About

Large-scale integration of intermittent renewable energy sources is calling for additional flexibility resources as well as more advanced modeling and optimization techniques to account for the increasing uncertainty and variability in power systems operation.

Our research develops fundamental models and theorems for scheduling and pricing of flexibility resources (fast-ramping generating units, energy storage devices, flexible demand) as well as defining and characterizing flexibility reserve in power systems operation. Our fundamental models pioneer the application of continuous-time optimization models in power systems, which uniquely defines ramping trajectory as an explicit variable and provides a more accurate modeling approach for reflecting the intertemporal characteristics and constraints of flexibility resources in scheduling and pricing of services in the systems.

Generation schedule using discrete-time and continuous-time unit commitment (figures taken from paper "Unit Commitment with Continuous-time Generation and Ramping Trajectory Models")

Select Publication

  • A. Bagherinezhad, R. Khatami, M. Parvania, “Continuous-Time Look-Ahead Flexible Ramp Scheduling in Real-time Operation,” International Journal of Electrical Power and Energy Systems, vol. 119, pp. 105895, July 2020. DOI
  • R. Khatami, M. Parvania, “Spatio-Temporal Value of Energy Storage in Transmission Networks,” IEEE Systems Journal, in press, 2020. DOI
  • R. Khatami, M. Parvania, A. Narayan, “Flexibility Reserve in Power Systems: Definition and Stochastic Multi-Fidelity Optimization,” IEEE Transactions on Smart Grid, vol. 11, no. 1, pp. 644-654, 2020. DOI
  • K. Oikonomou, M. Parvania, R. Khatami, “Deliverable Energy Flexibility Scheduling for Active Distribution Networks,” IEEE Transactions on Smart Grid, vol. 11, no. 1, pp. 655-664, 2020. DOI
  • R. Khatami, M. Parvania, “Stochastic Multi-Fidelity Scheduling of Flexibility Reserve for Energy Storage,” IEEE Transactions on Sustainable Energy, in press, 2019. DOI
  • R. Khatami, M. Parvania, “Continuous-time Locational Marginal Price of Electricity,” IEEE Access, vol. 7, pp. 129480-129493, 2019. DOI
  • R. Khatami, M. Parvania, P. Khargonekar, A. Narayan, “Continuous-time Stochastic Modeling and Estimation of Electricity Load,” in Proc. IEEE Conference on Decision and Control (CDC), Miami, FL, December 17-19, 2018. DOI
  • R. Khatami, M. Parvania, P. Khargonekar, “Scheduling and Pricing of Energy Generation and Storage in Power Systems,” IEEE Transactions on Power Systems, vol. 33, no. 4, pp. 4308-4322, July 2018. 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
  • M. Parvania, R. Khatami, “Continuous-time Marginal Pricing of Electricity,” IEEE Transactions on Power Systems, vol. 32, no. 3, pp. 1960-1969, May 2017. DOI
  • M. Parvania, A. Scaglione, “Unit Commitment with Continuous-time Generation and Ramping Trajectory Models,” IEEE Transactions on Power Systems, vol. 31, no. 4, pp. 3169-3178, July 2016. DOI

Funded Research Projects

  • Stochastic Continuous-time Flexibility Scheduling and Pricing in Wholesale Electricity Markets, U.S. Department of Energy, 2017-2020.
  • A function space theory for continuous-time flexibility scheduling in electricity markets, National Science Foundation, 2015-2018.

Collaborators

Prof. Pramod Khargonekar (University of California Irvine), Prof. Anna Scaglione (Arizona State University), Prof. Akil Narayan (University of Utah)