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Open AccessArticle

Cost Efficient Real Time Electricity Management Services for Green Community Using Fog

1
Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan
2
Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, Gyeongbuk 38541, Korea
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Authors to whom correspondence should be addressed.
This paper is an extended version of our paper published in Green Fog: Cost Efficient Real Time Power Management Service for Green Community. In Proceedings of the 14th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS-2020), Lodz, Poland, 1–3 July 2020.
Energies 2020, 13(12), 3164; https://doi.org/10.3390/en13123164
Received: 12 May 2020 / Revised: 1 June 2020 / Accepted: 14 June 2020 / Published: 18 June 2020
(This article belongs to the Special Issue Data-Intensive Computing in Smart Microgrids)
The computing devices in data centers of cloud and fog remain in continues running cycle to provide services. The long execution state of large number of computing devices consumes a significant amount of power, which emits an equivalent amount of heat in the environment. The performance of the devices is compromised in heating environment. The high powered cooling systems are installed to cool the data centers. Accordingly, data centers demand high electricity for computing devices and cooling systems. Moreover, in Smart Grid (SG) managing energy consumption to reduce the electricity cost for consumers and minimum rely on fossil fuel based power supply (utility) is an interesting domain for researchers. The SG applications are time-sensitive. In this paper, fog based model is proposed for a community to ensure real-time energy management service provision. Three scenarios are implemented to analyze cost efficient energy management for power-users. In first scenario, community’s and fog’s power demand is fulfilled from the utility. In second scenario, community’s Renewable Energy Resources (RES) based Microgrid (MG) is integrated with the utility to meet the demand. In third scenario, the demand is fulfilled by integrating fog’s MG, community’s MG and the utility. In the scenarios, the energy demand of fog is evaluated with proposed mechanism. The required amount of energy to run computing devices against number of requests and amount of power require cooling down the devices are calculated to find energy demand by fog’s data center. The simulations of case studies show that the energy cost to meet the demand of the community and fog’s data center in third scenario is 15.09% and 1.2% more efficient as compared to first and second scenarios, respectively. In this paper, an energy contract is also proposed that ensures the participation of all power generating stakeholders. The results advocate the cost efficiency of proposed contract as compared to third scenario. The integration of RES reduce the energy cost and reduce emission of CO 2 . The simulations for energy management and plots of results are performed in Matlab. The simulation for fog’s resource management, measuring processing, and response time are performed in CloudAnalyst. View Full-Text
Keywords: fog computing; green community; resource allocation; processing time; response time; green data center; microgrid; renewable energy; energy trade contract; real time power management fog computing; green community; resource allocation; processing time; response time; green data center; microgrid; renewable energy; energy trade contract; real time power management
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MDPI and ACS Style

Bukhsh, R.; Javed, M.U.; Fatima, A.; Javaid, N.; Shafiq, M.; Choi, J.-G. Cost Efficient Real Time Electricity Management Services for Green Community Using Fog. Energies 2020, 13, 3164. https://doi.org/10.3390/en13123164

AMA Style

Bukhsh R, Javed MU, Fatima A, Javaid N, Shafiq M, Choi J-G. Cost Efficient Real Time Electricity Management Services for Green Community Using Fog. Energies. 2020; 13(12):3164. https://doi.org/10.3390/en13123164

Chicago/Turabian Style

Bukhsh, Rasool; Javed, Muhammad U.; Fatima, Aisha; Javaid, Nadeem; Shafiq, Muhammad; Choi, Jin-Ghoo. 2020. "Cost Efficient Real Time Electricity Management Services for Green Community Using Fog" Energies 13, no. 12: 3164. https://doi.org/10.3390/en13123164

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