Start Date

2-10-2013 2:10 PM

End Date

2-10-2013 2:35 PM

Description

Abstract: A smart grid provides dynamic pricing signals which make users be possible to adjust their power demands accordingly. Renewable energy technologies equip a large number of residential homes the capability of local power generation. The varying price of power supply from a smart grid and the existence of local power generation bring opportunities and challenges for energy management at residential homes. This paper proposes a cost-driven residential energy management approach for the adaption of smart grid and local power generation. The target system makes cost-driven scheduling of household appliances by considering the real-time and/or predictable status of smart grid, local power generation, and power consumption demands. The proposed approach minimizes the overall daily electricity cost of household appliances by taking into account both weather and electricity tariff forecasts, predictable home activities, and the flexibility of electricity use.

Citation:

Zhao, W., Cooper, P., Perez, P. & Ding, L. (2014). Cost-Driven Residential Energy Management for Adaption of Smart Grid and Local Power Generation. In: Campbell P. and Perez P. (Eds), Proceedings of the International Symposium of Next Generation Infrastructure, 1-4 October 2013, SMART Infrastructure Facility, University of Wollongong, Australia.

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Oct 2nd, 2:10 PM Oct 2nd, 2:35 PM

Cost-Driven Residential Energy Management for Adaption of Smart Grid and Local Power Generation

Abstract: A smart grid provides dynamic pricing signals which make users be possible to adjust their power demands accordingly. Renewable energy technologies equip a large number of residential homes the capability of local power generation. The varying price of power supply from a smart grid and the existence of local power generation bring opportunities and challenges for energy management at residential homes. This paper proposes a cost-driven residential energy management approach for the adaption of smart grid and local power generation. The target system makes cost-driven scheduling of household appliances by considering the real-time and/or predictable status of smart grid, local power generation, and power consumption demands. The proposed approach minimizes the overall daily electricity cost of household appliances by taking into account both weather and electricity tariff forecasts, predictable home activities, and the flexibility of electricity use.

Citation:

Zhao, W., Cooper, P., Perez, P. & Ding, L. (2014). Cost-Driven Residential Energy Management for Adaption of Smart Grid and Local Power Generation. In: Campbell P. and Perez P. (Eds), Proceedings of the International Symposium of Next Generation Infrastructure, 1-4 October 2013, SMART Infrastructure Facility, University of Wollongong, Australia.