Energy Management Strategies for Distributed Energy Resources

The availability of high-resolution historical data from the grid, smart inverters, and advanced metering infrastructure has made it possible to develop accurate models of the state of the power system, available renewable generation, demands, and user preferences. This project aims to develop proactive, data-driven energy management strategies that combine real-time measurements with predictions of these models to optimally control a vast number of Distributed Energy Resources (DERs) for improved reliability and efficiency. The efficacy of these strategies is evaluated using an advanced test environment available in the Future Smart Grid Technologies lab. Additionally, a state-of-the-art monitoring and control infrastructure will be developed for the smart grid which enables large-scale integration and seamless operation of geographically dispersed DERs. This infrastructure will support the execution of decentralized, proactive, and data-driven energy management strategies, which will play a pivotal role in enhancing efficiency, reliability, and cybersecurity of the smart grid.

ACM BuildSys 2022 Best Paper Award

Omid Ardakanian, Saidur Rahman

Award

ASTech Award for Outstanding Achievement in AI/ML Advancement: Energy and Environmental Innovation

Omid Ardakanian

Award

A Co-simulation Platform for Evaluating Cyber Security and Control Applications in the Smart Grid

Omid Ardakanian, Ioanis Nikolaidis, Evandro de Souza

Conference Proceedings

Adaptive Congestion Control for Electric Vehicle Charging in the Smart Grid

Omid Ardakanian, Moosa Moghimi Haji, Abdullah Al Zishan

Peer-Reviewed Journal Article

Adaptive Control of Plug-in Electric Vehicle Charging with Reinforcement Learning

Omid Ardakanian, Moosa Moghimi Haji, Abdullah Al Zishan

Conference Proceedings

Advances in Distribution System Monitoring

Omid Ardakanian

Book Chapter

Adversarial Attacks on Machine Learning-Based State Estimation in Power Distribution Systems

Omid Ardakanian, Afia Afrin

Conference Proceedings

Bayesian Learning-Based Harmonic State Estimation in Distribution Systems with Smart Meter and DPMU Data

Omid Ardakanian, Wei Zhou

Peer-Reviewed Journal Article

Co-Chair of Energy Storage Workshop 2020

Omid Ardakanian

Conference/Symposium/Workshop Contribution

DPMU 2018 Workshop Co-Chair

Omid Ardakanian

Conference/Symposium/Workshop Contribution

Data Efficient Energy Disaggregation with Behind-the-meter Energy Resources

Omid Ardakanian, Xinlei Chen

Peer-Reviewed Journal Article

Data Efficient Solar Disaggregation with Behind-the-meter Energy Resources

Xinlei Chen

Master Thesis

Design and Optimal Operation of a Virtual Power Plant with Bidirectional Electric Vehicle Chargers

Saidur Rahman

Master Thesis

Detecting Adversarial Attacks on Distribution System State Estimation with Feature Attributions

Omid Ardakanian, Afia Afrin

Research Report

Disaggregating Solar Generation Using Smart Meter Data and Proxy Measurements from Neighbouring Sites

Omid Ardakanian, Moosa Moghimi Haji, Xinlei Chen

Conference Proceedings

Efficient Trading of Aggregate Bidirectional EV Charging Flexibility with Reinforcement Learning

Omid Ardakanian, Javier Sales-Ortiz

Conference Proceedings

Electric Vehicle Charging Station Resource Allocation: A Data-Driven Robust Optimization Approach

Mohammadhadi Rouhani

Master Thesis

EnergyBoost: Learning-based Control of Home Batteries

Omid Ardakanian, Baihong Qi, Mohammad Rashedi

Conference Proceedings

False Data Injection Attacks on Smart Grid Voltage Regulation with Stochastic Communication Model

Hao Liang, Yuan Liu, Omid Ardakanian, Ioanis Nikolaidis

Peer-Reviewed Journal Article

Guest Editorial Theory and Application of PMUs in Power Distribution Systems

Omid Ardakanian

Peer-Reviewed Journal Article

IEEE EPEC 2020 Publications Chair

Omid Ardakanian

Conference/Symposium/Workshop Contribution

Inverse Power Flow Problem

Omid Ardakanian

Peer-Reviewed Journal Article

Learning to Control Home Batteries in the Smart Grid

Baihong Qi

Master Thesis

Leveraging Sparsity in Distribution Grids: System Identification and Harmonic State Estimation

Omid Ardakanian

Peer-Reviewed Journal Article

Making a Virtual Power Plant out of Privately Owned Electric Vehicles: From Contract Design to Scheduling

Omid Ardakanian, Saidur Rahman, Javier Sales-Ortiz

Conference Proceedings

On Adversarial Robustness of Data-Driven State Estimation Techniques

Afia Afrin

Master Thesis

On Brittleness of Data-Driven Distribution System State Estimation to Targeted Attacks

Omid Ardakanian, Afia Afrin

Conference Proceedings

On Efficient Operation of a V2G-Enabled Virtual Power Plant

Omid Ardakanian, Saidur Rahman

Conference Proceedings

On Identification of Distribution Grids

Omid Ardakanian

Peer-Reviewed Journal Article

On the Control of Electric Vehicle Charging in the Smart Grid

Abdullah Al Zishan

Master Thesis

Practical Considerations in the Design of Distribution State Estimation Techniques

Omid Ardakanian, Moosa Moghimi Haji

Conference Proceedings

Reputation-Based Fair Power Allocation to Plug-in Electric Vehicles in the Smart Grid

Omid Ardakanian, Moosa Moghimi Haji, Abdullah Al Zishan

Conference Proceedings

Robust Sizing of Solar-Powered Charging Station with Co-located Energy Storage

Petr Musilek, Mohammadhadi Rouhani, Omid Ardakanian

Conference Proceedings

Solar Disaggregation: State of the Art and Open Challenges

Omid Ardakanian, Xinlei Chen

Conference Proceedings

Sparse Bayesian Harmonic State Estimation

Omid Ardakanian, Wei Zhou

Conference Proceedings

TPC Co-Chair of the Twelfth ACM International Conference on Future Energy Systems

Omid Ardakanian

Conference/Symposium/Workshop Contribution

Towards Efficient Co-Simulation of Cyber-Physical Systems

Talha Ibn Aziz

Master Thesis

ePerf 2018 Workshop Co-Chair

Omid Ardakanian

Conference/Symposium/Workshop Contribution