1.
Ann Oper Res
; 292(2): 753-770, 2020.
Article
in English
| MEDLINE
| ID: mdl-32863516
ABSTRACT
With the increasing presence of renewable energy sources in the electrical power grid, demand response via thermostatic appliances such as electric water heaters is a promising way to compensate for the significant variability in renewable power generation. We propose a multistage stochastic optimization model that computes the optimal day-ahead target profile of the mean thermal energy contained in a large population of heaters, given various possible wind power production and uncontrollable load scenarios. This optimal profile is calculated to make the variable net demand as even as possible.