly for a reference. For example you would have charging locations at residential neighborhoods, namely home charging. If you have a fleet of buses or truck, you could also have a depot where you normally leave these vehicles. You know what we call depot charging and then for example if you're moving from one city to the other or for example in a gas station that also has electric chargers. You would have what we call en route charging which normally has higher power because the people stop there very quickly just to charge and continue so it normally has higher power than at home. For example you can also do battery swapping in electric scooters that also is a possibility. You can also have workplace charging for example just if you happen to go to your workplace with a car. Some workplaces can also have chargers in there and then you can leave your car charging while you work and then pick it up when you are done with work. So these are just some examples that show that charging can be done at several locations and these locations many times can pose different challenges to the grid. And I will go in more detail to that in next department presentation. So many factors influence the profile of demand of electric vehicles on the grid. In terms of grid impacts we are mostly concerned about the amount of power that the electric vehicle charging demands. So we could see that for example en route charging as I was saying is many times the one with the highest power as it draws the highest power from the system it would potentially have the highest impact. Whereas some other locations that normally have a lower charging rates such as for example workplace or destination charging for example they normally have a lower. So it's very important for policymakers and as I was saying whatever user is interested to simulate the demand to be aware of these impacts in order to plan for their system in the best way possible. I will go back to the tool and show you an example of 100 buses. So this is being inspired by many cities in the world including some in Africa that are either planning or actually already have begun deploying some electric buses in their area. So, as I was saying this is a tool that you can find the website or just refresh to make a clean start. So basically I will first show the task. Here you have the tab that is called fleet. Here you can put whatever label you want and just write bus. Then I have to select the bus here I can select the stock just basically the size of the fleet 100. And normally for bus you would select private driving here in the bottom. There's other parameters such as average battery capacity and energy consumption and average weekday driving and week and driving that you can modify to make it suit the best way possible to your local context. By the way you also have here a full technical note explaining how to use the tool and all of the features it has. So, okay, we have the fleet, I will just have a fleet of 100 buses then I go to behavior profiles. This has for example information of the availability of charging solutions for the fleet. So for example here we would have the availability in weekdays and also weekends of 90% of depot charging in the case for buses. So this means that normally 90% of the bus drivers will access to this in a certain moment. And it's the same way for the other locations that you can change both the availability and also the default power that if you want to modify to a different rate. You can also for example here all of these characteristics have values by default but you can also. For example here you can define kind of an average arrival time of the bus with some variance. For example at 8pm and normally stays 12 hours but you can modify this for weekdays as much as you like to make it best suit your local context. So now on the results. So here we can see the effect that 10 buses sorry 100 buses could have. So for example we can see them by segment of my location. There is only one segment here. And so I will just explain this one. Basically we have this profile so 100 buses could mean potentially a peak demand of almost 2000 kilowatts or two megawatts. So we need to be a size of the demand of electricity and we can see that normally the charging tends to happen more at night, which is when the buses come back. The depot on average. We charge and also just to be deployed there until they leave again to their driving patterns in the next day. So here as I was saying, you can download the data you can access it here and you can also see several indicators here on the right in the upper right corner. Now I will continue with many cases in Africa. There's the share of electric vehicles is high for cars. So I will do a start again of the tool and I will now do a fleet of cars. So basically here I select vehicle type light duty vehicle, which refers to cars. Then I select just 1000 I will leave it default and all of the other parameters will be left default. So now I will go to the results and show the difference. So we can see here that as opposed to the buses and normally people when they come back with the car they come back from work so around six or seven. But again, you can modify this but by default they come more or less by six or seven back to their homes. So in the bus case, we would see that the charging had a peak around eight or nine. But in this case because of the behavior in this bit of cars would have a peak of the charging that is a bit earlier in the day. And this could also potentially be an issue for the system operators because in these both cases that have showed the peaks are at seven or onwards which is also when normally for