Jaein Jeong
Skip Abstract Section
Abstract
Building a micro-solar power system is challenging because it must address long-term system behavior under highly variable solar energy and consider a large design space. We develop a practical theory of micro-solar power systems that is materialized in a simulation suite that models component and system behavior over a long time scale and in an external environment that depends on time, location, weather, and local variations. This simulation provides sufficient accuracy to guide specific design choices in a large design space. Unlike the many macro-solar calculators, this design tool models detailed behavior of milliwatt systems in the worst conditions, rather than typical behavior of kilowatt systems in the best conditions. Our simulation suite is validated with a concrete design of micro-solar power systems, the HydroWatch node. With our simulation suite, micro-solar power systems can be designed in a systematic fashion. Putting the model and empirical vehicle together, the design choices in each component of a micro-solar power system are studied to reach a deployable candidate. The deployment is evaluated by analyzing the effects of different solar profiles across the network. The analysis from the deployment can be used to refine the next system-design iteration.
- Castaner, L. and Silvestre, S. 2002. Modeling Photovoltaic Systems Using PSpice. John Wiley & Sons, Huboken, NJ.Google Scholar
- 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 (EmNets'07). Google ScholarDigital 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 ScholarDigital Library
- Dubayah, R. and Rich, P. M. 1995. Topographic solar radiation models for gis. Int. J. Geog. Inf. Sci. 9, 4, 405--419.Google ScholarCross Ref
- Dunkels, A., Osterlind, F., Tsiftes, N., and He, Z. 2007. Software-based on-line energy estimation for sensor nodes. In Proceedings of the 4th IEEE Workshop on Embedded Networked Sensors (EmNets'07). Google ScholarDigital Library
- 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 (IPSN/SPOTS'06). Google ScholarDigital Library
- Fonseca, R., Dutta, P., Levis, P., and Stoica, I. 2008. Quanto: Tracking energy in networked embedded systems. In Proceedings of the 8th USENIX Symposium on Operating System Design and Implementation (OSDI'08). Google ScholarDigital 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 Multi-Hop Ad Hoc Networks: From Theory to Reality (REALMAN'06). Google ScholarDigital Library
- Ingelrest, F., Barrenetxea, G., Schaefer, G., Vetterli, M., Couach, O., and Parlange, M. 2010. Sensorscope: Application-specific sensor network for environmental monitoring. ACM Trans. Sens. Netw. Google ScholarDigital 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 (IPSN/SPOTS'05). Google ScholarDigital Library
- Kansal, A., Hsu, J., Zahedi, S., and Srivastava, M. B. 2007. Power management in energy harvesting sensor networks. ACM Trans. Embed. Compu. Syst. Google ScholarDigital 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 (SIGMETRICS). Google ScholarDigital Library
- Kim, S. 2007. Wireless sensor networks for high frequency sampling. Ph.D dissertation, University of California at Berkeley. Google ScholarDigital 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 (EmNets'05). Google ScholarDigital Library
- Li, D. and Chou, P. H. 2004. Maximizing efficiency of solar-powered systems by load matching. In Proceedings of the International Symposium on Low Power Electronics and Design (ISLPED). Google ScholarDigital 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 (OSDI'02). Google ScholarDigital Library
- 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 on 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 (ECRTS'06). Google ScholarDigital 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 (Sensys'04). Google ScholarDigital Library
- Newton, A. R. 1978. The simulation of large scale integrated circuits. Ph.D dissertation, University of California at Berkeley.Google Scholar
- Paradiso, J. A. 2006. Systems for human-powered mobile computing. In Proceedings of the IEEE Design Automation Conference (DAC). Google ScholarDigital Library
- Park, C. and Chou, P. H. 2006. Ambimax: Autonomous energy harvesting platform for multi-supply wireless sensor nodes. In Proceedings of the IEEE International Conference on Sensing, Communication and Networking (SECON).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 (MSWIM). Google ScholarDigital Library
