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Special Edition: Artificial Intelligence in the Modern Digital Utility with Bhavani Amirthlingam of Ameren and Jeremy Renshaw of EPRI [an Energy Central Power Perspectives™ Podcast]

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The ‘Energy Central Power Perspectives™ Podcast’ features conversations with thought leaders in the utility sector. Each two weeks we’ll connect with an Energy Central Power Industry Network...

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  • Oct 13, 2021 12:15 pm GMT
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This item is part of the Special Issue - 2021-10 - Advances in Utility Digitalization, click here for more

Artificial intelligence (AI) has transformed every industry it's touched, from commerce to transportation to social media, but arguably some of the most widespread impact that AI-enabled tools is on the electric power grid. Amid a time where utilities are seeking ways to make the supply and demand markets efficient, optimize the maintenance of immense stretches of assets across their coverage areas, and find ways to integrated clean energy resources, AI appears to be one of the key tools that will unlock new possibilities.

This digital topic is one that can quickly become complex and hard to understand, so the Energy Central Power Perspectives Podcast wanted to bring in some of the undisputed leaders in this space to help break it down for us and highlight the trends and opportunities that utilities everywhere should be honing in on. To do that, we were lucky enough to get into the podcast Bhavani Amirthalingam, the SVP and Chief Digital Information Officer of Ameren, coming off of the honor Forbes gave her as one of the top 50 innovative technology leaders this year. Joining her is one of the utility's key utility partners, Jeremy Renshaw of EPRI. Jeremy is the Senior Program Manager of Artificial Intelliigence at EPRI, and along with Bhavani he's helped to accelerate the impact of AI and machine learning on Ameren's grid that serves 2.4 million electric customers and 900,000 gas customers. These two titans of utility AI join Matt Chester of Energy Central in the podcast booth to discuss the past, present, and future of AI on the modern digital grid. 

A special thanks to EPRI for supporting this edition of the Energy Central Power Perspectives Podcast. 

Prefer to Read vs. Listening? Scroll Down to Read Transcript. Below the main episode you'll also find an exclusive Bonus Clip just for readers on EnergyCentral.com.

Key Links:

Jeremy Renshaw’s Energy Central Profile: https://energycentral.com/member/profile/jeremy-renshaw

EPRI on Energy Central: https://energycentral.com/o/EPRI

Learning to Run a Power Network with Artificial Intelligence: https://energycentral.com/c/iu/learning-run-power-network-artificial-intelligence

5 Artificial Intelligence Grand Challenges for the Electric Power Industry: https://energycentral.com/c/pip/5-artificial-intelligence-grand-challenges-electric-power-industry

Did you know? The Energy Central Power Perspectives Podcast has been identified as one of the industry's 'Top 25 Energy Podcasts': https://blog.feedspot.com/energy_podcasts/

 

Bonus Clip, Only Available to Listen to Here on EnergyCentral.com

 

Transcript

Matt Chester:
Hello, and welcome to the Energy Central Power Perspectives podcast. As regular listeners know, this show comes to you as a source for in depth discussion with leaders in the energy and utility industry. My name is Matt Chester, Energy Central's community manager and podcast producer and I'm excited for today's episode as we get to cross off another bucket list podcast guest, a celebrity in the CDO CIO space if you will. Having recently been featured in the Forbes list of the 50 most innovative CIOs. And on top of that, we're also going to have the privilege of speaking with a second noted leader at the intersection of artificial intelligence and power utilities. It's a real two for one episode. So you already know it's going to be packed with great information and conversation. The topic of AI in the power sector could not be more important, timely or promising. AI is being used by utilities for everything from optimizing the deployment of field workers, prioritizing vegetation management, immediately detecting issues anywhere across the grid, communicating with customers, citing new generation projects and so much more.

Matt Chester:
To keep us focused and directed on the most important utility AI discussions of today though, we want to introduce our esteemed guests. From the utility side are being joined by Bhavani Amirthalingam the SVP and chief digital information officer at Ameren. Ameren serves 2.4 million electric customers and 900,000 natural gas customers across the Missouri and Illinois regions and Bhavani is leading the charge in ensuring that the latest and greatest in digital technologies are being used to optimize that process. With over two decades of experience leading digital and information technology across both energy and non-energy companies, Bhavani has really created a well deserved reputation in this space. As I mentioned, Forbes named her as one of the top 50 innovative technology leaders this year, and we couldn't be more excited to have Bhavani with us today. Welcome to the podcast.

