Peak-to-Average Ratio Constrained Demand-Side Management With Consumer's Preference in Residential Smart Grid

TLDR

Demand‑side management in smart grids lets consumers shift usage to off‑peak hours, reducing the peak‑to‑average ratio, but its success depends on consumer acceptance. The paper proposes a household appliance scheduling scheme that incorporates a peak‑to‑average ratio constraint. The authors formulate an optimization problem that minimizes energy cost by selecting optimal appliance power and timing, extend it to a multi‑objective version that also reduces consumer inconvenience, and provide both centralized and distributed solution algorithms. Simulations demonstrate that the proposed schedule lowers total energy costs while respecting PAR limits and consumer preferences.

Abstract

In a smart grid network, demand-side management plays a significant role in allowing consumers, incentivized by utilities, to manage their energy consumption. This can be done through shifting consumption to off-peak hours and thus reducing the peak-to-average ratio (PAR) of the electricity system. In this paper, we begin by proposing a demand-side energy consumption scheduling scheme for household appliances that considers a PAR constraint. An initial optimization problem is formulated to minimize the energy cost of the consumers through the determination of the optimal usage power and operation time of throttleable and shiftable appliances, respectively. We realize that the acceptance of consumers of these load management schemes is crucial to its success. Hence, we then introduce a multi-objective optimization problem which not only minimizes the energy cost but also minimizes the inconvenience posed to consumers. In addition to solving the proposed optimization problems in a centralized manner, two distributed algorithms for the initial and the multi-objective optimization problems are also proposed. Simulation results show that the proposed demand-side energy consumption schedule can provide an effective approach to reducing total energy costs while simultaneously considering PAR constraints and consumers' preferences.