example solar PV generation is not there. So if we would have a big deployment of electric vehicles with this demand profile, we could maybe have an extra stress in the system because at those times it could be possible that there's no solar photovoltaic generation available. So in that case it could be necessary to a fire or increase the power output of for example a coal power plant. And this could mean more emissions and a higher price, which are of course effects that we would like to avoid. Now as I was saying, you can also with this tool model overlap overlapping or different fleets combined together. So for example, you can combine this 1000 cars with the original buses I showed. So for example here, we can have a hundred buses driving and then we go to the results. And then what we see here is that if we go to the by segment part, we can see that. Basically, see that what I was describing that normally cars tend to have a peak earlier and then buses later and then both of them combined could have a significant total demand that would put the system into stress. You can also, for example, here in this my location tab, see, for example, for the total combined fleet where this charging is taking place. Here we see that most of this most of it is in the case of cars at home, and in the case of buses in their depot, but also there is some level here in dark blue of charging in the workplace. Which is, as you can see closer to midday, more or less, and also some occasional charging in other places, for example, roadside charging or namely a public parking lot. I'll go back to presentation a bit to give context on the second model. It's about implementing and a man of store more flexible charging scheme. This is because as policymakers and overall public would be interested to go from challenges of great impacts to opportunities that can be opened by flexible or managed charging. So, for example, we see that if we have enough enough systems and also architectures in place we could avoid having such a big impact in some distribution networks. And if we, for example, can in somehow decrease the peaks of electricity demand because of charging or also maybe potentially move them to different times of the day in which they could have a lower impact on the grid. So, first I will explain the concept of managed charging as opposed to unmatched here and please here look at the upper right corner of my slide. So unmanaged charging would refer in this case to the case in which you basically just arrived with your people, you connected to the charging station. And regardless of if you will stay one full day, the charging power is at maximum connected to your people until the battery is full and then it just stops. So that would be the unmanaged case. In this case, on the other hand, is a case in which the because of various schemes we could use and the charging tries to take advantage of, for example, if you leave the vehicle there a long time. So, for example, if you leave a long time the vehicle there in the parking lots by using less power, but for more time, you could in the end have the same amount of energy so your battery could still be charged. If you leave it in a longer time with low power, then in that case you would stress the network, the electricity network less. So this is, for example, what we call balance charging is basically having a lower average charging power for the whole time in which you leave the vehicle and that way the charging power is less. Therefore, the impact on the grid is lower than if you just connect it and have it at full power, even if you wouldn't need that charging speed depending on the case. That is one way of managed or smart charging that would be the balanced case in which you basically for the whole time in which you leave the vehicle, you have a lower charging power utilized, but you can also use some other measures such as, for example, time of use, which is basically that the electric vehicle would see a different price of electricity each hour and therefore it would respond to that by moving the charging whenever possible to a lower price time. And also we could have what we call vehicle to grid or V1G, in which case instead of our price and each hour, the charging is influenced by the level of electricity demand in the whole system. So the charging there would try to accommodate to move as much as possible to times in which the load of the power system or the demand of electricity of the whole power system is the lowest to try to minimize the total impact of electric vehicle charging. So now I will go back to my example of 1000 cars and show the impact of balance. So I will again just reset. So here, cars. Okay, so this is the base case. We see that the peak is more or less 960 kilowatts. And this is unmanaged by default the tool provides a managed charging. And then I can activate the balanced version, which is one of the managed strategies here in the advanced options. If you remember, I was showing that the peak without balance charging was almost 1000 kilowatts. Here you see that with balance with decrease the peaks to less than 600 kilowatts. And with this the profile of charging is on average a bit higher probably, or at least on the lower levels are a bit higher than in the other case, but the highest point of demand is not as high and that can help to decrease the electricity demand. In peak times and therefore can help decrease the impact on the power grid. Now, I will show what happens if we use time of use types. So here in the same tab, advanced options, you can go to the time of use types here. Yeah, sorry, I just had an issue with my computer. I will be back just