Battery Status Monitor: The source of decision making for a Smart Micro-Grid Daniel Rendon, Cheryl Limas, Greg Turner - Advisor, Dr. D. Wetz - Advisor Department of Electrical Engineering, University of Texas at Arlington, Arlington, Texas Abstract The dependence on fossil fuels for the generation of the energy we consume is at inexcusable high rates taking into consideration the many renewable energy sources and technologies we have today. A solution to this problem could be the programmable smart micro-grid. The goal behind the smart micro-grid is to generate power by combining local renewable energy sources in such a way that power can be produced in the most efficient way possible. With this in mind, the smart micro-grid will not only reduce the dependence on fossil fuels, but will also reduce the use of transmission lines. No transmission lines transporting power to our homes open a new road to cheaper energy and eliminates one of the main causes for power outages. Before installing a smart micro-grid in your home or business, there is some serious programming involved. Every smart micro-grid needs a decision making source such as the battery status application. From this application it will decide or inform the user when critical decisions are to be made. Introduction Everyone pays an energy bill, but what if you could have power in your home for free or even better, get paid by your energy company instead of you paying them. This idea can be made possible with a smart-micro grid installed in your home. To get started, some energy sources such as solar panels or wind turbines are needed to be installed. These sources would be managed by a program designed using some sort of computer language. In our experiment we used NI’s (National Instruments) LabVIEW software in order to obtain data from our renewable sources and program an application, in accordance to that data, that will let us know when critical decisions are to be made. In order to program the battery status monitor we had to investigate how batteries behave and how they are rated. Using many different functions from LabVIEW, hardware such as the compact RIO and hall effect sensors, and knowledge on charging and discharging batteries we were able to calculate and display the battery status. Materials LabVIEW LabVIEW is a graphical programming platform that helps engineers scale from design to test and from small to large systems. It offers unprecedented integration with existing legacy software, IP, and hardware while capitalizing on the latest computing technologies. Compact RIO CompactRIO is a reconfigurable embedded control and acquisition system. The CompactRIO system’s rugged hardware architecture includes I/O modules, a reconfigurable FPGA chassis, and an embedded controller. Additionally, CompactRIO is programmed with NI LabVIEW graphical programming tools and can be used in a variety of embedded control and monitoring applications. Hall Effect Sensors L03S050D15 Methods Basic layout of the micro-grid’s main components and the transfer of energy: Wind Turbine Charge Control Solar Panel Charge Control Batteries INVERTERINVERTER Our goal was to determine the amount of current going in and coming out of the batteries. We were able to place three hall effect sensors on the wires transporting current to and out of the batteries. By using Kirchhoff’s current law in the node connecting these three wires with the battery, we determined whether current was leaving or entering the batteries. Using the FPGA sampling method to sample data once every 100us (above). The data from the hall effect sensors is gathered into a FIFO write function. This data is read and interpreted by the program on our main VI (below). In this specific part of the code, data is being converted from voltages to currents and KCL is being used to determine whether current is flowing in or out of the batteries. Σ i = 0 Results We programmed this loop (above) to turn true once every 1-4 minutes. Inside this loop we are taking the live current (obtained once every 1-4 minutes) coming in or out of the batteries and multiplying it by the amount of time the loop ran. This calculation gives us the amount of charge which we can subtract or add to the live charge of the batteries, thus giving us the current state of the batteries. Front Panel displaying the data obtained from the hall effect sensors. Data represents the transfer of energy in the micro-grid. Actual battery status monitor. Summary and Conclusions The smart micro-grid is still a work in progress with many different situations to be taken into consideration. Having said this, those situations are ready to be detected with the battery status monitor up and running. The priorities of energy direction is to be determined by the user and the different applications where the micro-grid is placed. Knowing the status of the energy storage is key to deciding what to do when critical conditions are encountered. In order to build the battery status monitor, we used the hall-effect sensors which detect current by displaying a voltage ranging from 0 to 4V. These voltages we converted to currents and along with Kirchhoff’s current law we were able to detect whether current was flowing in or out of the batteries. With this information and a loop keeping track of the current and time, we calculated the charge in and out of the batteries. Finally, obtaining the charge, we were able to calculate the status of the batteries. The battery status monitor along with some more programming will form the smart micro-grid. This technology will control how energy is distributed and provide the user with the most efficient way of running their home electricity. References "LabVIEW System Design Software." NI LabVIEW. National Instruments Corporation, Web. "NI LabVIEW for CompactRIO Developer's Guide." NI CompactRIO Developers Guide. N.p., n.d. Web. "DieHard Platinum Marine Battery Group Size 31M." Sears.com. Sears Brand, Web. "Hall Effect Current Sensors L03S***D15 Series." Tamura, Mar Web. "Maverick Wikis." Pulsed Power and Energy Lab Wiki. UT Arlington Web Publishing, n.d. Web. Acknowledgements Special thanks to Greg Turner and Dr. Wetz for advising us and allowing us to gain hands-on experience with programming and micro-grid technologies. Research Experience for Undergraduates in Sensors and Applications