Hybrid Energy Systems of the Future
Good morning everyone. Thank you for joining today's webinar. We're going to go ahead and get started. Thank you for attending today's webinar. It's the "Hybrid Energy System in the Future." My name is Alex and I'm excited to be part of NREL's ongoing Wind Energy Science Leadership series of webinars that includes an ongoing series of educational webinars that include presentations and discussions on wind energy-related topics, featuring speakers from the laboratory, strategic partners, and the energy industry. These webinars will discuss the challenges facing wind energy and the pathway forward for making wind one of the most prevalent energy sources of the future. If you haven't had an opportunity to
see the myriad of presentations that we've done over the past many, many months please look on our website and you'll be able to see some upcoming webinars in the next few months. Today you will learn about hybrid energy systems research, where NREL assesses the optimal design and operation for the deployment of hybrid energy plants, seeking to reduce costs and increase penetration by addressing technical, logistical and economic challenges. Before we begin: today's webinar will be recorded and available on demand and will be posted on NREL's website. Please mute your lines and turn off your cameras if you're not speaking. Next, we encourage you to use this app feature or raise your hand to ask questions at the end. We will be answering those questions, and if we do not get to those we will reach out to you after the webinar concludes.
And finally: I would like to introduce Paul Veers, NREL's chief engineer and senior research fellow, to say a few words before we begin. Paul? >>Paul: Thanks, Alex. Just want to thank the presenters today, who have put a lot of work into giving you a great webinar and point back to the origins of this series that Alex has helped us put together. We wanted to get a series that looked back to an IEA event, the Grand Vision of Energy Workshop that was held, and a subsequent article in Science magazine that looked at the grand challenges of wind energy. The recognition is that wind has come a long way. It's a very successful business;
it's now supplying five percent of the global electricity demand. But there is an expectation that as we move into a renewable energies future wind energy is going to be expected to do much more. It's going to be a basis for the bulk energy supply of the global electrical system. And it's going to be expected to supply perhaps half of all the electricity that we're generating around the world and that we're using. So, it's an order of magnitude change from where we are five percent to get to 50 percent, and there are significant research needs that are going to have to be addressed before we're going to make that kind of a transition, that order of magnitude transition.
So, in the grand challenges we identified three fundamental areas that this picture in front of us kind of illustrates. We have an understanding of the atmosphere, the basic fuel of the system. That is really inadequate for fine-tuning and controlling the plants that we have. The machines that we're building are now so large that the manufacturing processes and the aeroelastic behavior of these flexible rotating machines is pushing the edges of where we are already. But the fundamental reality of the grid, of the need for a grid to be supplied by wind and by a variable resource that is driven by the weather is going to change the way that we design wind turbines and design wind plants in the future. So, the system itself is critically important.
And I think the events are recently in Texas, where we had a severe weather event that caused every form of electrical generation to have issues at some point, and to be unavailable to deliver is a warning and an example of where systems that are expected to behave in one way may be forced to deliver in very difficult situations. And in the future, if we're pushing more and more toward renewable, toward wind and solar and other hybrid plant issues, we're going to have to have a system that can inherently deal with periods of generation scarcity due to weather-driven events: overcast weather, calm weather, and that system that is built to be resilient with those kind of changes ought to be a system that is more resilient to the extremes of a case like we had in Texas just earlier this month. So, with that I'd like to turn it over to the experts and hear about the energy system research that's going on on these hybrid systems. Our first speaker is Jen King. Jen, if you want to turn on your camera and take it from here.
>>Jen: Great. Thank you, Paul, and thank you for the introduction. Today I will be talking about autonomous energy systems. I'm a researcher here at NREL, mostly in controls and optimization. I've been working on this project for the past three years and have been accompanied by a huge team at NREL. It's so big we can't list them all, but they come from many of the different centers across NREL. So this is a huge, crosscutting team.
Before I get started, I want to provide further detail about what this webinar is going to be about and what this topic's going to be about. In particular this talk is going to talk about the integration of hybrid technologies for generation and demand. It's kind of both sides of the equation, including wind. These technologies work together to ensure the stability of the grid in high renewable penetration scenarios. And the rest of this webinar will emphasize the generation side of things, in particular, demonstrating that advanced design and control of generation specifically focused on utility scale wind. So what we'll be talking about: the system level to start. And we'll kind of start drilling down
into the generation technologies. On the power system side of things, the way the current power system operates is it's a large, centrally-operating system. And our future grid is going to look quite different, especially as we have increasing levels of wind and solar that are variable and power-electronics based, which pose from problems for our current grid.
They're going to use more communications, controls, data, etc. that still need to be developed, and of course that brings along cybersecurity issues. There's going to be other distributive technologies like EVs, grid-efficient buildings, distributed storage, etc. I'll talk a little bit about those and touch on those. There's
interdependencies between all of these that are linked together through the electricity grid. So let's touch on the grid as well. And then we'll talk about how this is becoming more distributed and more complex to operate, and that's really the crux of that this project has been about. Just drilling into this a little bit further: is the grid getting too complex to control? As we're adding more devices to the system we can't control this from a central perspective. The utility can't tell each residential building to turn on their nest at this particular time; we need a distributed approach; central control won't work anymore. So what we're working towards is the distributed hierarchical control that can control millions of controllable devices from EVs, smart homes, PV, wind, both at the distribution level and at the transmission level.