Bhavani Amirthalingam:
Thank you so much. Thanks for having me and I'm looking forward to it.

Matt Chester:
Great. Well, we're thrilled to have you. And like I said, if that wasn't exciting enough, we're also joined today by someone from one of Ameren's key partners in these smart technology implementations. I'm speaking of course of EPRI and specifically about Jeremy Renshaw, the senior program manager of artificial intelligence at EPRI. Frequent visitors to the energy central community platform will recognize Jeremy for his regular and high value contributions keeping us all informed about what's going on in the world of utility AI. Jeremy has been with EPRI since 2012, where he worked on nondestructeive evaluation and managed their used fuel and high level nuclear waste for a number of years before taking over the company’s AI work. Today, his efforts are focused in AI and machine learning technologies anywhere they can make a difference in the electric power industry to enhance safe, reliable, affordable, and environmentally advantageous power generation, transmission, and consumption. Jeremy, we're thrilled to have you with us today as well.

Jeremy Renshaw:
Thank you, Matt. I'm really excited to be here with you and Bhavani.

Matt Chester:
And before we dive too deeply into this, we do want to give a quick thanks to EPRI for making today's episode possible. EPRI provides global thought leadership, industry expertise and collaborative value to help the electricity sector identify issues, technology gaps, and broader needs that can be addressed through effective research and development programs for the benefit of society. Bhavani, let's start with you. Can you please help us to ground ourselves with the definition of what AI is and why Ameren is interested in this technology?

Bhavani Amirthalingam:
Sure. Artificial intelligence quite frankly, has been around for a long time and what it is, it's basically just machine displayed intelligence that simulates human behavior or thinking and can be trained using data and to solve specific problems. And so machines, as we know, can process more data. So greater volume, greater velocity and greater variety of data than the human mind can imagine. AI has helped take automation to new levels. While it's been around for a long time, as I mentioned earlier, what's really changing the game is just, if you think about the shift in compute and storage capacities over the last several years, that significant exponential growth in the ability to process data has really defined, taken AI to the next level. And if you think about volume of data, quite frankly, the volume of data available has outpaced even the ability to collect it and it has certainly outpaced the capacity for human processing.

Bhavani Amirthalingam:
You also have to be sensitive to, what we call, the life of the data. Data decays very rapidly with time. So to see things around technology that evolve around distributed processing, automation and AI now are critical to utilizing most of this data and time frames that the data is most valuable. That kind of gives you a little bit, just broader view of AI in general. When you think about Ameren, we lead, quite honestly, our industry overall. Few things are top of mind for us when we think about our customers. It is reliable, affordable, safe, secure, clean energy. So leveraging AI to really enhance the reliability and resiliency of our grid, helping our customers monitor energy usage, driving energy efficiency efforts, driving customer affordability, enriching customer experiences are all key items on our AI agenda.

Matt Chester:
And that's all very interesting, but from an outside perspective, it definitely seems like there's a lot of hype around AI where it can promise to do just about anything. So I'm curious about what some of the real world applications are that we can use AI on the grid today or in the near future. Jeremy, perhaps you can jump in on this one.

Jeremy Renshaw:
Absolutely. Matt. So you're right. It seems like every time you turn around, people are promising that AI can do everything. And certainly there are many things that AI can do to help us. AI, machine learning and data techniques are very valuable when we have lots of data, we're able to train algorithms based on them. One of they're not very good doing yet, is mimicking human intuition and our ability to think creatively, but as Bhavani mentioned, they're very good at processing large amounts of data very quickly, much faster than what a human could do. So there are a few things that we're working on and I'll just cover three of them today. I mean, there are many different projects ongoing at EPRI right now, the first one is looking at wind turbine gear boxes. So if you're looking at a wind turbine, they're very high up in the air, you don't want to go out into these remote locations very often, you don't have to.

Jeremy Renshaw:
So if we can monitor what's going on with a wind turbine farm and help to optimize how often and how frequently we go out to these wind farms, then we can save a lot of money and maintain reliability. So one of the things that we're working on at EPRI right now and doing this in combination with Ameren and other utilities, is looking at physics based machine learning, where we can bring machine learning models to wind turbine assets and detect what's going on using all of the sensors that are onboard to detect early stage faults and lower cost, easier to replace components versus larger scale degradation later, where replacement costs can be upwards of $350,000. So if we can save significant amounts of money, but also optimize how frequently we go out to get these turbines replaced on the right basis, it helps utilities to offer lower costs, save reliable energy that's very highly resilient. And Bhavani mentioned that, and this is one of the things that we're working on together to achieve that goal.

