Stochastic modeling and scalable predictive control for automated demand response

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.

Automated summary

This article presents a control-theoretic approach for an Automated Demand Response (ADR) program, with effectiveness demonstrated through modeling air conditioner power consumption, and introduces a new method of model predictive control. The scalability of the proposed method with respect to the number of consumers is emphasized.