And so just reiterating that: we're talking about technologies working together including grid interactive buildings, vehicles and mobility, advanced wind plants and advanced solar plants. We're having all of these technologies come together and work together in order to balance both sides of the equation, both generation and demand. And so what we defined as our project objective was to optimize and control a massively deployed distributed energy resource system in real time. And we chose the Bay Area because this is a very complex system with more than 10 million electric nodes at the distribution level, millions of customers, so we're talking about millions of controllable devices. And nobody knows how to do this.
What we need in order to address some of the challenges that we're facing with this problem is that we need it to be distributed, we mean that we need it to be fast enough to operate in real time. We can't have every device talking to one central location anymore. We need it to be broken up a little bit. It needs to be scalable, and it needs to be data aware. We need to be able to take advantage of data that's coming in at different time intervals; we need to be aware of cybersecurity issues, etc. And again, this is happening at the transmission,
distribution, and home levels, so across the whole spectrum. So I'll get us started here in talking about how we are addressing some of these challenges at the wind plant level. What you'll see is throughout the rest of this presentation is kind of some synergies between all of these hexagons. You can solve a lot of the problems for each individual domain from a controls perspective in a similar way. And we use the wind plant example as good example to show why that is.
So one of the examples that we have used is this wind farm. On the left is showing the wind direction of an actual wind plant, and on the right hand side is showing our distributed control technology. And it's showing that if turbines can communicate with each other then they can operate in a more synchronized way. And that's kind of how we want to operate the grid. We want technologies to work together towards a common goal. And in this case the turbines are moving into the wind direction that will create the most power.
On the left-hand side there's no sharing of information; every turbine for themselves. They have to figure out the wind direction based on their sensors. And on the right-hand side they're sharing information working towards a common objective: they get their faster, produce more power. And so how do we do this? We do this by breaking up the wind farm into cells. And that way we can solve this problem in an efficient manner by passing information between agents in a cell and within cells themselves. And so that allows us to speed up our optimization time from something that might have taken 15 minutes to solve from a centrally controlled perspective to two seconds, because you could take advantage of parallel computing. Each turbine is computing something on their own,
and we're able to reduce that computation time. So again, sharing this example first because we're using this kind of approach for all of the domains that we work across in this project. Moving on towards grid interactive efficient buildings we have a similar approach. Here we have building controllers and building models working together with the grid controller and the power system model. And so traditionally buildings
have focused on occupant comfort, and now we're talking about having that still fulfilled, but being able to contribute to an objective for the grid. This becomes a challenge as we're starting to coordinate larger numbers of buildings to integrate into the energy system. In this particular example we are just using a simplified representation of a commercial building, specifically modeling the bottom floor with five zones. If you have any questions about this let me know and I could point you to the experts in this field.
Then the next area that we've looked at is vehicles and mobility. We developed a simulation platform that looks at the mobility of vehicles in a city, and also developed optimal charging control strategies. All this is integrated with renewable energy. How does this work with variable energy and so on? So this is a video of vehicles in Austin, specifically what electric vehicles might look like: green is vehicles moving around with passengers; red is empty; black is just idle; and the orange dots are charging. And so this is our simulation platform that we're able to move vehicles across a city. And as you can imagine, where the vehicles decide to stop and charge
matters from a grid perspective, and it also matters from a time-of-day perspective, especially if it's particularly windy or a sunny time of day or not. In addition to that, we developed a consensus-based optimal charging algorithm for many vehicles. We can do this up to tens of thousands of vehicles. We use the exact same approach that we did for the wind problem, and we were able to apply this to charging stations. Think of the charging stations as the cells now, that is, these right here. And then each of the vehicles as the individual turbines. And so we're able to come up with a very similar
approach to solving this problem. And by having a similar approach to solving these problems we can much more easily integrate this into the whole Bay Area simulation, which is what we're after. Now the final technology that we're looking at here is PV, distributed PV in particular, and the grid. And again, we take a very similar approach to what we show with the wind problem. In order to solve – so this is a distribution system here on the right – in order to solve this problem in an efficient manner we break it up into areas.
And those areas pass information back and forth to each other. And within these areas they have nodes that could be PVs, EVs, or buildings, and they all work together towards this common goal. But only by separating them into areas can we solve this problem. Putting this all together we have simulated the San Francisco Bay Area with a million devices. So we have the grid integrated into this, we have solar PV, building nodes, EV charging and also EV is moving around the city, so basically moving around electrons. And so this is kind of the culmination of our project so far; we developed this complex, multidomain energy system simulation of the San Francisco Bay Area, and you can control devices here down to the one second level.
We do have a rebuild for this, so if you're interested in playing around with it, or developing control algorithms of your own please let me know and we can get you set up with that. So with that I will end this presentation here. I'll give you a summary of what we've done so far. We have integrated multiple domains on both the supply and generation side; we've developed novel distributed control techniques that can be applied across multiple domains; and we have this simulation framework that deploys millions of controllable devices. Again, a lot of this work is on GitHub, so if you're interest please let me know. And some of our ongoing work is in both resilient science and autonomous urbanization, really drilling down into what flexibility, buildings and transportation can provide to our system. So with that my time is up and I will be happy to take any questions in the Q&A session.
But now I would like to pass it off to my colleague, Paul Fleming, who will give a deeper dive on the control of wind farms at the utility scale. Paul? >>Paul: Thanks, Jen. So I'll be talking, like Jen said, about wind farm controls in the context that she provided this subset of the overall picture of improved system control. First, what is wind farm control? If we think of a normal wind turbine it will have its own wind turbine controller that is going to, in real time, control its blade pitch angles, generate a torque and yaw angle in order to operate the turbine safely, minimize loading, and try to maximize the power output up to rating of the turbine.
