Abstract
Micro-solar power system design is challenging because it must address long-term system behavior under highly variable solar energy conditions and consider a large space of design options. Several micro-solar power systems and models have been made, validating particular points in the whole design space. We provide a general architecture of micro-solar power systems---comprising key components and interconnections among the components---and formalize each component in an analytical or empirical model of its behavior. To model the variability of solar energy, we provide three solar radiation models, depending on the degree of information available: an astronomical model for ideal conditions, an obstructed astronomical model for estimating solar radiation under the presence of shadows and obstructions, and a weather-effect model for estimating solar radiation under weather variation. Our solar radiation models are validated with a concrete design, the HydroWatch node, thus achieving small deviation from the long-term measurement. They can be used in combination with other micro-solar system models to improve the utility of the load and estimate the behavior of micro-solar power systems more accurately. Thus, our solar radiation models provide more accurate estimations of solar radiation and close the loop for micro-solar power system modeling.
- BMS. 2008. Solar Radiation Research Laboratory. http://www.nrel.gov/midc/srrl_bms/.Google Scholar
- Cannon, T. W. and Hulstrom, R. L. 1988. The atmospheric optical calibration system. In Proceedings of the 20th IEEE Photovoltaic Specialists Conference.Google Scholar
- Chen, B., Jamieson, K., Balakrishnan, H., and Morris, R. 2001. Span: An energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks. In Proceedings of the 7th Annual International Conference on Mobile Computing and Networking. Google Scholar
Digital Library
- Corke, P., Valencia, P., Sikka, P., Wark, T., and Overs, L. 2007. Long-duration solar-powered wireless sensor networks. In Proceedings of the 4th IEEE Workshop on Embedded Networked Sensors. Google Scholar
Digital Library
- Dave, J. V., Halpern, P., and Myers, H. J. 1975. Computation of incident solar energy. IBM J. Res. Develop. 19, 6, 539--549. Google Scholar
Digital Library
- Dust Networks. 2006. Technical Overview of Time Synchronized Mesh Protocol (TSMP). http://www.dustnetworks.com/docs/TSMP_Whitepaper.pdf.Google Scholar
- Dutta, P., Hui, J., Jeong, J., Kim, S., Sharp, C., Taneja, J., Tolle, G., Whitehouse, K., and Culler, D. 2006. Trio: Enabling sustainable and scalable outdoor wireless sensor network deployments. In Proceedings of the 5th International Conference on Information Processing in Sensor Networks. Google Scholar
Digital Library
- Handziski, V., Köpke, A., Willig, A., and Wolisz, A. 2006. Twist: A scalable and reconfigurable testbed for wireless indoor experiments with sensor networks. In Proceedings of the 2nd International Workshop on Multihop Ad Hoc Networks: From Theory to Reality. Google Scholar
Digital Library
- Jiang, X., Polastre, J., and Culler, D. 2005. Perpetual environmentally powered sensor networks. In Proceedings of the 4th International Symposium on Information Processing in Sensor Networks. Google Scholar
Digital Library
- Kansal, A., Potter, D., and Srivastava, M. B. 2004. Performance aware tasking for environmentally powered sensor networks. In Proceedings of the Joint International Conference on Measurement and Modeling of Computer Systems. Google Scholar
Digital Library
- Kansal, A., Hsu, J., Zahedi, S., and Srivastava, M. B. 2007. Power management in energy harvesting sensor networks. ACM Trans. Embed. Comput. Syst. Google Scholar
Digital Library
- Kim, S. 2007. Wireless sensor networks for high frequency sampling. Ph.D dissertation, University of California at Berkeley. Google Scholar
Digital Library
- Landsiedel, O., Wehrle, K., and Götz, S. 2005. Accurate prediction of power consumption in sensor networks. In Proceedings of the 2nd IEEE Workshop on Embedded Networked Sensors. Google Scholar