Jeremy Renshaw:
Second, transmission and distribution grid assets are spread out all across the world and there are many different potential faults that can happen with these assets, anything from squirrels going on lines, to woodpecker holes, to various different components that can degrade or corrode. So one of the things that we're looking at doing is identifying the assets that are degrading through the imagery that we have and doing this to not only optimize the data collection process of using drones instead of helicopters and manual surveys, but also looking at with these different systems that we have. With drones, we're getting lots and lots more images than we've ever had available. So it's a data deluge, if you will, just this huge tsunami of data that's coming at the analysts and inspectors.

Jeremy Renshaw:
So, whereas we used to get maybe a few hundred or a few thousand images. Now we can get tens of thousands, up to millions of images of transmission and distribution assets. So it takes significantly longer to process these images, but that's something that machine learning and artificial intelligence can help us with, but we need to be able to first train these algorithms to identify what is defective and what is good. Do we have finally dis clotted , do we have an insulator that's cracked or a marker ball that's broken. So what we need to do is bring together very large data sets and not only bring the data together, but label the images so that we can train machine learning models to be able to understand what is a healthy component, what is a degraded component.

Matt Chester:
That's all so fascinating, Jeremy. And Bhavani, I want to turn it back over to you because we heard earlier how you're using AI to monitor your wind turbines. So I'm curious if you can tell us a little bit more about this project, as well as other relevant work at Ameren with AI tools to kind of bring it all together.

Bhavani Amirthalingam:
Happy to... I'll touch on, elaborate a little bit on what Jeremy did a fantastic job walking through, the business objective and goal and why we're doing what we're doing around our wind turbine initiative, but really the goal there is leveraging machine learning for early gearbox failure detection and we can have significant cost savings avoiding upwards of $350,000 in costs as Jeremy indicated earlier. What have there is really, we have wind speed, temperature, pressure, realtime power generation, and vibrating, monitoring sensors installed. As part of our predictive maintenance software that we have, we're able to do early detection of components savior, wind turbine, gear boxes, and really bring a higher level of confidence in predicting the probability of gearbox damage and improves overall model accuracy. It really is a partnership for us with several folks to be able to make this the our part of Ameren products, the innovators network and this is one of their key initiatives that we've been working on.

Bhavani Amirthalingam:
So as we continue to expand our clean energy and our wind renewable footprint, this is key capability that we'll continue to enhance. Two other initiatives I want to just touch on is one PingThings, that we actually are... An effort that we are partnering. Again with EPRI on, it's actually a collaboration between PingThings, Ameren and EPRI and the core of this is really again, leveraging smart meter data. So we've got millions of smart meters deployed across our service territories and the goal here is to be able to take the millions of screens of smartening the data that we receive, and being able to ingest that data, what we've done here, really in this PingThings file is about taking a year worth of this data and implementing it in this platform to test and enhance several large scale machine learning algorithms that leverage smart meter time series data.

Bhavani Amirthalingam:
Just to give you a feel, I mean, you're talking about 12 months of data for over a million smart meters that we pulled in and we're reading voltage, low current and reactive current measurements every 15 minutes. You can kind of think about the volume and velocity of data, that this platform is processing. And the real... If you go back to kind of the what we're defining things here, we're looking to develop prediction for correcting inaccurate space designation and need a transformer mapping because what that helps us do is it really helps us go more towards creation of a hyper accurate network model. Network models are extremely important for utilities, high business carriers to continue to drive higher degree of accuracy there. Even foundational enable these smart advanced tools to cross the footprint.

Bhavani Amirthalingam:
Since there haven't been a kind of best in class approach in this space, this pilot basically provided the ability to test rapid prototyping and experimentation through this partnership. So very excited about that. Another project I'll touch on is what we call the research project. Again, another collaborative effort within Ameren, Recurve and EPRI. What they're doing there is really it's tying back to our Ameren Illinois energy efficiency business program and leveraging again, AMI, marking their data better to support thriving enterprise. We've specially worked with team through the pandemic over the last 18 to 20 months giving customers really, for us to understand increasing the depth of customer target and step back and look at it. We've seen business showing an average of about 14% reduction in energy consumption in the early months after Covid-19. You look at individual accounts, they can range anywhere from like a 100% reduction to a 200% increase.

