An embedded prototype of a residential smart appliance scheduling system

Demand Response (DR) is seen as one of the key enabling factors in the emerging smart grid. DR takes many forms, including residential smart appliance scheduling. Scheduling algorithms capable of achieving near-minimum cost solutions with low computational overhead are required in order to autonomously respond to varying utility pricing signals. In this paper, the focus is upon an embedded software prototype implementation of a residential load scheduling system. It describes the implementation and testing of a heuristic algorithm for household energy management on a small embedded processor. The performance of the prototype implementation is validated against previously reported experiments and simulations. Test results indicate that the heuristic is efficient enough to be co-located on a small smart meter with limited memory and processing power without any difficulties, helping to open the way for practical consumer demand response.