Rajendra Nagar - IEEE Xplore Author Profile

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Author details

Rajendra Nagar

Publications

10

Citations

51

Publications by Year

20152022

Co-Authors:

Abhinav Narayan HarishKunal KhatriPurva MhasakarDeepak MishraShanmuganathan Raman

Show All Co-Authors (7)

Rajendra Nagar

Affiliation

Indian Institute of Technology, Jodhpur, India

Publication Topics

Mirror Symmetry,
Computer Vision,
Symmetric Objects,
Symmetry Axis,
Mirror Image,
Object Detection,
Pair Of Points,
Rotational Symmetry,
Scale-invariant Feature Transform,
Approximate Symmetry,
Computer Vision Problems,
Hough Transform

Biography

Rajendra Nagar received the B.Tech. degree from Indian Institute of Technology Jodhpur, India in 2013 and is currently a Ph.D. student in Electrical Engineering at Indian Institute of Technology Gandhinagar, India. His research interests include Computer Vision, 3D Shape Analysis, and Computer Graphics. Mr. Nagar was the recipient of the TCS Research Scholarship for the period 2015–2018 and was also awarded a gold medal for the best academic performance in B.Tech. Electrical Engineering at Indian Institute of Technology, Jodhpur, in 2013.(Based on document published on 17 January 2019).

Publications

10

Citations

51

Publications by Year

20152022

Co-Authors:

Abhinav Narayan Harish
Kunal Khatri
Purva Mhasakar
Deepak Mishra
Shanmuganathan Raman

Show All Co-Authors (7)

Author's Published Works

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Showing 1-25 of 111 results

Conferences (101)

Journals (7)

Magazines (3)

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BISITE Research Centre, University of Salamanca (USAL), Salamanca, Spain(5)
GECAD research group, Polytechnic of Porto (ISEP/IPP), Porto, Portugal(5)
Department of Engineering, University of Trás-os-Montes and Alto Douro, Vila Real, Portugal(4)
GECAD - Knowledge Engineering and Decision Support Research Center, IPP - Polytechnic Institute of Porto, Porto, Portugal(4)
University of Trás-os-Montes and Alto Douro, Vila Real, Portugal(4)
2016 IEEE Symposium Series on Computational Intelligence (SSCI)(4)
2017 IEEE Symposium Series on Computational Intelligence (SSCI)(4)
2012 23rd International Workshop on Database and Expert Systems Applications(3)
2012 IEEE Power and Energy Society General Meeting(3)
2013 IEEE Grenoble Conference(3)
IEEE(110)
IET(1)
Porto, Portugal(10)
Ljubljana, Slovenia(6)
Athens, Greece(5)
Honolulu, HI, USA(4)
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Results

Synthetic minority oversampling technique for synthetic meteorological data generation*

Diogo Viana;Maria Teixeira;José Baptista;Tiago Pinto

14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion (MEDPOWER 2024)

Year: 2024 | Conference Paper |

This study investigates different approaches for synthetic data generation of time series. The main focus of this study is the Synthetic Minority Oversampling Technique (SMOTE) model, which is widely applied in several situations due to its particular ability to deal with unbalanced datasets. In order to assess the effectiveness and accuracy of different models, a comparison between them is perfor...Show More

Synthetic minority oversampling technique for synthetic meteorological data generation*

Diogo Viana;Maria Teixeira;José Baptista;Tiago Pinto

14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion (MEDPOWER 2024)

Year: 2024 | Volume: 2024 | Conference Paper |

Electric Vehicle Batteries and Storage: A Literature Review of Current and Future Solutions

João Ferreira;António Jorge Gouveia;Cristiano Pendão;Arsénio Reis;Tiago Pinto;João Barroso

2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE)

