Vladimiro Miranda

8.6k total citations
202 papers, 6.2k citations indexed

About

Vladimiro Miranda is a scholar working on Electrical and Electronic Engineering, Safety, Risk, Reliability and Quality and Control and Systems Engineering. According to data from OpenAlex, Vladimiro Miranda has authored 202 papers receiving a total of 6.2k indexed citations (citations by other indexed papers that have themselves been cited), including 171 papers in Electrical and Electronic Engineering, 42 papers in Safety, Risk, Reliability and Quality and 34 papers in Control and Systems Engineering. Recurrent topics in Vladimiro Miranda's work include Electric Power System Optimization (62 papers), Energy Load and Power Forecasting (56 papers) and Optimal Power Flow Distribution (47 papers). Vladimiro Miranda is often cited by papers focused on Electric Power System Optimization (62 papers), Energy Load and Power Forecasting (56 papers) and Optimal Power Flow Distribution (47 papers). Vladimiro Miranda collaborates with scholars based in Portugal, Brazil and United States. Vladimiro Miranda's co-authors include Ricardo J. Bessa, Audun Botterud, João Tomé Saraiva, Adriana Castro, Jean Sumaili, Hrvoje Keko, Manuel Matos, N. Fonseca, Jun Wang and Leonel Carvalho and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied Energy and IEEE Transactions on Power Systems.

In The Last Decade

Vladimiro Miranda

196 papers receiving 5.8k citations

Peers

Vladimiro Miranda

EEE

CSE

SRRQ

RESE

James D. McCalley United States

C. Y. Chung Hong Kong

Payman Dehghanian United States

Zhaoyu Wang United States

F.D. Galiana Canada

Wei‐Jen Lee United States

G.T. Heydt United States

Kevin Tomsovic United States

Zhaoyang Dong Australia

Junbo Zhao United States

James D. McCalley United States

Vladimiro Miranda

5.4k ×1.1

EEE

2.6k ×1.8

CSE

2.3k ×2.0

SRRQ

271 ×0.3

263 ×0.9

RESE

Citations per year, relative to Vladimiro Miranda Vladimiro Miranda (= 1×) peers James D. McCalley

Countries citing papers authored by Vladimiro Miranda

Since Specialization

Citations

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

Fields of papers citing papers by Vladimiro Miranda

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vladimiro Miranda

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

All Works

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20 of 20 papers shown

Soares, Tiago, et al.. (2024). Virtual power plant optimal dispatch considering power-to-hydrogen systems. International Journal of Hydrogen Energy. 68. 1019–1032. 15 indexed citations

Massignan, Júlio A. D., et al.. (2021). Bayesian Inference Approach for Information Fusion in Distribution System State Estimation. IEEE Transactions on Smart Grid. 13(1). 526–540. 45 indexed citations

Moayyed, Hamed, et al.. (2019). Favorable properties of Interior Point Method and Generalized Correntropy in power system State Estimation. Electric Power Systems Research. 178. 106035–106035. 9 indexed citations

Costa, Flávio B., et al.. (2018). Wavelet-based analysis and detection of traveling waves due to DC faults in LCC HVDC systems. International Journal of Electrical Power & Energy Systems. 104. 291–300. 37 indexed citations

Miranda, Vladimiro. (2017). Successful large-scale renewables integration in portugal: Technology and intelligent tools. CSEE Journal of Power and Energy Systems. 3(1). 7–16. 8 indexed citations

Miranda, Vladimiro, et al.. (2013). Breaker status uncovered by autoencoders under unsupervised maximum mutual information training. 8 indexed citations

Araújo, F. M., et al.. (2012). Fiber laser sensor based on a phase-shifted chirped grating for acoustic sensing of partial discharges. Photonic Sensors. 3(1). 44–51. 16 indexed citations

Miranda, Vladimiro, et al.. (2011). A comparison of metaheuristics algorithms for combinatorial optimization problems. application to phase balancing in electric distribution systems. Latin American Applied Research - An international journal. 41(2). 113–120. 5 indexed citations

Miranda, Vladimiro, et al.. (2010). Metaheurística FEPSO aplicada a problemas de Optimización Combinatoria: Balance de Fases en Sistemas de Distribución Eléctrica. SHILAP Revista de lepidopterología. 3 indexed citations

10.

Bessa, Ricardo J., et al.. (2008). Wind Power Forecasting with Entropy-Based Criteria Algorithms. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 1–7. 6 indexed citations

11.

Silva, Armando M. Leite da, Leonidas C. Resende, Luiz Antônio da Fonseca Manso, & Vladimiro Miranda. (2008). Artificial Neural Networks Applied to Reliability and Well-Being Assessment of Composite Power Systems. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 1–6. 7 indexed citations

12.

Miranda, Vladimiro, et al.. (2007). A fuzzy dynamic programming approach for evaluation of expansion distribution cost in uncertainty environments. Latin American Applied Research - An international journal. 37(4). 227–234. 4 indexed citations

13.

Khodr, H.M., et al.. (2007). Optimal Design of Grounding System in Transmission Line. 2. 1–9. 7 indexed citations

14.

Miranda, Vladimiro, André Moreira, & Jorge Pereira. (2007). An Improved Fuzzy Inference System for Voltage/VAR Control. 306–311. 4 indexed citations

15.

Matos, Manuel, et al.. (2004). Metaheuristics applied to power systems. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT).

16.

Pereira, Jorge, João Tomé Saraiva, & Vladimiro Miranda. (2004). An integrated load allocation/state estimation approach for distribution networks. 180–185. 9 indexed citations

17.

Miranda, Vladimiro, et al.. (2004). Prediction of LV substation load curves with fuzzy inference systems. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 129–134. 3 indexed citations

18.

Miranda, Vladimiro, et al.. (2002). NEW EVOLUTIONARY PARTICLE SWARM ALGORITHM (EPSO) APPLIED TO VOLTAGE/VAR CONTROL. The Spanish Journal of Psychology. 9(2). 300–11. 70 indexed citations

19.

Saraiva, João Tomé, Vladimiro Miranda, & L.M.V.G. Pinto. (1996). Generation/transmission power system reliability evaluation by Monte-Carlo simulation assuming a fuzzy load description. IEEE Transactions on Power Systems. 11(2). 690–695. 60 indexed citations

20.

Miranda, Vladimiro, et al.. (1995). A General Methodology For Distribution Planning Under Uncertainty, Including Genetic Algorithms And Fuzzy Models In A Multi-Criteria Environment. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 15 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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