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As the grid evolves to meet surging energy demands while maintaining peak reliability, bridging the gap between cutting-edge academic research that can best enable these capabilities with real-world utility development has never been more critical.
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Developments like rapid electrification and inverter-based resources have pushed the grid past the limits of legacy modeling, which is why utility engineers need the advanced insights that universities and national labs can uniquely provide.
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To explore how academic research is translating into practical utility solutions, I'm thrilled to be joined by Dr.
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Liu Zhang, who's the Associate Professor and Director of the Center for Electric Power System Research at Clarkson University.
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Dr.
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Zhang is at the forefront of power engineering education and grid modernization research, focusing on power quality, electromagnetic transient analysis, and scalable grid compatibility for distributed energy resources.
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He'll also be diving into these exact topics at DTEC Northeast during his session, standardizing power quality modeling for DER grid compatibility at scale.
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So we'll talk more about that event in a moment.
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But Dr.
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Zhang, thanks so much for taking the time to connect.
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Thank you for having me.
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So I gave a very brief summary of kind of your current position at Clarkson, but tell us a little bit more about yourself, about your research, and the power engineering education at Clarkson, which I mean is there to support the development of sustainable, affordable, and resilient electric power systems of the future.
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Yeah, thanks so much.
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I'm Liu Jiang.
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I'm an associate professor of electrical engineering at Clarkson University.
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I'm also the director for Clarkson Center for Electrical Power Assistant Research.
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And then let's talk about a two-part, you know, my role as a professor in the university.
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First part is for research.
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And I'm particularly really working on the grid flexibilities for decarbonization, the renewable energy uncertainties and operational risk of the grid.
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The other piece of the research, as you talk about, is really the distribution system with more the distributed energy resources.
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And all of this research is indeed I do is in close collaboration with the power industries, including the New York Independent System Operator, New York ISO, the utility of Avangrid, the Transmission Utilities, New York Power Authority, NAIPA, and also the OEM, the G uh General Electric Venova.
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That indeed, that's where I am from before I became a professor.
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I worked at the GE before.
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Then I also see our mission of educating the next generation power engineers as an essential part to support the grid transition.
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So Clarkson University has a very long history of a power engineering program that connects the fundamental engineering education with the real world industry challenges.
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As a center director, I always see our power engineering research portfolio, our online master's program in power engineering.
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For example, for the online master's power engineering program, indeed was originally established in collaboration with National Grid to train an upscale utility engineer for the challenges exactly expressed by you with all the electrifications, with all the IBRs, with all the DERs to the grid.
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And our grid is more than 150 years old.
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We need the talent, we need new skills for our engineers to really ensure the smooth grid transition.
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So for that program itself, like for example, over the last 80 years, it has grown like significantly now.
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And um let me um really conclude this part that to really enable a sustainable, affordable, resilient electric power grid future, I think there are two things that are very critical.
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First, the talent, second, the technology.
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But at the end, it's really the talent who would develop the technology for the grid transition.
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That's why I think the university has a very unique role to play in this energy transition journey.
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No, thanks for laying that all out and and that that focus on talent and technology.
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There's there's so much there.
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I mean, the the workforce challenges have been talked about for how many years now, but it's it's coming on in a in a bigger way.
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Um, you know, for that that technology piece though, can you talk a little bit about what it means for the research being done there to have a practical impact in uh in utility workflows of the present?
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You know, when you look at modernizing the grid, and you mentioned the the legacy systems, how old a lot of these systems are, really need these necessary upgrades.
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But how much of the challenge with that is about integrating new technologies versus versus I mean enabling these upgrades?
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You know, what does grid modernization really mean from a modeling and research perspective?
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Yeah, that's a very interesting question here.
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Um maybe um I need to talk a little bit about the research here first, and then we will dive into the legacy grid components asset with the new technologies.
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Typically, like I look at the university research from the two lens here.
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Um, you know, maybe you you can do the research, you know, into the questions based on your literature surveys, the existing academia papers or industry-wide papers.
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The other research you can do really focus on the industry need.
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Let the utility or the power industry tell you what what kind of problem are there we need to solve, right, for the greater modernization.
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So, my research indeed falls into the second category.
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I work very closely with the industries.
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Um so that it really originated from my industry background.
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So my industry background really helps me tremendously to really try to bridge the theoretical research in the academia into the daily operational need from the power industries.
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Before I came to Clarkson, I work at the GE from 2016 to 2020 to really from the OEM perspective to develop technology for the power industry.
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Now, even while I'm a professor at Clarkson since May 2024, I've been a part-time principal consulting engineer at the utility Avon Grid, which deeply helps me understand how the utility really plan and operate the grid asset.
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And since like October 2025, I became a part-time engineering fellow at the Energy System Integration Group, ESEC, which is really giving me the opportunity to collect the subject, many experts across the country, or sometimes even globally, that really helped me to deepen my understanding what is the challenge faced by the utilities and industry in their daily life.
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So my understanding of the challenges and gaps in the power industry really further like enhanced by the power engineer educational program at Clarkson.
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Because we have our top of the program here, we have more than 100 utility engineers who are signed up for this uh the program here.
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So I have they give me a lot of opportunity to interact with the engineers who are really like putting hands-on onto the operation planning of the grid.
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And then the first hand insight into the challenges utility are encountering and the progress they are making in such areas for the grid modernization, digitalization, that really helped me to shape the research portfolio at Clarkson.
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So basically, this is really real-world perspectives, helping inform my research questions and that give our students um the engineers the new tools and the methodology they can take back to their organizations.
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So I guess, first of all, then my guess, my answer to your question, the first part is you know, from the academic research to the industry application, I think, in my opinion, is really the co-development of the new technology with the power industries.
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I don't really treat the industry as my advisor, I treat the industry as my partner.
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We work together to develop the technology, even before the technologies go to the field in the in the university.
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We already get the input, we already validated with the real data first.
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Like, for example, I'm just using maybe give two examples there.
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You know, I have been working with New York ISO um to develop a synthetic New York State Power Grid testbed for the energy economic study or market concept design.
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So the test bed itself is really the co-development between my research team at Clarkson and the New York SO team, uh the researchers or engineers who are managing the New York State Power Grid on the daily life.
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So we get the taskbed shaped up in a way that is validated by the New York ISO engineers.
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Now we're using that task bed to evaluate the new market design concepts or the products so that you can see that the research university can evaluate it even before they go to the field at the other side.
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The other example I will show there is, for example, we do the uh the the we call the investment prioritization for capacity upgrade utility.
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That project are really sponsored by by Avangrid, for example.
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No, we host the older utility data from Avangrid.
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We develop technology, we already validate the technology with all the Avangrid data, like what the utility will do to de-risk any new technology in before they implement your tool, uh the field.
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So not only we host using the data, we have we host the multiple stakeholder meetings with the utility, get a really broader team to get feedback, and uh really uncover the hoops, even the code and all the technical details to expose to the engineer, then them to look into our details of the technology before they go to the field.
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So that's just examples here, then um how really the academia research will support the grid modernization, how we are even developing the technology from the university um for the field demonstration or field deployment.
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I think that that is just an example.
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I also work closely with the utility like NIPA and the OEM, like GE.
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So the whole like the close partnership between the academia and the power industry really bridge the gap from the theoretical research in the university to the daily operation need for the for the the the the grid uh for the grid and the utilities.
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I think the that's your first question.
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I think the second piece of your question here is you are right, we the industry will manage like large legacy asset.