Year: 2024 | Conference Paper |

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With the progressive increase in electric vehicles and the carbon neutrality goals set for 2050, it is important to commit to optimizing batteries and their lifespan. Studies have been conducted to improve and understand storage systems and to determine the best ones to use in specific situations. Combining battery lifespan, the number of charging cycles, specific energy, and power can sometimes b...Show More

Electric Vehicle Batteries and Storage: A Literature Review of Current and Future Solutions

João Ferreira;António Jorge Gouveia;Cristiano Pendão;Arsénio Reis;Tiago Pinto;João Barroso

2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE)

Year: 2024 | Conference Paper |

Renewable energy communities and business models: a review

Dani Vidal;José Baptista;Hugo Morais;Joao Ferreira;Tiago Pinto

2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE)

Year: 2024 | Conference Paper |

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Renewable energy communities are increasingly becoming a field of great interest. This is mainly due to the advancement of technology but also the global concern to reduce carbon emissions and also create economic and social benefits. Business models play a crucial role in these communities, as a well-structured business model can facilitate the integration of innovative technologies, optimize the...Show More

Renewable energy communities and business models: a review

Dani Vidal;José Baptista;Hugo Morais;Joao Ferreira;Tiago Pinto

2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE)

Year: 2024 | Conference Paper |

Solar Intensity Prediction with Semi-Supervised Learning

José Pereira;Tiago Pinto;José Baptista

2024 IEEE Power & Energy Society General Meeting (PESGM)

Year: 2024 | Conference Paper |

The growth seen in the use of technologies that use natural resources as primary energy sources (eg.: wind, solar, etc.) has given rise to new problems in the management, control and planning of electrical energy systems. One of the most complex tasks is to predict the amount of energy produced by these types of technologies, since they depend on natural resources that are difficult to predict. Th...Show More

Solar Intensity Prediction with Semi-Supervised Learning

José Pereira;Tiago Pinto;José Baptista

2024 IEEE Power & Energy Society General Meeting (PESGM)

Year: 2024 | Conference Paper |

Synthetic Data Generation Models for Time Series: A Literature Review

Diogo Viana;Rita Teixeira;José Baptista;Tiago Pinto

2024 International Conference on Electrical, Computer and Energy Technologies (ICECET

Year: 2024 | Conference Paper |

Cited by: Papers (1)

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This article presents a comprehensive state of the art analysis of the challenging domain of synthetic data generation. Focusing on the problem of synthetic data generation, the paper explores various difficulties that are identified, especially in real-world problems such as those is the scope of power and, energy systems, including the amount of data, data privacy concerns, temporal consideratio...Show More

Synthetic Data Generation Models for Time Series: A Literature Review

Diogo Viana;Rita Teixeira;José Baptista;Tiago Pinto

2024 International Conference on Electrical, Computer and Energy Technologies (ICECET

Year: 2024 | Conference Paper |

Identification of Consumption Patterns in Household Appliances using Data Association Model

Luis Carneiro;Tiago Pinto;José Baptista

2024 IEEE Power & Energy Society General Meeting (PESGM)

Year: 2024 | Conference Paper |

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Currently, energy consumption in residential buildings is increasingly high. To meet demand, renewable energies are increasingly being used to produce more energy in a sustainable way, which has led to an increase in the load on the distribution network. Thus, with the exponential growth of dependence on technologies, studies on consumption patterns are increasingly common in order to try to under...Show More

Identification of Consumption Patterns in Household Appliances using Data Association Model

Luis Carneiro;Tiago Pinto;José Baptista

2024 IEEE Power & Energy Society General Meeting (PESGM)

Year: 2024 | Conference Paper |

Explainable Artificial Intelligence for Deep Synthetic Data Generation Models

Luís Valina;Brígida Teixeira;Arsénio Reis;Zita Vale;Tiago Pinto

2024 IEEE Conference on Artificial Intelligence (CAI)

Year: 2024 | Conference Paper |

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Artificial intelligence encapsulates a "black box" of undiscovered knowledge, propelling the exploration of Explainable Artificial Intelligence (XAI) in generative data synthesis and deep learning. Focused on unveiling these "black box" areas, pointed into interpretability and validation in synthetic data generation, shedding light on the intricacies of generative processes. XAI techniques illumin...Show More

