A stochastic resource-sharing network for electric vehicle charging

Angelos Aveklouris; Maria Vlasiou; Bert Zwart

doi:10.1109/TCNS.2019.2915651

A stochastic resource-sharing network for electric vehicle charging

Angelos Aveklouris (Corresponding author), Maria Vlasiou, Bert Zwart

Stochastic Operations Research

Research output: Contribution to journal › Article › Academic › peer-review

21 Citations (Scopus)

Abstract

We consider a distribution grid used to charge electric vehicles (EVs) such that voltage drops stay bounded. We model this as a class of resource-sharing networks, known as bandwidth-sharing networks in the communication network literature. We focus on resource-sharing networks that are driven by a class of greedy control rules that can be implemented in a decentralized fashion. For a large number of such control rules, we can characterize the performance of the system by a fluid approximation. This leads to a set of dynamic equations that take into account the stochastic behavior of EVs. We show that the invariant point of these equations is unique and can be computed by solving a specific AC optimal-power-flow problem (ACOPF), which admits an exact convex relaxation. We illustrate our findings with a case study using the SCE 47-bus network and several special cases that allow for explicit computations.

Original language	English
Article number	8709819
Pages (from-to)	1050-1061
Number of pages	12
Journal	IEEE Transactions on Control of Network Systems
Volume	6
Issue number	3
DOIs	https://doi.org/10.1109/TCNS.2019.2915651
Publication status	Published - Sept 2019

Funding

Manuscript received January 16, 2019; accepted April 21, 2019. Date of publication May 8, 2019; date of current version September 17, 2019. The work of Angelos Aveklouris was funded by a TOP grant of the Netherlands Organization for Scientific Research (NWO) through project 613.001.301. The work of Maria Vlasiou was supported by the NWO MEERVOUD under grant 632.003.002. The work of Bert Zwart was in part supported by the NWO VICI under grant 639.033.413. Recommended by Associate Editors M. Chertkov and M. R. Jovanovic. (Corresponding author: Angelos Aveklouris.) A. Aveklouris and M. Vlasiou are with the Eindhoven University of Technology, the Netherlands (e-mail:, [email protected]; [email protected]).

Keywords

AC power flow model
distribution network
electric vehicle charging
fluid approximation
linearized Distflow
queueing theory
stochastic processes

Access to Document

10.1109/TCNS.2019.2915651

Cite this

@article{4a4cce7b13334db59de1e402a0347f43,

title = "A stochastic resource-sharing network for electric vehicle charging",

abstract = "We consider a distribution grid used to charge electric vehicles (EVs) such that voltage drops stay bounded. We model this as a class of resource-sharing networks, known as bandwidth-sharing networks in the communication network literature. We focus on resource-sharing networks that are driven by a class of greedy control rules that can be implemented in a decentralized fashion. For a large number of such control rules, we can characterize the performance of the system by a fluid approximation. This leads to a set of dynamic equations that take into account the stochastic behavior of EVs. We show that the invariant point of these equations is unique and can be computed by solving a specific AC optimal-power-flow problem (ACOPF), which admits an exact convex relaxation. We illustrate our findings with a case study using the SCE 47-bus network and several special cases that allow for explicit computations.",

keywords = "AC power flow model, distribution network, electric vehicle charging, fluid approximation, linearized Distflow, queueing theory, stochastic processes",

author = "Angelos Aveklouris and Maria Vlasiou and Bert Zwart",

year = "2019",

month = sep,

doi = "10.1109/TCNS.2019.2915651",

language = "English",

volume = "6",

pages = "1050--1061",

journal = "IEEE Transactions on Control of Network Systems",

issn = "2325-5870",

publisher = "IEEE Control Systems Society",

number = "3",

}

TY - JOUR

T1 - A stochastic resource-sharing network for electric vehicle charging

AU - Aveklouris, Angelos

AU - Vlasiou, Maria

AU - Zwart, Bert

PY - 2019/9

Y1 - 2019/9

N2 - We consider a distribution grid used to charge electric vehicles (EVs) such that voltage drops stay bounded. We model this as a class of resource-sharing networks, known as bandwidth-sharing networks in the communication network literature. We focus on resource-sharing networks that are driven by a class of greedy control rules that can be implemented in a decentralized fashion. For a large number of such control rules, we can characterize the performance of the system by a fluid approximation. This leads to a set of dynamic equations that take into account the stochastic behavior of EVs. We show that the invariant point of these equations is unique and can be computed by solving a specific AC optimal-power-flow problem (ACOPF), which admits an exact convex relaxation. We illustrate our findings with a case study using the SCE 47-bus network and several special cases that allow for explicit computations.

AB - We consider a distribution grid used to charge electric vehicles (EVs) such that voltage drops stay bounded. We model this as a class of resource-sharing networks, known as bandwidth-sharing networks in the communication network literature. We focus on resource-sharing networks that are driven by a class of greedy control rules that can be implemented in a decentralized fashion. For a large number of such control rules, we can characterize the performance of the system by a fluid approximation. This leads to a set of dynamic equations that take into account the stochastic behavior of EVs. We show that the invariant point of these equations is unique and can be computed by solving a specific AC optimal-power-flow problem (ACOPF), which admits an exact convex relaxation. We illustrate our findings with a case study using the SCE 47-bus network and several special cases that allow for explicit computations.

KW - AC power flow model

KW - distribution network

KW - electric vehicle charging

KW - fluid approximation

KW - linearized Distflow

KW - queueing theory

KW - stochastic processes

UR - http://www.scopus.com/inward/record.url?scp=85073490981&partnerID=8YFLogxK

U2 - 10.1109/TCNS.2019.2915651

DO - 10.1109/TCNS.2019.2915651

M3 - Article

SN - 2325-5870

VL - 6

SP - 1050

EP - 1061

JO - IEEE Transactions on Control of Network Systems

JF - IEEE Transactions on Control of Network Systems

IS - 3

M1 - 8709819

ER -

A stochastic resource-sharing network for electric vehicle charging

Abstract

Funding

Keywords

Access to Document

Other files and links

Fingerprint

Stochactic processes on interacting networks

Cite this

A stochastic resource-sharing network for electric vehicle charging

Abstract

Funding

Keywords

Access to Document

Other files and links

Fingerprint

Research areas

Stochactic processes on interacting networks

Cite this