Digital Library
- Levis, P., Patel, N., Culler, D., and Shenker, S. 2004. Trickle: A self-regulating algorithm for code propagation and maintenance in wireless sensor networks. In Proceedings of the 1st Symposium on Networked Systems Design and Implementation. Google Scholar
Digital Library
- Madden, S., Franklin, M. J., Hellerstein, J. M., and Hong, W. 2002. Tag: A tiny aggregation service for ad-hoc sensor networks. In Proceedings of the 5th Symposium on Operating Systems Design and Implementation. Google Scholar
Digital Library
- Meteonorm. 2003. Meteonorm. http://www.meteotest.ch/pdf/am/mn_description.pdf.Google Scholar
- Montenegro, G., Kushalnagar, N., Hui, J., and Culler, D. 2007. Transmission of ipv6 packets over ieee 802.15.4 networks. http://tools.ietf.org/html/rfc4944.Google Scholar
- Moser, C., Brunelli, B., Thiele, L., and Benini, L. 2006a. Lazy scheduling for energy harvesting sensor nodes. In Proceedings of the IFIP Conference from Model-Driven Design to Resource Management for Distributed Embedded Systems.Google Scholar
- Moser, C., Brunelli, B., Thiele, L., and Benini, L. 2006b. Real-time scheduling with regenerative energy. In Proceedings of the 18th Euromicro Conference on Real-Time Systems. Google Scholar
Digital Library
- Moser, C., Thiele, L., Brunelli, D., and Benini, L. 2007. Adaptive power management in energy harvesting systems. In Proceedings of the Conference on Design, Automation and Test in Europe. Google Scholar
Digital Library
- Nahapetian, A., Lombardo, P., Acquaviva, A., Benini, L., and Sarrafzadeh, M. 2007. Dynamic reconfiguration in sensor networks with regenerative energy sources. In Proceedings of the Conference on Design, Automation and Test in Europe. Google Scholar
Digital Library
- Nath, S., Gibbons, P. B., Seshan, S., and Anderson, Z. R. 2004. Synopsis diffusion for robust aggregation in sensor networks. In Proceedings of the 2nd ACM Conference on Embedded Networked Sensor Systems. Google Scholar
Digital Library
- NSR. 2008. National Solar Radiation Database. http://rredc.nrel.gov/solar/old_data/nsrdb.Google Scholar
- Osterwald, R. R., Anderberg, A., Rummel, S., and Ottoson, L. 2002. Degradation analysis of weathered crystalline-silicon pv modules. In Proceedings of the 29th IEEE Photovoltaic Specialists Conference.Google Scholar
- Park, C. and Chou, P. H. 2006. Ambimax: Autonomous energy harvesting platform for multi-supply wireless sensor nodes. IEEE Sen. Ad Hoc Commun. Netw.Google Scholar
- Park, S., Savvides, A., and Srivastava, M. B. 2000. Sensorsim: A simulation framework for sensor networks. In Proceedings of the International Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems. Google Scholar
Digital Library
- Park, S., Savvides, A., and Srivastava, M. B. 2001. Simulating networks of wireless sensors. In Proceedings of the Winter Simulation Conference. Google Scholar
Digital Library
- Peterson, J. T., Flowers, E. C., and Rudisill, J. H. 1978. Urban-rural solar radiation and atmospheric turbidity measurements in the los angeles basin. J. Appl. Meteorol. 17, 11, 1595--1609.Google Scholar
Cross Ref
- Piorno, J. R., Bergonzini, C., Atienza, D., and Rosing, T. S. 2009. Prediction and management in energy harvested wireless sensor nodes. In Proceedings of the 1st International Conference on Wireless Communications, Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology.Google Scholar
- Polastre, J., Hill, J., and Culler, D. 2004. Versatile low power media access for wireless sensor networks. In Proceedings of the 2nd ACM Conference on Embedded Networked Sensor Systems. Google Scholar
Digital Library
- Polastre, J., Szewczyk, R., and Culler, D. 2005. Telos: Enabling ultra-low power wireless research. In Proceedings of the 4th International Symposium on Information Processing in Sensor Networks. Google Scholar
Digital Library
- Pradhan, S. S., Kusuma, J., and Ramchandran, K. 2002. Distributed compression in a dense microsensor network. IEEE Signal Process. Mag.Google Scholar
Cross Ref
