research-article

Collaborative energy conservation in a microgrid

Authors:

Harshad Khadilkar,

Zainul Charbiwala,

Kushan U. Tennakoon,

Rodzay bin Haji Abdul Wahab,

Liyanage Chandratilak De Silva,

Deva P. SeetharamAuthors Info & Claims

BuildSys '14: Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings

Pages 130 - 139

https://doi.org/10.1145/2674061.2674079

Published: 03 November 2014 Publication History

Abstract

KBFSC (Kuala Belalong Field Studies Centre) is a research centre located in a remote tropical evergreen rainforest in Brunei Darussalam in South East Asia. It is visited by biologists and ecologists from all over the world. Power is available at the centre for 8-10 hours per day from a diesel generator (DG). The diesel travels2-3 hours by road, by boat and on foot over harsh terrain to reach the centre from the closest gas station. This paper describes the software and hardware of a microgrid system that was designed and deployed at KBFSC to reduce the fuel consumption while improving duration of power availability. A key feature of the energy management software is a collaborative scheduler interface that provides visitors at the centre the choice of scheduling appliance usage. The system optimises generator active hours using a customised DG Optimiser technique, to ensure minimum diesel consumption. Simulations extrapolating from empirical data suggest that our system could reduce diesel consumption by a third, and total cost by 20%, while making power available 24 hours a day. In addition, a user study with 8 visitors and 4 administrators showed that the collaborative scheduler interface is effective and usable.

References

[1]

Cummins Power DG datasheets. http://www.cumminspower.com/.

[2]

HOMER - hybrid optimization of multiple energy resources. http://www.homerenergy.com/.

[3]

Solarising India: Commercial feasibility analysis and an implementation roadmap. http://www.ima-india.com/solarising-rural-india.pdf, 2006.

[4]

The Rising Sun: Grid Parity Gets Closer. KPMG, 2012.

[5]

Bertsekas, D. Dynamic Programming and Optimal Control, 2nd ed. Athena Scientific, 2000.

Digital Library

[6]

Bindner, H., Cronin, T., Lundsager, P., Manwell, J. F., Abdulwahid, U., and Baring-Gould, I. Lifetime modelling of lead acid batteries. 2005.

[7]

Erickson, T., Li, M., Kim, Y., Deshpande, A., Sahu, S., Chao, T., Sukaviriya, P., and Naphade, M. The Dubuque Electricity Portal: Evaluation of a city-scale residential electricity consumption feedback system. In SIGCHI Conference on Human Factors in Computing Systems (Paris, France, 2013).

Digital Library

[8]

Faudzulani, A., Tennakoon, K., and Malai, A. Life Underneath the Canopy: The Kuala Belalong Field Studies Centre Showcase. Universiti Brunei Darussalam, 2011.

[9]

Froehlich, J., Findlater, L., and Landay, J. The design of eco-feedback technology. In SIGCHI Conference on Human Factors in Computing Systems (Atlanta, GA, 2010).

Digital Library

[10]

Galvin, R., Yeager, K., and Stuller, J. Perfect Power. McGraw Hill, 2009.

[11]

Hafez, O., and Bhattacharya, K. Optimal planning and design of a renewable energy based supply system for microgrids. Renewable Energy 45 (2012), 7--15.

[12]

Hong, Y., and Li, C. Short-term real-power scheduling considering fuzzy factors in an autonomous system using genetic algorithms. Proceedings of Generation, Transmission and Distribution 153, 6 (Nov 2006), 684--692.

[13]

Kjeldskov, J., Skov, M., Paay, J., and Pathmanathan, R. Using mobile phones to support sustainability: A field study of residential electricity consumption. In SIGCHI Conference on Human Factors in Computing Systems (Austin, TX, 2012).

Digital Library

[14]

Manwell, J., and McGowan, J. Lead acid battery storage model for hybrid energy systems. Solar Energy 50, 5 (1993), 399--405.

[15]

Morais, H., Kadar, P., Faria, P., Vale, Z., and Khodr, H. Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming. Renewable Energy 35, 1 (2010), 151--156.

[16]

Nayar, C., Tang, M., and Suponthana, W. Wind/PV/diesel micro grid system implemented in remote islands in the republic of Maldives. In International Conference on Sustainable Energy Technologies (Nov 2008), 1076--1080.

[17]

Osborne, M., and Rubinstein, A. A Course in Game Theory. MIT Press, Cambridge, MA, 1994.

[18]

Prasetiawan, E. Modeling, simulation and control of an earthmoving vehicle powertrain simulator. PhD thesis, 2001.

[19]

Ross, M., Hidalgo, R., Abbey, C., and Joos, G. Energy storage system scheduling for an isolated microgrid. Renewable Power Generation 5, 2 (Mar 2011), 117--123.

[20]

Wharton, C., Rieman, J., Lewis, C., and Polson, P. Usability inspection methods. John Wiley & Sons, Inc., New York, NY, USA, 1994, ch. The Cognitive Walkthrough Method: A Practitioner's Guide, 105--140.

Digital Library

Cited By

Syafiq SRosli MDaud MRahman ASalleh MMohamad F(2019)Smart Energy Monitoring System for Residential in MalaysiaProceedings of the 3rd International Conference on Big Data and Internet of Things10.1145/3361758.3361766(18-22)Online publication date: 22-Aug-2019
https://dl.acm.org/doi/10.1145/3361758.3361766
Kapsalis VHadellis L(2017)Optimal operation scheduling of electric water heaters under dynamic pricingSustainable Cities and Society10.1016/j.scs.2017.02.01331(109-121)Online publication date: May-2017
https://doi.org/10.1016/j.scs.2017.02.013
Ahmad ASubhani MArshad N(2017)A Strategy to Reduce Grid Stress through Priority-based Inverter ChargingEnergy Procedia10.1016/j.egypro.2017.09.563134(555-566)Online publication date: Oct-2017
https://doi.org/10.1016/j.egypro.2017.09.563

Index Terms

Collaborative energy conservation in a microgrid
1. Computer systems organization
  1. Embedded and cyber-physical systems
  2. Real-time systems

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Published In

cover image ACM Conferences

BuildSys '14: Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings

November 2014

241 pages

ISBN:9781450331449

DOI:10.1145/2674061

General Chair:
Mani Srivastava
University of California, Los Angeles

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 03 November 2014

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SenSys '14

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SenSys '14: The 12th ACM Conference on Embedded Network Sensor Systems

November 3 - 6, 2014

Tennessee, Memphis

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Cited By

Syafiq SRosli MDaud MRahman ASalleh MMohamad F(2019)Smart Energy Monitoring System for Residential in MalaysiaProceedings of the 3rd International Conference on Big Data and Internet of Things10.1145/3361758.3361766(18-22)Online publication date: 22-Aug-2019
https://dl.acm.org/doi/10.1145/3361758.3361766
Kapsalis VHadellis L(2017)Optimal operation scheduling of electric water heaters under dynamic pricingSustainable Cities and Society10.1016/j.scs.2017.02.01331(109-121)Online publication date: May-2017
https://doi.org/10.1016/j.scs.2017.02.013
Ahmad ASubhani MArshad N(2017)A Strategy to Reduce Grid Stress through Priority-based Inverter ChargingEnergy Procedia10.1016/j.egypro.2017.09.563134(555-566)Online publication date: Oct-2017
https://doi.org/10.1016/j.egypro.2017.09.563

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