Title :
Real-Time Welfare-Maximizing Regulation Allocation in Dynamic Aggregator-EVs System
Author :
Sun Sun ; Min Dong ; Ben Liang
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Toronto, Toronto, ON, Canada
Abstract :
The concept of vehicle-to-grid (V2G) has gained recent interest as more and more electric vehicles (EVs) are put to use. In this paper, we consider a dynamic aggregator-EVs system, where an aggregator centrally coordinates a large number of dynamic EVs to provide regulation service. We propose a Welfare-Maximizing Regulation Allocation (WMRA) algorithm for the aggregator to fairly allocate the regulation amount among the EVs. Compared with previous works, WMRA accommodates a wide spectrum of vital system characteristics, including dynamics of EV, limited EV battery size, EV battery degradation cost, and the cost of using external energy sources for the aggregator. The algorithm operates in real time and does not require any prior knowledge of the statistical information of the system. Theoretically, we demonstrate that WMRA is away from the optimum by O(1/V), where V is a controlling parameter depending on EVs´ battery size. In addition, our simulation results indicate that WMRA can substantially outperform a suboptimal greedy algorithm.
Keywords :
electric vehicles; power grids; statistical analysis; EV battery degradation cost; V2G; WMRA algorithm; dynamic aggregator-EVs system; electric vehicles; external energy sources; limited EV battery size; real-time welfare-maximizing regulation allocation; statistical information; suboptimal greedy algorithm; vehicle-to-grid; welfare-maximizing regulation allocation algorithm; Batteries; Degradation; Energy states; Power grids; Power system dynamics; Real-time systems; Resource management; Aggregator-EVs system; V2G; electric vehicles; real-time algorithm; welfare-maximizing regulation allocation;
Journal_Title :
Smart Grid, IEEE Transactions on
DOI :
10.1109/TSG.2014.2300040