Implementing Heat Rate Reduction Solutions to Improve Plant Efficiency and Reduce Fuel Consumption

Implementing Heat Rate Reduction Solutions to Improve Plant Efficiency and Reduce Fuel Consumption

A reduction in heat rate can be pivotal for a thermal plant to maintain a competitive position in its market. But traditional methods for managing performance can be time-consuming or expensive. Learn how GE Vernova software can help you reduce your plant heat rate by up to 1% in 12 months.

GE Vernova experts join POWER Magazine to discuss how to improve plant efficiency quickly and economically with GE Vernova’s APM Performance Intelligence.

Reasons to watch the webinar:

• You have power assets that have heat rates higher than expected for your technology.
• You want to operationalize your heat rate management to replace manual processes and quickly identify performance issues.



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TRANSCRIPT
Hello and welcome to today's webcast titled Fueling Efficiency: Implementing an Economical and Fast Heat Rate Reduction Solution. I'm Aaron Larson, Executive Editor of Power Magazine, and today I'll be joined by Janet Webb, Senior Digital Product Manager for APM Reliability and Performance Suite, with GE Vernova. And also Aisha Murtaza, Technical Project Manager for APM Reliability and Performance Suite with GE Vernova. To begin. Janet, can you tell us a little bit about yourself and what you do in your position? Thank you. Aaron. Hi, I'm Janet Webb. I am the lead product manager for our APM Reliability and Performance software that includes Performance Intelligence, which is the product that we'll be focusing on today. I've been with GE for 17 years. Just the last couple in this digital software space.  
 
And prior to that in power generation, primarily focused in reliability engineering. And I am located in Virginia, about a four hour drive from Washington, DC. Thanks, Aaron. Well thanks, Janet. And Aisha, I'd also like to have you tell a little bit about your background and and explain what you do with GE Vernova. Thanks, Aaron. Well. Hello, everyone. Thank you for joining us here today. I'm Aisha, and I started my professional career seven years ago with GE as a power plant performance engineer. During my time on site, I also gained a lot of valuable experience when it comes to equipment reliability and maintenance. Fast forward to my current role. I lead the implementation of APM performance intelligence and, reliability plans here in the Middle East. The region mostly, leveraging my experience on the field and, you know, using GE’s digital solutions, I do my best to help our customers, in optimizing their operations and, day to day, power plant performance. I'm really excited to be here today, to talk to everyone about all the cool and incredible features of performance intelligence, that it brings to the table when it comes to monitoring and heat rate optimization.  
 
All right. Thanks, Aisha. And I'm looking forward to the discussion that we're going to have with both of you. Thanks for both of you being here. So today's, presentation is expected to last about 30 to 40 minutes, and it will be followed by a Q&A session, which should fill the rest of our time. And before we begin, I'd like to run through a few housekeeping items. In the webinar platform, you should see a chat area and a Q&A area. If you're experiencing any technical difficulty, you can ask for help using the chat function and our production staff will assist you to submit questions for our speakers, please enter those in the Q&A section rather than in the chat area. You can enter questions at any time during the presentation, and we'll answer as many as possible during the Q&A section at the end. Any that we don't get to during the live session will be answered via email after the webinar. Today's presentation will be archived on our server for up to one year, and future viewing will remain free of charge. You can use the same URL to reach the archive program as you did to reach the live program.  
 
The PowerPoint slides and handouts will be available for download from that web page after the presentation. A certificate of completion for professional development hours will be sent via email to every registered participant who attends. Before we begin, I'd like to thank GE Vernova for underwriting today's program. The company's generosity allows everyone to attend the presentation at no cost. And with that, I'd like to kind of tee things up with a little background. You know, I'm sure most of our audience realizes how important heat rate is for a thermal power plant. It's critical in maintaining a competitive position in the market. Heat rate is a very important aspect of all of the costs, the overall cost for power generation. It often accounts for anywhere from 60 to 80% of variable costs for a power plant, and even small improvements in heat rate can have a major impact on plants financials. The adoption of predictive and diagnostic software offers power generators the opportunity to more easily achieve improved heat rate while significantly reducing fuel consumption, and by reducing fuel, it often improves your CO2 emissions, they inherently go down with less fuel use, thus helping to attain emission reduction targets.  
 
