Online Algorithm for Demand Response with Inelastic Demands and Apparent Power Constraint

TL;DR

This paper introduces a competitive online algorithm for allocating inelastic power demands under non-linear apparent power constraints, addressing a key challenge in power system management with real-time decision-making.

Contribution

It presents the first competitive randomized online algorithms for demand response with quadratic apparent power constraints and extends to voltage constraints, supported by empirical evaluations.

Findings

Algorithm achieves competitive performance in simulations

Handles non-linear apparent power constraints effectively

Extends to voltage constraint scenarios

Abstract

A classical problem in power systems is to allocate in-coming (elastic or inelastic) demands without violating the operating constraints of electric networks in an online fashion. Although online decision problems have been well-studied in the literature, a unique challenge arising in power systems is the presence of non-linear constraints, a departure from the traditional settings. A particular example is the capacity constraint of apparent power, which gives rise to a quadratic constraint, rather than typical linear constraints. In this paper, we present a competitive randomized online algorithm for deciding whether a sequence of inelastic demands can be allocated for the requested intervals, subject to the total satisfiable apparent power within a time-varying capacity constraint. We also consider an alternative setting with nodal voltage constraint, using a variant of the online algorithm. Finally, simulation studies are provided to evaluate the algorithms empirically.