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And now we also have new technologies.
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For example, um, if you go to a substation, uh, there was one time I went to a substation.
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The substitution was built like in the early 1950s, right after the World War II.
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If you like look at the substation, it looks a little bit rusty, and uh, but the transformers are working so well.
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And the mineral oil that sample at the health sample test indicate that the the acid is more than 85% healthy.
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What it really means there is some legacy asset has been there for more than like 60 years or 70 years, but they are still running very well.
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And the what that but this is the legacy device are also being the new challenges because when they are designed, it's really for the synchronous generators and for the traditional load with motors.
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Now you have all the inverter-based generations, uh, energy storages and uh UV chargers and the flexor load and new control systems.
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I think that really the question here is how can we couple the new technology with our legacy asset?
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Then I think that's what the grid modelization really means.
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We're not really replacing all the legacy assets in a day.
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And it's more about we should using the new technology, working it out on the legacy grid asset that we have for the next decades, for the next decades to go, to come.
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Well, and and the approach to partnering with utilities at that level, I think is just so critical because it's not about what works in theory or what works on on paper, but the practical value of that.
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And I know that's something you've dug into in a big way with power quality issues, uh, power quality issues like voltage flicker and harmonic resonance.
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And they they've traditionally been localized edge case problems.
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But from a research standpoint, how is the rise of inverter-based resources changing the fundamental physics of the descriptive distribution grid that we've been talking about?
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And why is standardization become such a priority with this as we as we do shift from what's what makes sense on paper, what what's happening in in theory to the utility reality that the the folks doing this work have to deal with and sort out.
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Yeah, that's uh very interesting question here.
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You know, if you look at the fundamental change, is that the power electronics devices, no matter if for the IBRs, for the load, for example, data center, or for the even our computers, for example, are no longer than exceptions of the at the edge of the system.
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They're really becoming one of the dominant interfaces between the grid and the generator and the storage and the load now.
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So that is dramatically changed from you know, a couple of decades ago, you have all the singular generators, you have all the motors, which is uh very different from the we call it uh the party electronics-based generation or the load.
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And the inverter for the say for a solar farm, that really does not behave like a traditional passive load or singular generator.
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Typically, like the traditional generators, a motor, they have a fairly slower transit response time.
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They are usually in the time scale of seconds.
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Typically, when you do the study, it's in the millisecond study that will be good enough in terms of the time resolution.
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However, if you look at the the inverter-based resources like solar farm or wind farm, or even the emerging load, like a data center, they typically have a switching frequency of the transistors from a few kilohertz to a few tens of kilohertz.
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So that control, that kind of inverted-based resources or the load really interact dynamically with the electrical power grid that in a different way.
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So if you do the like say really trying to capture the dynamic or transit of the traditional power grid, your simulation time step maybe is like milliseconds level.
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However, for the new grid with all the inverter-based resources, the part electronically interface, the generations of load, you need to really do the micro second level.
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And then this is this this is the um when you like you really like in integrate this kind of new generations and load into the the weak distribution grid, you will see the phenomenon like voltage oscillations, flickers, and other power quality issues.
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Like it's really hard to capture.
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That's the reason why we need a standard standardization.
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The standardization really matters here.
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And I look at the standardization from primarily from two ways, I think.
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One is we need to standardize the dynamic performance requirement of the inverter-based generation resource and the load.
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The second part of I think standardization is to standardize the modeling practice and the greater impact study.
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Now, if you look at the first part, the standardization of the dynamic performance requirement, for example, the R2E 1547 for the DERs, they establish the requirement for the DER, the dynamic performance.
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However, typically they only like the performance only for single inverters.
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But for a solar farm, depends on the size.
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You may have two megawatt solar farm, five megawatt solar farm, or 10 megawatts solar farm.
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You have like tens of the inverter that were in parallel to build the size of the solar farm in the field.
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So the aggregated effects of this inverter fleet and their aggregated interaction with the grid will not be easily captured by the standard.
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So that is the gap indeed lead to the solar farm uh disconnections, what happened in the in upstate New York uh recently.
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They also lead to my view on the second need of the centralization of the modeling piece and the greater impact study.
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Now, we need to learn from the power quality issues, uh, the events in the field.
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We need to propose the screening criteria based on the dynamic performance of the inverter-based resource and develop the appropriate model, including the electric magnetic transit model, to fully evaluate the greater impact from the aggregated invert uh the uh the inverters.
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So, uh but if you look at all this, even for you when you do the standardizations, you still need to have another challenge here.
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Because the utility engineers they don't have these skills.
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It's something new to them.
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At the end, it's the engineer who will perform all the engineering study, standardized this impact study.
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Indeed, that's why the the power industry they they come to uh Clarkson, they ask us to set up the program to upskill their engineer with all the new issues and new uh new technologies and uh new training modules to help with the the utility with the skills um for the engineer to perform this kind of work.
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That has been very collaboration that has been very helpful.
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And and I think it underscores how how challenges and and issues like that are evolving.
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And I wanted to ask you how you've seen both the technical capability and utility perceptions or understandings of EVs and DERs change over the past few years.
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Because I think that was that was a certain approach to integration, a certain perception for that maybe five, 10 years ago versus what's today.
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And then that process to utilize them in a in a bigger way and leverage them is just is just different.
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Oh, yeah, absolutely.
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You know, I um have been in the field for roughly like more than a decade here, and uh work at uh all the different sectors, right?
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And from the OEM perspective to the academia research university perspective to the utility and the in the consortia.
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Like just for a few, like a few years ago, you know, much of the conversation was how should we do the integrate, do the integration, the connections with DERs, the EV into the grid, and what is the procedure, what it would be the what kind of study we need to do.
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Um, you know, the whole goal there is just trying to make sure that it doesn't create any reliability issues, et cetera, to the grid.
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And I think today the conversation really changed.
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Now we are talking about how should we design the program, how should we integrate the new technology like therms, and to really like integrate this asset into the grid, but without jeopardizing the reliability of the grid.
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And um, we are even talking about how can we use in the distributed energy uh resource like energy storage to defer the legacy grid asset upgrade.
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Um the other, I think the perception there is the flexibility from all this DERs and the EVs.
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For example, um the upstate in New York, there was a demonstration project called the Flex Solar Program there that increased the hosting capacity of the DER from 7.6 megawatt to 15 uh megawatt.
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That just doubled the hosting capacity with a little bit of trade-off of the solar cartelment.
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That's just the flexibility from the DERs to increase the hosting capacity of the grid and uh but without really uh jeopardizing the reliability.
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In the meantime, if you look at the the EVs, um the EV has a lot of diversities there.
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The diversity could be uh you know within the UV translations itself with multiple ports, it could be the charging behavior, you know, um peak at a different time from the feeder load, etc.
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And how do we understand all this flexibility and uh from the DRs and the EVs, and how should that can even just support the grid operation planning?
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And I think that the dialogue has been changed dramatically in the you know compared just a few years ago to where we are.
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So I think the if I conclude this what I'm my my observation there is, you know.
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I think the perception is really moving from the, you know, these are the new nodes and generator that we have to accommodate towards like these are the controllable assets.
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How can they become part of the grid operations or the toolkit uh that can support the grid translation?
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I think that's it's uh it's a dramatic change of the perceptions there we have.
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Well, and that's a heck of a baseline for what I know is you're gonna be digging into in a bigger way, your DTEC Northeast session.
