Charging scheduling of enterprise private parking-lot with renewable power: A simulation method based on markov decision processes

Fangzhu Ming; Feng Gao; Kun Liu; Zelin Nie

doi:10.23919/ChiCC.2019.8866289

Charging scheduling of enterprise private parking-lot with renewable power: A simulation method based on markov decision processes

Fangzhu Ming
, Feng Gao
, Kun Liu
, Zelin Nie

Faculty of Electronic and Information Engineering

Xi'an Jiaotong University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

With the development of renewable energy and electric vehicles (EVs), using renewable energy charging for EVs becomes an effective way to reduce environment pollution. In this paper, we study a charging scheduling problem in the enterprise private parking-lot considering the uncertainties of renewable energy and charging demand of EVs. In this model, the stochastic multistage decision problem is described as Markov decision processes (MDPs). In addition, a simulation-based dynamic programming (SBDP) method is proposed to get the optimal strategy and expected cost of purchasing electricity from the power grid. Finally, a real case study is analyzed. The results show that the method is applicable to various scale of EVs well and the cost of electricity purchasing has been reduced in the range of 9% and 47% depending on the scale of charging piles.

Original language	English
Title of host publication	Proceedings of the 38th Chinese Control Conference, CCC 2019
Editors	Minyue Fu, Jian Sun
Publisher	IEEE Computer Society
Pages	2254-2259
Number of pages	6
ISBN (Electronic)	9789881563972
DOIs	https://doi.org/10.23919/ChiCC.2019.8866289
State	Published - Jul 2019
Event	38th Chinese Control Conference, CCC 2019 - Guangzhou, China Duration: 27 Jul 2019 → 30 Jul 2019

Publication series

Name	Chinese Control Conference, CCC
Volume	2019-July
ISSN (Print)	1934-1768
ISSN (Electronic)	2161-2927

Conference

Conference	38th Chinese Control Conference, CCC 2019
Country/Territory	China
City	Guangzhou
Period	27/07/19 → 30/07/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Charging scheduling
Markov Decision Processes
Simulation-based dynamic programming
Stochastic optimization

Access to Document

10.23919/ChiCC.2019.8866289

Cite this

Ming, F., Gao, F., Liu, K., & Nie, Z. (2019). Charging scheduling of enterprise private parking-lot with renewable power: A simulation method based on markov decision processes. In M. Fu, & J. Sun (Eds.), Proceedings of the 38th Chinese Control Conference, CCC 2019 (pp. 2254-2259). Article 8866289 (Chinese Control Conference, CCC; Vol. 2019-July). IEEE Computer Society. https://doi.org/10.23919/ChiCC.2019.8866289

@inproceedings{26e524724ccb4ddf81336b1488251eaf,

title = "Charging scheduling of enterprise private parking-lot with renewable power: A simulation method based on markov decision processes",

abstract = "With the development of renewable energy and electric vehicles (EVs), using renewable energy charging for EVs becomes an effective way to reduce environment pollution. In this paper, we study a charging scheduling problem in the enterprise private parking-lot considering the uncertainties of renewable energy and charging demand of EVs. In this model, the stochastic multistage decision problem is described as Markov decision processes (MDPs). In addition, a simulation-based dynamic programming (SBDP) method is proposed to get the optimal strategy and expected cost of purchasing electricity from the power grid. Finally, a real case study is analyzed. The results show that the method is applicable to various scale of EVs well and the cost of electricity purchasing has been reduced in the range of 9\% and 47\% depending on the scale of charging piles.",

keywords = "Charging scheduling, Markov Decision Processes, Simulation-based dynamic programming, Stochastic optimization",

author = "Fangzhu Ming and Feng Gao and Kun Liu and Zelin Nie",

note = "Publisher Copyright: {\textcopyright} 2019 Technical Committee on Control Theory, Chinese Association of Automation.; 38th Chinese Control Conference, CCC 2019 ; Conference date: 27-07-2019 Through 30-07-2019",

year = "2019",

month = jul,

doi = "10.23919/ChiCC.2019.8866289",

language = "英语",

series = "Chinese Control Conference, CCC",

publisher = "IEEE Computer Society",

pages = "2254--2259",

editor = "Minyue Fu and Jian Sun",

booktitle = "Proceedings of the 38th Chinese Control Conference, CCC 2019",

}

Ming, F, Gao, F, Liu, K & Nie, Z 2019, Charging scheduling of enterprise private parking-lot with renewable power: A simulation method based on markov decision processes. in M Fu & J Sun (eds), Proceedings of the 38th Chinese Control Conference, CCC 2019., 8866289, Chinese Control Conference, CCC, vol. 2019-July, IEEE Computer Society, pp. 2254-2259, 38th Chinese Control Conference, CCC 2019, Guangzhou, China, 27/07/19. https://doi.org/10.23919/ChiCC.2019.8866289

Charging scheduling of enterprise private parking-lot with renewable power: A simulation method based on markov decision processes. / Ming, Fangzhu; Gao, Feng; Liu, Kun et al.
Proceedings of the 38th Chinese Control Conference, CCC 2019. ed. / Minyue Fu; Jian Sun. IEEE Computer Society, 2019. p. 2254-2259 8866289 (Chinese Control Conference, CCC; Vol. 2019-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Charging scheduling of enterprise private parking-lot with renewable power

T2 - 38th Chinese Control Conference, CCC 2019

AU - Ming, Fangzhu

AU - Gao, Feng

AU - Liu, Kun

AU - Nie, Zelin

PY - 2019/7

Y1 - 2019/7

N2 - With the development of renewable energy and electric vehicles (EVs), using renewable energy charging for EVs becomes an effective way to reduce environment pollution. In this paper, we study a charging scheduling problem in the enterprise private parking-lot considering the uncertainties of renewable energy and charging demand of EVs. In this model, the stochastic multistage decision problem is described as Markov decision processes (MDPs). In addition, a simulation-based dynamic programming (SBDP) method is proposed to get the optimal strategy and expected cost of purchasing electricity from the power grid. Finally, a real case study is analyzed. The results show that the method is applicable to various scale of EVs well and the cost of electricity purchasing has been reduced in the range of 9% and 47% depending on the scale of charging piles.

AB - With the development of renewable energy and electric vehicles (EVs), using renewable energy charging for EVs becomes an effective way to reduce environment pollution. In this paper, we study a charging scheduling problem in the enterprise private parking-lot considering the uncertainties of renewable energy and charging demand of EVs. In this model, the stochastic multistage decision problem is described as Markov decision processes (MDPs). In addition, a simulation-based dynamic programming (SBDP) method is proposed to get the optimal strategy and expected cost of purchasing electricity from the power grid. Finally, a real case study is analyzed. The results show that the method is applicable to various scale of EVs well and the cost of electricity purchasing has been reduced in the range of 9% and 47% depending on the scale of charging piles.

KW - Charging scheduling

KW - Markov Decision Processes

KW - Simulation-based dynamic programming

KW - Stochastic optimization

UR - https://www.scopus.com/pages/publications/85074429010

U2 - 10.23919/ChiCC.2019.8866289

DO - 10.23919/ChiCC.2019.8866289

M3 - 会议稿件

AN - SCOPUS:85074429010

T3 - Chinese Control Conference, CCC

SP - 2254

EP - 2259

BT - Proceedings of the 38th Chinese Control Conference, CCC 2019

A2 - Fu, Minyue

A2 - Sun, Jian

PB - IEEE Computer Society

Y2 - 27 July 2019 through 30 July 2019

ER -

Charging scheduling of enterprise private parking-lot with renewable power: A simulation method based on markov decision processes

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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