Explainable Artificial Intelligence for Deep Synthetic Data Generation Models

Luís Valina;Brígida Teixeira;Arsénio Reis;Zita Vale;Tiago Pinto

2024 IEEE Conference on Artificial Intelligence (CAI)

Year: 2024 | Conference Paper |

Decision-making models in the optimization of electric vehicle charging station locations: a review

João Pinto;Vítor Filipe;José Baptista;Antonio Oliveira;Tiago Pinto

2024 IEEE 22nd Mediterranean Electrotechnical Conference (MELECON)

Year: 2024 | Conference Paper |

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The number of electric vehicles is increasing progressively for various reasons, including economic and environmental factors. There has also been a technological development regarding both the operation and charging of these vehicles. Therefore, it is very important to reinforce the charging infrastructure, which can be optimised through the application of computational tools. There are several a...Show More

Decision-making models in the optimization of electric vehicle charging station locations: a review

João Pinto;Vítor Filipe;José Baptista;Antonio Oliveira;Tiago Pinto

2024 IEEE 22nd Mediterranean Electrotechnical Conference (MELECON)

Year: 2024 | Conference Paper |

Maximizing PV Hosting Capacity in Unbalanced Distribution Systems with High EVs Penetration

Jairo G. Yumbla Romero;Juan M. Home-Ortiz;Tiago Pinto;José R. S. Mantovani

2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)

Year: 2023 | Conference Paper |

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This paper presents a stochastic scenario-based mixed-integer nonlinear programming (MINLP) model to maximize the photovoltaic-based (PV-based) hosting capacity in unbalanced distribution systems with high penetration of electric vehicles (EVs). The solution of the proposed model determines the optimal operation of voltage regulators (VRs), switched capacitor banks (SCBs), and energy storage devic...Show More

Maximizing PV Hosting Capacity in Unbalanced Distribution Systems with High EVs Penetration

Jairo G. Yumbla Romero;Juan M. Home-Ortiz;Tiago Pinto;José R. S. Mantovani

2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)

Year: 2023 | Conference Paper |

Automated energy management and learning

Gabriel Santos;Brígida Teixeira;Tiago Pinto;Zita Vale

2023 IEEE Conference on Artificial Intelligence (CAI)

Year: 2023 | Conference Paper |

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Automatic energy management systems allow users’ active participation in flexibility management while assuring their energy demands. We propose a transparent framework for automated energy management to increase trust and improve the learning process, combining machine learning, experts’ knowledge, and semantic reasoning. A practical example of thermal comfort shows the advantages of the framework...Show More

Automated energy management and learning

Gabriel Santos;Brígida Teixeira;Tiago Pinto;Zita Vale

2023 IEEE Conference on Artificial Intelligence (CAI)

Year: 2023 | Conference Paper |

Application of XAI-based framework for PV Energy Generation Forecasting

Brígida Teixeira;Leonor Carvalhais;Tiago Pinto;Zita Vale

2023 IEEE Conference on Artificial Intelligence (CAI)

Year: 2023 | Conference Paper |

Cited by: Papers (3)

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The structural changes in the energy sector caused by renewable sources and digitization have resulted in an increased use of Artificial Intelligence (AI), including Machine Learning (ML) models. However, these models’ black-box nature and complexity can create issues with transparency and trust, thereby hindering their interpretability. The use of Explainable AI (XAI) can offer a solution to thes...Show More

Application of XAI-based framework for PV Energy Generation Forecasting

Brígida Teixeira;Leonor Carvalhais;Tiago Pinto;Zita Vale

2023 IEEE Conference on Artificial Intelligence (CAI)

Year: 2023 | Conference Paper |

Designing augmented reality cards as an educational resource to teach Portuguese Sign Language

