A low-carbon oriented probabilistic approach for transmission expansion planning

Jing Qiu; Zhaoyang Dong; Junhua Zhao; Ke Meng; Fengji Luo; Kit Po Wong; Chao Lu

doi:10.1007/s40565-015-0105-3

A low-carbon oriented probabilistic approach for transmission expansion planning

Jing Qiu
, Zhaoyang Dong^*
, Junhua Zhao
, Ke Meng
, Fengji Luo
, Kit Po Wong
, Chao Lu

^*Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

22 Citations (Scopus)

18 Downloads (CityUHK Scholars)

Abstract

Following the deregulation of the power industry, transmission expansion planning (TEP) has become more complicated due to the presence of uncertainties and conflicting objectives in a market environment. Also, the growing concern on global warming highlights the importance of considering carbon pricing policies during TEP. In this paper, a probabilistic TEP approach is proposed with the integration of a chance constrained load curtailment index. The formulated dynamic programming problem is solved by a hybrid solution algorithm in an iterative process. The performance of our approach is demonstrated by case studies on a modified IEEE 14-bus system. Simulation results prove that our approach can provide network planners with comprehensive information regarding effects of uncertainties on TEP schemes, allowing them to adjust planning strategies based on their risk aversion levels or financial constraints. © 2015, The Author(s).

Original language	English
Pages (from-to)	14-23
Journal	Journal of Modern Power Systems and Clean Energy
Volume	3
Issue number	1
DOIs	https://doi.org/10.1007/s40565-015-0105-3
Publication status	Published - 1 Jan 2015
Externally published	Yes

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

UN SDGs

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

SDG 13 Climate Action

Research Keywords

Dynamic programming
Emission reduction
Power system planning
Risk management

Publisher's Copyright Statement

This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

Access Output

10.1007/s40565-015-0105-3

191680965.pdfFinal Published version, 940 KBLicence: CC BY

Other Access Options

Check CityUHK Library

Permanent Link

Right click to copy link

Cite this

@article{d823b775cb714d02a2ebc648fbe5a29e,

title = "A low-carbon oriented probabilistic approach for transmission expansion planning",

abstract = "Following the deregulation of the power industry, transmission expansion planning (TEP) has become more complicated due to the presence of uncertainties and conflicting objectives in a market environment. Also, the growing concern on global warming highlights the importance of considering carbon pricing policies during TEP. In this paper, a probabilistic TEP approach is proposed with the integration of a chance constrained load curtailment index. The formulated dynamic programming problem is solved by a hybrid solution algorithm in an iterative process. The performance of our approach is demonstrated by case studies on a modified IEEE 14-bus system. Simulation results prove that our approach can provide network planners with comprehensive information regarding effects of uncertainties on TEP schemes, allowing them to adjust planning strategies based on their risk aversion levels or financial constraints. {\textcopyright} 2015, The Author(s).",

keywords = "Dynamic programming, Emission reduction, Power system planning, Risk management",

author = "Jing Qiu and Zhaoyang Dong and Junhua Zhao and Ke Meng and Fengji Luo and Wong, \{Kit Po\} and Chao Lu",

note = "Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].",

year = "2015",

month = jan,

day = "1",

doi = "10.1007/s40565-015-0105-3",

language = "English",

volume = "3",

pages = "14--23",

journal = "Journal of Modern Power Systems and Clean Energy",

issn = "2196-5625",

publisher = "State Grid Electric Power Research Institute Nanjing Branch",

number = "1",

}

TY - JOUR

T1 - A low-carbon oriented probabilistic approach for transmission expansion planning

AU - Qiu, Jing

AU - Dong, Zhaoyang

AU - Zhao, Junhua

AU - Meng, Ke

AU - Luo, Fengji

AU - Wong, Kit Po

AU - Lu, Chao

N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

PY - 2015/1/1

Y1 - 2015/1/1

N2 - Following the deregulation of the power industry, transmission expansion planning (TEP) has become more complicated due to the presence of uncertainties and conflicting objectives in a market environment. Also, the growing concern on global warming highlights the importance of considering carbon pricing policies during TEP. In this paper, a probabilistic TEP approach is proposed with the integration of a chance constrained load curtailment index. The formulated dynamic programming problem is solved by a hybrid solution algorithm in an iterative process. The performance of our approach is demonstrated by case studies on a modified IEEE 14-bus system. Simulation results prove that our approach can provide network planners with comprehensive information regarding effects of uncertainties on TEP schemes, allowing them to adjust planning strategies based on their risk aversion levels or financial constraints. © 2015, The Author(s).

AB - Following the deregulation of the power industry, transmission expansion planning (TEP) has become more complicated due to the presence of uncertainties and conflicting objectives in a market environment. Also, the growing concern on global warming highlights the importance of considering carbon pricing policies during TEP. In this paper, a probabilistic TEP approach is proposed with the integration of a chance constrained load curtailment index. The formulated dynamic programming problem is solved by a hybrid solution algorithm in an iterative process. The performance of our approach is demonstrated by case studies on a modified IEEE 14-bus system. Simulation results prove that our approach can provide network planners with comprehensive information regarding effects of uncertainties on TEP schemes, allowing them to adjust planning strategies based on their risk aversion levels or financial constraints. © 2015, The Author(s).

KW - Dynamic programming

KW - Emission reduction

KW - Power system planning

KW - Risk management

UR - https://www.scopus.com/pages/publications/84945354819

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84945354819&origin=recordpage

U2 - 10.1007/s40565-015-0105-3

DO - 10.1007/s40565-015-0105-3

M3 - RGC 21 - Publication in refereed journal

SN - 2196-5625

VL - 3

SP - 14

EP - 23

JO - Journal of Modern Power Systems and Clean Energy

JF - Journal of Modern Power Systems and Clean Energy

IS - 1

ER -

A low-carbon oriented probabilistic approach for transmission expansion planning

Abstract

Bibliographical note

UN SDGs

Research Keywords

Publisher's Copyright Statement

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Cite this