Przemysław Janik

1.3k total citations
71 papers, 960 citations indexed

About

Przemysław Janik is a scholar working on Electrical and Electronic Engineering, Control and Systems Engineering and Artificial Intelligence. According to data from OpenAlex, Przemysław Janik has authored 71 papers receiving a total of 960 indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Electrical and Electronic Engineering, 32 papers in Control and Systems Engineering and 13 papers in Artificial Intelligence. Recurrent topics in Przemysław Janik's work include Energy Load and Power Forecasting (24 papers), Smart Grid Energy Management (22 papers) and Microgrid Control and Optimization (17 papers). Przemysław Janik is often cited by papers focused on Energy Load and Power Forecasting (24 papers), Smart Grid Energy Management (22 papers) and Microgrid Control and Optimization (17 papers). Przemysław Janik collaborates with scholars based in Poland, Germany and Czechia. Przemysław Janik's co-authors include T. Łobos, Vishnu Suresh, Zbigniew Leonowicz, Jacek Rezmer, Tomasz Sikorski, Michał Jasiński, Josep M. Guerrero, Paweł Kostyła, Daniel Bejmert and Hortensia Amarís and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.

In The Last Decade

Przemysław Janik

67 papers receiving 908 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Przemysław Janik Poland 15 754 350 179 106 100 71 960
Wei‐Jen Lee United States 17 932 1.2× 473 1.4× 127 0.7× 113 1.1× 85 0.8× 46 1.1k
Duane Robinson Australia 17 812 1.1× 405 1.2× 75 0.4× 99 0.9× 53 0.5× 110 1.1k
Amr S. Zalhaf Egypt 21 791 1.0× 417 1.2× 125 0.7× 101 1.0× 94 0.9× 58 1.1k
Kazem Pourhossein Iran 17 515 0.7× 186 0.5× 141 0.8× 163 1.5× 33 0.3× 31 785
Vishnu Suresh Poland 15 510 0.7× 215 0.6× 168 0.9× 94 0.9× 130 1.3× 58 727
Srete Nikolovski Croatia 20 1.1k 1.5× 882 2.5× 117 0.7× 135 1.3× 91 0.9× 133 1.5k
Hakan Açıkgöz Türkiye 18 781 1.0× 300 0.9× 393 2.2× 240 2.3× 50 0.5× 80 1.1k
Shameem Ahmad Bangladesh 20 885 1.2× 495 1.4× 156 0.9× 190 1.8× 37 0.4× 98 1.1k
S. Suresh Kumar India 10 760 1.0× 281 0.8× 224 1.3× 35 0.3× 39 0.4× 27 1.0k
Ubiratan Holanda Bezerra Brazil 17 926 1.2× 504 1.4× 53 0.3× 55 0.5× 45 0.5× 107 1.2k

Countries citing papers authored by Przemysław Janik

Since Specialization
Citations

This map shows the geographic impact of Przemysław Janik'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 Przemysław Janik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Przemysław Janik more than expected).

Fields of papers citing papers by Przemysław Janik

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Przemysław Janik. 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 Przemysław Janik. The network helps show where Przemysław Janik may publish in the future.

Co-authorship network of co-authors of Przemysław Janik

This figure shows the co-authorship network connecting the top 25 collaborators of Przemysław Janik. A scholar is included among the top collaborators of Przemysław Janik 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 Przemysław Janik. Przemysław Janik is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Suresh, Vishnu, et al.. (2025). A Comparative Study of Machine Learning Models for PV Energy Prediction in an Energy Community. Energies. 18(22). 5980–5980.
2.
Suresh, Vishnu, et al.. (2025). PV Generation Prediction Using Multilayer Perceptron and Data Clustering for Energy Management Support. Energies. 18(6). 1378–1378. 2 indexed citations
4.
Janik, Przemysław, et al.. (2023). Prediction of Regional PV Power Generation Based on LSTM-CNN. 1–6. 1 indexed citations
5.
Suresh, Vishnu, et al.. (2023). Load Forecasting for the Laser Metal Processing Industry Using VMD and Hybrid Deep Learning Models. Energies. 16(14). 5381–5381. 13 indexed citations
6.
Janik, Przemysław, et al.. (2023). Aggregated wind power characteristic curves and artificial intelligence for the regional wind power infeed estimation. Electrical Engineering. 106(1). 655–671. 4 indexed citations
7.
Janik, Przemysław, et al.. (2022). Proposal of a regional grid cluster model for analysis of electrical power network performance. Archives of Electrical Engineering. 601–613. 4 indexed citations
9.
Jasiński, Michał, Tomasz Sikorski, Jacek Rezmer, et al.. (2021). Clustering Methods for Power Quality Measurements in Virtual Power Plant. Energies. 14(18). 5902–5902. 18 indexed citations
10.
Jasiński, Michał, Tomasz Sikorski, Jacek Rezmer, et al.. (2021). A Case Study on a Hierarchical Clustering Application in a Virtual Power Plant: Detection of Specific Working Conditions from Power Quality Data. Energies. 14(4). 907–907. 6 indexed citations
11.
Jasiński, Michał, Tomasz Sikorski, Jacek Rezmer, et al.. (2021). A Case Study on Data Mining Application in a Virtual Power Plant: Cluster Analysis of Power Quality Measurements. Energies. 14(4). 974–974. 6 indexed citations
12.
Suresh, Vishnu, Najmeh Bazmohammadi, Przemysław Janik, et al.. (2021). Optimal location of an electrical vehicle charging station in a local microgrid using an embedded hybrid optimizer. International Journal of Electrical Power & Energy Systems. 131. 106979–106979. 25 indexed citations
13.
Suresh, Vishnu, Przemysław Janik, & Michał Jasiński. (2020). Metaheuristic approach to optimal power flow using mixed integer distributed ant colony optimization. Archives of Electrical Engineering. 335–348. 9 indexed citations
14.
Sikorski, Tomasz, Michał Jasiński, Paweł Kostyła, et al.. (2020). A Case Study on Distributed Energy Resources and Energy-Storage Systems in a Virtual Power Plant Concept: Technical Aspects. Energies. 13(12). 3086–3086. 44 indexed citations
15.
Rezmer, Jacek, Michał Jasiński, Tomasz Sikorski, et al.. (2020). A Case Study on Battery Energy Storage System in a Virtual Power Plant: Defining Charging and Discharging Characteristics. Energies. 13(24). 6670–6670. 16 indexed citations
16.
Jasiński, Michał, Tomasz Sikorski, Jacek Rezmer, et al.. (2020). A Case Study on Power Quality in a Virtual Power Plant: Long Term Assessment and Global Index Application. Energies. 13(24). 6578–6578. 12 indexed citations
17.
Janik, Przemysław, et al.. (2015). MUSIC algorithm for estimation of parameters of signals in power system. 37. 2236–2240. 1 indexed citations
18.
Janik, Przemysław, et al.. (2013). Performance characterization of a PV system using wavelet transform and genetic algorithm. Renewable Energy and Power Quality Journal. 495–500. 1 indexed citations
19.
Janik, Przemysław, et al.. (2010). Methods for fast detection of voltage sags as a crucial prerequisite for reliable operation of dynamic voltage restorer. PRZEGLĄD ELEKTROTECHNICZNY. 35–37. 2 indexed citations
20.
Janik, Przemysław, et al.. (2006). Power Quality Assessment Using Neuro-Fuzzy Approach. 1 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.

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