A farm, then, is a collection, a wind farm is a collection of these turbines operating individually using the information they measure themselves to maximize their own objectives. So that might be what we call wind farm control today. And this can be considered a type of greedy algorithm, being that each individual agent is trying to maximize its own objectives and not cooperating with other turbines. When we think about where we want to go we think about a broadening of this approach, either having individual turbines share information between each other – this is a lot like the consensus approach that Jen presented in the previous talk, but it could also be able turbines pursuing global objectives, farm-wide objectives, rather than pursuing individualized turbine objectives. Or finally, in the bottom right quadrant of this figure, it could be both simultaneously. So the wind farm control of the future will look maybe more like this, where turbines are sharing information between each other, and considering their objective functions the total power output and the overall best value minimization of loads, as well as perhaps controlling themselves in the context of a hybrid plant, or an overall system.
So wind farm control is the coordination of the control actions of individual turbines. Why implement wind farm control if it's adding this complexity to the systems? One reason is to increase energy production. So by coordinating the turbine control activities, as I'll show later, you can increase the energy production of the farm; you can also reduce the damage incurred by the turbines and increase the lifetime of the turbines by dealing with things like wake-induced loading. And finally, you can increase the value of wind energy to the grid by understanding and controlling the flow you can more accurately control the power and provide support for the grid, and also, again, in the context of this broader talk, really participate in the control of the system that Jen discussed. The value of wind farm control to existing wind farms is still a research subject, but typical ranges of numbers include one to two percent AEP gain from implementing a technology like wake steering, a type of wind farm control at existing sites, with perhaps higher possibilities if we're talking about large, modern rotors and maybe higher possibilities, again, for offshore sites with their particular atmospheric conditions.
We also see potential for one to five AEP gain coming from wind farm level control with communication. So things like the consensus control algorithm that Jen discussed. In addition to value coming from load reductions this is much more specified to the specific site as to how you want to gain that value, either through lifetime extensions or reduce O&M or something else. Still, though, the even higher value of wind farm control comes in when it's incorporated into the design phase. So this might mean using wind farm control to produce a more cost-effective layout as a way of dealing with the wake limitations that are put in place. Or maybe it represents providing plans for coordinating with other types of generation, either on the site or outside of the site. So really we see then even more leverage that can be applied through these techniques of coordinated control of a farm.
So drilling down a little bit more deeply we can think – I think of wind farm control in two main types that you see the most often. One are axial induction control, which affect generally the pitch and torque control systems of the turbine. They can be steady or dynamic, and they generally are looking to control things about the wake depth or the power of the turbine themselves directly without regards to the wakes. In wake steering you use either the yaw controller, or let's say more futuristically the tilt angle of the turbine. These are going to be necessarily slow adjustments and you're going to have control over the wake depth and the position of the wake. So this visualization is kind of showing the difference in how the wake is being controlled.
The rest of the talk I'd like to focus on wake steering, the type of wind farm control that I spend the most time on. This is the simulation from our Large Eddy Simulation tool, SOFA, showing a farm operating with five turbines aligned to the wind flow, or in a baseline case where they all maintain their alignment in yaw angle, or a controlled case where the front turbines are using wake steering to deflect the wakes. What you can see is the LES simulation is predicting an increase of about 13-14 percent from wind farm control in terms of energy production over this period by using this type of wake redirection control.
In research of wind farm control, you see three main types of research. One is into the design of wind farm control. This includes making the engineering models used to design wind farm controls and then also the tools, like the optimization methods and things like that that we might employ to figure out how best to – what is the optimal way to get what we want out of wind farm control.
There's also implementation questions. So consensus I think falls into this bucket of how do we actually control a farm in real time when all this information is coming in and needs to be synthesized and actions taken in a quick way. So techniques like consensus control, which focus on fast convergence of like group information are really important in this space. And on the right, a lot of effort on validation of these new models that predict how wind farm properties will change under non-nominal controlled conditions. On the design side an important tool out of the wind energy controls group at NREL is the open source software framework, FLORIS. FLORIS is available for download on GitHub,
and through this tool we intend to collaborate with people inside and outside of NREL. It also is where we develop new models and also our optimization strategies. It can be used for the design of wind farm controls to predict the performance of controls, and to optimize with the farm layout, or a couple of use cases. But there are more, and
provide a number of example use cases within the provided examples that come with FLORIS if you're interested in trying it. It's pretty easy to set up, and then you could run an example like the one I've plotted on the bottom, just showing different types of wake models that could be optionally used in FLORIS, running from the famous Jenson model through more Gaussian-type wake. Okay, so in terms of validation I'd like to talk about one campaign that we've done to validate this type of control that took place at a commercial wind farm in the U.S. We placed wake steering strategies onto the turbines labeled T2 and T4 in the figure on the right. They were trying to control their wakes for the benefit of Turbine 3. The control strategy was designed using FLORIS, and also FLORIS predicts what the increase in power production will be. So this field campaign gave us the opportunity to assess
the capability of FLORIS to design the controller and also to see how well FLORIS would predict what the gains would be in advance. Additionally it gave us some opportunity to work on the control strategies. This was more or less an open loop control strategy, and future work will focus on incorporating closed loop strategies such as consensus.