in a sec. Yeah, so about that, I had an issue with my computer, but I'm here. I will share my screen again. Okay, so now I will go back to what I was showing here. So basically, some of your styles. So yeah, we have here as an input, the daily tariff structure that you can modify yourself. For example, you can grab this and modify either one specific point of the daily tariff schedule, or also you can grab this in several cases, for example, like this. And that way you can also yourself modify what kind of profile is an input for this kind of scheme. So we have here that the price is always that nighttime when there's less demand, and then it begins to increase reaching a peak around after four or five p.m. until more or less 10 p.m. when it begins to decrease again. So let's see what impact this has on the chart. What we see here is a second, bring this back to cars. So what we see here is an interesting impact. We see that before, without time of use, there is for cars. There was a peak around seven or eight, but because this tariff has the lowest point here after 9 p.m., we see that there is a shift in this case on the results, which go to the result that the peak now instead of at 6 or 7 p.m. With this kind of charging scheme is around midnight, which is where the price is lowest. So this shows that in practice, the charging profile can in practice be influenced by the time of use tariff. So with this you can simulate what kind of impact all of these different daily or hourly prices you can set could affect the charging profile. Now we'll also show another case, which is the B1G, which is basically active control with any directional charging vehicle to green. So basically, here the signal that the charging response to is not the price, but the demand of the system. In this case, if you go to the Power Grid tab, if you go down here, you see the power system demand curve by each hour of a week. You can also modify this either by dragging this or by updating a file that would have the demand of your own area of interest. So then with this, this is the profile that will influence the signal that will be given to the charging in this case of the B1G scheme. So basically what we see here is that as normally happens, the demand is lowest here in the evenings and nights of the weekends. So what we will see is normally a shift that will happen and we will have a higher peaks in the weekends than on the week. Yes. So here we can see that the demand, the charging behavior in this case because of this charging scheme is effectively influenced by when the non electric vehicle demand is highest or lowest actually. Because under this scheme, the aim is to reduce the total, which is the non electric vehicle plus electric vehicle demand. So in this case, as the demand of the rest of the system is already lower in these moments of the weekend on the evenings and nights, then this charging schemes accommodate the demand to the points whenever possible to the points in which the system demand is lowest. Okay, I will go back to my presentation in just a second. Okay, yeah, here we are back. So this last model is about, and it's also as I was saying available in the tool is about, it's about estimating the CO2 emissions directly achievable or related to EV charging. So first I will explain the logic of this and then I will show it in the tool so that you're going to have an idea of how it works. So, in this case, how does the tool estimate the emissions? The idea of the tool in this case is to estimate the emissions that are directly due to electric vehicle charging and not because of any other reason. Now, that's the tool model that basically this is done. Calculating first the net load, which is basically the total demand minus the renewable generation, for example solar photovoltaic or wind power. And so that one is calculated in the case without and also in the case with electric vehicle charging. Then for both cases, the tool simulates what is called an economic dispatch or basically an algorithm to operate a simplified power system to see which plants would be operating to meet that net load. And then by comparing the emissions in the case with and in the case without electric vehicle charging. Then the tool comes up with an estimate of what are the carbon dioxide emissions that are directly because of charging electric vehicles. So basically, here on the right we see a small diagram that's here in the lightning sign. This shows the cumulative power sum. Basically the total demand at that moment. And then the money sign, it would be the energy price of each power plant. So basically, what it shows is that in some cases, the higher the demand, it could be necessary depending on the power system to fire an additional power plant that could be more expensive than the previous one. So because of this, having more demand of electricity could result many times into having higher both emissions because of firing more emitting plants but also higher prices because sometimes just to meet a bit of extra demand you cannot generate enough with the current active needs. In some of these cases, you may have to turn on an additional plant that could be more expensive and also have a more CO2 emissions. So I will go back to the tool here. And I will after this, I will take all your questions and then go to that. So, okay, I will just reset it to make a clean start again. Here, I will continue as always with the cars example. So, and it is 1000 1000 cars. I will not use any smart charging I will just illustrate how the emissions calculations work. So, basically here, and I will show that you can define here and accommodate to your specific