- Raghunathan, V., Kansal, A., Hsu, J., Friedman, J., and Srivastava, M. 2005. Design considerations for solar energy harvesting wireless embedded systems. In Proceedings of the 4th International Symposium on Information Processing in Sensor Networks. Google Scholar
Digital Library
- Robinson, E. and Valente, R. J. 1982. Atmospheric turbidity over the united states from 1967 to 1976. U.S. Environmental Protection Agency Report 600382076. http://nepis.epa.gov/Adobe/PDF~/200/5K9J.PDF.Google Scholar
- Scaglione, A. and Servetto, S. 2002. On the interdependence of routing and data compression in multi-hop sensor networks. In Proceedings of the 8th Annual International Conference on Mobile Computing and Networking. Google Scholar
Digital Library
- Shnayder, V., Hempstead, M., Chen, B., Werner-Allen, G., and Welsh, M. 2004. Simulating the power consumption of large-scale sensor network applications.In Proceedings of the 2nd ACM Conference on Embedded Networked Sensor Systems. Google Scholar
Digital Library
- Simjee, F. and Chou, P. H. 2006. Everlast: Long-life, supercapacitor-operated wireless sensor node. In Proceedings of the International Symposium on Low Power Electronics and Design. Google Scholar
Digital Library
- Simon, G., Volgyesi, P., Maroti, M., and Ledeczi, A. 2003. Simulation-based optimization of communication protocols for large-scale wireless sensor networks. In Proceedings of the IEEE Aerospace Conference.Google Scholar
- Sorber, J., Kostadinov, A., Garber, M., Brennan, M., Corner, M. D., and Berger, E. D. 2007. Eon: A language and runtime system for perpetual systems. In Proceedings of the 5th ACM Conference on Embedded Networked Sensor Systems. Google Scholar
Digital Library
- Sundresh, S., Kim, W., and Agha, G. 2004. Sens: A sensor, environment and network simulator. In Proceedings of the 37th Annual Simulation Symposium. Google Scholar
Digital Library
- Szewczyk, R., Mainwaring, A., Polastre, J., Anderson, J., and Culler, D. 2004. An analysis of a large scale habitat monitoring application. In Proceedings of the 2nd ACM Conference on Embedded Networked Sensor Systems. Google Scholar
Digital Library
- Tolle, G., Polastre, J., Szewczyk, R., Culler, D., Turner, N., Tu, K., Burgess, S., Dawson, T., Buonadonna, P., Gay, D., and Hong, W. 2005. A macroscope in the redwoods. In Proceedings of the 3rd ACM Conference on Embedded Networked Sensor Systems. Google Scholar
Digital Library
- Varshney, M., Xu, D., Srivastava, M., and Bagrodia, R. 2007. squalnet: A scalable simulation and emulation environment for sensor networks. In Proceedings of the 7th International Conference on Information Processing in Sensor Networks. Google Scholar
Digital Library
- Vigorito, C. M., Ganesan, D., and Barto, A. G. 2007. Adaptive control of duty cycling in energy-harvesting wireless sensor networks. IEEE Sens. Ad Hoc Commun. Netw.Google Scholar
- Werner-Allen, G., Swieskowski, P., and Welsh, M. 2005. Motelab: A wireless sensor network testbed. In Proceedings of the 4th International Symposium on Information Processing in Sensor Networks. Google Scholar
Digital Library
- Ye, W., Heidemann, J., and Estrin, D. 2004. Medium access control with coordinated adaptive sleeping for wireless sensor networks. IEEE/ACM Trans. Netw. 3. Google Scholar
Digital Library
- Ye, W., Silva, F., and Heidemann, J. 2006. Ultra-low duty cycle mac with scheduled channel polling. In Proceedings of the 4th ACM Conference on Embedded Networked Sensor Systems. Google Scholar
Digital Library
- Zhang, J., Zhou, G., Huang, C., Son, S. H., and Stankovic, J. A. 2007. Tmmac: An energy efficient multi-channel mac protocol for ad hoc networks. In Proceedings of the IEEE International Conference on Communications.Google Scholar
- Zhang, P., Sadler, C. M., Lyon, S. A., and Martonosi, M. 2004. Hardware design experiences in zebranet. In Proceedings of the 2nd ACM Conference on Embedded Networked Sensor Systems. Google Scholar
Digital Library
Index Terms
Predicting the Long-Term Behavior of a Micro-Solar Power System
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