These figures are showing the main results of the test. The figures on the right show, for the wind directions, where the downstream turbine is in the wake of the upstream turbine the percentage less energy produced by that turbine, relative to a free-stream turbine not in a wake. So at the direction of, for instance, the North campaign of 224 or 223 degrees or so the downstream turbine is directly in the wake, and so it only produces about 65 percent of the energy of an unwaked turbine. The blue sort of shaded line is what that energy production is under normal conditions, and the magenta-shaded line is that energy production under controlled operation. The dashed lines represent what FLORIS was predicting the results
would be. And so we see that we were able to increase the energy production of those downstream turbines and they were in the amounts that FLORIS was expecting. If you're interested to learn more about this field validation campaign, these two particular papers are available on an open source journal, so they can be downloaded without requiring payment. And so here's the titles of the two papers covering this research campaign. More papers based
on this campaign are still coming out, looking at the loads and also the flows through the farm, written by some of my colleagues who worked on a campaign with me, so look for those. Okay, so coming to some conclusions. Wind farm controls is a really active field of research with a lot of progress being made and a feeling of accelerating deployment and acceptance. We've been working in wind farm control now for maybe quite some years, but I still think there are some challenges remaining for the future, and these will govern our upcoming research. In the space of modeling we still need to look at large array effects in detail and also how wind farm control will function offshore; this is really our present focus. In terms of implementation, how best to control large numbers of turbines, rather than the small numbers of turbines you saw in the previous validation campaign in an efficient way. How to implement this control in the context of hybrid plants, so plants that have
more than just wind energy production included in them. How to do this real time and robustly, as well as how to estimate online the status of the flow and the controller. And finally, validation. We need additional validation campaigns, and this is obviously in the plans, but validation for larger arrays with control, validation for offshore wind plants, and validation of the loads models used in these studies. These are just some topic areas; there are others. Okay, so with that I think I'll also be looking forward to taking questions at the end of the session, but I'll now turn over the podium to my colleague, Aaron Barker. >>Aaron: Thank you, Paul.
Good morning everyone, my name is Aaron Barker. I'm a researcher in hybrid energy systems at NREL and I've been working on this for about two years now. Today's talk is on hybrid design and analysis, or design and analysis of utility-scale hybrid energy systems. So just a brief overview of my presentation today. We're going to talk a little bit about why hybrids are the future, the benefits that we're seeing in hybrid system development and the industry feedback that we're getting, some of the technical and political challenges that are associated with hybrid energy systems. We'll talk a lot about the hybrid optimization and
performance platform, or HOPP, that's being developed here at NREL, so the capabilities and results that we're seeing from that. And maybe a bit about what's coming next. >>Jen: Hey Aaron? Sorry to interrupt but I can't see your slides. Do you mind sharing them again? >>Aaron: Oh. No problem. >>Jen: Perfect. Thank you. Carry on.
>>Aaron: Okay, thank you, Jen. Okay, so you haven't missed anything but some text, but here's the presentation overview, again. Great. So here's why I think hybrids are shaping up to be the future of some of these renewable energy generation technologies. So wind, solar PV and storage hybrid power plants represent 4.6 GW of installed capacity in the U.S. currently. And this is up almost 1.5 GW year on year since 2019. So we're seeing a really rapid increase in the development of these projects. In addition
to that we're at almost 15 GW in the pipeline for immediate deployment, and there's a further 69 GW of hybrid power plant capacity that's awaiting approval in the interconnection queues. So the interconnection ques is sort of an important piece of this hybrid power plant puzzle. Right now we're hearing from the industry that the typical interconnection queue time is nearly three years and potentially longer, depending on the location and the size of the interconnection being requested. And so with that comes a number of constraints on developers both large and small. So larger operators want to maximize the utility of this interconnection to deploy more capacity, while the smaller operators feel that they have to build as much as possible since they may only get one shot, and in many cases can only afford to have one shot at an interconnection agreement. There are yet others in the hybrid space who have not seen the light, either technologically or economically but are doing it anyway. And that's sort of a powerful paradigm shift that we're
notifying, that people are getting on board with hybrids and there's a rapid industry turnaround, despite the fact that a lot of technical challenges are yet to be addressed. So let's talk about some of the benefits of hybrid systems first. So one of the key benefits of hybrid systems, at least in the wind and solar PV space is the complementarity of these resources. And the complementarity effectively is the combination of these two resources and the generation profile that they provide, and quite often these wind and solar profiles are different enough that they act to derisk the overall generation profile of the renewable plant. And this has a further effect of maximizing the utility of the interconnection.
So on the left-hand side of the slide here we're progressing through a year from January to December, and we're looking at the Pearson or correlation coefficient on an hourly basis throughout the year between wind and solar PV. Now the Pearson r correlation coefficient here is a measure of how well-correlated these resources are on an hourly basis, where blue represents highly-correlated, meaning that when wind is high solar is high, and red representing when wind is high solar is low, or vice versa. And so complementary in this case in terms of energy generation profile you're actually looking for times when wind is high for solar to be low and vice versa. This is actually a good thing. And what we're seeing is that, for the majority of the year in the majority of the country we do have this complementarity, or these negatively correlated resources. And the takeaway from this is that these are extremely complementary resource profiles and we can leverage that to our advantage. So we would look to build plants where wind and solar are both abundant and have these complementary resources profiles which, fortunately, is a lot of the U.S.