Bhavani Amirthalingam:
So, obviously huge range over here and through this collaborative effort we're able to focus analytics on including uptake of live measures and meetings, ventilation and air conditioning, HVAC measure for our customers. And really, the underlying goal, as I mentioned earlier, is identifying those customers would benefit from efficiency retrospect like with high percentage of savings, and just reducing administrative costs and driving this higher efficiency for them.

Matt Chester:
Excellent and I want to hear from Jeremy on this too, it sounds like the data challenges and also the data opportunities are key area and an area focus that all the stakeholders need to come together to solve. So Jeremy, from your and EPRI's perspective, is there a concerted effort to engage in all these dataset combinations and unlocking what they can do?

Jeremy Renshaw:
Yes, absolutely. One of the things with artificial intelligence is that data is key and one of the items that I would say is that many electric power utilities almost suffer from very high reliability. What we're trying to do with artificial intelligence is help to identify areas where we can get better and identify faults and early stage degradation, but because there has been such a focus for so many years on these items, there's not a whole lot of data that any individual utility has on what faults and failures look like because they do such a good job of maintaining these assets.

Jeremy Renshaw:
And if you look at the power availability, it's something like 99.97% if we exclude storm related damage. So in terms of normal system operation reliability it's really just off the charts. There's very few things that can compare. Where that gets challenging is that with gathering data sets, no individual utility typically has the amount of data required and Bhavani mentioned this earlier. So with one of the things that we're trying to do is bring together these different data sets across utility fleets from around the world and help label and identify those data sets for degradation or indications or signals of interest so that we can help to train artificial intelligence algorithms, to be able to help us to identify these early stage degradations, faults or off normal conditions earlier so that we can respond to them in the most appropriate manner.

Jeremy Renshaw:
One of the things EPRI is doing is bringing together what we're calling the EPRI10 data sets or the 10 most valuable data sets for the electric power industry. And just is an example of what some of these are. These are looking at everything from the T and D assets that we talked about earlier to power plant, operational data, satellite data, advanced metering infrastructure data that Bhavani just mentioned, and many others. So we're trying to bring these different data sets together from around the world and then release them out to the AI and electric power industries to be able to more accurately, more quickly and more cheaply develop these algorithms. And an example of why this is important is if we go back to our transmission and distribution image asset database, the estimated value, or if you will, cost of bringing all of these data sets together from the different utilities is higher than $10 million.

Jeremy Renshaw:
So if you imagine, if any AI developer were to try and put this together, they'd have an initial investment of $10 million, which is a huge barrier, especially for small startups. And then if they try to go and deploy this, that means that the cost for utility and hence for all of us who pay an electric bill every month goes up pretty significantly. Whereas if they can get in for free or at a very low cost to be able to start developing these algorithm, the cost goes down for everyone. So this is an area where EPRI, Ameren and various other utilities are all working together to bring these data sets together, to provide these out to the AI and electric power industries for really the benefit of everyone.

Matt Chester:
So continuing on that topic, Bhavani going back to you, can you talk about how Ameren is organizing their data to make the most of it for AI or any other applications?

Bhavani Amirthalingam:
Sure, absolutely. I think couple of things I'll touch on. Truly for data to provide value to an organization, it needs to be complete, accurate, understandable, accessible, right? So these are all key aspects that we focus on. When you think about how we organize data, how we leverage data, our goal and focus is to start with building data architecture and data governance, at every implementation and taking kind of a data first mindset on what data is captured, how is it cataloged, where is it stored, how does it access operation user analytical use? So thinking of those aspects, as well as thinking about how do you drive self service from a data and analytics standpoint. So that part of it is like really up skilling the organization as well and training your workers across the company on how to access, consume, analyze, leverage this data is critical. So I'd say you think about those key aspects, Jeremy did a fantastic job talking about just this collaboration that's needed for us, as well as just every utility, our industry, 24/7 being always honesty, reliability needs for our customers.

Bhavani Amirthalingam:
We truly need large volumes of relevant data to train models, to enable AI, to scale, to continue to enhance reliability. So many times no single large utility would have those sufficient source of data on their failures or events in order to train models and the partnership we have with EPRI and the work we've done with them and continue to, I think it's really critical for the future. Other, I just indicate in terms of efforts, we've made significant progress in terms of data and analytics. When you think about our customer space and our grid space we've built out and continue on a journey of a cloud data lake environment, as we have seen an exponential growth of our data, and that's a foundational effort that enabling a lot of the analytics and automation and AI that we believe will increasingly play an important role in our operations, as we've all just discussed several opportunities here, that when you think about it, as it relates to customer experience and reliability and affordability for our customers.

