Optimal decision making model for GENCO under the Emission Trading Scheme

X. R. Li; C. W. Yu; F. J. Luo; S. R. Ren; Z. Y. Dong; Y. Wu; K. Meng; K. P. Wong; Y. Xu

doi:10.1109/PESGM.2012.6345267

Optimal decision making model for GENCO under the Emission Trading Scheme

X. R. Li, C. W. Yu, F. J. Luo, S. R. Ren, Z. Y. Dong, Y. Wu, K. Meng, K. P. Wong, Y. Xu

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

2 Citations (Scopus)

Abstract

Emission Trading Schemes(ETS) has been implemented in electricity industrial activities. A large number of existing and potential GENCO are subject to ETS and targeted for emission reduction. A dynamic decision making model is proposed to deal with the multimarket trading problem for GENCO. During each trading period, the operation of GENCO is divided into production process and trading process. These two processes are considered dynamic and stochastic so that the results of decision making are given process by process for each planning period. To solve the multi-period stochastic optimization problem, Differential Evolution(DE) algorithm is adopted to give the results of each period. Comparisons between different scenarios show that the proposed model can provide good tradeoff between profit-making and emission reduction. © 2012 IEEE.

Original language	English
Title of host publication	2012 IEEE Power and Energy Society General Meeting, PES 2012
DOIs	https://doi.org/10.1109/PESGM.2012.6345267
Publication status	Published - 2012
Externally published	Yes
Event	2012 IEEE Power and Energy Society General Meeting, PES 2012 - San Diego, CA, United States Duration: 22 Jul 2012 → 26 Jul 2012

Publication series

Name	IEEE Power and Energy Society General Meeting
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2012 IEEE Power and Energy Society General Meeting, PES 2012
Place	United States
City	San Diego, CA
Period	22/07/12 → 26/07/12

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 9 Industry, Innovation, and Infrastructure
SDG 13 Climate Action

Research Keywords

Carbon Market
Differential Evolution(DE)
Electricity market
Emission Trading Schemes (ETS)

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10.1109/PESGM.2012.6345267

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Cite this

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title = "Optimal decision making model for GENCO under the Emission Trading Scheme",

abstract = "Emission Trading Schemes(ETS) has been implemented in electricity industrial activities. A large number of existing and potential GENCO are subject to ETS and targeted for emission reduction. A dynamic decision making model is proposed to deal with the multimarket trading problem for GENCO. During each trading period, the operation of GENCO is divided into production process and trading process. These two processes are considered dynamic and stochastic so that the results of decision making are given process by process for each planning period. To solve the multi-period stochastic optimization problem, Differential Evolution(DE) algorithm is adopted to give the results of each period. Comparisons between different scenarios show that the proposed model can provide good tradeoff between profit-making and emission reduction. {\textcopyright} 2012 IEEE.",

keywords = "Carbon Market, Differential Evolution(DE), Electricity market, Emission Trading Schemes (ETS)",

author = "Li, {X. R.} and Yu, {C. W.} and Luo, {F. J.} and Ren, {S. R.} and Dong, {Z. Y.} and Y. Wu and K. Meng and Wong, {K. P.} and Y. Xu",

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].; 2012 IEEE Power and Energy Society General Meeting, PES 2012 ; Conference date: 22-07-2012 Through 26-07-2012",

year = "2012",

doi = "10.1109/PESGM.2012.6345267",

language = "English",

isbn = "9781467327275",

series = "IEEE Power and Energy Society General Meeting",

booktitle = "2012 IEEE Power and Energy Society General Meeting, PES 2012",

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Li, XR, Yu, CW, Luo, FJ, Ren, SR, