Title :
Optimal power flow and energy-sharing among multi-agent smart buildings in the smart grid
Author :
ByungChul Kim ; Lavrova, Olga
Abstract :
Buildings account for about 40% of total energy consumption. Efficient building energy control can considerably reduce energy costs. A smart grid takes advantage of bi-directional energy and information flow between the utility grid and the energy user. Smart buildings can charge or discharge energy or power from multiple buildings (multi-agent systems) using smart meters via battery storage in the smart buildings. However, there is very little research on how to share energy among multi-agent systems and optimal power flow among smart buildings (multi-agent systems) in the smart grid. In this paper, the authors use an advanced optimization method to present optimal power flow and energy-sharing among smart buildings. With this research, it is expected that this method can improve the smart grid optimal power flow and energy-sharing stability among smart buildings, and enhance energy dissipation balance to reach stability among many smart buildings in the smart grid.
Keywords :
building management systems; energy consumption; load flow; multi-agent systems; smart power grids; advanced optimization method; battery storage; bi-directional energy; building energy control; energy costs; energy dissipation balance; energy user; energy-sharing stability; information flow; multi-agent smart buildings; multi-agent systems; optimal power flow; smart grid; smart meters; total energy consumption; utility grid; Batteries; Genetic algorithms; Linear programming; Load flow; Multi-agent systems; Smart buildings; Smart grids; Battery Storage System; Multiple Traveling Salesman Problem; Optimal Power Flow; Smart Building; Smart Grid;
Conference_Titel :
Energytech, 2013 IEEE
Conference_Location :
Cleveland, OH
DOI :
10.1109/EnergyTech.2013.6645336