EnerPlan: Smart energy management planning for home users

Abstract

The impending energy crisis has driven up the cost of electricity at an exponential rate. Managing electric consumption thus has become a very crucial task especially for home consumers. In this paper we present EnerPlan, a non-intrusive method to aid consumers to reduce their energy cost by advising them a consumption plan for their devices. Our system builds consumer classes based on regional statistical data. Using these classes a target consumer's device load and distribution is inferred. This inferred data is used to construct a device usage plan. Following this plan can reduce the electric bill of the consumer. We use expert-based and auto-generated fuzzy rules to generate the planning. Results show that in absence of experts, planning through auto-generated is also useful. The results further demonstrate that the data prepared using the proposed approach can be used to save electricity and the plans generated by EnerPlan can reduce electricity bills of consumers. © 2012 Springer-Verlag.