As U.S. energy consumption rises, mechanisms to manage peak demand have become increasingly important. The rise in the demand for energy is beginning to strain the country’s aging infrastructure, potentially threatening the stability of electricity grids. To address this issue, new technologies that ensure the sustainability of electricity services and improve demand management are emerging.
The development and growth of smart energy grids has increased the ability to monitor and communicate power supply as well as pricing and demand among utility providers and consumers. The software architecture to collect, manage, analyze, scale and secure this information is currently being designed.
As part of the Los Angeles Smart Grid Demonstration project, Dr. Viktor Prasanna, director of the Center for Energy Informatics at USC, and his team are currently researching optimization techniques to understand and manage electricity consumption. "Our research focuses on the areas of Semantic Web, integration and analysis of high throughput data, large scale distributed computing, and social computing," said Dr. Prasanna. The research effort, which is sponsored by the Department of Energy, is a joint collaboration between the Los Angeles Department of Water and Power, researchers at the USC Viterbi School, and USC Facilities Management.
The communication between stakeholders in the smart grid is continuous, taking the form of streams of control and data events such as power usage, production, pricing, feedback, etc., which are transmitted across a widely distributed infrastructure.
"We are examining existing protocols and techniques for demand response, and demonstrating their applicability (or not) for the Smart Grid,"said Dr. Prasanna. "In particular, we will consider two specific challenges imposed by the Smart Grid - the real time nature of data and the large scale at which it operates."
Effective integration, analysis and feedback of energy information are essential for the benefits of the Smart Grid to be realized by various stakeholders: power utilities, residential, commercial and institutional consumers, and service and application providers. This can lead to a lower peak demand on utilities, reduced consumption and decreased costs for consumers as well as help organizations plan and optimize their energy usage to meet sustainability goals.
The project features four research areas: Security and Privacy in Stream Processing Systems; Semantic Complex Event Processing for Information Integration in the Smart Grid; Cloud Computing for Scalable Smart Grid Information Processing and Management; and Machine Learning for Predictive Modeling of Energy Usage.
For more information, http://cei.usc.edu/.