Matt Chester:
Great. And let's just cut to the chase here for those who are listening in today, who are excited about what you guys are sharing, how can they keep tabs on what's brewing in the world of AI and electric power. Jeremy, I believe you have some specific events you guys are working towards right now.

Jeremy Renshaw:
Yes. In fact, just recently at the end of September, we had our AI and electric power summit. And within that summit, we released a series of grand challenges for the AI and electric power industry. And we'll have ongoing meetings on those as well as we're starting to plan our 2022 AI and electric power summit. And that will be somewhere in a to be determined location in Europe. And we're really looking to bring the global community, get together with that meeting and these grand challenges. And it's very easy to keep up to date on these. Can either go to our website, ai.epri.com, and on our website, you can sign up for our newsletter that comes out once a month, and that provides all the information that you would need on our events, on ongoing projects and other updates.

Matt Chester:
Great. Thanks for that. And now, as we're coming close to the end of the podcast, both Bhavani and Jeremy, we want our audience to come away from this episode, not only knowing AI better, but also knowing you, the experts, better on a personal basis. So with that it's time for our crowd favorite lightning round. I'm going to throw out some quick, get to know you questions and I'll look for you each to provide your one word or one phrase answers. Are you both ready?

Jeremy Renshaw:
Sure.

Bhavani Amirthalingam:
Let's go.

Matt Chester:
Great. Let's do it. To keep it simple since we have two of you on, let's have Bhavani answer each question first and then Jeremy will follow up. So here we go. What is your favorite holiday?

Bhavani Amirthalingam:
Christmas.

Jeremy Renshaw:
I'm going to cheat and go with two. I'm going to go with Christmas and with Halloween because I love them both.

Matt Chester:
Fair enough. What is your go-to snack at the vending machine?

Bhavani Amirthalingam:
Kit Kat.

Jeremy Renshaw:
I'll go with that Twix bar.

Matt Chester:
Excellent. What's some thing that your coworkers, listening into the podcast today, may not know about you?

Bhavani Amirthalingam:
My fear for water and height.

Jeremy Renshaw:
For me, I like to build really cool things for my kids like playgrounds, Treehouse, obstacle courses and such.

Matt Chester:
Terrific. What would be your dream job if not working at Ameren or EPRI?

Bhavani Amirthalingam:
For me it would be an entrepreneur. Doing something where I'm leveraging technology to solve whatever it is that the world needs at that point.

Jeremy Renshaw:
And for me, I think I'd say food critic because I love eating.

Matt Chester:
Excellent. Well then let's finish with this. What are you each most passionate about?

Bhavani Amirthalingam:
I think I'm passionate about the change that is ahead of us. I just look at the last 18 months, I think it's been amazing. Well, it's been challenging itself has been amazing to see how the world has come together and I have more hope for our future collectively than I've ever had. And so I think I'm passionate about the things that we can all do collectively for just making this a better place.

Jeremy Renshaw:
Well, I think I'm right in line with Bhavani, I think the thing that I'm most passionate about is really trying to make the world a better place. We've had so many people who've come before us that have provided so many great things. Whether it's electricity, cars, planes, trains, indoor plumbing, the list goes on. I really want to be a part of making the world a better place for future generations.

Matt Chester:
I love that. So you both did perfectly well and in our lightning round. It's always a fun rankle and because you went through it flawlessly and you're good sports with us. We'll give you the floor for the last question. Where do you see AI heading in the coming years both from a utility and an R&D perspective?

Bhavani Amirthalingam:
I touched on this earlier, but if you look at bottom line, it's the purpose, you look at our purpose, the mission. For Ameren and in almost every utility, it's delivering safe, secure, clean, reliable, and affordable power to our customers. That's at the heart of our purpose and mission.

Bhavani Amirthalingam:
So leveraging data, to predict and prevent equipment failures, that's just going to result in greater safety and reliability, using data to drive better customer experiences and lower bills, drive energy efficiency and affordability for our customers is happening now and will only continue to accelerate. Data can guide where we put distributed energy resources on the grid, driving greater reliability and efficiency for the grid, as well as helping us build a cleaner grid together. So using advanced technology, Jeremy touched on this like drones coupled with data to be more efficient and effective at things like vegetation management, equipment inspection, I think they're happening in pockets. I just think this is going to be done across utility at scale. So these are probably a few examples that are happening in pockets and what I'm excited about and what I see is going is just happening at scale across our industry.

