Multiperiod Stochastic Peak Shaving Using Storage

Publikationstyp
Preprint
Date Issued
2020-07-06
Author(s)
Flamm, Benjamin  
Ramos, Guillermo
Eichler, Annika  
Lygeros, John  
TORE-URI
https://hdl.handle.net/11420/45107
Citation
arXiv: 2007.02928 (2020)
Publisher DOI
10.48550/arXiv.2007.02928
ArXiv ID
2007.02928v1
We present an online stochastic model predictive control framework for demand charge management for a grid-connected consumer with attached electrical energy storage. The consumer we consider must satisfy an inflexible but stochastic electricity demand, and also receives a stochastic electricity inflow. The optimization problem formulated solves a stochastic cost minimization problem, with given weather forecast scenarios converted into forecast demand and inflow. We introduce a novel weighting scheme to account for cases where the optimization horizon spans multiple demand charge periods. The optimization scheme is tested in a setting with building demand and photovoltaic array inflow data from a real office building. The simulation study allows us to compare various design and modeling alternatives, ultimately proposing a policy based on causal affine decision rules.
Subjects
eess.SY
cs.SY