ABSTRACT
Renewable energy harvested from the environment is an attractive option for providing green energy to homes. Unfortunately, the intermittent nature of renewable energy results in a mismatch between when these sources generate energy and when homes demand it. This mismatch reduces the efficiency of using harvested energy by either i) requiring batteries to store surplus energy, which typically incurs ~20% energy conversion losses; or ii) using net metering to transmit surplus energy via the electric grid's AC lines, which severely limits the maximum percentage of possible renewable penetration. In this paper, we propose an alternative structure wherein nearby homes explicitly share energy with each other to balance local energy harvesting and demand in microgrids. We develop a novel energy sharing approach to determine which homes should share energy, and when, to minimize system-wide efficiency losses. We evaluate our approach in simulation using real traces of solar energy harvesting and home consumption data from a deployment in Amherst, MA. We show that our system i) reduces the energy loss on the AC line by 60% without requiring large batteries, ii) scales up performance with larger battery capacities, and iii) is robust to changes in microgrid topology.
- Electric Vehicle Battery. http://en.wikipedia.org/wiki/Electric_vehicle_battery#cite_note-18k-23.Google Scholar
- Freeing the Grid: Best and Worst Practices in State Net Metering Policies and Interconnection Procedures. http://www.newenergychoices.org/uploads/FreeingTheGrid2009.pdf, 2009.Google Scholar
- State of California Executive Order S-21-09. http://gov.ca.gov/executive-order/13269, 2009.Google Scholar
- Database of State Incentives for Renewables and Efficiency. http://www.dsireusa.org, 2010.Google Scholar
- SERC: State Environmental Resource Center. http://www.serconline.org/netmetering/stateactivity.html, 2011.Google Scholar
- A. Chakrabortty. Wide-Area Control of Large Power Systems Using Dynamic Clustering and TCSC-Based Redesigns. In IEEE Transctions on Smart Grid, Vol. 3, No. 3, pages 1503--1514, 2012.Google ScholarCross Ref
- A. Chakrabortty and A. Salazar. Building a dynamic electro-mechanical model for the Pacific AC intertie using distributed synchrophasor measurements. In European Transactions on Electric Power: Special Issue on PMU Applications, Vol. 21, No. 4, pages 1657--1672, 2011.Google Scholar
- A. Chakrabortty, J. H. Chow and A. Salazar. A Measurement-based Framework for Dynamic Equivalencing of Power Systems using Wide-Area Phasor Measurements. In IEEE Transactions on Smart Grid, Vol. 1, No. 2, pages 68--81, 2011.Google ScholarCross Ref
- A. Thatte, and L. Xie. Towards a Unified Operational Value Index of Energy Storage in Smart Grid Environment. In IEEE Transactions on Smart Grid, Vol. 3, No. 3, pages 1418--1426, 2012.Google ScholarCross Ref
- M. Behl, M. Aneja, H. Jain, and R. Mangharam. Enroute: An energy router for energy-efficient buildings. In IPSN, 2011.Google Scholar
- F. J. Jin and K. G. Shin. Pack sizing and reconfiguration for management of large-scale batteries. In Proceedings of International Conference on Cyber-Physical Systems, 2012. Google ScholarDigital Library
- X. Jiang, M. Van Ly, J. Taneja, P. Dutta, and D. Culler. Experiences with a high-fidelity wireless building energy auditing network. In SenSys, pages 113--126, 2009. Google ScholarDigital Library
- A. Kansal, J. Hsu, S. Zahedi, and M. B. Srivastava. Power management in energy harvesting sensor networks. ACM Transction on Embedded Computer Systems, 6(4):1539--9087, 2007. Google ScholarDigital Library
- L. Xie, Y. Gu, A. Eskandari, and M. Ehsani. Fast MPC-based Coordination of Wind Power and Battery Energy Storage Systems. In Journal of Energy Engineering, Vol. 138, No. 2, pages 43--53, 2012.Google Scholar
- D. Larruskain, I. Zamora, A. MazÃşn, O. Abarrategui, and J. Monasterio. Transmission and distribution networks: Ac versus dc. 9th Spanish-Portuguese Congress on Electrical Engineering, 2005.Google Scholar
- M. D. Ilic, L. Xie and J. Joo. Efficient coordination of wind power and price-responsive demand Part I: theoretical foundations. In IEEE Transactions on Power Systems Vol. 26, No. 4, pages 1875--1884, 2011.Google ScholarCross Ref
- M. D. Ilic, L. Xie and J. Joo. Efficient coordination of wind power and price-responsive demand Part II: case studies. In IEEE Transactions on Power Systems Vol. 26, No. 4, pages 1885--1893, 2011.Google ScholarCross Ref
- A. Mishra, D. Irwin, P. Shenoy, J. Kurose, and T. Zhu. Smartcharge: Cutting the electricity bill in smart homes with energy storage. e-Energy, 2012. Google ScholarDigital Library
- T. Nghiem, M. Behl, G. Pappas, and R. Mangharam. Green scheduling: Scheduling of control systems for peak power reduction. In International Green Computing Conference and Workshops (IGCC), 2011. Google ScholarDigital Library
- L. Rao, X. Liu, M. Ilic, and J. Liu. Distributed coordination of internet data centers under multiregional electricity markets. Proceedings of the IEEE, 100(1):269--282, 2012.Google ScholarCross Ref
- L. Rao, X. Liu, L. Xie, and W. Liu. Minimizing electricity cost: Optimization of distributed internet data centers in a multi-electricity-market environment. In INFOCOM, 2010. Google ScholarDigital Library
- L. Rao, X. Liu, L. Xie, and W. Liu. Coordinated energy cost management of distributed internet data centers in smart grid. IEEE Transactions on Smart Grid, 3(1):50--58, 2012.Google ScholarCross Ref
- S. M. Schoenung. Energy storage systems cost update {a study for the doe energy storage systems program}. Tech. Rep. SAND2011--2730, Sandia National Laboratories, 2011.Google ScholarCross Ref
- N. Sharma, J. Gummeson, D. Irwin, and P. Shenoy. Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems. In SECON, 2010.Google ScholarCross Ref
- T. Zhu, A. Mishra, D. Irwin, N. Sharma, P. Shenoy, and D. Towsley. The Case for Efficient Renewable Energy Management for Smart Homes. In ACM BuildSys, 2011. Google ScholarDigital Library
- T. Zhu, A. Mohaisen, Y. Ping, and D. Towsley. DEOS: Dynamic Energy-Oriented Scheduling for Sustainable Wireless Sensor Networks. In INFOCOM, 2012.Google ScholarCross Ref
- T. Zhu, S. Xiao, P. Yi, D. Towsley, and W. Gong. A Secure Energy Routing Protocol for Sharing Renewable Energy in Smart Microgrid. In IEEE SmartGridComm, 2011.Google Scholar
- T. Zhu, Y. Gu, T. He and Z.-L. Zhang. Eshare: A Capacitor-driven Energy Storage and Sharing Network for Long-term Operation. In SenSys, 2010. Google ScholarDigital Library
- T. Zhu, Z. Zhong, T. He, and Z.-L. Zhang. Energy-Synchronized Computing for Sustainable Sensor Networks. In Elsevier Ad Hoc Networks Journal, 2010. Google ScholarDigital Library
- T. Zhu, Z. Zhong, T. He and Z.-L. Zhang. Exploring link correlation for efficient flooding in wireless sensor networks. In Proceedings of the 7th USENIX conference on Networked Systems Design and Implementation (NSDI), 2010. Google ScholarDigital Library
- T. Zhu, Z. Zhong, Y. Gu, T. He and Z.-L. Zhang. Leakage-aware Energy Synchronization for Wireless Sensor Networks. In MobiSys, 2009. Google ScholarDigital Library
- T. Zhu, Z. Zhong, Y. Gu, T. He, and Z.-L. Zhang. Feedback Control-based Energy Management for Ubiquitous Sensor Networks. In IEICE Transactions on Communications, Vol. E93-B, No.11, pages 2846--2854, Nov. 2010.Google Scholar
- J. Yao, X. Liu, W. He, and A. Rahman. Dynamic control of electricity cost with power demand smoothing and peak shaving for distributed internet data centers. In ICDCS, 2012. Google ScholarDigital Library
Index Terms
- Sharing renewable energy in smart microgrids
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