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Um, can you touch on what some of the specific findings and frameworks and methodologies that you're gonna fully showcase to attendees in Boston?
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I look forward to it first.
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And uh my I think the session is called uh you know standard standard standardizing, sorry, power quoting modeling for DER greater compatibility at a scale.
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So this is really emphasizing on the practical methods for identifying, analyzing, and resolving issues such as the flicker and the voltage instabilities from the DERs.
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So this is not this is really from the field.
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And um in the upstate New York, in the past couple of years, we have seen the multiple solar farms creating the flicker and light issues.
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And uh at the end, what happened there is the solar farm has been shutting down, they get disconnected to resolve the issues first when we are trying to find a solution.
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And then basically, what we did there is we need to bring the really the power quality monitoring from the field of management and also the electric magnetic transient analysis skills, plus uh the small inverter control design, all of them together trying to understand uh the dynamic phenomenon between the distributed energy resources with the legacy grid.
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So I think the message there is there's no single modeling techniques can answer all the questions.
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It's about collaboration.
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Is your models coupled with measurement data, together with the technology behind the resources that can help you to resolve the issues there?
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And of course, I will dive more into that uh with the presentations and and the discussion with the the DTEC um uh Northeastern conference, but the the ultimate goal here is really trying to connect the those pieces into engineering methodology that utility can use.
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Um, then with as the the distributed energy resources become more popular and the more dominating the the distribution systems.
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Well, and and I think some of that is hinted at in the title of the session itself, that it's at scale, that these this research, that this understanding that you're gonna be able to outline isn't just about a pilot project or a or a one-off.
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It's something that that makes sense at scale.
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And I mean, is there anything else you can say about the because I know you're gonna be presenting with uh with Victor from NIPO, where there's is highlighting their the work out of their agile lab.
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Um, you know, is there any details then and project specifics from that you that you think will be applicable to other utilities that they can look at at something similar uh at scale that isn't just gonna be a one-off for them?
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That's a very good uh observation.
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I think the the value of a partnership is we can really combine the research, you know, with a high fidelity test environment that uh Naipa Edgez Lab has.
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Indeed, uh we have been working with um LaiPA since the day one.
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NAIPA Agile's lab was established, which is dated back to 2018.
00:25:55.839 --> 00:26:02.960
At that time, um New York State was um uh shooting for the 9 gigawatt offshore wind at that time.
00:26:03.119 --> 00:26:12.160
Clarkson is the the university, I think it's probably the first university in the North America to develop the offshore wind model.
00:26:12.880 --> 00:26:30.319
Um, using the model coupled with the Agile's the whole New York State grid model to understand what is the the risk when you're integrating the the large the offshore wind, the inverter-based resort to the New York State, the grid.
00:26:31.599 --> 00:26:35.440
So that is just one example in the last few years.
00:26:35.599 --> 00:26:37.759
That partnership has evolved quite a lot.
00:26:37.839 --> 00:26:52.720
We did offshore wind far uh wind farm modeling, we did a mesh at VDC collaboration, trying to look at how the you know using the mesh H VDC to connect different uh wind farms together to couple with the New York State grid.
00:26:52.880 --> 00:27:08.559
We're also currently doing the grid forming converter control with the Azure Lab, and indeed um uh we're also working on the how the Azure Lab, the facility, can help this support even the power quality issues in the distribution systems.
00:27:08.799 --> 00:27:24.400
So I think the the digital twin or digital grid uh that Naipa IGES have provide a very good platform to mimic the real grid operation of the whole New York State grid.
00:27:24.640 --> 00:27:38.559
And uh the university role there is really trying to develop the models with all the cutting-edge technologies, and before they really implement into the field, we can de-risk the technology with Agile's facility there.
00:27:38.720 --> 00:27:56.880
I think this is really at the end, is the collaboration there, is collaboration between the the small-scale um lab modeling or test to the to at a bigger scale at um state-level power grid that Agile's lab has.
00:27:57.039 --> 00:28:05.039
So I think the collaboration has been extremely um helpful to risk the new technologies.
00:28:06.319 --> 00:28:06.720
Excellent.
00:28:06.880 --> 00:28:11.359
Well, looking forward to full details uh at DTech Northeast.
00:28:11.519 --> 00:28:16.400
Um, and then just in terms of looking, looking forward, looking out, you know, that's that's happening later this year.
00:28:16.480 --> 00:28:30.720
But if we look out a bit a bit further, maybe the next three to five years, how do you see any of these power quality issues and opportunities further developing or shaping the utility reality across the market as well as workflows?
00:28:31.599 --> 00:28:36.240
Yeah, I expect that the power quality issues have become much more often.
00:28:36.559 --> 00:28:52.319
And indeed, I think the power quality issues is it's it's it will be become a part of the power system planning uh issues rather than something that you investigated only after a problem already appears.
00:28:52.559 --> 00:28:54.640
So basically, we should be more proactive.
00:28:54.880 --> 00:29:01.440
We need to be proactive to understand the potential issues even before they uh occur.
00:29:02.240 --> 00:29:09.119
Um if you look at the number of the diversity of the inverter-based resources, they are they will continue to increase.
00:29:09.359 --> 00:29:14.400
Now we will see more EV charging stations, we will see more batteries, we will see more solar farms.
00:29:14.559 --> 00:29:20.319
We also will see the more new uh converter control technology, for example, grid forming.
00:29:20.799 --> 00:29:29.200
And uh at the same time, uh the many distribution systems will remain the very electrical, we call it electrical weak or weak grid issues there.
00:29:29.440 --> 00:30:00.799
So that combination with popularities of the all these new um technologies or new inverter-based resources coupled with the the aging infrastructure plus the weak, the weak grid, I think that just highlights we need a better screening tools, we need a better EMT models, we need a better coordinations among the devices across the department in the utility sectors, and even between the utility and the developer and the OEM.
00:30:01.039 --> 00:30:10.559
That understanding the technology will be really critical, and that the coordination across the sectors will be an enabler, in my opinion.
00:30:11.440 --> 00:30:12.480
Makes a lot of sense.
00:30:12.640 --> 00:30:15.519
Um, well, last question for you, uh Dr.
00:30:15.680 --> 00:30:16.160
Leo.
00:30:16.319 --> 00:30:21.039
I um you know, we've been talking a lot about power quality, power everything.
00:30:21.119 --> 00:30:22.880
So tell me tell me something powerful.
00:30:23.039 --> 00:30:33.680
What's a piece of advice that that anchors you or is something that you've you've seen in the wider the wider space, your wider scope that you think makes sense for the for the energy sector?
00:30:34.559 --> 00:30:41.759
Yeah, I will say don't confuse a more sophisticated model with a better decision.
00:30:42.559 --> 00:30:45.839
The power system is becoming more complex.
00:30:46.559 --> 00:30:52.960
There's a temptation that we need to respond to it by making every model more detailed, more complex.
00:30:53.519 --> 00:31:00.480
But the real value of an engineering is knowing what level of detail matters for the decision we need to make.
00:31:00.960 --> 00:31:20.240
I also think the industry needed to become more comfortable with the idea that uncertainty is not something that we can eliminate, or the more complex modeling is needed for all the problems or all the decisions we need we we need to uh solve or focus on.
00:31:20.559 --> 00:31:28.960
So I think we need to make sure we don't overcomplicate the modeling for the issues we are trying to solve.
00:31:29.279 --> 00:31:37.920
In the meantime, we also need to make sure the model is accurate enough for the problem we're trying to solve.
