Jump to content, Georgia Institute of Technology, College of Engineering, School of Electrical and Computer Engineering (ECE), ECE Research, ECE Research Labs
College of Engineering
Search | Contact ECE | Feedback | BuzzPort
GT Home > COE Home > ECE Home > Research > Labs > ACES, Advanced Computational Electricity Systems
Georgia Tech
Advanced Computational Electricity Systems(ACES)

RESEARCH

SMART GRID SIMULATOR

Tanguy F. Hubert

Utility demand response programs provide the economic incentives and signals to minimize the cost of energy consumption. These economic drivers are tied directly to consumer energy utilization and to temporal patterns of energy consumption. While a significant portion of demand response results in temporally shifted demand, the economic information provides continuous input into the cost of energy therefore motivating its optimal utilization.

Impact of Storage for Losses Reduction

In the short term, demand response allows the customer to minimize its overall electricity cost for a day, but in the longer term, price signals are the incentives for deployment of efficient devices, controls and technologies.

SMART GRID SIMULATOR

We utilized a simulation approach both through software and test-beds to determine the demand response algorithms, the optimal scheduling strategies, the design of optimal utility prices signals, and the information architecture for short-term demand response programs. Parametric modeling addresses the impact of various production, storage, efficiency and use into the cost function. In particular, we investigate the extent to which human comfort can be perturbed to achieve optimal demand responses. In large buildings and facilities the energy efficiency social consciousness is investigated to address human control that embeds the common objectives of demand response.

 

Last revised on Aug. 25, 2011