So to kick things off, and before we really dive into the technology, Aisha, could you tell us a little bit about what you've seen happening in the past ten years, and how it's impacted the way power generation, power generators think about heat rate? Yeah, absolutely. So I think over the last ten years, you know, I'm sure we can all agree that we've seen we've seen sort of a shift or a change in market dynamics, mostly driven by fluctuating fuel prices and the government regulations when it comes to, emissions. And this has caused a lot of the power generators to adapt to these changes and operate their plants with a lot more flexibility, which is, you know, as as we can all understand, it's not very easy. And it requires deep understanding of heat rate dynamics to get the best economic returns. In addition to that, I think there's also been a lot of growth, you know, in the renewable energy sources like wind and solar. And what that has done is it has added a lot of variability to the grid. And once again, you know, the traditional power plants have had to adapt to these changes, and optimize the heat rate. More so than ever in order to, you know, efficiently ramp their generation, up and down as needed. What do you think, Janet?  
 
I'm sure you have something interesting to add here. Yeah. Yeah, I, I totally agree. I think we are seeing more than ever power plants are interested in improving heat rate, maintaining heat rate. So one of the things that we've been able to do with the software, with Performance Intelligence, is add the ability to have accuracy during part load operation and potentially find performance issues during part load. So, for example, you could have someone who says, you know, I'm going to run at 85% of full load. We have the advanced modeling capability now to provide that accuracy where you will see if you have a performance issue. Whereas in the past, you know, it's it's easy to miss at part load because you're still able to make power. You don't necessarily realize that you're using extra fuel to do so. And so we've actually had a customer who was operating at part load through the shoulder season.  
 
Worked with us on that modeling and detected multiple issues, opportunities for efficiency improvements that they were able to address before peak season and before being called to, to full load, where they would have come up with a ten megawatt shortfall. So really significant. And, you know, the factors were compressor fouling, combustion tuning, things that are common in, in thermal performance, but that they wouldn't have had the visibility to without having the software tool. All right. Thanks to both of you. And at this point we've got a couple of poll questions loaded. And I'd like to roll out the first one to, see what our audience is, is struggling with particularly what is your biggest heat rate concern. And we've got three options there listed. Is it fuel caused or carbon emissions or outage potential? So, just take a moment and, and kind of give us what's your biggest heat rate concern is. You know, we'll wait just a few seconds for these to come in. Looking at the results, it looks like about half are worried about or have their biggest concern as fuel costs. So fuel costs followed by carbon emissions and then outage potential.  
 
So, not surprising. And, Aisha, you mentioned about, data analytics. How has data availability changed the way teams bring heat rate? Yeah, I again, I think we can all agree that, you know, availability of data has been a game changer in all industries, really. And speaking specifically to to power generation, with advances in sensor technology, when instrumented modern equipment, advanced data collection systems, you know, the ease of deploying and accessing, applications on, on the cloud. I mean, I think we've essentially gained superpowers, right? I mean, you can now, keep a real time eye on the operations and performance of your plant. You don't have to be physically present on site. You can be, you know, thousands of miles away at a corporate head office or even in a different country. Like, you know, like I do, I, I'm not really on the site, but I can help customers, with their operations just by, you know, simply monitoring their day to day operations and, and, and performance thanks to solutions like, Performance Intelligence.  
 
In addition to that, the availability of data has also opened the world of, you know, predictive possibilities to machine learning and data analytics. You can now foresee equipment failures in advance and, and also equipment issues that can mess up with your heat rate goals. Right? Janet, what about you? Have anything to add again? Yeah, I, I would build off of that, to say, you know, in addition to having these improved analytics, better detection, Performance Intelligence takes it a step further by adding automated alerts to that with recommended actions. So when there's a potential performance issue, you're receiving an alert and it's telling you where to look, to, to walk through kind of how that works. The models that are developed are tuned to your equipment design and then validated, with the as running data. So you've got entitlement where you should be performing. And as I mentioned, that could be full load or part load. And then when there's a difference between your expected performance and the calculated performance you receive an alert, that that comes with the recommendation and really helps get to the root cause faster.  
 
So it's more visibility, but also a productivity enhancement. Yeah. And Janet, you mentioned Performance Intelligence. And I know the definition of that is it's a thermal performance monitoring tool that enables power teams to make a noticeable impact on their heat rate. How does PI actually... That's a that's a great question. And and one of the most common ones that, you know, pop up during our discussions with the customer during implementation. And I think what's important to understand here is that at the core of performance intelligence are these very powerful physics based models like, and, like Janet had mentioned they're developed using your plant’s design data. They're tuned to your specific configuration. They're running continuously in the background at the back end, model calculating performance KPIs using the light sensor values, which are once again, coming from your plant. So this all is happening at the back end now through the different features and applications of the front end software Performance Intelligence. You have the power to access both summarized insights, as well as dive deep into the detailed analytics of your power plant’s performance. Right. So you can use all of this information. Conduct weekly, monthly, quarterly reviews. To really keep an eye on how your plant is performing. So essentially, you're not just staying informed, but you're also actively strategizing, right?  
 
