Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Countries citing papers authored by Michael Negnevitsky
Since
Specialization
Citations
This map shows the geographic impact of Michael Negnevitsky's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Negnevitsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Negnevitsky more than expected).
Fields of papers citing papers by Michael Negnevitsky
This network shows the impact of papers produced by Michael Negnevitsky. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Negnevitsky. The network helps show where Michael Negnevitsky may publish in the future.
Co-authorship network of co-authors of Michael Negnevitsky
This figure shows the co-authorship network connecting the top 25 collaborators of Michael Negnevitsky.
A scholar is included among the top collaborators of Michael Negnevitsky based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Michael Negnevitsky. Michael Negnevitsky is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zhao, Gang, Xiaolin Wang, Michael Negnevitsky, & Chengjiang Li. (2022). An up-to-date review on the design improvement and optimization of the liquid-cooling battery thermal management system for electric vehicles. Applied Thermal Engineering. 219. 119626–119626.251 indexed citations breakdown →
Negnevitsky, Michael, et al.. (2017). The potential of low load diesel application in increasing renewable energy source penetration. eCite Digital Repository (University of Tasmania).7 indexed citations
Haque, Md Enamul, et al.. (2012). Enhanced control of a direct drive grid connected wind energy system with STATCOM. eCite Digital Repository (University of Tasmania). 1–6.4 indexed citations
14.
Hasan, Kazi N., Md Enamul Haque, Michael Negnevitsky, & Kashem M. Muttaqi. (2008). Control of energy storage interface with a bidirectional converter for photovoltaic systems. eCite Digital Repository (University of Tasmania). 1–6.28 indexed citations
15.
Haruni, A. M. O., Michael Negnevitsky, Md Enamul Haque, & Kashem M. Muttaqi. (2008). Implementation of artificial intelligence technique to model arc furnace responses. eCite Digital Repository (University of Tasmania). 1–6.3 indexed citations
16.
Agalgaonkar, Ashish P., et al.. (2008). Subsynchronous torsional behaviour of a hydraulic turbine-generator unit connected to a HVDC system. Research Online (University of Wollongong). 1–6.3 indexed citations
17.
Negnevitsky, Michael, et al.. (2006). Smoothing Output Power of a Doubly Fed Wind Turbine with an Energy Storage System. eCite Digital Repository (University of Tasmania). 1–5.7 indexed citations
18.
Muttaqi, Kashem M., et al.. (2005). Dynamics of a hydro-wind hybrid isolated power system. eCite Digital Repository (University of Tasmania). 1. 231–236.3 indexed citations
19.
Potter, Cameron & Michael Negnevitsky. (2003). An Expert System Application for Hydro Electric Generator Scheduling in Tasmania. eCite Digital Repository (University of Tasmania). 22(3). 167.1 indexed citations
20.
Negnevitsky, Michael. (1995). An Expert System Application for Clearing Overloads. International Journal of Power and Energy Systems. 15(1). 9–13.5 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.