Efficient scheduling of household appliances

an application of the analytical hierarchical process and the knapsack problem in smart grids to reduce peak consumption

Abstract

The current scenario of growing energy demand emerges on the agenda discussions about the efficiency of the actual electrical distribution systems. Beyond, the constant increase in energy demand at peak hours requires a sustainable and low-cost solution to reduce the stress of the electrical distribution systems. To solve this problem, a methodology based on demand-side management and dynamic pricing was proposed, which consists of planning the use of the customer's household appliances using decision and optimization algorithms, in order to reduce energy consumption during business hours peak, providing relief to electrical distribution systems and savings to consumers. However, the planning in the use of an appliance to the customers is not a simple task, given the complexity in the scheduling these appliances and customer preferences. In the literature, there is a wide discussion about heuristics and multi-objective algorithms that can be used to solve this problem. However, in this work, an algorithm using the analytical hierarchical process in conjunction to the knapsack problem modeling was developed to solve this problem. This algorithm makes a schedule for the usage of the appliances. After testing, it was found that the developed algorithm was capable of planning the use of household appliances for different consumer profiles, achieving energy savings of at least 20 percent during peak hours. The results suggest that the method, when applied to a wider range of consumers, can be used to reduce stress levels on the generation system at peak times to a satisfactory level, contributing to better balancing of the daily load.