activity
20232025
most citedFedWOA: A Federated Learning Model that uses the Whale Optimization Algorithm for Renewable Energy Prediction

3 citations · 3 across the 7 of their papers we have counts for

collaborators

7 papers

cs.GT2025

Microgrids Coalitions for Energy Market Balancing

Viorica Chifu, Cristina Bianca Pop, Tudor Cioara +1

With the integration of renewable sources in electricity distribution networks, the need to develop intelligent mechanisms for balancing the energy market has arisen. In the absenc…

cs.LG2025

From Transformers to Large Language Models: A systematic review of AI applications in the energy sector towards Agentic Digital Twins

Gabriel Antonesi, Tudor Cioara, Ionut Anghel +3

Artificial intelligence (AI) has long promised to improve energy management in smart grids by enhancing situational awareness and supporting more effective decision-making. While t…

cs.NE2025

Evolutionary model for energy trading in community microgrids using Hawk-Dove strategies

Viorica Rozina Chifu, Tudor Cioara, Cristina Bianca Pop +1

This paper proposes a decentralized model of energy cooperation between microgrids, in which decisions are made locally, at the level of the microgrid community. Each microgrid is…

cs.NI2024

Edge Offloading in Smart Grid

Gabriel Ioan Arcas, Tudor Cioara, Ionut Anghel +2

The energy transition supports the shift towards more sustainable energy alternatives, paving towards decentralized smart grids, where the energy is generated closer to the point o…

cs.LG2024

A Deep Q-Learning based Smart Scheduling of EVs for Demand Response in Smart Grids

Viorica Rozina Chifu, Tudor Cioara, Cristina Bianca Pop +2

Economic and policy factors are driving the continuous increase in the adoption and usage of electrical vehicles (EVs). However, despite being a cleaner alternative to combustion e…

cs.LG20233 cited

FedWOA: A Federated Learning Model that uses the Whale Optimization Algorithm for Renewable Energy Prediction

Viorica Chifu, Tudor Cioara, Cristian Anitiei +2

Privacy is important when dealing with sensitive personal information in machine learning models, which require large data sets for training. In the energy field, access to househo…