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Faegheh Moazeni

assistant professor

Lehigh University

United States

Research Interests

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About

Dr. Faegheh Moazeni is an Assistant Professor at Lehigh University, located in the United States. Her research interests encompass data-driven economic dispatch, predictive control of water and energy systems, and cybersecurity frameworks for smart infrastructure. Recent publications include works on the operational management of distributed energy resources and the stability of microgrids, focusing on both renewable energy and water distribution systems.

Articles (20)

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2021

Collaborators (4)

Shirley Clark

Professor of Environmental Engineering

Penn State Harrisburg

UNITED STATES

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Y. C. Ethan Yang

Associate Professor

Lehigh University

UNITED STATES

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Oluwabunmi Iwakin

Lehigh University

UNITED STATES

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Arindam Banerjee

Professor

Lehigh University

UNITED STATES

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Faegheh Moazeni

Research Interests

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About

Articles (20)

Enhanced imitation learning of robust nonlinear model predictive control via temporal convolutional neural network for DC shipboard microgrid

Microgrid Power Sharing: Adaptive vs. Nonlinear Predictive Models

A Two-Stage Nonlinear Model Predictive Control for Navigation-Driven Power Allocation in Autonomous Naval Ships

Data-driven economic dispatch towards operational management of distributed energy resources for grid-connected water–energy microgrids

Optimal cybersecurity framework for smart water system: Detection, localization and severity assessment

Machine learning models for the economic dispatch of islanded micro water-energy systems

Stability-guaranteed data-driven nonlinear predictive control of water distribution systems

Economic dispatch of offshore renewable energy resources for islanded communities with optimal storage sizing

Automation-Driven Robust Neural Predictive Control for DC Shipboard Microgrids

Data-Driven Nonlinear Model Predictive Control for Power Sharing of Inverter-Based Resources

Chance-constrained vulnerability assessment of smart water distribution systems against stealthy false data injection attacks

Flood Risks of Cyber‐Physical Attacks in a Smart Storm Water System

Stability and Feasibility-Driven Predictive Control for Next-Generation Naval Microgrids

Neural Networks-Based Detection of Line Overflow Cyberattacks on AC State-Estimation of Smart Grids

Predictive control of interlinked water-energy microgrids

Neural Networks-Based Detection of Line Overflow Cyberattacks on AC State-Estimation of Smart Grids

Detection of false data injection attacks leading to line congestions using Neural networks

Removal of heavy metals from aqueous solutions using carbonised banana and orange peels

Formulating false data injection cyberattacks on pumps’ flow rate resulting in cascading failures in smart water systems

Interactive nonlinear multiobjective optimal design of water distribution systems using Pareto navigator technique

Collaborators (4)

Shirley Clark

Y. C. Ethan Yang

Oluwabunmi Iwakin

Arindam Banerjee

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