Jeremy Renshaw:
Yeah. And I promise I'm not trying to steal Bhavani's responses, but I think we're just very much in line, we have very similar goals. So in the future, we definitely want to use artificial intelligence, machine learning to improve flexibility and resiliency, reduce carbon emissions and environmental impacts while we improve safety and reduce costs. I mean, I think there are many things that are ongoing right now to help get us there. Both the things that we talked about today, as well as other efforts that we have that are ongoing in terms of developing training for AI and data science, looking at improved forecasting of both energy usage and weather forecasting and merging those together to optimize the usage of resources. And really the list goes on.

Jeremy Renshaw:
There's so many things that we're looking at and working with utilities on today to be able to develop the technologies tomorrow, while of course trying to avoid something like Skynet. You can't go through an AI podcast without mentioning something on Skynet, but really we're looking at how can we develop these advanced tools into technologies that help enable our workers to do what they do best and take away some of the mundane and time consuming tasks that artificial intelligence and other automation technologies can help with.

Matt Chester:
Terrific. Well, Bhavani and Jeremy it's been wonderful having you both on the podcast today, the complimentary perspectives from the utility side, as well as from the solutions provider side, gave us really well rounded and fleshed out level of insight. So thank you so much for that. I'm sure the audience will have just as much fun listening as we've had recording today. And perhaps this is just the beginning of an annual pilgrimage where you both can make it back to the Energy Central Power Prospectus podcast. And by then, who knows what'll be the headlines drawing attention in the world of AI this time next year. But until then again, thank you so much for joining us today.

Bhavani Amirthalingam:
My pleasure. Thank you so much for having us, Matt really enjoyed the conversation.

Jeremy Renshaw:
Yes. Thanks Matt. This has been great. Thank you Bhavani.

Matt Chester:
You can always keep up with what Ameren and EPRI are doing via the energy central community platform where hopefully we can count on Bhavani and Jeremy to keep us updated moving forward. And if you have any questions or comments, the comments section of the energy central post with this episode is open and on behalf of the entire energy central team, thanks to everyone for listening today. Once again, I'm Matt Chester. The most relevant conversations of the utility industry today are happening in the energy central community. So we look forward to you joining us and sharing your insights at energycentral.com and we'll see you next time on the Energy Central Power Perspectives podcast.

 


About Energy Central Podcasts

The ‘Energy Central Power Perspectives™ Podcast’ features conversations with thought leaders in the utility sector. At least twice monthly, we connect with an Energy Central Power Industry Network community member to discuss compelling topics that impact professionals who work in the power industry. Some podcasts may be a continuation of thought-provoking posts or discussions started in the community or with an industry leader that is interested in sharing their expertise and doing a deeper dive into hot topics or issues relevant to the industry.

The ‘Energy Central Power Perspectives™ Podcast’ is the premiere podcast series from Energy Central, a Power Industry Network of Communities built specifically for professionals in the electric power industry and a place where professionals can share, learn, and connect in a collaborative environment. Supported by leading industry organizations, our mission is to help global power industry professionals work better. Since 1995, we’ve been a trusted news and information source for professionals working in the power industry, and today our managed communities are a place for lively discussions, debates, and analysis to take place. If you’re not yet a member, visit www.EnergyCentral.com to register for free and join over 200,000 of your peers working in the power industry.

The Energy Central Power Perspectives™ Podcast is hosted by Jason PriceCommunity Ambassador of Energy Central. Jason is a Business Development Executive at West Monroe, working in the East Coast Energy and Utilities Group. Jason is joined in the podcast booth by the producer of the podcast, Matt Chester, who is also the Community Manager of Energy Central and energy analyst/independent consultant in energy policy, markets, and technology.  

If you want to be a guest on a future episode of the Energy Central Power Perspectives™ Podcast, let us know! We’ll be pulling guests from our community members who submit engaging content that gets our community talking, and perhaps that next guest will be you! Likewise, if you see an article submitted by a fellow Energy Central community member that you’d like to see broken down in more detail in a conversation, feel free to send us a note to nominate them.  For more information, contact us at community@energycentral.com. Podcast interviews are free for Expert Members and professionals who work for a utility.  We have package offers available for solution providers and vendors. 

Happy listening, and stay tuned for our next episode! Like what you hear, have a suggestion for future episodes, or a question for our guest? Leave a note in the comments below.

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Thanks once again to EPRI for making this episode possible. 

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