About

Distributed flexibility resources such as flexible loads energy storage devices, and renewable resources with controllable inverters, represent sources of energy flexibility in power distribution networks. This flexibility, if managed properly, not only provides a range of services (e.g., flexible energy, frequency regulation) to power systems but also creates a source of revenue for distribution system operators who would offer energy flexibility in the markets.

Our research develops fundamental models for defining and optimizing distributed energy flexibility in distribution buses, as well as deliverable energy flexibility as the aggregate distributed flexibility that is available for offering to the wholesale energy market, without jeopardizing the operational constraints of distribution networks. Our proposed queuing system for modeling load flexibility provides a framework for aggregating a large population of distributed flexible loads to supply energy flexibility in power distribution systems while satisfying the service quality constraints of customers.

Framework for scheduling deliverable energy flexibility in distribution systems (figure taken from paper: Deliverable Energy Flexibility Scheduling for Active Distribution Networks)

Select Publication

  • K. Oikonomou, M. Parvania, R. Khatami, “Deliverable Energy Flexibility Scheduling for Active Distribution Networks,” IEEE Transactions on Smart Grid, in press, 2019. DOI
  • R. Khatami, M. Heidarifar, M. Parvania, P. Khargonekar, “Scheduling and Pricing of Flexible Loads in Power Systems,” IEEE Journal of Selected Topics in Signal Processing, vol. 12, no. 4, pp. 645-656, Aug. 2018. DOI
  • K. Oikonomou, M. Parvania, R. Khatami, “Optimal Demand Response Scheduling for Water Distribution Systems,” IEEE Transactions on Industrial Informatics, vol. 14, no. 11, pp. 5112-5122, 2018. DOI
  • F. Angizeh, M. Parvania, M. Fotuhi-Firuzabad, A. Rajabi-Ghahnavie, “Flexibility Scheduling for Large Customers,” IEEE Transactions on Smart Grid, vol. 10, no. 1, pp. 371-379, 2019. DOI
  • R. Khatami, M. Parvania, A. Bagherinezhad, “Continuous-time Model Predictive Control for Real-time Flexibility Scheduling of Plugin Electric Vehicles,” in Proc. 10th IFAC Symposium on Control of Power & Energy Systems (CPES2018), Tokyo, Japan, September 4-6, 2018. DOI
  • M. Parvania, M. Fotuhi-Firuzabad, M. Shahidehpour, “ISO’s Optimal Strategies for Scheduling the Hourly Demand Response in Day-ahead Markets,” IEEE Transactions on Power Systems, vol. 29, no. 6, pp. 2636–2645, Nov. 2014. DOI
  • M. Parvania, M. Fotuhi-Firuzabad, M. Shahidehpour, “Optimal Demand Response Aggregation in Wholesale Electricity Markets,” IEEE Transactions on Smart Grid, vol. 4, no. 4, pp. 1957–1965, Dec. 2013. DOI
  • M. Parvania, M. Fotuhi-Firuzabad, “Demand Response Scheduling by Stochastic SCUC,” IEEE Transactions on Smart Grid, vol. 1, no. 1, pp. 89–98, June 2010. DOI

Funded Research Projects

  • Stochastic Continuous-time Flexibility Scheduling and Pricing in Wholesale Electricity Markets, U.S. Department of Energy, 2017-2020.