So if you if you're aware of the issues, you can plan proactively all the maintenance actions that can be channeled, to where they're needed, mostly to, you know, optimize heat rate and operate efficiently. And and what level of information can they can users get from this? Is it heat rate at a plant level or more insights at the assets level? Yeah. You know, anytime anyone asks me this question, I just tell them it's like having Performance Intelligence is like having a microscope hook for your plant. So so with Performance Intelligence, you get a magnifying glass, on critical KPIs. So you have visibility at fleet level, you know, all those matrixes, like power generation, heat rate, fuel consumption. And you can go all the way down to equipment performance parameters. So we're talking, turbine efficiency, heat exchanger effectiveness, for some of the assets. We also provide sectional KPIs like, steam turbine, HP, LP, IP efficiencies, steam flows, which can help you in really, you know, knowing where the issue is. So it's just all about giving you the power to spot the issues and, you know, fix them properly as well. All right. Very interesting.  
 
Thanks, Aisha. And at this point let's roll out, poll question number two. And in this question it's do you use an in-house method or technology for heat rate management? Simple. Yes or no? You know, are you guys, in the audience using this type of technology? Going to wait for a few answers here to come in and see where where our audience stands. Initial results are about a 60/40 split, with 60% saying yes. And it seems to be hanging right around those levels So still a lot of people still not using this technology, which, you know, I think opens up a lot of opportunity for people to improve their heat rates. If they do start. So why is software needed to reduce heat rate? And how does that work? Janet, can you give a little more background on that? Yeah, I think there's a couple of great opportunities. You know, first would be if you have heat rate improvement goals and capacity improvement goals and you don't have, you know, the CapEx for a big hardware upgrade or potentially that's in the plans. But, you know, it could be years down the road.  
 
Software is, a much smaller investment to start to see those improvements in heat rate. But even I would say for our customers who have in some cases done a hardware upgrade, they are leveraging performance intelligence, to, to operationalize that heat rate management in an ongoing process so that, you know, maintaining and not having missed opportunities that they don't have is ability to you could have a leaking valve at any time in operation. And, you know, it might be a couple of megawatts, but as you find a couple of these different opportunities, you know, it really adds up. We had a customer who didn't realize that they weren't using the best temperature for their chiller for, you know, initiating use of their chiller as they had made other changes around the plant over time. And this was a case where it was a GE person who is monitoring their thermal performance with Performance Intelligence, but able, you know, was able to notify them that even though it was just a few degrees off, that this was really a significant impact of when they should be initializing that use of the chiller versus not. Yeah, that's great insight and kind of answers my my next question, which in the title it says that this is a fast and economical solution in improving the heat rate. And from everything we've talked about so far, it kind of comes down to visibility and data that improves productivity. So is there anything you can expand on from that, Aisha? Yep. Yep. Absolutely, Aaron. So it really does boil down to, you know, the importance of visibility and how data can be leveraged to gain valuable insights. And, and let's, let's talk about a couple of features of performance intelligence... itself and how, you know, that same visibility can help you in gaining valuable insights.  
 
So the performance dashboard of Performance Intelligence, is like your performance summary hub, right? It provides you, with all the performance summaries of all the equipment, different operating conditions, ensuring that you are consistently monitoring performance throughout your plan. This will be, you know, like a high level summary. Like I said, now, if you want to dive a little bit deeper, into what exactly are your equipment doing? The thermal performance feature, provides you with valuable insights into equipment degradation trends over a period of time. And it shows you how you're equipment has been performing or the performance, you know, has evolved over a period of time. To put a cherry on top, you have some predefined set of trends that highlight the equipment with the most significant impact on heat rate, and all of this information combined, is essentially your key to promptly identify the issues and channel your maintenance efforts where they’re needed the most. So I know that was a lot of theory. So if I give you a practical example, right. So let's say the condenser is showing the highest level of degradation at your plant. Your performance engineer can deep dive, into factors like condensers, inlet and outlet, conditions, its effectiveness, vacuum levels to gather data driven insights all through performance intelligence. This way, your maintenance team can proactively plan to inspect the condenser looking for potential leakages or scaling issues and take the necessary actions during the scheduled time downtime. Yeah, that's a great example. And and so how does Performance Intelligence fit into existing strategies and improve upon them in some ways? Yeah.  
 
