Optimal coordination of vehicle-to-grid batteries and renewable generators in a distribution system

被引：29

作者：

Wang, Lu ^{[1
]}

Sharkh, Suleiman ^{[1
]}

Chipperfield, Andy ^{[1
]}

机构：

[1] Univ Southampton, Fac Engn & Environm, Southampton SO17 1BJ, Hants, England

来源：

ENERGY | 2016年 / 113卷

关键词：

Vehicle-to-grid; Distributed generators; Optimal coordination; Decentralized dispatch; Dynamic programming; ELECTRIC VEHICLES; ENERGY MANAGEMENT; DISPATCH; INTEGRATION; BENEFITS;

D O I：

10.1016/j.energy.2016.07.125

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

The increasing penetration of electric vehicles (EVs) and renewable generators (RGs) in the power grid is an inevitable trend to combat air pollution and reduce the usage of fossil fuels. This will challenge distribution networks, which have constrained capacity. However, appropriate dispatch of electric vehicles via vehicle-to-grid (V2G) operation in coordination with the distributed renewable generators can provide support for the grid, reduce the reliance on traditional fossil-fuel generators and benefit EV users. This paper develops a novel agent-based coordinated dispatch strategy for EVs and distributed renewable generators, taking into account both grid's and EV users' concerns and priorities. This optimal dispatch problem is formulated as a distributed multi-objective constraint optimisation problem utilizing the Analytic Hierarchy Process and is solved using a dynamic-programming-based algorithm. The proposed strategy is tested on a modified UK Generic Distribution System (UKGDS). The electricity network model is simplified using a virtual sub-node concept to alleviate the computation burden of a node's agent. Simulation results demonstrate the feasibility and stability of this dispatch strategy. (C) 2016 Elsevier Ltd. All rights reserved.

引用

页码：1250 / 1264

页数：15

共 37 条

[11] Optimal charging of an electric vehicle using a Markov decision process [J].

Iversen, Emil B. ;

Morales, Juan M. ;

Madsen, Henrik .

APPLIED ENERGY, 2014, 123 :1-12

[12] Distributed Coordination of Electric Vehicles Providing V2G Services [J].

Karfopoulos, Evangelos L. ;

Hatziargyriou, Nikos D. .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2016, 31 (01) :329-338

[13] Design of Emergency Demand Response Program Using Analytic Hierarchy Process [J].

Kim, Dong-Min ;

Kim, Jin-O. .

IEEE TRANSACTIONS ON SMART GRID, 2012, 3 (02) :635-644

[14] Synergistic Control of Plug-In Vehicle Charging and Wind Power Scheduling [J].

Li, Chiao-Ting ;

Ahn, Changsun ;

Peng, Huei ;

Sun, Jing .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2013, 28 (02) :1113-1121

[15] Emission-Concerned Wind-EV Coordination on the Transmission Grid Side With Network Constraints: Concept and Case Study [J].

Li, Zhengshuo ;

Guo, Qinglai ;

Sun, Hongbin ;

Wang, Yao ;

Xin, Shujun .

IEEE TRANSACTIONS ON SMART GRID, 2013, 4 (03) :1692-1704

[16] Modeling the Benefits of Vehicle-to-Grid Technology to a Power System [J].

Ma, Yuchao ;

Houghton, Tom ;

Cruden, Andrew ;

Infield, David .

IEEE TRANSACTIONS ON POWER SYSTEMS, 2012, 27 (02) :1012-1020

[17]

Masuch N., 2012, 2012 IEEE International Electric Vehicle Conference (IEVC), P1

[18]

Miller S., 2012, P 11 INT C AUT AG MU, V1, P281

[19] Real CO2 emissions benefits and end user's operating costs of a plug-in Hybrid Electric Vehicle [J].

Millo, Federico ;

Rolando, Luciano ;

Fuso, Rocco ;

Mallamo, Fabio .

APPLIED ENERGY, 2014, 114 :563-571

[20] An efficient two stage stochastic optimal energy and reserve management in a microgrid [J].

Mohan, Vivek ;

Singh, Jai Govind ;

Ongsakul, Weerakom .

APPLIED ENERGY, 2015, 160 :28-38

← 1 2 3 4 →