So on the righthand side here another benefit of hybrids is the daily resource profile provides more consistent power output and provides the ability to provide continuous power, whether that's to the grid or to an island at load. So in this image here the green at the top represents the generation coming from all technologies, so wind, PV and storage at a site in the mid-south in the U.S., which has been optimally designed to provide a continuous load of 10,000 kW or ten MW. The pink here represents the generation just from the wind and PV, and then when we break that into its individual components, looking at the orange being the generation profile of the solar PV and the blue being the generation of the wind we can see just how complementary those resource profiles are, and they act essentially to provide more consistent and dependable power when they're used together. So this enables supplying continuous loads, but it also unlocks new markets for renewables, so these being things like ancillary services, capacity markets, supplying these continuous loads, or things like fuel production in islanded systems. There are, however, some technical and political challenges that we face in the design and analysis of hybrid plants. So one of the first challenges is that there are few readily-available design tools that can actually deal with hybrids at the utility scale. So we've had tools for a number of
years like the NREL-developed HOMER, which looks mostly at microgrid, islanded and distributed systems, but we have fewer tools that can look at utility-scale plants at the component level. And that's something we're seeking to address with the HOPP tool, which I'll talk about in a minute. So in addition to that the interconnection laws, which have recently changed in the last three or four years, coming with FERC Order 845, have been approved to allow overbuilding on an interconnection but only to about 20 percent. So still probably not to the extent that hybrids can truly benefit from, and there's definitely potential to extent that further and leverage the benefits of hybrid plants even more.
We have heard feedback from industries, so I recently went through the Energy I-Corps program and spoke to 75 industry and research participants, and overwhelming feedback coming from that is that these plants are often harder to finance, due to the financiers' lack of familiarity with hybrid design tools, their proxies and their outputs, which essentially just means they're either paying a higher rate for more risk, or they're not able to get these projects off the ground. But in reality hybrid plants should act to derisk these projects, and so it's really about providing the right design tools, the right policy and the right information to address this. Another issue technically with hybrid plants is that curtailment of individual technologies affects individual minutiae in the financial calculations, like the production tax credit, or the calculation of partnership flip. And so this is something that really needs to be addressed to operate these plants together in a collocated manner and really leverage the benefits. And to do that requires controls and policy. So some of the background of hybrids at NREL, there are a lot of projects actually going on in the hybrid space, and this isn't an exhaustive list, but all of these are addressing hybrid power plants specifically. So on the systems integration and analysis side the SPIA project, led by Kaitlyn Murphy, is looking at renewable energy-based hybrid generation systems.
The design bucket, which the HOPP tool falls into, also consists of REopt and has been funded, along with the Hybrid LDRD, which is looking at integrated design of hybrid plants at the component level. And then on the operations side we have the FlexPower project, MIRACL, and the DELTA Seed LDRD, looking at thermal emulator design. So now into the breakdown of the hybrid optimization and performance platform, or HOPP. HOPP is essentially a tool for component-level utility scale analysis of hybrid plants, and it leverages a bunch of other technologies from NREL like the SAM, or System Advisory Model, and the REopt tool. So HOPP is able to take in individual generation technologies, such as wind, solar, storage, geothermal and hydro, and optimize the initial sizing of those technologies for a given technology cost, for a given location, and for the specific project or load that needs to be met. And it does that initially using REopt. It then passes that optimal system sizing to the HOPP tool, which also has its own volatilization or plant estimation tool at the component level.
So you can really deep-dive into the impact of component sharing, of shared interconnection, and of the performance of all these technologies in a hybrid system. So that then runs the SAM module, and you iterate on this, producing the energy and financial metric and optimizing for your end result of choice. And so it makes this a very powerful analysis tool for system-level design incorporating component level. So these are some of the capabilities that that allows with HOPP. So on the analysis front it can tell us things like where to build collocated hydro plants. While we're already learning that resources are often complementary in this country, and that's a huge benefit to hydro plants, but we can look to maximize that using the HOPP tool. We're also learning about where
and how much to overbuild on an interconnection using hybrid power plants, when and where to include storage – and this is all dependent on technology costs and progression in the future, and the component-level performance of these tools, which is something that we can now study. So in this lower image on the left-hand side here we can see a solar addition scenario which is adding solar to existing turbines, and the net present value benefit that that provides for hybrid plants. And so the progression of this scenario is mapping out decreasing solar PV costs into the future. And the expanding green area is showing where hybrids will start to provide net present value benefit in that scenario. So it allows us to also look at the future, at technology changes and see how that might affect where and how these technologies will develop.
On the optimization front the HOPP tool allows us to optimize hybrid plants down to the component level. So this animation in the top right is showing the individual placement of wind turbines and solar PV panels being optimized for the best AP value that can be produced. And this can also be done for a host of other metrics to produce the optimum design of a hybrid power plant.
It also includes control and dispatch algorithms for wind-solar storage, and we're looking at bringing these down to the one-minute timescale, so we can really look at how to operate these hybrid power plants. And it's looking like the performance of these hybrid power plants, using these techniques, can be improved by more than five percent. Delving into the cost side, or the component-level cost side of HOPP we have an additional tool called HybridBOSSE, which is a hybrid balance of station, or hybrid Balance of Plant Estimation Tool. And using this we performed a baseline cost study
for 100 MW of wind, 100 MW of solar PV combining to create a 200 MW hybrid power plant, and we've compared this to an independent or non-collocated plant just consisting of those wind and solar PV plants and not leveraging any of the benefits of hybrids. So we did this for three different levels of cost saving: level one, consisting just of management and substation and grid connection sharing, and then level two, additionally including site preparation, and level three, also including the crane equipment cost sharing. And what we found were that the biggest cost drivers impacting hybrids or providing benefit for hybrids were reduction in costs of substation, grid connection consisting of transmission and distribution, and management and development. And these total costs savings at level one were anywhere from
9.4 percent all the way up to 11 percent for this baseline plant at a level three cost sharing. What do we need overall to achieve the vision of hybrids? So we've already talked about the technoeconomic analysis and that's a really important component. So we need this system-level view at a high level but incorporating component-level design. Where can we do it, where is it most viable and what technological changes might impact this the most. Beyond that, when we look to actually build, design and operate these sites we need to incorporate atmospheric sciences and siting so that we can overlay these hybrid power plants, or potential locations for them with other industries. And this may actually unlock sites that were previously overlooked or unlock alternative uses of this energy.