Tânia Rocha;Tiago Pinto;Diana Carvalho;Paulo Martins;João Barroso

2022 Third International Conference on Digital Creation in Arts, Media and Technology (ARTeFACTo)

Year: 2022 | Conference Paper |

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This paper presents an educational resource to support the teaching of Portuguese sign language. This educational resource emerges in response to the significant needs for the development of adequate digital tools to support deaf people in different tasks, especially in the language learning process. This work is motivated by the results and conclusions from previous studies that identify augmente...Show More

Designing augmented reality cards as an educational resource to teach Portuguese Sign Language

Tânia Rocha;Tiago Pinto;Diana Carvalho;Paulo Martins;João Barroso

2022 Third International Conference on Digital Creation in Arts, Media and Technology (ARTeFACTo)

Year: 2022 | Conference Paper |

Schedule Peer-to-Peer Transactions of an Energy Community Using Particle Swarm

Miguel Vieira;Ricardo Faia;Tiago Pinto;Zita Vale

2022 18th International Conference on the European Energy Market (EEM)

Year: 2022 | Conference Paper |

Cited by: Papers (2)

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The integration of distributed energy resources contributes to accomplishing a balance between the supply and demand inside a local market. The operation of these markets is based on the peer-to-peer negotiations between users, whose cooperation leads to an increase in the social welfare of the community, thus creating a more user-centric market. This work fits in the context of the energy communi...Show More

Schedule Peer-to-Peer Transactions of an Energy Community Using Particle Swarm

Miguel Vieira;Ricardo Faia;Tiago Pinto;Zita Vale

2022 18th International Conference on the European Energy Market (EEM)

Year: 2022 | Conference Paper |

Blockchain-based Local Electricity Market Solution

Gabriel Santos;Ricardo Faia;Helder Pereira;Tiago Pinto;Zita Vale

2022 18th International Conference on the European Energy Market (EEM)

Year: 2022 | Conference Paper |

Cited by: Papers (2)

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The growth of renewable energy sources usage at the local level contributes to decentralizing the power and energy systems. Nowadays, there is an increment of residential consumers becoming prosumers able to consume their generation or sell it to the public grid to reduce the electricity bill. This great penetration of electricity compromises the proper functioning of the system. Local electricity...Show More

Blockchain-based Local Electricity Market Solution

Gabriel Santos;Ricardo Faia;Helder Pereira;Tiago Pinto;Zita Vale

2022 18th International Conference on the European Energy Market (EEM)

Year: 2022 | Conference Paper |

Advanced Clearing Model in Prosumer Centric Local Flexibility Market

Rui Carvalho;Ricardo Faia;Gabriel Santos;Tiago Pinto;Zita Vale

2022 18th International Conference on the European Energy Market (EEM)

Year: 2022 | Conference Paper |

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The local flexibility market models have emerged as a market-based solution to respond to the challenges that the increase in distributed energy resources caused in the power and energy systems. Using Smart Grid enabling technologies, consumers and prosumers are prepared to respond to any possible demand-side flexibility event. In this scope, this work presents an advanced bidding model for the pr...Show More

Advanced Clearing Model in Prosumer Centric Local Flexibility Market

Rui Carvalho;Ricardo Faia;Gabriel Santos;Tiago Pinto;Zita Vale

2022 18th International Conference on the European Energy Market (EEM)

Year: 2022 | Conference Paper |

Consumer Flexibility Aggregation Using Partition Function Games With Non-Transferable Utility

Tiago Pinto;Michael Wooldridge;Zita Vale

Year: 2021 | Volume: 9 | Journal Article |

Cited by: Papers (3)

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This paper explores the aggregation of electricity consumers flexibility. A novel coalitional game theory model for partition function games with non-transferable utility is proposed. This model is used to formalize a game in which electricity consumers find coalitions among themselves in order to trade their consumption flexibility in the electricity market. Utility functions are defined to enabl...Show More