So Performance Intelligence has assisted a lot of our customers in transitioning, towards a condition based, maintenance approach. I remember, one of our customers, they were following a very traditional maintenance strategy. Performing offline water wash only during planned outages, without considering the actual extent of the compressor fouling. And here's where Performance Intelligence, you know, really came into the picture. We deployed the offline water wash advisor. And it recommended an earlier wash, based on the level of compressor fouling. Now, during the post deployment phase, we encourage our customer to go ahead with the water wash, as suggested by the tool. And, you know, to our satisfaction and delight. We we immediately noticed, recovery, both in terms of heat rate and megawatt perfectly aligning with the predictive outcomes from the water wash advisor. Yeah, Janet? Do you have anything to add here?  
 
Yeah. There's a there's an interesting case that we saw as well. This summer in North America related to the wildfires in Canada. I'm sure many of you know that covered a very wide geographical area. And so our power plant operator saw an impact on their performance while they were ingesting smoke, you know, as a result of the smoke, but also increased compressor fouling. And so we have a customer in, you know, affected in this region who saw that they had an earlier recommendation to do the offline water wash than they would have expected. And certainly earlier than a time based interval. So that was very insightful. We also have heard from, from customers that they're regularly scheduling the water wash. And it's it's sort of the flip side of this where they're doing it very frequently to make sure that they don't have a lot of degradation. But it's potentially too frequent in terms of being economically optimized. And so this is actually we were speaking recently to a potential customer who's interested in learning more about PI and considering implementing it. And their comment was, you know, we think this is going to tell us when we can do this less frequently. You know, in the US, this is a, you know, call it roughly a $50,000 maintenance event.  
 
And so if you can eliminate one in a year, that's a pretty significant impact. You know that that can be very important. So, many utilities have been streamlining their workforces due to budget constraints, and some have been losing, you know, long time employees due to just aging and retiring at high rates. So how can the heat rate best be managed in these cases where you've got new employees, or just there’s fewer employees behind the scenes? Yeah, I would say it's common to have a performance engineer who monitors multiple sites across the fleet. And so they can't really have eyes on all the equipment But, software can. It's where this, you know, alerting capability can really bring the issue to someone's attention quickly if they're, if they're focused at one site and an issue comes up on another site that that maybe they wouldn't see, and a week could go by. They're, they're getting the alert that tells them that that's where they should shift their attention. We we see this with our predictive analytics as well in terms of reliability, availability, software. The power generators are facing more complexity than ever before with multiple generation types and the flexible operation that that goes along with that, etc..  
 
But they aren't often getting more resources to manage that complexity. And so automation, and software in general has, has really, a lot of power to, to help us navigate through that. Aisha, anything that you would add? Yeah, I think apart from, you know, real time monitoring, as you as you've mentioned, I think it can really help in allocating resources when it comes to maintenance outages, planned or unplanned. Like I mentioned, you know, the determined performance tool will really help you in identifying, you know, the bad actor or the asset that has to be prioritized during outage. So you can, you know, really manage your resources, very well during outages as well. Great point. So at this point, we've got our third poll question. Let's roll that out.  
 
Question is do you manage thermal performance via an M&D center, a monitoring and diagnostic center for those that may not know the term, by individual plans, or currently have anyone looking at thermal performance? So how are you monitoring thermal performance? We’ll wait for these results to come in a little bit. Looks it looks like a fairly even split between those that do it with an M&D center, and those that do it by individual plant. Actually individual plant has moved up the list. Now it's about 50% are doing it at the plant level. About 30% at M&D centers and about 20% aren't doing it at this point. So that's, again, an opportunity for some people to really make some improvements that they could benefit their heat rate. So we've talked about how important this can be for, for different plants. And it seems as if it would be great for everyone.  
 
Anyone that could do this. But are there candidates that maybe don't that wouldn't be good for utilizing the software? Yeah. It's, I would say there are cases where we have not recommended Performance Intelligence after looking at the potential for value. So an example, because the value is so closely tied to the improved fuel savings and increased capacity based on improving efficiency. If if it's a single peaking site, there's maybe not a lot of opportunity there, to, to get that return on investment in terms of fuel savings. But I will say that where we have, for example, one customer with a fleet, that includes multiple peaking sites, they are leveraging performance intelligence to understand best and worst actors. You know, which unit would you bring online? Yeah. In peak demand, where would you prioritize maintenance, that kind of thing. So there is some value there. And then the other, instance that I would note is, for utility customers where they're not directly impacted by that fuel cost. There's, there's less interest and maybe less opportunity for value.  
 
