Fernando Lezama

2.1k total citations
98 papers, 1.5k citations indexed

About

Fernando Lezama is a scholar working on Electrical and Electronic Engineering, Control and Systems Engineering and Artificial Intelligence. According to data from OpenAlex, Fernando Lezama has authored 98 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Electrical and Electronic Engineering, 29 papers in Control and Systems Engineering and 9 papers in Artificial Intelligence. Recurrent topics in Fernando Lezama's work include Smart Grid Energy Management (70 papers), Electric Power System Optimization (37 papers) and Microgrid Control and Optimization (29 papers). Fernando Lezama is often cited by papers focused on Smart Grid Energy Management (70 papers), Electric Power System Optimization (37 papers) and Microgrid Control and Optimization (29 papers). Fernando Lezama collaborates with scholars based in Portugal, Mexico and Brazil. Fernando Lezama's co-authors include Zita Vale, João Soares, Tiago Pinto, Pedro Faria, Ricardo Faia, Omid Abrishambaf, Bruno Canizes, Michael Kaisers, Pablo Hernández-Leal and John F. Franco and has published in prestigious journals such as SHILAP Revista de lepidopterología, Renewable and Sustainable Energy Reviews and Applied Energy.

In The Last Decade

Fernando Lezama

86 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fernando Lezama Portugal 20 1.3k 564 172 136 109 98 1.5k
Nicola Sorrentino Italy 21 1.2k 0.9× 680 1.2× 204 1.2× 118 0.9× 72 0.7× 135 1.4k
Daniele Menniti Italy 22 1.4k 1.1× 760 1.3× 220 1.3× 133 1.0× 82 0.8× 154 1.6k
Koen Kok Netherlands 22 1.4k 1.0× 768 1.4× 135 0.8× 104 0.8× 101 0.9× 80 1.6k
Duong Tung Nguyen United States 12 1.0k 0.8× 550 1.0× 112 0.7× 145 1.1× 49 0.4× 29 1.2k
Dimitrios Papadaskalopoulos United Kingdom 21 1.7k 1.3× 707 1.3× 181 1.1× 218 1.6× 54 0.5× 72 1.8k
Alessandro Burgio Italy 17 701 0.5× 398 0.7× 152 0.9× 107 0.8× 59 0.5× 83 947
Bo Chai China 12 1.1k 0.8× 607 1.1× 128 0.7× 83 0.6× 60 0.6× 41 1.2k
Shichang Cui China 18 1.2k 0.9× 725 1.3× 107 0.6× 78 0.6× 26 0.2× 63 1.3k
Jinye Zhao United States 13 1.9k 1.4× 566 1.0× 89 0.5× 256 1.9× 46 0.4× 35 2.3k
Sung-Yong Son South Korea 16 673 0.5× 308 0.5× 89 0.5× 136 1.0× 53 0.5× 66 843

Countries citing papers authored by Fernando Lezama

Since Specialization
Citations

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

Fields of papers citing papers by Fernando Lezama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fernando Lezama

This figure shows the co-authorship network connecting the top 25 collaborators of Fernando Lezama. A scholar is included among the top collaborators of Fernando Lezama 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 Fernando Lezama. Fernando Lezama 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.
Almeida, José, João Soares, Fernando Lezama, et al.. (2025). A systematic review of explainability in computational intelligence for optimization. Computer Science Review. 57. 100764–100764. 1 indexed citations
2.
Lezama, Fernando, et al.. (2024). Towards Fair Energy Communities: Integrating Storage, Sharing and Pricing Strategies. IFAC-PapersOnLine. 58(13). 320–325.
3.
Lezama, Fernando, et al.. (2024). Assessing PV Integration with Evolutionary Algorithms: Insights from the 2024 Competition on Evolutionary Computation in the Energy Domain. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 1738–1744.
4.
Lezama, Fernando, et al.. (2024). Modern distribution system expansion planning considering new market designs: Review and future directions. Renewable and Sustainable Energy Reviews. 202. 114709–114709. 13 indexed citations
5.
Almeida, José, João Soares, Steffen Limmer, et al.. (2024). Community-Based Energy Sharing using Game Theory Approaches for Benefit Distribution. 1–6.
6.
Faria, Pedro, et al.. (2023). A Robust Model for Portfolio Management of Microgrid Operator in the Balancing Market. Energies. 16(4). 1700–1700. 1 indexed citations
7.
Leite, Jônatas Boás, et al.. (2023). Probabilistic-based Optimization for PV Hosting Capacity with Confidence Interval Restrictions. 1933–1940. 1 indexed citations
8.
Lezama, Fernando, José Almeida, João Soares, Bruno Canizes, & Zita Vale. (2023). Insights into the 2022 WCCI-GECCO Competition: Statistical Analysis of Evolutionary Computation in the Energy Domain. 789–794.
9.
Soares, João, et al.. (2023). A Risk-Based Planning Approach for Sustainable Distribution Systems Considering EV Charging Stations and Carbon Taxes. IEEE Transactions on Sustainable Energy. 14(4). 2294–2307. 30 indexed citations
10.
11.
Franco, John F., et al.. (2022). A Specialized Long-Term Distribution System Expansion Planning Method With the Integration of Distributed Energy Resources. IEEE Access. 10. 19133–19148. 38 indexed citations
12.
Rodríguez‐González, Ansel Y., et al.. (2022). WCCI/GECCO 2020 Competition on Evolutionary Computation in the Energy Domain: An overview from the winner perspective. Applied Soft Computing. 125. 109162–109162. 11 indexed citations
13.
Faia, Ricardo, João Soares, Tiago Pinto, et al.. (2021). Optimal Model for Local Energy Community Scheduling Considering Peer to Peer Electricity Transactions. IEEE Access. 9. 12420–12430. 76 indexed citations
14.
Lezama, Fernando, João Soares, Bruno Canizes, & Zita Vale. (2021). A Statistical Analysis of Performance in the 2021 CEC-GECCO-PESGM Competition on Evolutionary Computation in the Energy Domain. 2021 IEEE Symposium Series on Computational Intelligence (SSCI). 1–8. 2 indexed citations
15.
Ramos, Sérgio, et al.. (2020). A Mixed Binary Linear Programming Model for Optimal Energy Management of Smart Buildings. Energies. 13(7). 1719–1719. 25 indexed citations
16.
Del-Valle-Soto, Carolina, et al.. (2019). New Detection Paradigms to Improve Wireless Sensor Network Performance under Jamming Attacks. Sensors. 19(11). 2489–2489. 6 indexed citations
17.
Canizes, Bruno, João Soares, Ângelo Costa, et al.. (2019). Electric Vehicles’ User Charging Behaviour Simulator for a Smart City. Energies. 12(8). 1470–1470. 59 indexed citations
18.
Soares, João, Tiago Pinto, Fernando Lezama, & Hugo Morais. (2018). Survey on Complex Optimization and Simulation for the New Power Systems Paradigm. Complexity. 2018(1). 64 indexed citations
19.
Lezama, Fernando, João Soares, Pablo Hernández-Leal, et al.. (2018). Local Energy Markets: Paving the Path Toward Fully Transactive Energy Systems. IEEE Transactions on Power Systems. 34(5). 4081–4088. 247 indexed citations
20.
Soares, João, Fernando Lezama, Tiago Pinto, & Hugo Morais. (2018). Complex Optimization and Simulation in Power Systems. Complexity. 2018(1). 2 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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