Consumer Flexibility Aggregation Using Partition Function Games With Non-Transferable Utility

Tiago Pinto;Michael Wooldridge;Zita Vale

Year: 2021 | Volume: 9 | Journal Article |

Optimal Model for Local Energy Community Scheduling Considering Peer to Peer Electricity Transactions

Ricardo Faia;João Soares;Tiago Pinto;Fernando Lezama;Zita Vale;Juan Manuel Corchado

Year: 2021 | Volume: 9 | Journal Article |

Cited by: Papers (67)

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The current energy strategy of the European Union puts the end-user as a key participant in electricity markets. The creation of energy communities has been encouraged by the European Union to increase the penetration of renewable energy and reduce the overall cost of the energy chain. Energy communities are mostly composed of prosumers, which may be households with small-size energy production eq...Show More

Optimal Model for Local Energy Community Scheduling Considering Peer to Peer Electricity Transactions

Ricardo Faia;João Soares;Tiago Pinto;Fernando Lezama;Zita Vale;Juan Manuel Corchado

Year: 2021 | Volume: 9 | Journal Article |

Exploiting flexibility of end-users at DSO-TSO levels acting in dynamic coalitions

Fernando Lezama;Tiago Pinto;Ricardo Faia;Zita Vale

2020 IEEE Power & Energy Society General Meeting (PESGM)

Year: 2020 | Conference Paper |

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In this paper, we propose and analyze a coalitional game in which end-users with different characteristics and preferences can cooperate to offer their flexibility to upper-level entities such as the DSO and TSO. We formulate the problem as a cooperative game in which users need to decide the percentage of flexibility they want to offer to DSO and TSO, while searching for the coalition structures ...Show More

Exploiting flexibility of end-users at DSO-TSO levels acting in dynamic coalitions

Fernando Lezama;Tiago Pinto;Ricardo Faia;Zita Vale

2020 IEEE Power & Energy Society General Meeting (PESGM)

Year: 2020 | Conference Paper |

Application Ontology for Multi-Agent and Web-Services’ Co-Simulation in Power and Energy Systems

Brígida Teixeira;Gabriel Santos;Tiago Pinto;Zita Vale;Juan M. Corchado

Year: 2020 | Volume: 8 | Journal Article |

Cited by: Papers (16)

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Power and energy systems are very complex, and several tools are available to assist operators in their planning and operation. However, these tools do not allow a sensitive analysis of the impact of the interaction between the different sub-domains and, consequently, in obtaining more realistic and reliable results. One of the key challenges in this area is the development of decision support too...Show More

Application Ontology for Multi-Agent and Web-Services’ Co-Simulation in Power and Energy Systems

Brígida Teixeira;Gabriel Santos;Tiago Pinto;Zita Vale;Juan M. Corchado

Year: 2020 | Volume: 8 | Journal Article |

Adaptive Learning in Electricity Market Negotiations Based on Determinism Theory

IEEE Intelligent Systems

Year: 2020 | Volume: 35, Issue: 1 | Magazine Article |

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This research proposes a novel methodology for adaptive learning in electricity markets negotiations, based on the principles of the determinism theory. The determinism theory states that all events are predetermined due to the cause-effect rule. At the same time, it is unmanageable to consider all causes to a certain effect, making it impossible to predict future events. However, in a controlled ...Show More

Adaptive Learning in Electricity Market Negotiations Based on Determinism Theory

IEEE Intelligent Systems

Year: 2020 | Volume: 35, Issue: 1 | Magazine Article |

Multi-agent semantic interoperability in complex energy systems simulation and decision support

Gabriel Santos;Tiago Pinto;Zita Vale;Juan Manuel Corchado

2019 20th International Conference on Intelligent System Application to Power Systems (ISAP)

Year: 2019 | Conference Paper |

Cited by: Papers (5)