And then on the design and operations side we need to look to optimally design and operate these plants both on grid, off grid, and for different applications like potentially fuel production. And fortunately NREL is in a unique position to do this. Not only do we have research staff that are working really hard on hybrid energy systems and these new tools that are being developed but we also have the ARIES campus, or the Advanced Research for Integrated Energy Systems. So this consists of both hardware and emulation components, and using both of these together we're uniquely positioned to study and emulate utility-scale hybrid power plants at a 300 MW or for a large power level. And this is going to be an enormous capability for studying how these hybrid plants behave in the real world going forward. So some upcoming work on this hybrid development. So continuing on the hybrid optimization and
power performance model development we'll also be developing fuels modules for H2, ethanol, ammonia and other fuels, and additionally transport modules. We're going to be validating these performance results against industry figures, and looking at finer timescales and more complex optimization and modeling capabilities. On the balance of station side, which is an important driver for understanding the costs and the cost savings of hybrid plants, we'll be looking to expand HybridBOSSE and publicly release it and expand this to include additional technologies to incorporate in that mix also. So that's been my presentation. Thank you very much. I'd like to pass you over to my colleague, Vahan Gevorgian, who's going to talk about variable generation in hybrid power plants. >>Vahan: Hello. Am I being heard and seen?
>>Jen: Yep. >>Vahan: Okay, you guys see my slides, correct? >>Aaron: Yes. >>Vahan: All right. Yeah, I'm going to talk about the hybrid generation research going on at NREL,
which is a combined teamwork between power systems engineering center and Flatirons team at the National Wind Technology Center. The hybrid renewable energy systems that combine variable solar and wind energy sources have a potential and they're very well-positioned to lead up the global scale – to lead the global scaleup of renewable generation globally at affordable, low-cost levels, and they also offer new opportunities for equipment vendors, new revenue streams for plant operators. And they also have a potential of becoming a new source of dispatchability, flexibility and reliability to the grid, and also resiliency, for that matter. With declining cost of energy storage systems, in particular battery energy storage, addition of energy storage component into such hybrid plants would transform variable renewable generation into a source of energy that could potentially disrupt the market for traditional single technology players. Overall this emerging concept of hybrid renewable power plants offer many new opportunities to existing industry stakeholders and they can change the global renewable energy markets.
However, there are several critical questions related to both technical and economic aspects for such hybrid plants that need to be answered. And as Aaron mentioned in his presentation, many questions still wait to be addressed by the research community. For example, how are benefits of such multi-technology collocated plants can be fully quantified in terms of generation costs, system reliability and operational flexibility. What are the full set of use cases for such hybrid plants? How should individual technology components be optimally sized? And what is the optimal way to control individual hybrid power plants and also clusters of such plants on a hybrid scale? So the main idea of hybridization is to achieve more benefits at reduced per-unit cost. And one important benefit of course is based on the complementary nature of this resource which will end up in reduced or in some cases no transmission buildup to integrate larger amount of variable generation with much higher capacity factor, by combining these resources.
On top of that we have emerging new reliability challenges that are coming upon us. Some of them are already manifesting themselves in many places in the world, in some places in the United States, especially in Ireland power grids. So on our way to 100 percent renewable grid would be seeing all these problems essentially listed here. And the main one is the inability of the inverter-based resources to maintain the grid strength. Inverters can do many things but they cannot provide more current than they are designed for, and therefore this will end up in reduced grid strength, and also will have significant impact on the protection of a grid, and how we protect individual devices in the grid from defaults.
This is combined with the degrading synchronizing torque because synchronized machines are going away. Reduced inertia – that also raises the question who is going, and how is going to form the grid. New local and wide-area stability challenges will emerge, too, because we'll be seeing more of the different types of control interactions, different type of subsynchronous oscillations and resonances when you have many inverters trying to do the same thing in parallel. The grid will require more flexibility, of course. This is dictated with a shape of a solar power production; you need lots of flexibility resources in evenings and mornings. And also the resiliency services: what happens if you need to start the grid after the blackouts? So black start services and resiliency services are also very important.
