Abstract
We consider a general class of dynamic programming (DP) problems with nonseparable objective functions. We show that for any problem in this class, there exists an augmented-state DP problem that satisfies the principle of optimality and the solutions to which yield solutions to the original problem. Furthermore, we identify a subclass of DP problems with naturally forward separable objective functions for which this state-augmentation scheme is tractable. We extend this framework to stochastic DP problems, proposing a suitable definition of the principle of optimality. We then apply the resulting algorithms to the problem of optimal battery scheduling with demand charges using a data-based stochastic model for electricity usage and solar generation by the consumer.
Original language | English (US) |
---|---|
Article number | 9116976 |
Pages (from-to) | 1602-1617 |
Number of pages | 16 |
Journal | IEEE Transactions on Automatic Control |
Volume | 66 |
Issue number | 4 |
DOIs | |
State | Published - Apr 2021 |
Keywords
- Battery management systems
- Dynamic programming
- Optimal scheduling
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering