How much demand side flexibility do we need?: Analyzing where to exploit flexibility in industrial processes

Abstract

We introduce a novel approach to demand side management: Instead of using flexibility that needs to be defined by a domain expert, we identify a small subset of processes of e. g. an industrial plant that would yield the largest benefit if they were time-shiftable. To find these processes we propose, implement and evaluate a framework that takes power usage time series of industrial processes as input and recommends which processes should be made flexible to optimize for several objectives as output. The technique combines and modifies a motif discovery algorithm with a scheduling algorithm based on mixed-integer programming. We show that even with small amounts of newly introduced flexibility, significant improvements can be achieved, and that the proposed algorithms are feasible for realistically sized instances. We thoroughly evaluate our approach based on real-world power demand data from a small electronics factory.