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Low-Cost Self-Governing Energy Management System for Micro-Grids

Undergraduate #359
Discipline: Technology and Engineering
Subcategory: Electrical Engineering

Alex Ramirez - California State University, Bakersfield


The United States is responsible for wasting more energy than it uses. According to an analysis by Lawrence Livermore National Laboratory in 2013, the U.S. wastes more than 61% of the energy it produces. For a society that wastes a great deal of energy, the development of an energy management system for micro-grids would be beneficial. Such a system that is disconnected from the grid would not only have positive ecological consequences but economic benefits as well. By maximizing the usage of alternative energy we can then in turn stop producing unnecessary energy. Micro-grids have become increasingly popular with the introduction of ad hoc network enabled devices. We developed a Wireless Sensor Network (WSN) to operate efficiently and remotely. Our WSN is the outcome of multiple interconnected wireless devices providing flexibility and mobility in data collection. Our WSN consists of a central station and multiple sensing stations. Energy consumption values are passed from the sensing stat to the central station that is connected to a computer running Matlab. We used Matlab to compute the optimized energy each sensing station should consume. Using Matlab’s algorithm for Mixed Integer Linear Programming (MILP) we were able to simulate solar generation and battery reserves. Once the values are calculated, Matlab sends these energy consumption values to the central station to distribute among corresponding sensing stations. The sensing stations utilize a Proportional Integral (PI) controller in order to reach the desired energy consumption. We found this to be efficient when considering the networks size. We also found our system to efficiently control the energy consumed based on the scheme we chose to run. For future research we plan on expanding our network to test size limitations as well as developing alternative strategies to handle larger networks. Also, we plan on connecting our system to a physical battery being charged by solar generation.

References: Baoxian Zhang – Hussein T.Mouftah – Wireless Networks WirelessNetw – 2006
Shrestha, Pramen P., and Prajakta Kulkarni. ‘Factors Influencing Energy Consumption Of Energy Star And Non-Energy Star Homes.’ Journal Of Management In Engineering 29.3 (2013): 269 -278. Business Source Premier. Web. 2 June 2015.
Han, Dae-Man, and Jae-Hyun Lim. ‘Design and implementation of smart home energy management systems based on zigbee.’ Consumer Electronics, IEEE Transactions on 56.3 (2010): 14171425.
Ricquebourg, Vincent, et al. ‘The smart home concept: our immediate future.’ E-Learning in Industrial Electronics, 2006 1ST IEEE International Conference on. IEEE, 2006.
Van Dam, S. S., C. A. Bakker, and J. D. M. van Hal. ‘Home Energy Monitors: Impact Over The Medium-Term.’ Building Research & Information 38.5 (2010): 458-469. Business Source Premier. Web. 2 June 2015. http://blog.opower.com/2013/08/the-tradition-continues-theunited-states-wastes-more-energy-than-it-uses

Funder Acknowledgement(s): The authors would like to acknowledge the Department of Defense and National Science Foundation for their support.

Faculty Advisor: Saeed Jafarzadeh, sjafarzadeh@csub.edu

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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