case in an area. It's the same because the emissions depend directly on the electricity mix, which plants the area has. Here you can define, for example, the prices of each generation type, its capacity and what emissions it produces per energy unit generated and so on. In this case, you can modify this to have the most accurate estimate possible that is also suited to the area you are modeling, whether if it's a small country, a big country, a region or whatever that is in their intention to model. So here, basically, then we'll just go to results and go to the emissions tab. So with this, and this shows the total emissions including a little vehicles. And here we see, I mean, we can also if you want we can show the non EV emissions, which in the default system are a lot higher than the emissions we have by this. So, focusing on the emissions directly related to an electric vehicles. We also have here weekly curve that has the same resolution as for the electricity. You can hear, download the data, you can see which is the estimate of a marginal EV electric vehicle emissions, because of my week. And also you can with that provide an estimate of for the best system that you are modeling. How much emissions. This could mean in a whole year if we assume that this weekly profile holds for the whole year. You can effectively estimate the emissions because of the little charging. And therefore, if you combine it with all of the other features of the tool. For example, different value schemes or different kinds of it or behaviors, you can assess tradeoffs between different measures in terms of emissions and also in terms of electricity demand, both of which provide results that can be seen in charts. And also that can be downloaded as data files for any user please interested to assess this results. So with that, and again apologies for technical issues, I will finish my live demo and I will go on to answer the questions you have in the Q&A. Okay, I have here the first question would be, what's the impact of integrating renewables, particularly solar on the grid to manage EV charging demand. So, I think here, if I understood the question correctly, and I think this could be seen in a different way. So, and actually, what we have shown in our analysis and our recommendation is that you can, if you have flexible charging in place, you can actually sometimes integrate more. than renewables, depending on the day. Why is this, this is because for example in some power systems we have seen in the world. What happens sometimes is this excess number generation for example because of wind or solar photovoltaic generation being too high at times. And sometimes this generation is curtailed basically the system cannot take that extra generation and some of the output is lost. And sometimes if this happens, having flexible demand would mean that if you are aware that the generation is very high at some point the availability of solar photovoltaic resource is very high at some point. Then you could, if you have flexibility on the charging side, you could increase or shift the charging of your related vehicle to those moments, and that way you could avoid that electricity being lost. So in that case, of course, other solutions would include battery storage, but in the context we're looking at now which is electric vehicle charging. If you have that in place, you could actually increase the integration of variable renewables. If you are able to allocate that demand to a time of the day in which the renewable generation is higher or at its highest. Thank you. I also have a question here that is about an option about geothermal energy generation. I will just show a bit more that the part of the tool where you can define your generation fleet. Here, this is just a default combination of power plants. So by default the system has 250 megawatts of cold power generation with a certain price that you don't modify and also some emissions. It has some variability because then the simulation tool generates a random variable to modify and generate different smaller plants to simulate a bit more, a smaller system that could have different plants with slightly different prices and slightly different emissions factors. So by default the tool comes with a cold and oil, a gas, a solar PV, wind onshore and a hydro plant. But you can also modify this to your own system by for example deleting any of these plants. You can delete the hydro, for example, you can modify the type. These types of coal, oil, gas, combined cycle of gas, for example, and nuclear solar PV, wind and hydro. We don't have yet specifically a bioenergy plant, although you could maybe try to replicate it by modifying the price and the emissions factor of the gas. So definitely this is a good suggestion so we will see in the future if we can also add a bioenergy type of plant so that you can also add it if it reflects better your system. As I was saying I think you could do a quite decent approximation of that by modifying the price and the emissions per energy generated accordingly to make it follow as best as possible the bioenergy plant. Okay so we also have a question similar to the question that was directed to Shane on the tool he presented that is about if there's any possibility to add other currencies to the tool. In this case, my answer will be similar. So the idea of this is to understand trade offs. So, basically proportionally, a power plant is a bit more expensive than the other one, for example now that we are talking about the electricity mix simulation and the emissions. So regardless of the currency, if one plant is more expensive than the other one, if the algorithm