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This work introduces a multi-agent systems' society, in power and energy, for simulation and decision support. A semantic data model is considered to describe the domain concepts, providing a way to achieve semantic communication between the systems involved. Sharing a common vocabulary enables systems' interoperability. A semantic registration and search platform, where systems can register their...Show More

Multi-agent semantic interoperability in complex energy systems simulation and decision support

Gabriel Santos;Tiago Pinto;Zita Vale;Juan Manuel Corchado

2019 20th International Conference on Intelligent System Application to Power Systems (ISAP)

Year: 2019 | Conference Paper |

Classification of local energy trading negotiation profiles using artificial neural networks

Angelo Pinto;Tiago Pinto;Isabel Praça;Zita Vale

2019 IEEE Power & Energy Society General Meeting (PESGM)

Year: 2019 | Conference Paper |

Cited by: Papers (1)

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Electricity markets are evolving into a local trading setting, which makes it for unexperienced players to achieve good agreements and obtain profits. One of the solutions to deal with this issue is to provide players with decision support solutions capable of identifying opponents' negotiation profiles, so that negotiation strategies can be adapted to those profiles in order to reach the best pos...Show More

Classification of local energy trading negotiation profiles using artificial neural networks

Angelo Pinto;Tiago Pinto;Isabel Praça;Zita Vale

2019 IEEE Power & Energy Society General Meeting (PESGM)

Year: 2019 | Conference Paper |

A Local Electricity Market Model for DSO Flexibility Trading

Ricardo Faia;Tiago Pinto;Zita Vale;Juan Manuel Corchado

2019 16th International Conference on the European Energy Market (EEM)

Year: 2019 | Conference Paper |

Cited by: Papers (16)

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The necessity of end-user engagement in power systems have become a reality in recent times. One of the solutions to this engagement is the creation of local energy markets. The distribution systems operators are compelled to investigate and optimize their asset investment cost in reinforcement of grids by introducing smart grid functionalities in order to avoid investments. The congestion managem...Show More

A Local Electricity Market Model for DSO Flexibility Trading

Ricardo Faia;Tiago Pinto;Zita Vale;Juan Manuel Corchado

2019 16th International Conference on the European Energy Market (EEM)

Year: 2019 | Conference Paper |

Distributed learning of energy contracts negotiation strategies with collaborative reinforcement learning

Tiago Pinto;Zita Vale

2019 16th International Conference on the European Energy Market (EEM)

Year: 2019 | Conference Paper |

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The evolution of electricity markets towards local energy trading models, including peer-to-peer transactions, is bringing by multiple challenges for the involved players. In particular, small consumers, prosumers and generators, with no experience on participating in competitive energy markets, are not prepared for facing such an environment. This paper addresses this problem by proposing a decis...Show More

Distributed learning of energy contracts negotiation strategies with collaborative reinforcement learning

Tiago Pinto;Zita Vale

2019 16th International Conference on the European Energy Market (EEM)

Year: 2019 | Conference Paper |

A Review of the Main Machine Learning Methods for Predicting Residential Energy Consumption

Alfonso González-Briones;Guillermo Hernández;Tiago Pinto;Zita Vale;Juan M. Corchado

2019 16th International Conference on the European Energy Market (EEM)

Year: 2019 | Conference Paper |

Cited by: Papers (13)

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The ability to predict future energy consumption is very important for energy distribution companies because it allows them to estimate energy needs and supply them accordingly. Consumption prediction makes it possible for those companies to optimize their processes by, for example, providing them with knowledge about future periods of high energy demand or by enabling them to adapt their tariffs ...Show More

A Review of the Main Machine Learning Methods for Predicting Residential Energy Consumption

Alfonso González-Briones;Guillermo Hernández;Tiago Pinto;Zita Vale;Juan M. Corchado

2019 16th International Conference on the European Energy Market (EEM)

Year: 2019 | Conference Paper |

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