Energy usage optimization in Smart Homes is a critical problem: over 30% of the energy consumption of the world resides in the residential sector. Usage awareness and manual appliance control alone are able to reduce consumption by 15%. This result could be improved if appliance control is automatic, especially if renewable sources are present locally. In this paper, a Smart Home Energy Management system that aims at automatically controlling appliances in groups of smart homes belonging to the same neighborhood is proposed. Not only is electric power distribution considered, but also renewable energy sources such as wind micro-turbines and solar panels. The proposed strategy relies on two algorithms. The Cost Saving Task Scheduling algorithm is aimed at scheduling high-power controllable loads during off-peak hours, taking into account the expected usage of the non-controllable appliances such as fridge, oven, etc. This algorithm is run whenever a new need of energy from a controllable load is detected. The Renewable Source Power Allocation algorithm re-allocated the starting time of controllable loads whenever surplus of renewable source power is detected making use of a distributed max-consensus negotiation. Performance evaluation of the algorithms tested proves that the proposed approach provides an energy cost saving that goes between 35% and 65% with reference to the case where no automatic control is used.

A novel Smart Home Energy Management system: Cooperative neighbourhood and adaptive renewable energy usage

PILLONI, VIRGINIA;ATZORI, LUIGI
2015

Abstract

Energy usage optimization in Smart Homes is a critical problem: over 30% of the energy consumption of the world resides in the residential sector. Usage awareness and manual appliance control alone are able to reduce consumption by 15%. This result could be improved if appliance control is automatic, especially if renewable sources are present locally. In this paper, a Smart Home Energy Management system that aims at automatically controlling appliances in groups of smart homes belonging to the same neighborhood is proposed. Not only is electric power distribution considered, but also renewable energy sources such as wind micro-turbines and solar panels. The proposed strategy relies on two algorithms. The Cost Saving Task Scheduling algorithm is aimed at scheduling high-power controllable loads during off-peak hours, taking into account the expected usage of the non-controllable appliances such as fridge, oven, etc. This algorithm is run whenever a new need of energy from a controllable load is detected. The Renewable Source Power Allocation algorithm re-allocated the starting time of controllable loads whenever surplus of renewable source power is detected making use of a distributed max-consensus negotiation. Performance evaluation of the algorithms tested proves that the proposed approach provides an energy cost saving that goes between 35% and 65% with reference to the case where no automatic control is used.
978-1-4673-6432-4
978-1-4673-6432-4
Renewable sources; Smart Home; Energy Management Systems
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11584/134129
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