But again, with exceptions to, to every rule, we do have utility customers who are using PI to do that kind of due diligence to maintain a low heat rate and, you know, pass on as little cost as possible to an end customer. So I would say to, to all of you joining us that if you think this is potentially a good solution, please do connect with us. And we can go through that investigation with you and, and help determine is there a good value story. This is where our solution architects and our subject matter experts like Aisha, can really help work through that with you. And I would say broadly, you know, we have we have a, a software suite across APM and beyond that we offer from GE Vernova. That the goal of our solution architects is to really understand your specific pain points and what software is going to add the most value. And from an adoption perspective, we see a lot of success with, you know, starting with the biggest area of concern, maybe just at one site, realizing that value and then taking the step to, you know, does this apply at other sites or are there than other products in the portfolio that that would take care of kind of the next biggest concern?  
 
So I think that's the adoption process that that we see a lot of people use, and, and really get a lot of value from. Yeah, it seems like just dipping your toe in the water would be a good way to get you on the right path. So one of the barriers, you know, that I've heard from people in the industry to buying these types of software solutions, is that they have a feeling that it's going to take a long time to deploy and and that once it is deployed, maybe the employees aren't going to embrace it the way they expect them to and and utilize it to the best of its abilities. So how do you address those type of issues with Performance Intelligence? It is about a six month deployment. It it's partly due to these detailed advanced models that are built specific to your equipment. It's not just as easy as clicking the download button, unfortunately. But it it's a it's a process that our services team leads and connects as needed with, you know, your IT or engineering team, to have connectivity to the site.  
 
So in the case of a cloud solution, this is a little bit different than if it's, it's an on premise solution with, with hardware at the site. In that case, we can either connect where there is connectivity allowed. But, in certain regions where that's not an option, we can also fully configure the software and deliver it on a server. But it's something that that our services team will take you through. So it's, it's not a lot of touch time on your end, even though it's a six month process overall. The other thing I want to note here is the change management process that I think we've touched on a little bit. The we see the most success when there's a plan to adopt the software. And managing navigating through that change, with the whole team, that's, that's very done very intentionally. So as the plant manager setting expectations, letting the team of users know that you support them. That that can be incredibly beneficial. And then as the, the engineer or the end user, making sure that you're really carving out the time to adopt something new, and reaching out and working with GE if you get stuck in any way. So it's it's having everyone on board. With the overall benefit and business benefit as well as productivity, and visibility benefits.  
 
It's I've got a quick anecdote here. I was in a conference this summer in Atlanta, Georgia, a users conference. And after all the technical sessions, we were, you know, sitting in kind of the networking opportunity with some friends who run a power plant in North America. And they were noting one of their colleagues who, who wasn't there, but who had been at the plant, you know, for something like 40 years. And, and they were doing this very affectionately, but they were saying, you know, how, you know, so-and-so doesn't want anything new. Totally resistant to any new process, new tool, etc. until he sees the value and then he becomes the biggest cheerleader or the biggest advocate telling everyone about, you know, you've got to use this new thing and I just appreciated it so much because I was like, you're telling the, the journey of, of software adoption, like you're telling the story and, you know, totally un-, un- provoked or, you know, we weren't talking about software specifically.  
 
So I appreciated that. Yeah. Aisha, do you have anything to add on this topic? Yeah. Yeah. So, so so I just mentioned, you know, the implementation cycle can take up to, six months and and again, you know, as she's mentioned, it's because our approach, it relies on physics based models, which are anything but one size fits all. Right? So, so we use, the plans, heat mass balances and the design data sheets amongst all the other design information available, which is, you know, collected as part of our site surveys when the project is kicked off. And, and the models are very customized to your specific configuration and, and operations. When these models are developed, they, they go through a very exhaustive cycle of validation at different operating loads. Right. Whatever is the range of operation. And we, we go through this, this thorough exercise, to make sure that the results which are coming out of these models, you know, those are the baseline, really, that they're very accurate and, and and robust. In terms of change management, which is, you know, a very important aspect for all our customers. And we spend a lot of time, you know, discussing this with our customers and, and our adoption journey. It really begins at that kickoff meeting with you.  
 
