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Author:

Yan, Yamin (Yan, Yamin.) | Shang, Wen-Long (Shang, Wen-Long.) | Yan, Jie (Yan, Jie.) | Liao, Qi (Liao, Qi.) | Wang, Bohong (Wang, Bohong.) | Song, Houbing (Song, Houbing.) | Liu, Yongqian (Liu, Yongqian.)

Indexed by:

EI Scopus SCIE

Abstract:

Building a new power system with renewable energy as the main body is the only way to solve the problem of global climate change and achieve the dual carbon goal. However, the increasing penetration rate of renewable energy and large-scale electric vehicles have brought great challenges to the safe and reliable operation of traditional power system, resulting in the inability to effectively meet the enormous urban electricity demand in real time. In response, this paper proposes to adopt mobilized and distributed batteries and establishes a two -stage logistic and scheduling optimization model, thereby realizing the power transportation between renew-able energy power plants and cities. The first stage model aims to optimize the battery transportation and lo-gistics scheme with minimizing the total battery procurement and transportation cost as the objective function, considering various constraints including railway transport capacity limitation, battery supply and demand balance, and other technologies. The second stage model aims to maximize the peak shaving effect of urban power system and optimize the railway departure time with mobile batteries, considering the train operation, battery supply limitation, and battery transportation balance constraints. Finally, a quantitative economic evaluation of six cities (Heilongjiang, Gansu, Fujian, Shanghai, Jilin, and Liaoning) in China is presented, and the results indicate that the average levelized cost of electricity is as low as 0.052 $/kWh, illustrating the great technical and economic performance of battery logistics and scheduling. In addition, the impact of various sensitive factors on the economic performance of the urban energy system is implemented.

Keyword:

Urban energy system Two -stage model Logistic and scheduling optimization Mobilized and distributed battery

Author Community:

  • [ 1 ] [Yan, Yamin]North China Elect Power Univ, Sch Renewable Energy, State Key Lab Alternate Elect Power Syst Renewable, Beijing 102206, Peoples R China
  • [ 2 ] [Yan, Jie]North China Elect Power Univ, Sch Renewable Energy, State Key Lab Alternate Elect Power Syst Renewable, Beijing 102206, Peoples R China
  • [ 3 ] [Liu, Yongqian]North China Elect Power Univ, Sch Renewable Energy, State Key Lab Alternate Elect Power Syst Renewable, Beijing 102206, Peoples R China
  • [ 4 ] [Shang, Wen-Long]Beijing Univ Technol, Coll Metropolitan Transportat, Beijing Key Lab Traff Engn, Beijing 100124, Peoples R China
  • [ 5 ] [Liao, Qi]China Univ Petr, Beijing Key Lab Urban Oil & Gas Distribut Technol, Fuxue Rd 18, Beijing 102249, Peoples R China
  • [ 6 ] [Wang, Bohong]Zhejiang Ocean Univ, Natl & Local Joint Engn Res Ctr Harbor Oil & Gas S, Zhejiang Key Lab Petrochem Environm Pollut Control, 1 Haida South Rd, Zhoushan 316022, Peoples R China
  • [ 7 ] [Song, Houbing]Embry Riddle Aeronaut Univ, Secur & Optimizat Networked Globe Lab SONG Lab, Daytona Beach, FL 32114 USA
  • [ 8 ] [Shang, Wen-Long]Beijing Jiaotong Univ, Sch Traff & Transportat, Beijing, Peoples R China
  • [ 9 ] [Shang, Wen-Long]Imperial Coll London, Ctr Transport Studies, London, England

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Source :

RESOURCES CONSERVATION AND RECYCLING

ISSN: 0921-3449

Year: 2022

Volume: 187

1 3 . 2

JCR@2022

1 3 . 2 0 0

JCR@2022

ESI Discipline: ENVIRONMENT/ECOLOGY;

ESI HC Threshold:47

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count: 16

SCOPUS Cited Count: 18

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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