00:31:38.559 --> 00:31:45.119
So I think the with the system is getting more complex, we need to really watch out.
00:31:45.279 --> 00:31:58.240
We don't really complicate it itself by modeling the complex system in a complex way that there's no solution or no decision can be made from the complex modeling the complex system.
00:31:58.640 --> 00:32:02.160
Um that that is, I think is very critical.
00:32:02.400 --> 00:32:10.240
But at the end, at the end of the world, uh at the end of the energy transition journey is really the talent.
00:32:10.640 --> 00:32:24.640
We need to have the talent with engineer, uh engineers and and um with the skills to really navigate the transition of the complex power system.
00:32:25.920 --> 00:32:30.799
Yeah, the the goes back to what you mentioned, the talent and technology being foundational.
00:32:30.880 --> 00:32:43.119
And I know we didn't get all the way into the talent piece, but that that your that your program, that your research is enabling and providing the baseline for that talent, that current generation, that next generation.
00:32:43.279 --> 00:32:46.799
Like that's what when we talk about workforce challenges, what does it look like to solve them?
00:32:47.039 --> 00:32:58.720
Exactly what you're you're doing and and showcasing is is what it looks like, which is easy to say, but I mean difficult to do in in terms of getting getting that out there, but that's why we need to get it out there more.
00:32:59.359 --> 00:33:00.079
Exactly.
00:33:00.400 --> 00:33:06.960
And indeed, I I think the we need to share more of the challenges from the field and also sharing the solutions.
00:33:07.119 --> 00:33:11.839
That's why I look forward to the the Northeastern uh the DTEC Northeastern conference.
00:33:11.920 --> 00:33:15.680
So we will target dive more into some of the topics here, power qualities.
00:33:15.839 --> 00:33:28.799
I will even showcase some of the the real case, how the uh the utility uh we work with the utility to solve the problem, how the findings have been integrated into the the utility workflow.
00:33:28.960 --> 00:33:48.640
So it's not just a pilot project, it's indeed how can we learn from the field the grid disturbances and how can we integrate into our, for example, interconnection procedures so that way we can be more proactively to prevent this kind of grid issues to be happening in the near futures.
00:33:48.960 --> 00:33:59.680
And all that underscores why we're really looking forward to what you have to say and outline at DTech Northeast, which is gonna be taking place November 2nd through 4th in Boston, Massachusetts.
00:33:59.839 --> 00:34:06.079
And then your session specifically is standardizing power quality modeling for DER grid compatibility at scale.
00:34:06.160 --> 00:34:09.599
That's going to take place November 3rd from 1045 to 11:30.
00:34:09.760 --> 00:34:10.320
So, Dr.
00:34:10.480 --> 00:34:16.320
Leo, really appreciate you taking the time to connect with us today and looking forward to catching up in Boston.
00:34:16.960 --> 00:34:18.559
Thanks so much and look forward to it.
00:34:19.440 --> 00:34:23.679
As always, thank you for listening to the Factor This podcast.
00:34:23.840 --> 00:34:27.760
Please do like and subscribe wherever you find your favorite podcast.
00:34:28.000 --> 00:34:29.119
Let us know how we're doing.
00:34:29.280 --> 00:34:30.960
You can find me on LinkedIn.
00:34:31.039 --> 00:34:34.800
I'm Jeremiah Kerpowitz, and always looking forward to hearing your feedback.
00:34:34.960 --> 00:34:40.559
Tell us what we can do better with the show, or if you have an idea for an episode, please get in touch.
00:34:40.719 --> 00:34:41.920
Stay in touch.
00:00:05.440 --> 00:00:18.160
As the grid evolves to meet surging energy demands while maintaining peak reliability, bridging the gap between cutting-edge academic research that can best enable these capabilities with real-world utility development has never been more critical.
00:00:18.559 --> 00:00:30.640
Developments like rapid electrification and inverter-based resources have pushed the grid past the limits of legacy modeling, which is why utility engineers need the advanced insights that universities and national labs can uniquely provide.
00:00:31.440 --> 00:00:37.039
To explore how academic research is translating into practical utility solutions, I'm thrilled to be joined by Dr.
00:00:37.200 --> 00:00:43.759
Liu Zhang, who's the Associate Professor and Director of the Center for Electric Power System Research at Clarkson University.
00:00:44.000 --> 00:00:44.320
Dr.
00:00:44.399 --> 00:00:57.119
Zhang is at the forefront of power engineering education and grid modernization research, focusing on power quality, electromagnetic transient analysis, and scalable grid compatibility for distributed energy resources.
00:00:57.359 --> 00:01:05.840
He'll also be diving into these exact topics at DTEC Northeast during his session, standardizing power quality modeling for DER grid compatibility at scale.
00:01:06.000 --> 00:01:08.079
So we'll talk more about that event in a moment.
00:01:08.159 --> 00:01:08.640
But Dr.
00:01:08.799 --> 00:01:11.120
Zhang, thanks so much for taking the time to connect.
00:01:11.519 --> 00:01:13.040
Thank you for having me.
00:01:13.760 --> 00:01:31.040
So I gave a very brief summary of kind of your current position at Clarkson, but tell us a little bit more about yourself, about your research, and the power engineering education at Clarkson, which I mean is there to support the development of sustainable, affordable, and resilient electric power systems of the future.
00:01:31.920 --> 00:01:33.040
Yeah, thanks so much.
00:01:33.359 --> 00:01:34.640
I'm Liu Jiang.
00:01:34.799 --> 00:01:38.560
I'm an associate professor of electrical engineering at Clarkson University.
00:01:38.799 --> 00:01:43.840
I'm also the director for Clarkson Center for Electrical Power Assistant Research.
00:01:44.079 --> 00:01:50.239
And then let's talk about a two-part, you know, my role as a professor in the university.
00:01:50.560 --> 00:01:52.480
First part is for research.
00:01:52.640 --> 00:02:03.519
And I'm particularly really working on the grid flexibilities for decarbonization, the renewable energy uncertainties and operational risk of the grid.
00:02:03.920 --> 00:02:11.680
The other piece of the research, as you talk about, is really the distribution system with more the distributed energy resources.
00:02:11.919 --> 00:02:32.319
And all of this research is indeed I do is in close collaboration with the power industries, including the New York Independent System Operator, New York ISO, the utility of Avangrid, the Transmission Utilities, New York Power Authority, NAIPA, and also the OEM, the G uh General Electric Venova.
00:02:32.560 --> 00:02:36.159
That indeed, that's where I am from before I became a professor.
00:02:36.240 --> 00:02:38.240
I worked at the GE before.
00:02:38.560 --> 00:02:49.120
Then I also see our mission of educating the next generation power engineers as an essential part to support the grid transition.
00:02:49.280 --> 00:03:00.400
So Clarkson University has a very long history of a power engineering program that connects the fundamental engineering education with the real world industry challenges.
00:03:00.639 --> 00:03:08.800
As a center director, I always see our power engineering research portfolio, our online master's program in power engineering.
00:03:09.360 --> 00:03:31.599
For example, for the online master's power engineering program, indeed was originally established in collaboration with National Grid to train an upscale utility engineer for the challenges exactly expressed by you with all the electrifications, with all the IBRs, with all the DERs to the grid.
00:03:31.840 --> 00:03:35.680
And our grid is more than 150 years old.
00:03:35.919 --> 00:03:43.439
We need the talent, we need new skills for our engineers to really ensure the smooth grid transition.