So there are a number of projects, as Aaron mentioned, going on in NREL; I want to talk about a couple of them. So the FlexPower project is the GMLC-funded project that is going to look at many aspects of these challenges, as I described, and that includes both resource assessment, economic assessment and control aspects of these multitechnology hybrid power plants. So in this chart we show the technology mixes that are being considered in this project; it doesn't mean that all of them will be collocated in one side, but they all will be modeled and controlled, so we try to understand how these technologies can work together in the collocated hybrid plants. That includes different types of energy storage technologies that cover different timescales. We are also looking at some site-specific aspects of adding hydro power or pump storage hydro component into this project. So the FlexPower concept, or the project is an ongoing project with also the demonstration task that would be conducted at Flatirons campus. As part of this
work we are looking at hybridization potential across the continental United States. And this task has several stages; this is a description of a workflow. We started looking at the complementarity of a PV and wind resource at the high resolution, both on a daily basis and a seasonal basis, how the hydropower component also can be included into risk potential assessment. Then we'll do a scenario buildup that will look at placement of different types of hybrid plants across the country, and with different sizes of energy storage. And then at the end we'll choose a region in the U.S. and do a regional-scale study to benefit the benefits
of this technology on a regional scale; very likely it is going to be California ISO footprint, and we'll do with using the commercial Plexus tool or maybe NREL will develop a seed modeling tool. So our preliminary resource assessment results are very promising. These maps are showing the daily and seasonally correlation between wind and solar resources. This is in addition to what Aaron showed in his presentation. So we can see these dark areas, or darker areas, are the areas where the resource complementarity is high and potentially these are the places where their collocated plants have a potential. And they cover a
huge area of landmass in the continental United States. So this is very promising and as I said now, we're working on understanding how the hydro resource in particular the [inaudible] variable hydro resource has any complementarity that works together with wind and solar. Many benefits of hybridization are listed here. This is a very long list. But the bottom line: we're planning to demonstrate them all in a real hardware demonstration by testing at the Flatirons campus utilizing our testing assets. So that will include pretty much all timescales,
anywhere from economic dispatch down to frequency regulation and even more advanced and faster reliability services such as our [inaudible] inertia, [inaudible] frequency response. We'll demonstrate grid-forming and black start capabilities. We're also going to demonstrate how hybrid plants can provide start services, where many services can be provided at the same time. It's clear how to do it technically but these services – it's not easy to do it from an economic point of view because many of these services are scattered through different timescales and benefit different stakeholders, so stacking them is also a challenge on how to do it in the most optimized way. So here is the – I know this is a very busy slide but this is a demonstration platform that will be used in a FlexPower project. We'll utilize our four grid simulators, existing one and a new upcoming 20 MW one. Our existing wind and solar generation and storage assets.
We're building the control layer over it. And then also we're using the remote integration with hydrogen storage [inaudible] and also the electrolyzer and also capacitor capabilities at Idaho National Lab. So this is a multilateral project and we are getting now into demonstration and testing stage that hopefully we'll start this spring. Some of the aspects of this have already been demonstrated, and one case where the hybrid plants help from a resiliency standpoint was dictated by [inaudible] when last October we had this explosion at a substation at Flatirons campus; you all know about it. And the site was without grid connection for several weeks. And Flatirons team operated the
hybrid power system at Flatirons campus to operate the site utilizing wind and solar generation. And this was done for an extended period of time; it's more than 24 hours with no help from this. So by introducing the controls that have been developed under different DOE-funded projects and improving it by adding more advanced controls that have been implemented by Gemec.
So here is one example of the extended operation of a hybrid plant when you use the PV battery and the wind battery to provide power to the loads. And this is one example. This was very encouraging because this is [inaudible] communication[inaudible] very robust control method that was implemented by Flatirons team.
We've done a number of hybrid plant demonstrations utilizing PV-BESS technologies, or battery technologies. These are the tests where we're doing the PV production profile shaping. This is mainly to address the PV integration challenges in places like California, where the evening PV ramp poses significant reliability challenges because it requires a lot of flexibility resources. So it's a big integration challenge in terms of both cost and reliability. So we can see by controlling the PV and storage, even during the very highly, highly variable [inaudible] basically by controlling the storage you can achieve – and using the forecast you can achieve any shape you want and make the plant fully dispatchable with a very slow morning and evening ramp rate. So these type of controls
are going to essential for systems with a very high level of PV penetration. We're looking also at the [inaudible] hybridization with other technologies as well. Another example is the project, we call it SuperFACTS. It's a super-flexible AC transmission systems. We funded – Office of Electricity-funded project which is also being implemented at Flatirons campus. For this we'll be utilizing not only battery but also synchronous condenser to address some of the evolving challenges I mentioned in my earlier slides.
So this is going to be a really flexible and scalable solution providing – offering the solution to many challenges. And the main one, of course, reducing the grid strength. We're planning to demonstrate this in [inaudible] hardware at the Flatirons campus utilizing our grid-forming battery and the synchronous generator that is being procured and will be installed at the 2.5 MW dynamometer. We already modeled this in a very high level of details and demonstrated many use case. How this combination of grid-forming battery and the synchronous condenser as part of a larger hybrid power plant can provide resiliency services, for example as a black start and can be used for a black start or a transmission or subtransmission systems on a regional scale.
One example of that step-by-step is shown here, how you can use first the battery, then start the synchronous condenser then energize a portion of a transmission system at a time and bring the system back to life. If there happens to be a solar and wind generation on the same BOS as part of a hybrid plan for wind and solar can be started utilizing this technology as well. So this is just a couple of examples I mentioned, but as I said, there is a few more exciting projects going on. There is not enough time to cover them all but I'll
be glad to share with the people who are interested or have questions about this. So as a conclusion or summary, as I mentioned the utility-scale hybrid power plants offer new opportunities for renewable energy industry and they have a potential to disrupt the market because of the benefits they're offering. Hybridization allows maximizing the values of the existing and future generating assets. We can help transforming the variable generation into a fully-dispatchable and flexible source of energy, and also provide full range, full spectrum of existing essential reliability services, evolving future stability or new-evolving stability services and also help improving the resiliency and security of the power grid.
