2 papers accepted to ECC 20

Our papers on minimum-time charging of energy storage via approximate conic relaxation [1] and on generation cost reduction [2] have been accepted to European Control Conference 2020!

[1] J. Guthrie and E. Mallada, “Minimum-Time Charging of Energy Storage in Microgrids via Approximate Conic Relaxation,” in 19th IEEE European Control Conference (ECC), 2020.
[Bibtex] [Abstract] [Download PDF]

We study the problem of maximizing energy transfer to a load in a DC microgrid while respecting constraints on bus voltages and currents, and accounting for the impact of neighboring constant power loads. Both the objective and dynamics give rise to indefinite quadratic terms, resulting in a non-convex optimization problem. Through change of variables and relaxations we develop a closely related second-order cone program. The problem retains the same feasible set as the original problem but utilizes a linear approximation of the non-convex objective. We demonstrate how this can be used to design approximately optimal charging profiles for periodic pulsed loads in real time.

@inproceedings{gm2020ecc,
  abstract = {We study the problem of maximizing energy transfer to a load in a DC microgrid while respecting constraints on bus voltages and currents, and accounting for the impact of neighboring constant power loads.  Both the objective and dynamics give rise to indefinite quadratic terms, resulting in a non-convex optimization problem. Through change of variables and relaxations we develop a closely related second-order cone program. The problem retains the same feasible set as the original problem but utilizes a linear approximation of the non-convex objective. We demonstrate how this can be used to design approximately optimal charging profiles for periodic pulsed loads in real time.},
  author = {Guthrie, James and Mallada, Enrique},
  booktitle = {19th IEEE European Control Conference (ECC)},
  grants = {CAREER-1752362, CPS-1544771, ENERGISE-DE-EE0008006, AMPS-1736448, TRIPODS-1934979, EPCN-1711188, ARO-W911NF-17-1-0092},
  keywords = {Power Networks},
  month = {5},
  pubstate = {accepted, submitted Oct. 2019},
  title = {Minimum-Time Charging of Energy Storage in Microgrids via Approximate Conic Relaxation},
  url = {https://mallada.ece.jhu.edu/pubs/2019-Preprint-GM-b.pdf},
  year = {2020}
}
[2] Y. Shen, M. Bichuch, and E. Mallada, “On the Value of Energy Storage in Generation Cost Reduction,” in 19th IEEE European Control Conference (ECC), 2020.
[Bibtex] [Abstract] [Download PDF]

This work seeks to quantify the benefits of using energy storage toward the reduction of the energy generation cost of a power system. A two-fold optimization framework is provided where the first optimization problem seeks to find the optimal storage schedule that minimizes operational costs. Since the operational cost depends on the storage capacity, a second optimization problem is then formulated with the aim of finding the optimal storage capacity to be deployed. Although, in general, these problems are difficult to solve, we provide a lower bound on the cost savings for a parametrized family of demand profiles. The optimization framework is numerically illustrated using real-world demand data from ISO New England. Numerical results show that energy storage can reduce energy generation costs by at least 2.5 percent.

@inproceedings{sbm2020ecc,
  abstract = {This work seeks to quantify the benefits of using energy storage toward the reduction of the energy generation cost of a power system.  A two-fold optimization framework is provided where the first optimization problem seeks to find the optimal storage schedule that minimizes operational costs. Since the operational cost depends on the storage capacity, a second optimization problem is then formulated with the aim of finding the optimal storage capacity to be deployed. Although, in general, these problems are difficult to solve, we provide a lower bound on the cost savings for a  parametrized family of demand profiles.
The optimization framework is numerically illustrated using real-world demand data from ISO New England. Numerical results show that energy storage can reduce energy generation costs by at least 2.5 percent.},
  author = {Shen, Yue and Bichuch, Maxim and Mallada, Enrique},
  booktitle = {19th IEEE European Control Conference (ECC)},
  grants = {CAREER-1752362, CPS-1544771, ENERGISE-DE-EE0008006, AMPS-1736448, TRIPODS-1934979, EPCN-1711188, ARO-W911NF-17-1-0092},
  keywords = {Power Networks},
  month = {5},
  pubstate = {accepted, submitted Oct. 2019},
  title = {On the Value of Energy Storage in Generation Cost Reduction},
  url = {https://mallada.ece.jhu.edu/pubs/2019-Preprint-SBM.pdf},
  year = {2020}
}