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Scheduling distributed energy resource operation and daily power consumption for a smart building to optimize economic and environmental parameters

Pooranian, Zahra, Abawajy, Jemal H, Vinod, P and Conti, Mauro 2018, Scheduling distributed energy resource operation and daily power consumption for a smart building to optimize economic and environmental parameters, Energies, vol. 11, no. 6, pp. 1-17, doi: 10.3390/en11061348.

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Title Scheduling distributed energy resource operation and daily power consumption for a smart building to optimize economic and environmental parameters
Author(s) Pooranian, Zahra
Abawajy, Jemal HORCID iD for Abawajy, Jemal H orcid.org/0000-0001-8962-1222
Vinod, P
Conti, Mauro
Journal name Energies
Volume number 11
Issue number 6
Article ID 1348
Start page 1
End page 17
Total pages 17
Publisher MDPI
Place of publication Basel, Switzerland
Publication date 2018-05-25
ISSN 1996-1073
Keyword(s) microgrid
energy management
smart building
energy storage system (ESS)
mixed integer linear programming (MILP)
photovoltaic (PV)
Summary In this paper, we address the problem of minimizing the total daily energy cost in a smart residential building composed of multiple smart homes with the aim of reducing the cost of energy bills and the greenhouse gas emissions under different system constraints and user preferences. As the household appliances contribute significantly to the energy consumption of the smart houses, it is possible to decrease electricity cost in buildings by scheduling the operation of domestic appliances. In this paper, we propose an optimization model for jointly minimizing electricity costs and CO2emissions by considering consumer preferences in smart buildings that are equipped with distributed energy resources (DERs). Both controllable and uncontrollable tasks and DER operations are scheduled according to the real-time price of electricity and a peak demand charge to reduce the peak demand on the grid. We formulate the daily energy consumption scheduling problem in multiple smart homes from economic and environmental perspectives and exploit a mixed integer linear programming technique to solve it. We validated the proposed approach through extensive experimental analysis. The results of the experiment show that the proposed approach can decrease both CO2emissions and the daily energy cost.
Language eng
DOI 10.3390/en11061348
Field of Research 09 Engineering
02 Physical Sciences
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2018, the authors
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30113315

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.