needs to see which plant it will use to meet that extra demand, it will always go for the cheaper one. So, and so in those terms the algorithm shouldn't be affected by the currency you use. Thank you for the question. I hope I answered it but please if I didn't answer it enough and you can put another question and I will do my best. Here, we also have another question that says whether it's possible to feed the data from the tool to a solar modeling tool such as Homer and I am not personally familiar with that tool you mentioned but what you can do as I was showing with the tool is you can get the results and basically you can download a data CSV files. So, what you can do is to manually set, for example, if you want to simulate several cases or scenarios, you can modify and do as many simulations as you want, download all of those data files of the results, for example by segment or by location and then with that you can simulate. If what you want is to input data, in this cases, for example, what we have currently available until now is to modify either here through the use of this dragging function I showed you, for example, you can modify here the demand or uploading a file of the demand and that here you can see like the simulation of the generation mix. So if you would like to feed the tool with data, for example, of the solar foldable type generation profile, that is not yet available, there is a function that we are thinking of deploying and because we understand that it will give the users and still even more flexibility to modify the results. But up to now, you can only use the default profile that we have here for solar PV generation, which you can use, you can check here if you select all of the ones you can just leave the profile here. So this default profile and it begins to provide energy of solar PV more or less at 7am and then it reaches its peak around midday and then it goes back down more or less at 5.30 or 6pm. So we chose this profile because we thought it was representative enough of many countries that have solar PV generation. But we definitely are working and we plan at some point in the future to allow users to also modify that profile so that they can better reflect the local context of the availability of electricity from solar foldable type. Okay, I will now go on with the other questions. Okay, here I think the last question that I have to answer up to now based on the questions I see in the Q&A is whether most grid and charging stations systems are equipped for B1G to be implemented and if not what and when it will take. Basically, this is not always the case. This is because the infrastructure has to be in place so the charging stations need to have a communication protocols available in their equipment. You can read in our report about grid integration of electric vehicles, the policy manual report I mentioned. You can read there are some examples we list. But so up to this point, just a summary, this is not something that is very widespread or implemented. This is in many cases on the piloting phase, on the demonstration phase of this B1G or active grid control charging scheme. So this is not yet available at scale in many cases. So if you want to see what is the progress, for example, on these pilot projects, I would suggest to check the report. And then you can see some specific examples of where this has been done and what the key lessons learned are and also how these pilots performed. Okay, I don't see any more open questions that I would reply now. So please be aware that if there's any questions that you had that we didn't reply today or maybe a question that you'll come up later. Feel free to email us as Shane and myself were showing in the case of the working group where Shane is participating. The email is jeff.immobility.wg1.ie.org. And in the case of the working group that is related to PV charging, this is gef.immobility.wg4.ie.org. So with that, please feel free to give us any feedback or send us any questions you may have and we will be happy to answer it. Okay, perfect. Yeah, so I think after checking all the Q&A questions, I would like again to thank all of you for your participation in this event. I would like to thank also all of my colleagues here at the IA side who have been helping me both prepare the new features of the tool. And also they were colleagues that helped in organizing this event. And also Anika Bergeri and all of her colleagues who helped us from the Africa platform to prepare this event and to ensure that it reached all of the possible stakeholders that are interested in this topic. So we are very happy to have had your participation today. We had over 100 participants, which is something that makes us very happy and very proud. We are looking forward to having more collaboration with you. Just a few notes before closing, so we will send you a survey to get feedback from this event, which will come later. And also if you have any material on electric vehicle developments that you would like to share with us, please feel free to send it to us through the emails that we share. Also lastly, we will say update, upload this recording to the website and you can find this event page on the IA website, which is www.iea.org. There you can find not only this event, but also all of the other reports and events and analysis we have produced at the IA, which we will be very happy to have you check so that you can be informed of our work. So with that, I would like to thank you again for your participation and your questions today. And just let me finish by saying that we would love to see you again in future events. So many thanks and have a great day.