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)



Tanguy F. Hubert

This project addresses the strategies to achieve optimal management from a customer's perspective using a day-ahead planning approach. Linear, programming and simulated annealing methods, are developed and compared. A user-friendly human-machine interface based on the proposed control scheme has been implemented.



Among the key parameters describing a given homegrid, some have fixed values, such as electrical and mechanical parameters, wattage ratings, or distributed generation efficiency. Other parameters can be forecasted on a day-ahead basis. Local weather forecast allows the estimation of the local renewable energy production for the next day. Local dayahead price forecast gives the next day's hourly prices of electricity. A schedule of the generation and storage systems and PHEV determines what their status will be for the next 24 hours. In the future, it is expected that the local control system will also be able to estimate the essential loads consumption for the next day, using data such as the day of the week, the season, or the habits of the customer. Finally, it appears that, from a customer's point of view, the non-essential loads are the only degrees of freedom existing in the system.


Last revised on Aug. 25, 2011