Hybrid Energy Systems of the Future

Hybrid Energy Systems of the Future

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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

2021-04-03 09:52

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