Right. And and I say this because, the implementation team, the subject matter experts, the data integration team, they work side by side with you throughout the implementation process, throughout the model development and, model validation phases as well. And, and we do this proactively. So that, you know, you are very comfortable with the results, which are coming out of the models. Because it's not really, like I mentioned, not a one size fits all. And and we need a lot of tuning to make sure that, you know, we get the best possible results out of these models. During implementation, we also conduct Performance Intelligence awareness sessions. So that you that so that you're very comfortable with the different features, the different tools, of the software itself. So that, you know, when the solution is deployed there are no surprises. It's just seamless adoption. And when it comes to our enterprise customers, we go one step further and we conduct these awareness sessions, with, with each side. Because we really want every member in your team to be familiar with the software, to use it so that, you know, they can so that, you know, they, they don't just log in once a month, but it becomes a part of their, you know, day to day, activities.  
 
Apart from these awareness sessions, once the solution is live. We also have dedicated, training sessions, which are once again, led by our subject matter experts. So that, you know, you're very, very so that you yourself become an expert when it comes to, using the software. After deployment, after training, you don't have to worry. We’re not going to go, you know, anywhere. There's also a post deployment support phase, where we keep regular communication, with our customers to answer any questions they have. To, you know, really help them in getting valuable insights from the software. So our goal is, you know, not just to deploy the software. It's not just a one time solution. I think, you know, it's a it's a partnership between GE and their customers. It's a journey. And we really want you to know why you're clicking that button or why are you going to this feature rather than just, you know, click this button and this is how you navigate the different parts of the software. Yeah. I think that customer support is a really important piece of that puzzle. So how does this performance, intelligence integrate with other GE Vernova digital software? It's, it's in our Asset Performance Management suite of products.  
 
So some of you may remember that that previously this was under Operations Performance Management, OPM. And we've we've recently, last year, migrated into APM because of the synergies that we see with reliability and with other products for our customers who have a broader solution set. But but as an example, when you get an alert in PI, it's in the same alert screen as your Smart Signal or Reliability+ alerts. They both leverage what we call blueprints and all of that navigation is the same. Now you can also see that alert in a dashboard view. But as you as you navigate the software, if you if you want to see that full list together, you can. It works the same way in terms of creating a case from an alert where you, you want to take further action and you want to to, go through that workflow with the right individuals connected, and documenting through that process. So it's it's all integrated together. The other thing that I'll mention is, the summary dashboard that Aisha has been referring to is configurable by whoever you choose to be to have that admin level access in the software. So even after it's fully delivered, if the person using it wants to see something differently, those changes can be made. And that's part of the, you know, making that type of change is part of the training that Aisha is referring to.  
 
Yeah. Very interesting that that you have that capability after the fact. Now some people in the audience may be asking, you know I've got a performance guarantee in a, you know, customer service contract. Do I really need a thermal performance tool? How would you answer that? Yeah, I would say in some cases, No. We have customers who, as you know, I mentioned before, utilities in particular. Who are less impacted by a fuel cost. And they believe that their performance guarantee meets their goals. And so that in in some cases is enough. If you have that agreement and you are someone who's wanting to maintain a low heat rate and improve fuel savings, there's, I think, a lot of opportunity beyond the guarantee. Which really says, you know, on on some periodic rhythm, there's going to be a performance test if there's, if the equipment falls short. And often this is just the gas turbine, not at the plant level. Then there will be liquidated damages paid for that shortfall. It doesn't, in that case, tell you where the issues might be. And it doesn't give you those insights over time to get back the, you know, 2, 3 and 5 megawatts that we've been talking about. So maybe you still need the guarantee, but there really could have been a lot more fuel savings in the interim. Yeah. So so what really makes this Performance Intelligence tool unique? Is there anything that you can point to? Yeah, I think one of the primary factors that sets Performance Intelligence apart, is our is our modeling approach, which, which, you know, I've, I've highlighted previously as well.  
 
These are powerful thermodynamic models. They're developed, you know, using, plant specific design information like heat mass balances, design data sheets, performance codes, performance test reports. And we spend a lot of time and effort in, in validating these models, thoroughly, so that they generally represent a digital replica of your, of your, of your plant. And the other thing I think which, which makes this software unique is the active engagement of SMEs throughout the implementation. So from the time of kickoff, conducting awareness sessions, conducting PI trainings, and then also supporting post deployment. We really feel that this is something that makes this software unique. You're getting, you know, on the go recommendations. We're encouraging customers, on on following the suggests the suggestions provided by the tool. And I think this kind of engagement from an industrial SMEs is, is is missing in other products. Yeah. I think that that handholding can really be important to making a successful transition. So what does the roadmap look like? What are your plans for performance intelligence? We have a feature that just came out this year and I'll I'll call it a beta version at the at the moment, we haven't released this to all customers, but it's all about performance test and reporting. So you can perform a standard PTC, performance test, for example.  
 
