Scheduling Delays and Curtailment for Household Appliances with Deterministic Load Profiles using MPC

TL;DR

This paper introduces a self-triggered model predictive control scheme for scheduling household appliances with deterministic load profiles, effectively managing delays and curtailment to optimize power demand within thresholds.

Contribution

It presents a novel continuous optimization approach with an inhomogeneous time grid for scheduling deterministic load profiles, improving upon existing methods.

Findings

Outperforms mixed-integer MPC in numerical tests

Successfully manages appliance scheduling with delay and curtailment

Demonstrates effectiveness in a case study with multiple appliances

Abstract

Smart home appliances can time-shift and curtail their power demand to assist demand side management or allow operation with limited power, as in an off-grid application. This paper proposes a scheduling process to start appliances with time-varying deterministic load profiles. Self-triggered model predictive control is used to limit the household net power demand below a given threshold. Meanwhile, deterministic load profiles are more difficult to schedule compared to variable charging or thermal loads because system failure will occur once power demand is not satisfied. The proposed scheme formulates the decision of the load shifting time as a continuous optimization problem, and an inhomogeneous time grid system is introduced to handle the optimization of different appliances and their consensus at this resolution. The efficacy of the proposed scheme is studied by numerical comparison with a mixed-integer MPC controller and by a case study of three home appliances and an interruptible washing machine.