00:03:44.000 --> 00:03:51.759
So for that program itself, like for example, over the last 80 years, it has grown like significantly now.
00:04:08.400 --> 00:04:21.120
And um let me um really conclude this part that to really enable a sustainable, affordable, resilient electric power grid future, I think there are two things that are very critical.
00:04:21.360 --> 00:04:25.199
First, the talent, second, the technology.
00:04:25.439 --> 00:04:32.480
But at the end, it's really the talent who would develop the technology for the grid transition.
00:04:32.720 --> 00:04:40.319
That's why I think the university has a very unique role to play in this energy transition journey.
00:04:40.879 --> 00:04:45.680
No, thanks for laying that all out and and that that focus on talent and technology.
00:04:45.759 --> 00:04:46.800
There's there's so much there.
00:04:46.879 --> 00:04:53.199
I mean, the the workforce challenges have been talked about for how many years now, but it's it's coming on in a in a bigger way.
00:04:53.439 --> 00:05:06.240
Um, you know, for that that technology piece though, can you talk a little bit about what it means for the research being done there to have a practical impact in uh in utility workflows of the present?
00:05:06.480 --> 00:05:14.800
You know, when you look at modernizing the grid, and you mentioned the the legacy systems, how old a lot of these systems are, really need these necessary upgrades.
00:05:14.879 --> 00:05:22.240
But how much of the challenge with that is about integrating new technologies versus versus I mean enabling these upgrades?
00:05:22.399 --> 00:05:26.800
You know, what does grid modernization really mean from a modeling and research perspective?
00:05:27.600 --> 00:05:30.160
Yeah, that's a very interesting question here.
00:05:30.399 --> 00:05:41.839
Um maybe um I need to talk a little bit about the research here first, and then we will dive into the legacy grid components asset with the new technologies.
00:05:42.160 --> 00:05:47.199
Typically, like I look at the university research from the two lens here.
00:05:47.519 --> 00:05:58.639
Um, you know, maybe you you can do the research, you know, into the questions based on your literature surveys, the existing academia papers or industry-wide papers.
00:05:58.959 --> 00:06:02.240
The other research you can do really focus on the industry need.
00:06:02.639 --> 00:06:10.639
Let the utility or the power industry tell you what what kind of problem are there we need to solve, right, for the greater modernization.
00:06:10.879 --> 00:06:14.000
So, my research indeed falls into the second category.
00:06:14.160 --> 00:06:16.560
I work very closely with the industries.
00:06:16.800 --> 00:06:22.399
Um so that it really originated from my industry background.
00:06:22.560 --> 00:06:31.600
So my industry background really helps me tremendously to really try to bridge the theoretical research in the academia into the daily operational need from the power industries.
00:06:31.839 --> 00:06:43.360
Before I came to Clarkson, I work at the GE from 2016 to 2020 to really from the OEM perspective to develop technology for the power industry.
00:06:43.680 --> 00:07:00.879
Now, even while I'm a professor at Clarkson since May 2024, I've been a part-time principal consulting engineer at the utility Avon Grid, which deeply helps me understand how the utility really plan and operate the grid asset.
00:07:01.120 --> 00:07:25.920
And since like October 2025, I became a part-time engineering fellow at the Energy System Integration Group, ESEC, which is really giving me the opportunity to collect the subject, many experts across the country, or sometimes even globally, that really helped me to deepen my understanding what is the challenge faced by the utilities and industry in their daily life.
00:07:27.040 --> 00:07:37.279
So my understanding of the challenges and gaps in the power industry really further like enhanced by the power engineer educational program at Clarkson.
00:07:37.439 --> 00:07:45.519
Because we have our top of the program here, we have more than 100 utility engineers who are signed up for this uh the program here.
00:07:45.680 --> 00:07:55.360
So I have they give me a lot of opportunity to interact with the engineers who are really like putting hands-on onto the operation planning of the grid.
00:07:55.519 --> 00:08:12.000
And then the first hand insight into the challenges utility are encountering and the progress they are making in such areas for the grid modernization, digitalization, that really helped me to shape the research portfolio at Clarkson.
00:08:12.319 --> 00:08:26.399
So basically, this is really real-world perspectives, helping inform my research questions and that give our students um the engineers the new tools and the methodology they can take back to their organizations.
00:08:26.720 --> 00:08:42.879
So I guess, first of all, then my guess, my answer to your question, the first part is you know, from the academic research to the industry application, I think, in my opinion, is really the co-development of the new technology with the power industries.
00:08:43.039 --> 00:08:47.679
I don't really treat the industry as my advisor, I treat the industry as my partner.
00:08:48.159 --> 00:08:55.840
We work together to develop the technology, even before the technologies go to the field in the in the university.
00:08:56.080 --> 00:09:01.600
We already get the input, we already validated with the real data first.
00:09:01.759 --> 00:09:06.000
Like, for example, I'm just using maybe give two examples there.
00:09:06.320 --> 00:09:17.200
You know, I have been working with New York ISO um to develop a synthetic New York State Power Grid testbed for the energy economic study or market concept design.
00:09:17.440 --> 00:09:32.320
So the test bed itself is really the co-development between my research team at Clarkson and the New York SO team, uh the researchers or engineers who are managing the New York State Power Grid on the daily life.
00:09:32.559 --> 00:09:39.759
So we get the taskbed shaped up in a way that is validated by the New York ISO engineers.
00:09:39.919 --> 00:09:54.720
Now we're using that task bed to evaluate the new market design concepts or the products so that you can see that the research university can evaluate it even before they go to the field at the other side.
00:09:54.960 --> 00:10:08.960
The other example I will show there is, for example, we do the uh the the we call the investment prioritization for capacity upgrade utility.
00:10:09.200 --> 00:10:13.120
That project are really sponsored by by Avangrid, for example.
00:10:13.279 --> 00:10:16.159
No, we host the older utility data from Avangrid.
00:10:16.720 --> 00:10:28.879
We develop technology, we already validate the technology with all the Avangrid data, like what the utility will do to de-risk any new technology in before they implement your tool, uh the field.
00:10:29.279 --> 00:10:53.039
So not only we host using the data, we have we host the multiple stakeholder meetings with the utility, get a really broader team to get feedback, and uh really uncover the hoops, even the code and all the technical details to expose to the engineer, then them to look into our details of the technology before they go to the field.
00:10:53.200 --> 00:11:10.559
So that's just examples here, then um how really the academia research will support the grid modernization, how we are even developing the technology from the university um for the field demonstration or field deployment.
00:11:10.720 --> 00:11:13.039
I think that that is just an example.
00:11:13.120 --> 00:11:16.720
I also work closely with the utility like NIPA and the OEM, like GE.
00:11:16.879 --> 00:11:32.639
So the whole like the close partnership between the academia and the power industry really bridge the gap from the theoretical research in the university to the daily operation need for the for the the the the grid uh for the grid and the utilities.
00:11:32.799 --> 00:11:34.799
I think the that's your first question.
00:11:34.960 --> 00:11:43.519
I think the second piece of your question here is you are right, we the industry will manage like large legacy asset.
00:11:44.240 --> 00:11:46.639
And now we also have new technologies.
00:11:46.799 --> 00:11:52.879
For example, um, if you go to a substation, uh, there was one time I went to a substation.
00:11:53.279 --> 00:11:59.279
The substitution was built like in the early 1950s, right after the World War II.
00:11:59.519 --> 00:12:05.200
If you like look at the substation, it looks a little bit rusty, and uh, but the transformers are working so well.