- Park, S., Savvides, A., and Srivastava, M. B. 2001. Simulating networks of wireless sensors. In Proceedings of the Winter Simulation Conference. Google ScholarDigital Library
- 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 (Sensys'04). Google ScholarDigital 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 (IPSN/SPOTS'05). Google ScholarDigital Library
- Pop, V., Bergveld, H. J., Notten, P. H. L., and Regtien, P. P. L. 2005. State-of-the-art of battery state-of-charge determination. Ins. Physics Publish. Meas. Sci. Techno.Google Scholar
- Pradhan, S. S., Kusuma, J., and Ramchandran, K. 2002. Distributed compression in a dense microsensor network. IEEE Signal Proces. Mag.Google ScholarCross 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 (IPSN/SPOTS'05). Google ScholarDigital Library
- Randall, J. F. 2005. Designing Indoor Solar Products, Photovoltaic Technologies for AES. John Wiley & Sons, Hoboken, NJ.Google Scholar
- Rao, R., Vrudhula, S., and Rakhmatov, D. N. 2003. Battery modeling for energy-aware system design. IEEE Comput. Google ScholarDigital Library
- Roundy, S., Otis, B. P., Chee, Y.-H., Rabaey, J. M., and Wright, P. 2003. A 1.9ghz rf transmit beacon using environmentally scavenged energy. In Proceedings of the International Symposium on Low Power Electronics and Design (ISLPED).Google Scholar
- Roundy, S. J. 2003. Energy scavenging for wireless sensor nodes with a focus on vibration to electricity conversion. Ph.D. dissertation, University of California at Berkeley.Google Scholar
- 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 (Sensys'04). Google ScholarDigital Library
- Sikka, P., Corke, P., Valencia, P., Crossman, C., Swain, D., and Bishop-Hurley, G. 2006. Wireless adhoc sensor and actuator networks on the farm. In Proceedings of the 5th International Conference on Information Processing in Sensor Networks (IPSN/SPOTS'06). Google ScholarDigital 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 (ISLPED). Google ScholarDigital 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
- Sober, 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 (Sensys'07). Google ScholarDigital Library
- Sundresh, S., Kim, W., and Agha, G. 2004. Sens: A sensor, environment and network simulator. In Proceedings of the 37th Annual Simulation Symposium (ANSS'04). Google ScholarDigital 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 (Sensys'04). Google ScholarDigital Library
- Taneja, J., Jeong, J., and Culler, D. 2008. Design, modeling, and capacity planning for micro-solar power sensor networks. In Proceedings of the 7th International Conference on Information Processing in Sensor Networks (IPSN/SPOTS'08). Google ScholarDigital Library
- Tovar-Pescador, J., Pozo-Vázquez, D., Ruiz-Arias, J. A., Batlles, J., López, G., and Bosch, J. L. 2006. On the use of the digital elevation model to estimate the solar radiation in areas of complex topography. Meteorol. Appl., 297--287.Google Scholar
- 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 (IPSN/SPOTS'07). Google ScholarDigital Library
- Vigorito, C. M., Ganesan, D., and Barto, A. G. 2007. Adaptive control of duty cycling in energy-harvesting wireless sensor networks. In Proceedings of the IEEE International Conference on Sensing Communications, and Networking (SECON).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 (IPSN/SPOTS'05). Google ScholarDigital 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 ScholarDigital 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 (Sensys'06). Google ScholarDigital Library
- 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 (Sensys'04). Google ScholarDigital Library
Index Terms
- A practical theory of micro-solar power sensor networks
Recommendations
Predicting the Long-Term Behavior of a Micro-Solar Power System
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, ...
Modeling of the ND 240QCJ SHARP photovoltaic solar module and study the influence of the variation of the parameters
AbstractSolar energy is inexhaustible on a human scale and freely available in very large quantities. In addition, during the operational phase, the production of electricity by means of photovoltaic panels is not polluting. The modeling, simulation and ...
Comments