Scheduling Distributed Energy Resource Operation and Daily Power Consumption for a Smart Building to Optimize Economic and Environmental Parameters
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 househol...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-05-01
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| Series: | Energies |
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| Online Access: | http://www.mdpi.com/1996-1073/11/6/1348 |
| _version_ | 1818007980950421504 |
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| author | Zahra Pooranian Jemal H. Abawajy Vinod P Mauro Conti |
| author_facet | Zahra Pooranian Jemal H. Abawajy Vinod P Mauro Conti |
| author_sort | Zahra Pooranian |
| collection | DOAJ |
| description | 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 CO2 emissions 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 CO2 emissions and the daily energy cost. |
| first_indexed | 2024-04-14T05:22:53Z |
| format | Article |
| id | doaj.art-cfdaad12987b4a1493f8e7236f4c471a |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-14T05:22:53Z |
| publishDate | 2018-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-cfdaad12987b4a1493f8e7236f4c471a2022-12-22T02:10:06ZengMDPI AGEnergies1996-10732018-05-01116134810.3390/en11061348en11061348Scheduling Distributed Energy Resource Operation and Daily Power Consumption for a Smart Building to Optimize Economic and Environmental ParametersZahra Pooranian0Jemal H. Abawajy1Vinod P2Mauro Conti3Department of Mathematics, University of Padua, Padua 35131, ItalySchool of Information Technology, Deakin University, Geelong, VIC 3125, AustraliaDepartment of Mathematics, University of Padua, Padua 35131, ItalyDepartment of Mathematics, University of Padua, Padua 35131, ItalyIn 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 CO2 emissions 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 CO2 emissions and the daily energy cost.http://www.mdpi.com/1996-1073/11/6/1348MicrogridEnergy ManagementSmart BuildingEnergy Storage System (ESS)Mixed Integer Linear Programming (MILP)Photovoltaic (PV). |
| spellingShingle | Zahra Pooranian Jemal H. Abawajy Vinod P Mauro Conti Scheduling Distributed Energy Resource Operation and Daily Power Consumption for a Smart Building to Optimize Economic and Environmental Parameters Energies Microgrid Energy Management Smart Building Energy Storage System (ESS) Mixed Integer Linear Programming (MILP) Photovoltaic (PV). |
| title | Scheduling Distributed Energy Resource Operation and Daily Power Consumption for a Smart Building to Optimize Economic and Environmental Parameters |
| title_full | Scheduling Distributed Energy Resource Operation and Daily Power Consumption for a Smart Building to Optimize Economic and Environmental Parameters |
| title_fullStr | Scheduling Distributed Energy Resource Operation and Daily Power Consumption for a Smart Building to Optimize Economic and Environmental Parameters |
| title_full_unstemmed | Scheduling Distributed Energy Resource Operation and Daily Power Consumption for a Smart Building to Optimize Economic and Environmental Parameters |
| title_short | Scheduling Distributed Energy Resource Operation and Daily Power Consumption for a Smart Building to Optimize Economic and Environmental Parameters |
| title_sort | scheduling distributed energy resource operation and daily power consumption for a smart building to optimize economic and environmental parameters |
| topic | Microgrid Energy Management Smart Building Energy Storage System (ESS) Mixed Integer Linear Programming (MILP) Photovoltaic (PV). |
| url | http://www.mdpi.com/1996-1073/11/6/1348 |
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