Networked Redistribution Grid (NRG) Software Engineering Project



Period: January 2014 - March 2014
View Project on GitHub

The Networked Redistribution Grid (NRG) project was an undergraduate software engineering project developed by a team of computer science students of the College of Engineering, Computer Science and Technology (ECST) in California State University of Los Angeles (Cal State LA). The developers were computer science undergraduates, William Klein, Michael Holloway, Tony Liang, and Laura Mann.

The NRG is a software system that moderates the daily tide of energy usage to reduce dependency on inefficient power plants. The system only works with devices embedded with a NRG Wi-Fi remote chip. With the chip embedded, the devices will receive data about the devices. The system maintains a database of relevant historical data of devices, the weather, and the grid. With this data, it can predict future grid usage and generate the current grid deficit. It anticipates demand and reduces power usages of non-essential devices. As a result, the system reduces overall power generation cost and environmental stress. Unlike other smart grid plans, which rely on the end user to change the power usages of their devices, the NRG adjusts consumption rates automatically when needed. It also allows manual control of the system for emergencies.

Previously, in a software design class, a team of computer science students created the NRG project's requirements and design. Therefore, the developers would be implementing and testing the NRG software. The implementation of the NRG is partially completed. The developers only implemented feasible modules of the software. William, Michael, Tony, and Laura designed and implemented the data management, predictive, response, and control interface functions of the NRG respectively. They also added more requirements for their respective functions if necessary, designed detailed diagrams of the functions, wrote test cases for the functions, and created the functional requirements validation matrix for testing NRG.