Energy Demand Management in a Residential Building Using Multi-objective Optimization Algorithms

Abstract

Demand Side Management (DSM) is one of the most important functions of a smart building that allows customers to make informed decisions about their energy consumption and remodulate their load profile in order to reduce overall operational cost and carbon emission levels. This paper presents a demand side management strategy based on shifting load from peak hours where electricity prices are high to off-peak hours where electricity prices are low. This helps the scheduler to optimally decide the ON/OFF status of appliances to reduce the electricity bill and the peaks related to high energy consumption (PAR), while maintaining the user’s comfort. The optimization problem proposed in this paper is formulated mathematically as a multi-objective optimization problem that involves constraints and consumer preferences. A bio-inspired meta-heuristic algorithm “Black widow optimization” based on the Pareto front has been developed to solve this optimization problem and manage the trade-off between conflicting objectives. Simulations were performed based on a smart home equipped with multiple appliances and a time-of-use (TOU) pricing scheme that encourages customers to use energy during off-peak hours. The algorithms were implemented on Matlab R2021a, and the results validate the performance of proposed techniques in terms of electricity cost reduction, peak to average ratio and waiting time minimization.