00:12:05.360 --> 00:12:14.000
And the mineral oil that sample at the health sample test indicate that the the acid is more than 85% healthy.
00:12:14.159 --> 00:12:23.519
What it really means there is some legacy asset has been there for more than like 60 years or 70 years, but they are still running very well.
00:12:24.000 --> 00:12:35.759
And the what that but this is the legacy device are also being the new challenges because when they are designed, it's really for the synchronous generators and for the traditional load with motors.
00:12:35.919 --> 00:12:43.039
Now you have all the inverter-based generations, uh, energy storages and uh UV chargers and the flexor load and new control systems.
00:12:43.279 --> 00:12:51.519
I think that really the question here is how can we couple the new technology with our legacy asset?
00:12:51.759 --> 00:12:54.720
Then I think that's what the grid modelization really means.
00:12:54.879 --> 00:12:59.919
We're not really replacing all the legacy assets in a day.
00:13:00.000 --> 00:13:13.200
And it's more about we should using the new technology, working it out on the legacy grid asset that we have for the next decades, for the next decades to go, to come.
00:13:13.759 --> 00:13:26.399
Well, and and the approach to partnering with utilities at that level, I think is just so critical because it's not about what works in theory or what works on on paper, but the practical value of that.
00:13:26.559 --> 00:13:33.840
And I know that's something you've dug into in a big way with power quality issues, uh, power quality issues like voltage flicker and harmonic resonance.
00:13:33.919 --> 00:13:37.039
And they they've traditionally been localized edge case problems.
00:13:37.200 --> 00:13:46.480
But from a research standpoint, how is the rise of inverter-based resources changing the fundamental physics of the descriptive distribution grid that we've been talking about?
00:13:46.559 --> 00:14:02.799
And why is standardization become such a priority with this as we as we do shift from what's what makes sense on paper, what what's happening in in theory to the utility reality that the the folks doing this work have to deal with and sort out.
00:14:03.519 --> 00:14:06.879
Yeah, that's uh very interesting question here.
00:14:06.960 --> 00:14:23.440
You know, if you look at the fundamental change, is that the power electronics devices, no matter if for the IBRs, for the load, for example, data center, or for the even our computers, for example, are no longer than exceptions of the at the edge of the system.
00:14:23.600 --> 00:14:29.279
They're really becoming one of the dominant interfaces between the grid and the generator and the storage and the load now.
00:14:29.519 --> 00:14:45.919
So that is dramatically changed from you know, a couple of decades ago, you have all the singular generators, you have all the motors, which is uh very different from the we call it uh the party electronics-based generation or the load.
00:14:46.639 --> 00:14:54.720
And the inverter for the say for a solar farm, that really does not behave like a traditional passive load or singular generator.
00:14:54.960 --> 00:15:03.039
Typically, like the traditional generators, a motor, they have a fairly slower transit response time.
00:15:03.679 --> 00:15:05.919
They are usually in the time scale of seconds.
00:15:06.159 --> 00:15:12.399
Typically, when you do the study, it's in the millisecond study that will be good enough in terms of the time resolution.
00:15:12.559 --> 00:15:28.639
However, if you look at the the inverter-based resources like solar farm or wind farm, or even the emerging load, like a data center, they typically have a switching frequency of the transistors from a few kilohertz to a few tens of kilohertz.
00:15:28.799 --> 00:15:38.480
So that control, that kind of inverted-based resources or the load really interact dynamically with the electrical power grid that in a different way.
00:15:38.960 --> 00:15:49.519
So if you do the like say really trying to capture the dynamic or transit of the traditional power grid, your simulation time step maybe is like milliseconds level.
00:15:49.679 --> 00:16:00.080
However, for the new grid with all the inverter-based resources, the part electronically interface, the generations of load, you need to really do the micro second level.
00:16:00.399 --> 00:16:16.799
And then this is this this is the um when you like you really like in integrate this kind of new generations and load into the the weak distribution grid, you will see the phenomenon like voltage oscillations, flickers, and other power quality issues.
00:16:16.960 --> 00:16:18.879
Like it's really hard to capture.
00:16:19.120 --> 00:16:22.799
That's the reason why we need a standard standardization.
00:16:23.039 --> 00:16:25.360
The standardization really matters here.
00:16:25.519 --> 00:16:30.399
And I look at the standardization from primarily from two ways, I think.
00:16:30.720 --> 00:16:38.720
One is we need to standardize the dynamic performance requirement of the inverter-based generation resource and the load.
00:16:38.960 --> 00:16:45.840
The second part of I think standardization is to standardize the modeling practice and the greater impact study.
00:16:46.159 --> 00:17:00.480
Now, if you look at the first part, the standardization of the dynamic performance requirement, for example, the R2E 1547 for the DERs, they establish the requirement for the DER, the dynamic performance.
00:17:00.720 --> 00:17:06.799
However, typically they only like the performance only for single inverters.
00:17:06.960 --> 00:17:09.599
But for a solar farm, depends on the size.
00:17:09.680 --> 00:17:14.079
You may have two megawatt solar farm, five megawatt solar farm, or 10 megawatts solar farm.
00:17:14.240 --> 00:17:19.200
You have like tens of the inverter that were in parallel to build the size of the solar farm in the field.
00:17:19.359 --> 00:17:29.920
So the aggregated effects of this inverter fleet and their aggregated interaction with the grid will not be easily captured by the standard.
00:17:30.240 --> 00:17:38.799
So that is the gap indeed lead to the solar farm uh disconnections, what happened in the in upstate New York uh recently.
00:17:39.039 --> 00:17:45.039
They also lead to my view on the second need of the centralization of the modeling piece and the greater impact study.
00:17:45.200 --> 00:17:49.359
Now, we need to learn from the power quality issues, uh, the events in the field.
00:17:49.519 --> 00:18:06.000
We need to propose the screening criteria based on the dynamic performance of the inverter-based resource and develop the appropriate model, including the electric magnetic transit model, to fully evaluate the greater impact from the aggregated invert uh the uh the inverters.
00:18:06.240 --> 00:18:13.920
So, uh but if you look at all this, even for you when you do the standardizations, you still need to have another challenge here.
00:18:14.400 --> 00:18:18.319
Because the utility engineers they don't have these skills.
00:18:18.720 --> 00:18:20.160
It's something new to them.
00:18:20.799 --> 00:18:26.480
At the end, it's the engineer who will perform all the engineering study, standardized this impact study.
00:18:26.720 --> 00:18:47.920
Indeed, that's why the the power industry they they come to uh Clarkson, they ask us to set up the program to upskill their engineer with all the new issues and new uh new technologies and uh new training modules to help with the the utility with the skills um for the engineer to perform this kind of work.
00:18:48.160 --> 00:18:50.880
That has been very collaboration that has been very helpful.
00:18:51.200 --> 00:18:56.799
And and I think it underscores how how challenges and and issues like that are evolving.
00:18:56.960 --> 00:19:06.880
And I wanted to ask you how you've seen both the technical capability and utility perceptions or understandings of EVs and DERs change over the past few years.
00:19:07.039 --> 00:19:14.880
Because I think that was that was a certain approach to integration, a certain perception for that maybe five, 10 years ago versus what's today.
00:19:14.960 --> 00:19:21.200
And then that process to utilize them in a in a bigger way and leverage them is just is just different.
00:19:21.599 --> 00:19:23.279
Oh, yeah, absolutely.
