New EMS to Incorporate Smart Parking Lots Into Demand Response

被引：31

作者：

Akhavan-Rezai, Elham ^{[1
]}

Shaaban, Mostafa F. ^{[2
]}

El-Saadany, Ehab F. ^{[1
]}

Karray, Fakhri ^{[1
]}

机构：

[1] Univ Waterloo, Elect & Comp Engn Dept, Waterloo, ON N2L 3G1, Canada

[2] Amer Univ Sharjah, Elect Engn Dept, Sharjah 26666, U Arab Emirates

来源：

IEEE TRANSACTIONS ON SMART GRID | 2018年 / 9卷 / 02期

关键词：

Artificial neural network; demand response; distribution systems; energy management system; electric vehicles; decision-making; Markov chain; and smart parking lots; IN ELECTRIC VEHICLES; ENERGY MANAGEMENT; SIDE MANAGEMENT; LOAD MODELS; COORDINATION; OPTIMIZATION; CAPACITY; SYSTEMS;

D O I：

10.1109/TSG.2016.2587901

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Demand response (DR) seeks to involve end-use customers in modifying their electricity usage and to offer incentive payments to encourage lower electricity use at times of high prices. This paper provides an approach that realizes DR by developing an energy management system for incorporating aggregated plug-in electric vehicles (PEVs) in parking lots. This approach includes real-time interaction between the aggregator and PEV owners, whereby the aggregator proposes a number of offers and the owner responds based on his/her preference. The optimization problem is defined as mixed integer nonlinear programming. An extensive performance evaluation using MATLAB/GAMS simulation of the 38-bus test system verifies the success and effectiveness of the proposed method.

引用

页码：1376 / 1386

页数：11

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