Intelligent Energy Management Systems for Net-Zero-Energy Houses

Issue: Commercial and residential buildings consumed almost 40% of the primary energy and approximately 70% of the electricity in the United States in 2012, and the trend continues to escalate. Renewable energy resources now attract worldwide enthusiasm because of the reduced consumption of traditional energy resources and lower carbon emissions. These benefits have given rise to a vast increase in sustainable energy projects, and the U.S. Department of Energy has envisioned that 20% of the country’s electricity will come from wind energy by 2030; meanwhile solar energy generation will meet 14% of U.S. electricity demand. The concept of the net-zero-energy house gives a promising vision to be widely adopted in future city constructions since it can provide its own power demand from on-site renewable energy generation and thus significantly reduce reliance on traditional energy resources. Although renewable energy minimized demands on traditional non-renewable resources, the inherent intermittency and variability of on-site renewables still complicates their real-world deployment and operation cost effectively.

Objective: The goal of this project is to develop a software-based energy management system for a residential net-zero-energy house. Upon completion of the 10-week training, REU students will (i) have a better understanding of the net-zero-energy house, (ii) gain experience with such general-purpose computer programs such as Matlab/Simulink, (iii) formulate a basic mathematical model for a net-zero-energy house, and (iv) select an optimization algorithm for solving energy scheduling problems.

Student Involvement: Three sample problems that students will address are to: (i) study the equivalent electrical models of net-zero energy house components in Matlab/Simulink, (ii) implement a basic energy scheduling algorithm, and (iii) evaluate the effectiveness and usability of the proposed energy management system under various operating conditions (e.g., wind speed, solar irradiation).