NexSys PhD researcher Maryam Pourmahdi, based in UCD’s School of Electrical and Electronic Engineering, was recently awarded the Best Paper Award at the Universities Power Engineering Conference (UPEC) in TU Dublin.
We catch up with Maryam below.
What is your NexSys research about and what are you working on at the moment?
My research focuses on creating better and more efficient devices called “rectifiers” that convert alternating current (AC) from the grid to direct current (DC) for use in various applications like electric vehicle charging, power supplies, and hydrogen production. I’m currently working on a design that not only improves energy efficiency but also reduces electromagnetic interference noise, making it safer and more grid friendly. The title of my NexSys project is ‘Advanced Active rectifiers for grid connected applications.’
How did you become interested in this research field?
I was initially intrigued by the challenges of modern power systems and the importance of energy efficiency. With the growing demand for DC power in various applications, the role of rectifiers becomes critical. This led me to explore how these devices could be designed to be more efficient, reliable, and compatible with the power grid.
What is one interesting fact about your research area people may not know about?
My research offers ‘grid-friendly’ rectifiers that not only reduce electrical noise but also maintain stable interactions with the electrical grid. This is critical for preventing disruptions and failures. Additionally, my work has applications in electrolysers for green hydrogen production, making them more efficient and compact.
What is the wider relevance of your research to the energy transition?
The efficiency and reliability of rectifiers are paramount, especially when applied to electrolysers—devices pivotal to the production of green hydrogen, an emerging clean energy source. As the world shifts towards cleaner energy solutions, my research on advanced rectifiers can significantly enhance the efficiency of hydrogen production systems. This translates to reduced energy waste, lower greenhouse gas emissions, and more affordable green hydrogen, potentially accelerating policy shifts towards this sustainable energy option.
You recently won a Best Paper Award at the Universities Power Engineering Conference in TU Dublin. Congratulations! What was the paper about?
The paper title was “Dual-Cuk High Step-up Bridgeless PFC Converters with Continuous Input and Output Currents”. This paper proposes two novel types of dual-Cuk bridgeless rectifiers for voltage conversion in power systems. These grid-friendly rectifiers overcome the limitations of conventional boost rectifiers and offer several significant advantages including high reliability, low voltage stress across the semiconductors, continuous input and output current, and high step-up voltage operation capability.
What is something people may find surprising about you?
Outside the lab, I have a passion for painting and portraiture, where I find a different kind of creative expression compared to my scientific work. I also enjoy playing the guitar, which serves as a melodic break from the analytical world. Additionally, I love feeding birds; it’s a simple act that brings me immense joy and a sense of connection to nature.
Introducing NexSys research through the lens of publication abstracts
by Brian Boyle and Stefan Müller
Brian Boyle is a Postdoctoral Researcher in the School of Politics and International Relations at University College Dublin. Brian’s main research interests include social inequalities and representation in political behaviour and political communication, with a focus on the use of quantitative and computational social science approaches.
Stefan Müller is an Assistant Professor and Ad Astra Fellow in the School of Politics and International Relations at University College Dublin. His research focuses on political representation, party competition, political communication, public opinion, and quantitative text analysis. Stefan is a core member of the Connected_Politics Lab, a fellow at the UCD Geary Institute for Public Policy, a member of the UCD Energy Institute, co-author of the quanteda R package, and maintainer of the Irish Polling Indicator. He established the Text & Policy Research Group at UCD.
Keen to learn more about NexSys and unsure where to start? In this blog post, we use bibliometrics, the statistical analysis of publications, to introduce the NexSys team and their research.
We were curious to find out how our team’s prior work relates to the core aims of the NexSys programme, and which issues relating to the strands of NexSys have been addressed in past abstracts of publications. Our results illustrate the depth and breadth of NexSys research.
Over 2,600 publications from ten different subject areas
We systematically collected information on previous academic publications from the NexSys team. The Elsevier Scopus database contains abstracts and citation information on over 85 million documents, across more than 25,000 peer-reviewed journals, books, and conference papers. Of the 74 NexSys team members listed on the project staff page [data collected in January 2023], 59 were present in the Scopus database. This covered all staff members with the exception of our PhD Students and non-academic members of the team.
While over half of NexSys researchers have an engineering background, the full team covers ten different subject areas, including architecture, computer science, economics, and social policy. The engineers themselves come from over seven sub-fields, including chemical, civil, electrical, marine, and mechanical engineering.
Searching the Scopus database by author returned 3,200 publications, 2,880 of which contained a valid digital object identifier (DOI), and relevant summary description text (e.g. article abstracts). The NexSys members’ publications were spread across a variety of formats, including 2,000 journal articles, 600 conference papers, as well as 160 books and book chapters.
