Arghya Mallick

Arghya Mallick

PhD researcher at TU Delft

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portfolio

publications

Paper Title Number 4

Published in GitHub Journal of Bugs, 2024

This paper is about fixing template issue #693.

Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
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Distributed Coordination of Multi-microgrids in Active Distribution Networks for Provisioning Ancillary Services

Published in IEEE Systems Journal, 2024

This paper presents a distributed optimization framework using the Alternating Direction Method of Multipliers (ADMM) to coordinate multiple microgrids for provisioning passive voltage support ancillary services to the transmission grid. The approach introduces novel mixed-integer inequalities to model feasible active and reactive power exchanges, leveraging inverter capabilities and storage flexibility to ensure grid support without centralized control.

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Hybrid Model Predictive Control Framework for Efficient Operation of a Five-Port Converter Interfaced DC Microgrid

Published in IEEE Transactions on Industrial Electronics, 2025

This article proposes a hybrid Model Predictive Control (MPC) framework for DC microgrids utilizing a five-port converter to optimize power sharing among PV, batteries, fuel cells, and supercapacitors while strictly adhering to manufacturer operational constraints. The study validates a hierarchical control architecture—combining supervisory MPC with local PI regulation—through a 2 kW experimental prototype, demonstrating robustness under stochastic generation and load fluctuations.

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A User-Centric Game for Balancing V2G Benefits With Battery Degradation of Electric Vehicles

Published in IEEE Transactions on Transportation Electrification, 2025

This paper presents a user-centric Vehicle-to-Grid (V2G) framework utilizing a game-theoretic, horizon-splitting strategy to dynamically arbitrate between financial revenue and battery health preservation based on explicit user preference signals. The approach integrates an enhanced semi-empirical degradation model and is validated for robustness and sensitivity under parameter uncertainty against standard multi-objective optimization benchmarks.

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talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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