00:19:23.599 --> 00:19:32.559
You know, I um have been in the field for roughly like more than a decade here, and uh work at uh all the different sectors, right?
00:19:32.640 --> 00:19:39.920
And from the OEM perspective to the academia research university perspective to the utility and the in the consortia.
00:19:40.160 --> 00:19:54.400
Like just for a few, like a few years ago, you know, much of the conversation was how should we do the integrate, do the integration, the connections with DERs, the EV into the grid, and what is the procedure, what it would be the what kind of study we need to do.
00:19:54.720 --> 00:20:03.200
Um, you know, the whole goal there is just trying to make sure that it doesn't create any reliability issues, et cetera, to the grid.
00:20:03.839 --> 00:20:08.319
And I think today the conversation really changed.
00:20:08.960 --> 00:20:23.200
Now we are talking about how should we design the program, how should we integrate the new technology like therms, and to really like integrate this asset into the grid, but without jeopardizing the reliability of the grid.
00:20:23.599 --> 00:20:35.200
And um, we are even talking about how can we use in the distributed energy uh resource like energy storage to defer the legacy grid asset upgrade.
00:20:35.599 --> 00:20:42.400
Um the other, I think the perception there is the flexibility from all this DERs and the EVs.
00:20:42.640 --> 00:20:58.000
For example, um the upstate in New York, there was a demonstration project called the Flex Solar Program there that increased the hosting capacity of the DER from 7.6 megawatt to 15 uh megawatt.
00:20:58.160 --> 00:21:03.519
That just doubled the hosting capacity with a little bit of trade-off of the solar cartelment.
00:21:03.680 --> 00:21:12.720
That's just the flexibility from the DERs to increase the hosting capacity of the grid and uh but without really uh jeopardizing the reliability.
00:21:13.039 --> 00:21:19.519
In the meantime, if you look at the the EVs, um the EV has a lot of diversities there.
00:21:19.759 --> 00:21:32.799
The diversity could be uh you know within the UV translations itself with multiple ports, it could be the charging behavior, you know, um peak at a different time from the feeder load, etc.
00:21:33.039 --> 00:21:44.799
And how do we understand all this flexibility and uh from the DRs and the EVs, and how should that can even just support the grid operation planning?
00:21:44.960 --> 00:21:53.759
And I think that the dialogue has been changed dramatically in the you know compared just a few years ago to where we are.
00:21:54.000 --> 00:21:59.759
So I think the if I conclude this what I'm my my observation there is, you know.
00:22:00.319 --> 00:22:09.680
I think the perception is really moving from the, you know, these are the new nodes and generator that we have to accommodate towards like these are the controllable assets.
00:22:09.839 --> 00:22:16.160
How can they become part of the grid operations or the toolkit uh that can support the grid translation?
00:22:16.240 --> 00:22:21.519
I think that's it's uh it's a dramatic change of the perceptions there we have.
00:22:22.160 --> 00:22:28.880
Well, and that's a heck of a baseline for what I know is you're gonna be digging into in a bigger way, your DTEC Northeast session.
00:22:29.119 --> 00:22:38.319
Um, can you touch on what some of the specific findings and frameworks and methodologies that you're gonna fully showcase to attendees in Boston?
00:22:39.680 --> 00:22:41.200
I look forward to it first.
00:22:41.359 --> 00:22:51.839
And uh my I think the session is called uh you know standard standard standardizing, sorry, power quoting modeling for DER greater compatibility at a scale.
00:22:52.240 --> 00:23:06.559
So this is really emphasizing on the practical methods for identifying, analyzing, and resolving issues such as the flicker and the voltage instabilities from the DERs.
00:23:06.720 --> 00:23:09.759
So this is not this is really from the field.
00:23:09.920 --> 00:23:20.079
And um in the upstate New York, in the past couple of years, we have seen the multiple solar farms creating the flicker and light issues.
00:23:20.559 --> 00:23:30.160
And uh at the end, what happened there is the solar farm has been shutting down, they get disconnected to resolve the issues first when we are trying to find a solution.
00:23:30.319 --> 00:24:02.079
And then basically, what we did there is we need to bring the really the power quality monitoring from the field of management and also the electric magnetic transient analysis skills, plus uh the small inverter control design, all of them together trying to understand uh the dynamic phenomenon between the distributed energy resources with the legacy grid.
00:24:03.200 --> 00:24:08.799
So I think the message there is there's no single modeling techniques can answer all the questions.
00:24:09.039 --> 00:24:10.480
It's about collaboration.
00:24:10.880 --> 00:24:21.839
Is your models coupled with measurement data, together with the technology behind the resources that can help you to resolve the issues there?
00:24:22.000 --> 00:24:38.480
And of course, I will dive more into that uh with the presentations and and the discussion with the the DTEC um uh Northeastern conference, but the the ultimate goal here is really trying to connect the those pieces into engineering methodology that utility can use.
00:24:38.720 --> 00:24:48.720
Um, then with as the the distributed energy resources become more popular and the more dominating the the distribution systems.
00:24:49.200 --> 00:25:01.920
Well, and and I think some of that is hinted at in the title of the session itself, that it's at scale, that these this research, that this understanding that you're gonna be able to outline isn't just about a pilot project or a or a one-off.
00:25:02.000 --> 00:25:04.319
It's something that that makes sense at scale.
00:25:04.480 --> 00:25:15.200
And I mean, is there anything else you can say about the because I know you're gonna be presenting with uh with Victor from NIPO, where there's is highlighting their the work out of their agile lab.
00:25:15.680 --> 00:25:29.039
Um, you know, is there any details then and project specifics from that you that you think will be applicable to other utilities that they can look at at something similar uh at scale that isn't just gonna be a one-off for them?
00:25:30.480 --> 00:25:33.119
That's a very good uh observation.
00:25:33.359 --> 00:25:45.279
I think the the value of a partnership is we can really combine the research, you know, with a high fidelity test environment that uh Naipa Edgez Lab has.
00:25:45.519 --> 00:25:50.480
Indeed, uh we have been working with um LaiPA since the day one.
00:25:50.640 --> 00:25:55.519
NAIPA Agile's lab was established, which is dated back to 2018.
00:25:55.839 --> 00:26:02.960
At that time, um New York State was um uh shooting for the 9 gigawatt offshore wind at that time.
00:26:03.119 --> 00:26:12.160
Clarkson is the the university, I think it's probably the first university in the North America to develop the offshore wind model.
00:26:12.880 --> 00:26:30.319
Um, using the model coupled with the Agile's the whole New York State grid model to understand what is the the risk when you're integrating the the large the offshore wind, the inverter-based resort to the New York State, the grid.
00:26:31.599 --> 00:26:35.440
So that is just one example in the last few years.
00:26:35.599 --> 00:26:37.759
That partnership has evolved quite a lot.
00:26:37.839 --> 00:26:52.720
We did offshore wind far uh wind farm modeling, we did a mesh at VDC collaboration, trying to look at how the you know using the mesh H VDC to connect different uh wind farms together to couple with the New York State grid.
00:26:52.880 --> 00:27:08.559
We're also currently doing the grid forming converter control with the Azure Lab, and indeed um uh we're also working on the how the Azure Lab, the facility, can help this support even the power quality issues in the distribution systems.
00:27:08.799 --> 00:27:24.400
So I think the the digital twin or digital grid uh that Naipa IGES have provide a very good platform to mimic the real grid operation of the whole New York State grid.
