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.

DPMU 2018 Workshop Co-Chair

Omid Ardakanian

Conference/Workshop

ePerf 2018 Workshop Co-Chair

Omid Ardakanian

Conference/Workshop

Advances in Distribution System Monitoring

Omid Ardakanian

Book Chapter

Harmonic State Estimation in Distribution Systems with Smart Meter and DPMU Data

Omid Ardakanian, Wei Zhou

Scholarly Refereed Journal

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

Omid Ardakanian

Scholarly Refereed Journal

On Identification of Distribution Grids

Omid Ardakanian

Scholarly Refereed Journal

Sparse Bayesian Harmonic State Estimation

Omid Ardakanian, Wei Zhou

Conference Proceedings