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- Title
Stochastic modeling and scalable predictive control for automated demand response.
- Authors
Kobayashi, Koichi; Hiraishi, Kunihiko
- Abstract
Automated demand response (ADR) is a utility program that is designed to achieve electricity conservation. An ADR program is regarded as the problem of controlling the power consumption of a set of consumers. In this article, we propose a control‐theoretic approach for an ADR program. First, a mathematical model of the power consumption is proposed. This model can express complex behavior by switching a Markov chain. Its effectiveness is illustrated by modeling the power consumption of an air‐conditioner. Next, a new method of model predictive control for a set of consumers is developed using the proposed model. The control strategy at each time is chosen from a given finite set by solving a mixed integer linear programming (MILP) problem. The advantage of the proposed method is that the MILP problem is scalable with respect to the number of consumers. To show its effectiveness, we present a numerical example.
- Subjects
MIXED integer linear programming; STOCHASTIC models; PREDICTION models; ELECTRIC power conservation; MARKOV processes; PREDICTIVE control systems
- Publication
International Journal of Robust & Nonlinear Control, 2021, Vol 31, Issue 6, p2001
- ISSN
1049-8923
- Publication type
Article
- DOI
10.1002/rnc.5313