00:27:24.640 --> 00:27:38.559
And uh the university role there is really trying to develop the models with all the cutting-edge technologies, and before they really implement into the field, we can de-risk the technology with Agile's facility there.
00:27:38.720 --> 00:27:56.880
I think this is really at the end, is the collaboration there, is collaboration between the the small-scale um lab modeling or test to the to at a bigger scale at um state-level power grid that Agile's lab has.
00:27:57.039 --> 00:28:05.039
So I think the collaboration has been extremely um helpful to risk the new technologies.
00:28:06.319 --> 00:28:06.720
Excellent.
00:28:06.880 --> 00:28:11.359
Well, looking forward to full details uh at DTech Northeast.
00:28:11.519 --> 00:28:16.400
Um, and then just in terms of looking, looking forward, looking out, you know, that's that's happening later this year.
00:28:16.480 --> 00:28:30.720
But if we look out a bit a bit further, maybe the next three to five years, how do you see any of these power quality issues and opportunities further developing or shaping the utility reality across the market as well as workflows?
00:28:31.599 --> 00:28:36.240
Yeah, I expect that the power quality issues have become much more often.
00:28:36.559 --> 00:28:52.319
And indeed, I think the power quality issues is it's it's it will be become a part of the power system planning uh issues rather than something that you investigated only after a problem already appears.
00:28:52.559 --> 00:28:54.640
So basically, we should be more proactive.
00:28:54.880 --> 00:29:01.440
We need to be proactive to understand the potential issues even before they uh occur.
00:29:02.240 --> 00:29:09.119
Um if you look at the number of the diversity of the inverter-based resources, they are they will continue to increase.
00:29:09.359 --> 00:29:14.400
Now we will see more EV charging stations, we will see more batteries, we will see more solar farms.
00:29:14.559 --> 00:29:20.319
We also will see the more new uh converter control technology, for example, grid forming.
00:29:20.799 --> 00:29:29.200
And uh at the same time, uh the many distribution systems will remain the very electrical, we call it electrical weak or weak grid issues there.
00:29:29.440 --> 00:30:00.799
So that combination with popularities of the all these new um technologies or new inverter-based resources coupled with the the aging infrastructure plus the weak, the weak grid, I think that just highlights we need a better screening tools, we need a better EMT models, we need a better coordinations among the devices across the department in the utility sectors, and even between the utility and the developer and the OEM.
00:30:01.039 --> 00:30:10.559
That understanding the technology will be really critical, and that the coordination across the sectors will be an enabler, in my opinion.
00:30:11.440 --> 00:30:12.480
Makes a lot of sense.
00:30:12.640 --> 00:30:15.519
Um, well, last question for you, uh Dr.
00:30:15.680 --> 00:30:16.160
Leo.
00:30:16.319 --> 00:30:21.039
I um you know, we've been talking a lot about power quality, power everything.
00:30:21.119 --> 00:30:22.880
So tell me tell me something powerful.
00:30:23.039 --> 00:30:33.680
What's a piece of advice that that anchors you or is something that you've you've seen in the wider the wider space, your wider scope that you think makes sense for the for the energy sector?
00:30:34.559 --> 00:30:41.759
Yeah, I will say don't confuse a more sophisticated model with a better decision.
00:30:42.559 --> 00:30:45.839
The power system is becoming more complex.
00:30:46.559 --> 00:30:52.960
There's a temptation that we need to respond to it by making every model more detailed, more complex.
00:30:53.519 --> 00:31:00.480
But the real value of an engineering is knowing what level of detail matters for the decision we need to make.
00:31:00.960 --> 00:31:20.240
I also think the industry needed to become more comfortable with the idea that uncertainty is not something that we can eliminate, or the more complex modeling is needed for all the problems or all the decisions we need we we need to uh solve or focus on.
00:31:20.559 --> 00:31:28.960
So I think we need to make sure we don't overcomplicate the modeling for the issues we are trying to solve.
00:31:29.279 --> 00:31:37.920
In the meantime, we also need to make sure the model is accurate enough for the problem we're trying to solve.
00:31:38.559 --> 00:31:45.119
So I think the with the system is getting more complex, we need to really watch out.
00:31:45.279 --> 00:31:58.240
We don't really complicate it itself by modeling the complex system in a complex way that there's no solution or no decision can be made from the complex modeling the complex system.
00:31:58.640 --> 00:32:02.160
Um that that is, I think is very critical.
00:32:02.400 --> 00:32:10.240
But at the end, at the end of the world, uh at the end of the energy transition journey is really the talent.
00:32:10.640 --> 00:32:24.640
We need to have the talent with engineer, uh engineers and and um with the skills to really navigate the transition of the complex power system.
00:32:25.920 --> 00:32:30.799
Yeah, the the goes back to what you mentioned, the talent and technology being foundational.
00:32:30.880 --> 00:32:43.119
And I know we didn't get all the way into the talent piece, but that that your that your program, that your research is enabling and providing the baseline for that talent, that current generation, that next generation.
00:32:43.279 --> 00:32:46.799
Like that's what when we talk about workforce challenges, what does it look like to solve them?
00:32:47.039 --> 00:32:58.720
Exactly what you're you're doing and and showcasing is is what it looks like, which is easy to say, but I mean difficult to do in in terms of getting getting that out there, but that's why we need to get it out there more.
00:32:59.359 --> 00:33:00.079
Exactly.
00:33:00.400 --> 00:33:06.960
And indeed, I I think the we need to share more of the challenges from the field and also sharing the solutions.
00:33:07.119 --> 00:33:11.839
That's why I look forward to the the Northeastern uh the DTEC Northeastern conference.
00:33:11.920 --> 00:33:15.680
So we will target dive more into some of the topics here, power qualities.
00:33:15.839 --> 00:33:28.799
I will even showcase some of the the real case, how the uh the utility uh we work with the utility to solve the problem, how the findings have been integrated into the the utility workflow.
00:33:28.960 --> 00:33:48.640
So it's not just a pilot project, it's indeed how can we learn from the field the grid disturbances and how can we integrate into our, for example, interconnection procedures so that way we can be more proactively to prevent this kind of grid issues to be happening in the near futures.
00:33:48.960 --> 00:33:59.680
And all that underscores why we're really looking forward to what you have to say and outline at DTech Northeast, which is gonna be taking place November 2nd through 4th in Boston, Massachusetts.
00:33:59.839 --> 00:34:06.079
And then your session specifically is standardizing power quality modeling for DER grid compatibility at scale.
00:34:06.160 --> 00:34:09.599
That's going to take place November 3rd from 1045 to 11:30.
00:34:09.760 --> 00:34:10.320
So, Dr.
00:34:10.480 --> 00:34:16.320
Leo, really appreciate you taking the time to connect with us today and looking forward to catching up in Boston.
00:34:16.960 --> 00:34:18.559
Thanks so much and look forward to it.
00:34:19.440 --> 00:34:23.679
As always, thank you for listening to the Factor This podcast.
00:34:23.840 --> 00:34:27.760
Please do like and subscribe wherever you find your favorite podcast.
00:34:28.000 --> 00:34:29.119
Let us know how we're doing.
00:34:29.280 --> 00:34:30.960
You can find me on LinkedIn.
00:34:31.039 --> 00:34:34.800
I'm Jeremiah Kerpowitz, and always looking forward to hearing your feedback.
00:34:34.960 --> 00:34:40.559
Tell us what we can do better with the show, or if you have an idea for an episode, please get in touch.
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