And when you go into the software, you would you would select the dates and the times that the operator ran the test. And Performance Intelligence will tell you where the criteria met. And it actually lists each individual criteria. You can click into each one and see why it wasn't met if if it wasn't, and you can also in addition to the standard PTC tests, you can develop your own testing criteria as well. And then you can download the report as an Excel file, just, you know, click a button, download. So very fast report generation. And you can also see the previous performance tests side by side. So if I'm testing every six months and I want to see the last four and what the changes were, it's easy to see that in a single review. So I think it's a great automation tool, that that's going to really increase productivity. And this came out of specific customer requests from multiple customers for this functionality. So what we're going to do, when we look at future roadmap, say 2024, it's really continued to focus on the user experience. I think that there is a ton of great functionality in the software. And now in the in the vein of continuous improvement, we're going to continue to look at how can we get the user from the point where they're seeing something initially to the to the point where they're they're seeing those detailed, you know, that detailed data, etc., as quickly as possible. And how we're doing this is where we're starting with, you know, the this product is co-developed with performance engineers in GE Vernova. And most of them, several of them have spent decades as performance engineers in power plants themselves.  
 
And so we're working with that team in our and our user experience team to develop some proposed changes, and then taking that to existing customers to get their input, because ultimately it's it's about the end user, but it's hard to approach people sometimes with a blank sheet of paper. And so we'll come with some proposed changes and then build off of that feedback from there. That sounds like a great way to do it, you know, to get some initial points and then focus and and develop them from there. So at this point we'll transition into the Q&A portion of the program. Thank you both. Janet and Aisha. That was really a great presentation. And you really answered a lot of good, or provided a lot of good information. I'd also like to point out to the audience that we have a couple of interactive features that you can download from the handouts tab. So if you look on the platform, those handouts will be active now and you can take a little bit of time before you leave the platform to download these interactive features that are available.  
 
They'll also be available on the website after the program, in case you forget. We've had a number of questions come in. And so during the course of this, portion, we'll answer as many that that we can. Any that we don't get to, due to time constraints, we'll answer via email after the program. So rest assured you will get an answer to your question. But, to begin, let's get right into it. First question is, does this software also address reliability in addition to performance enhancements? I can start on that and then I'll let you know you can fill in. So it's we have a separate product kind of under the same umbrella of reliability and performance, that we call Reliability+ or SmartSignal. That's really focused on reliability and availability. And I think the two are very complementary to each other.  
 
Now, there may be some cases where Performance Intelligence would alert you to a performance issue that's also tied to an equipment issue that would cause reliability problems. But really the the bulk of of that predictive analytics for reliable is in that Reliability+ product. And, Aisha, I know you work closely with both so feel free to add. Yeah. So I think, you know, I see a lot of value, especially, in customers that use, you know, both of these solutions together. And we've developed, you know, templates with them, that they can save, which, you know, which help in, you know, giving them additional value. Right? So you have some recommendations from the performance side and you can tie closely to the reliability side. And just one thing I'd like to add regarding the Reliability+ like Janet mentioned, it's an early warning detection system. So you know it's really helping you in in buying time to know when this equipment might fail. And you can, you know, plan all the maintenance actions well in advance to avoid any downtime or surprises. Okay. Thank you both. What is the difference between this Performance Intelligence Pi and software like ETA Pro?  
 
Yeah, I think some of the things that I would note as differentiators, the, the alerts and diagnostics that we've discussed, that, that alerting capability that comes with a recommendation and, and really helps get to root cause faster. We have, a couple of what we call economic advisors that Aisha and I have discussed a little bit, the offline water wash, as well as inlet filter that really shows you as a future prediction, what's the optimal time to to do this maintenance. And we're we have plans in the longer term roadmap to continue building out, for additional equipment like condenser, HRSG, etc.. I would also note the, the ability to, to be accurate at part load and detect issues at part load, especially if we're talking about GE equipment, because our performance model performance engineers also developed you know helped design the equipment itself. And so there's there's certainly a higher level of accuracy there, with GE equipment though, the solution is applicable across all OEMs. And lastly, I would say if you have APM, as we noted, this is this is integrated with the rest of your products. So it's it's a, it's an all in one, you know, easy to, to operate. Aisha, anything that you would add? I think you've, you've, you've covered it quite well and, and the same point I'd like to emphasize is the accuracy on, on the, part load. So you know, since our models are physics based thermodynamic models. We try to make them as accurate as possible to a range of operating load. So. Well, I mean, they won't be 100% accurate at, at part load, but they would be very close to those numbers.  
 
Okay. Thank you. Next question is what steps are what steps you are considering for the deployment of a predictive model? I touched on that a little bit just in the last answer, where I talked about the economic advisors. So those are forward looking. And we do want to add more of those maintenance opportunities in addition to offline water wash and inlet filter. Otherwise, generally Performance Intelligence is less predictive. That's more the functionality that you get from Reliability+. Where they're doing that prediction and actually can predict, often times weeks or months into the future when there's a potential reliability issue, that could come up down the road. So, Aisha, anything else on that one? Yeah, I think I, I think regarding the thermodynamic models, I think there's just one point. I'd like to add that we also are following industrial standards, AMSE standards for the gas turbine, PDC But as you mentioned, they're mostly, you know, performance based models rather than predictive. All right. How much is scan time of this software? I'm not sure I quite understand. What they mean by scan time. Aisha? Yeah, me neither. But, but I mean, if the question is, how much of data are we feeding into these live models? Since these are, you know, the the prime agenda of this tool is to gauge performance.  
 
And as we know, performance doesn't really change every second, every minute. So our best practice is to kind of take an average of the last which is coming in, from your plant life. Take an average of that. Some customers prefer taking the timestamp value. So, you know, it really depends on your preference. But we usually recommend, to take an average of the last and feed them into the models. And like I mentioned, the best way to use the software is to understand the performance over a period of time, rather than looking at it minute by minute. Yeah, it's also it's often more a longer term look, other than maybe when you're getting an alert of something that's been detected. And if for whoever asked the the question, if we missed it, please refer to, reword and put in a little bit more detail. Sure. And, I know during your presentation you gave some examples, but this attendee would like, could you furnish a couple of instances where this software has effectively enhanced heat rate? Any specifics that you could give from from past experience?  
 
Yeah, well, I can start. So I remember for, for one of the customers, they had an air cool condenser on their site. And then they noticed that, you know, their megawatt, ST megawatt generation in particular, they were they were not meeting their target. So using the different KPIs provided by the model, we, we started, examining, the different parameters. And, and it turned out that, you know, the, they were not operating their ACC, as per the, let's say, the performance curves of the condenser itself provided by the supplier. Now, since our models were based on these performance curves. Right. So they were they were suggesting, that this might be the issue that you're not running the ACC fans in a very optimized way. So we we did a bit of adjustment in that analysis. There is a tool called What If. Which is kind of, you know, a digital twin where you can play around with the inputs, change the inputs here and there. Ask the software to simulate the results, and you can get the results at different simulations. Right. So we, we did some runs on And through all these different scenarios, we were able to, optimize the way they run their ACC, which helped them in reducing their auxiliary consumption as well. And they noticed an improvement, you know, in their, ST, steam turbine, generation as well.  
 
This is one example which, you know, just happened recently. Off the top of my head. Great. And I know we're coming up on the top of the hour. I would like to ask one more question. It says is the SME essential for overseeing performance monitoring through the software? Can you fill, I mean, obviously it's going to be very helpful. And and it's going to be able to provide a lot of great insight. But I am assuming you can train these plants to have an expert of their own that can really monitor this stuff. What what would you say? I think someone with just a bit of knowledge about performance, someone who can differentiate performance from operations. Right. Because it's not something that you would monitor minute by minute. I think someone with just basic background of thermodynamics, a mechanical engineer fresh out of college, who would be able to get maximum value out of this. And if it's an SME who's monitoring, that's, that's an ideal situation. Right. All right, well, I want to respect everybody's time, but thank you both. I mean, I feel like this was really an informative session and you provided great insight and answered some, some questions. We did not get to even half of the questions. So many of these will be answered via email after the session. I apologize for that. But, again, I want to thank you both.  
 
I want to again, thank GE Vernova for underwriting today's event. And thank everyone for attending. Aisha, do you have any last words you want to leave the audience with? Well, thank you very much for for listening to us. And, you know, we will do our best to answer all the questions. And and in case we we're unable to, you know, you know where to find us. So to do that, if you have any further questions. And, Janet, I'll give you a chance to to leave some last words as well. Yeah, I'll just second that. Thank you. And hope to get a chance to partner with you in the future. And really bring a lot of value. Okay. Well, thank you both. And, again, thank you, to all of the attendees. I hope you found the presentation beneficial. And I hope you have a great rest of your day. Thanks.