This is all I have, and I can stop sharing my screen. >>Jen: Thank you, Vahan. We will now move into the Q&A portion of this webinar. There are a few questions that have already come in on the chats. Please put them in the chat or raise your hand. We can get this started. There's a few that were already
answered by Aaron but I just want to inform the whole group. Aaron, if you mind repeating: Is HOPP available for others to use, and what generation technologies does it include? >>Aaron: Yeah, thanks, Jen. So yeah, HOPP is publicly available. It's on GitHub at GitHub.com/NREL/HOPP and the link is in the chat. And so right now we have wind, solar, PV, CSP, storage, geothermal and hydro technologies. And those are all able to be used in hybrid systems together, though there is a focus, particularly on wind and solar PV systems, and that's where a majority of the development effort has gone. But we're always happy to talk about how to incorporate new technologies or expand the reach of the existing technologies.
>>Jen: Thank you, Aaron. The next question comes from James. I think this is targeted towards Aaron or Vahan: Regarding atmospheric science, siting and risk analysis are models taking into account changes in the long-term environment, elevated greenhouse gas metrics and advanced weather simulation? >>Aaron: Yeah, so I'm happy to field that one. That's a great question. We actually do have a paper in the works studying the impact of climate change and CO2 changes and changes in variability in our atmosphere on how hybrid systems will perform. So it's still early days but we will be
looking at various different future scenarios and how the resource profiles might change, what impact that might have on energy production certainty, variability of these plants. And we're going to use that as a vehicle to study other or not hybrids will provide benefits in a more uncertain future, or a future with large changes to our atmosphere. >>Jen: Great. Thank you, Aaron. And then finally the last question we have – sorry, two questions: have you guys done the PV versus wind correlations globally, or can it be done globally? Also to you, Aaron and Vahan. >>Aaron: Yeah, they can definitely be done globally. Right now we have looked at the
continental U.S. but also at Alaska and Hawaii. So I don't think those Alaska and Hawaii results have been published anywhere yet but they are quite interesting, and they do vary a little bit, especially in Alaska I think, due to the terrain. So there's some interesting findings there, and hopefully we'll get those all out the door pretty soon. We do have the code and could run that for anywhere where there's coincident wind and solar information available. >>Vahan: It also can be done not only for land-based hybrid systems but also for offshore hybrid systems because with the evolving floating PV technology it might be possible to build hybrid plants that includes both offshore wind and solar, and combining with other technologies such as marine hydrokinetic we may be a whole new brand of hybrid plants, so I believe that type of the complementarity analysis would be also very important. But I'm not aware of anyone doing it.
>>Jen: And I guess another question along those same lines – keep you both on the line here, is: Aaron's maps of wind and solar correlation were negative across Texas and the southern plains in the summer, while Vahan's maps showed positive correlations there. Could you maybe discuss the methods you used? >>Aaron: Vahan, would you like to go first? >>Vahan: Definitely. So the work, the correlation was done in the slides I showed by Sig team based on our wind and solar data sets. So I'm not sure – I didn't pay attention to the graph shown or the chart shown by Aaron but we can go and do a deep dive and see if there is indeed contradictory stuff. But I'm not sure – can you elaborate on it, Aaron? >>Aaron: Sure, yeah, thanks Vahan.
Speaking for our results, those correlations were done on an hourly basis for the data from 2013 from the wind tool kit and NSRDB, so we have actually done both hourly and daily profiles of correlation and they're sometimes quite different. The hourly is more indicative of how a system will perform in the energy markets, maybe without storage if it's closest to indicating how that would perform, while the daily gets closer to the total energy provided at the site over a day. So more like a time lag, storage-based system complementarity, and both are important to look at. And then it's broken down by month also and that profile changes quite a lot across months. There's actually been some really interesting research by Patrick Brown, looking at these complementarity profiles both in the same year and in different years. So for example, taking both the wind and solar from 2013 or variously taking one from 2012 and 2013. And quite often doing it in alternate years completely reverses the trend of complementarity.
So I would just say overall it's quite a fickle thing. It's very site dependent; it's very dependent on the source of the data, very dependent on the timescale. So there's a lot of things to dive into there and I'd love to catch up, Vahan, and have a look, Vahan. >>Vahan: And the other aspect of it is the HOPP [inaudible]. So the analysis I showed was done at the 135 meters, and of course the higher you go in HOPP [inaudible] the correlation will change. So I'm not sure if that also has an impact.
>>Aaron: Definitely. Yeah, we were at 100 meters, I think. So it does make quite a big difference. >>Jen: Those are really good points to clarify. Thank you both. So the next question is: Do the existing NREL tools cover offshore wind and hydrogen generation in the sense of having an offshore wind turbine with a built-in electrolyzer? Again, probably Aaron – I know that you're working on some of that stuff. >>Aaron: We have just recently finished created a hydrogen generation model for Penma Electrolysis. And so that's the first step towards the hydrogen generation piece. As for offshore we're not quite
there yet. All of the existing effort has been land-based or focused on land-based technologies. >>Jen: Thank you, Aaron. I do want to pivot really quickly to one of the earlier talks, specifically to Paul. Can you talk about how wind farm controls will adapt as we move into these hybrid scenarios and try to achieve the president's goals for clean electricity by 2035? >>Paul: Yeah, that's a good question. I think it's probably a research question, to be honest. But trying to guess – things that might impact the strategy you choose without hybrids, for instance curtailment or low power prices, might be different in a situation where you have hybrid plants, you have other things that you could be doing with more energy production. And they might change the calculations. So I think it's a really great impact that I think
about with controls which is you're trying to balance a number of competing objectives using a number of potential actuation and the hybrids are giving you alternative objectives, the ability to like, for instance store and use energy later. And
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