Title :
Demand Response for Residential Electric Vehicles With Random Usage Patterns in Smart Grids
Author :
Rassaei, Farshad ; Wee-Seng Soh ; Kee-Chaing Chua
Author_Institution :
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore
Abstract :
Electric vehicles (EVs) are expected to become widespread in future years. Thus, it is foreseen that EVs will become the new high-electricity-consuming appliances in the households. The characteristics of the extra power load that they impose on the distribution grid follow the patterns of people´s random usage behaviors. In this paper, we seek to provide answers to the following question: assigning real-world randomness to the EVs´ availability in the households and their charging requirements, how can EVs´ demand response (DR) help to minimize the peak power demand and, in general, shape the aggregated demand profile of the system? We present a general demand-shaping problem applicable for limit order bids to a day-ahead (DA) energy market. We propose an algorithm for distributed DR of the EVs to shape the daily demand profile or to minimize the peak demand. Additionally, we put these problems in a game framework. Extensive simulations show that, for certain practical distributions of EVs´ usage, it is possible to accommodate EVs for all the users in the system and yet achieve the same peak demand as when there is no EV in the system without any changes in the users´ commuting behaviors.
Keywords :
demand side management; domestic appliances; electric vehicles; power consumption; power markets; smart power grids; DA energy market; EV demand response; aggregated demand profile; day-ahead energy market; distribution grid; general demand shaping problem; high electricity consuming appliance; peak power demand minimization; random usage pattern; residential electric vehicle DR; smart grid; Algorithm design and analysis; Electric vehicles; Load modeling; Power demand; Smart grids; Day-ahead (DA) market; demand response (DR); electric vehicle (EV); flexible load; limit order bids; random usage patterns; residential load; smart grids; vehicle-to-grid (V2G);
Journal_Title :
Sustainable Energy, IEEE Transactions on
DOI :
10.1109/TSTE.2015.2438037