Differences Across Disciplines
We provide descriptive analyses of publication abstracts using the quanteda R package (Benoit et al. 2018) for quantitative text analysis. The table below lists the number of abstracts from each subject area. We also report the abstracts’ most frequent terms and phrases, after removing punctuation characters, numbers, and so-called “stopwords” which appear in almost all scientific publications.
The list underscores the depth of our research, but also shows that researchers from most disciplines have directly worked on one or more of the core issues of the NexSys programme.
Most Frequent Features in Publication Abstract by Subject Area
Mechanical Engineering (598 abstracts): building (166 mentions), performance (156), experimental (148), system (127), compared (125), potential (118), damage (112), flow (112), numerical (112), energy (107)
Other/Non-academic (187 abstracts): system (68 mentions), adaptation (55), ieee (54), network (53), voltage (52), impact (49), methodology (48), control (46), load (45), power_systems (44)
Politics and Social Policy (33 abstracts): housing (48 mentions), parties (24), voters (23), policy (20), social (17), electoral (15), support (14), problems (13), government (13), party (12)
The Focus on the Five Strands
NexSys consists of five strands: four hub strands (Water; Cities and Communities; Transport; Offshore Wind), and the Energy Systems core strand linking these four areas.
We explore how the NexSys team’s research fits into each strand (due to the overarching scope of the Energy Systems core strand, this was excluded from the current analysis). In order to classify the database of publication abstracts, we used a two-stage procedure. First, we selected ‘seed words’ that were narrowly and directly related to each strand (water; cities, city, community; transport, infrastructure; wind, offshore wind). We then checked whether or not an abstract contained none, one, or more than one of these keywords.
With this initial simple classification, we moved on to so-called keyness analysis, a method through which frequent words can be identified (see, e.g., Bondi and Scott 2010; Zollinger 2022). Taking each strand in turn, we set the abstract texts that were identified as belonging to that strand based on the dictionary search as our target category, and all other abstract texts as the reference group. We then compared the relative frequency of features (this could be words or multi-word expressions) across each set of documents and identified words strongly associated with a specific category.
Words that occur very often in documents in our target category, but do not appear much in any of the reference documents, would produce a relatively high Chi2 value. Words that appear frequently in the reference documents, but not very often in the target documents would contain negative values.
From the keyness analysis, we took the ten most distinctive features for each strand and ran new dictionary searches using this expanded set of keywords to re-classify the publication abstracts, which are outlined below.
Strand Classification – Keyness Analysis 10 Most Distinct Features
After this second round of classification, we took each set of abstracts labelled under each strand and then ran a final keyness analysis. For abstracts falling into each of the four strands, we compared publications by engineers with researchers across all other subject areas. This allows us to explore how our team’s overall previous research aligns with the NexSys strands. The keyness analysis also helps us understand how the focus on each strand differs across research fields.
The results for each strand are displayed in the figures below.
Broadly speaking, we observe clear differences in terms of both the language used across each of the four strands, as well as between engineering and other disciplines’ focus within each strand.
Engineering research tends to have a more focused scope, that is directly tied to concepts surrounding measurement, technology, and physical systems. The remaining research fields, meanwhile, tend to relate to a somewhat broader level of analysis, with the most distinct terms focusing on people-centred aspects of each strand. Examples include urban areas, specific locations and places, and the human impact of climate change.
This very preliminary result highlights that NexSys researchers have focused on a combination of the technical questions and societal effects of these technologies.
What we learned
Exploring the abstract texts from the NexSys team’s previous publications highlights the breadth of research experience and knowledge offered within the programme. It is clear that bringing together researchers from a broad range of subject areas is a key advantage of NexSys in its endeavour to develop technical, political, and social solutions to reach our net zero energy goals. This initial textual analysis shows how NexSys addresses the programme’s core objectives from various angles.
Benoit, Kenneth, Kohei Watanabe, Haiyan Wang, Paul Nulty, Adam Obeng, Stefan Müller, and Akitaka Matsuo. 2018. “Quanteda: An R Package for the Quantitative Analysis of Textual Data.” The Journal of Open Source Software 3 (30): 774. https://doi.org/10.21105/joss.00774
Bondi, Marina, and Mike Scott, eds. 2010. Keyness in Texts. Amsterdam: John Benjamins. https://doi.org/10.1075/scl.41
Zollinger, Delia. 2022. “Cleavage Identities in Voters’ Own Words: Harnessing Open-Ended Survey Responses.” American Journal of Political Science published ahead of print. https://doi.org/10.1111/ajps.12743
Next Generation Energy Systems (NexSys) is an all-island multidisciplinary research programme, involving nine different research institutions, alongside industry partners from across the energy sector. The programme’s key aims include tackling the challenges of energy decarbonisation, and developing evidence-based pathways for a just, net-zero energy system.