Automating energy management in green homes

Abstract

Homes powered fully or partially by renewable sources such as solar are becoming more widely adopted, however energy management strategies in these environments are lacking. This paper presents the first results of a study that explores home automation techniques for achieving better utilization of energy generated by renewable technologies. First, using a network of off-the-shelf sensing devices, we observe that energy generation and consumption in an off-grid home is both variable and predictable. Moreover, we find that reactive energy management techniques are insufficient to prevent critical battery situations. We then present a recommendation based system for helping users to achieve better utilization of resources. Our study demonstrates the feasibility of three recommendation components: an early warning system that allows users of renewable technologies to make more conservative decisions when energy harvested is predicted to be low; a task rescheduling system that advises users when high-power appliances such as clothes dryers should be run to optimize overall energy utilization; and an energy conservation system that identifies sources of energy waste and recommends more conservative usage.

Residential energy simulation and scheduling: A case study approach

“…We implement and execute experiments that were proposed without validation in related work: rescheduling appliances for better energy efficiency [3] and replacing centralized batteries with distributed, appliance-specific batteries. By integrating cost models to the scheduler, we are also able to demonstrate the costbenefit of local green energy generation and storage.…”

“…An example is NEST thermostat [16], which learns temperature patterns in the home and automatically sets appropriate temperatures. We envision similarly adaptable appliances, a concept presented in [3]. Periodic appliances such as dishwashers or washing machines are typically open to rescheduling, as their timing is flexible by nature.…”

“…In this case study, we use the washer, dryer and dishwasher as our smart appliances, from precedent set in [3]. The scheduling parameters are provided in Table 2.…”

“…Home energy simulators have been developed as part of other research endeavors [3] [1] [2], but they are either specific to the residence or scenario being investigated, or particular to one aspect of energy consumption. For example, the Department of Energy's NZERTF project [4] has established a user-model centric energy simulation, but the results are determined by actually emulating the user models on a real house, prohibiting widespread use.…”

“…However, the work does not strive to automate the process, choosing instead to leave power management decisions in the hands of users. [3] presents automated energy efficiency improvement in homes that are partially powered by green energy with storage. The work proposes an energy management system that provides early warnings, and suggests task rescheduling for maximizing energy.…”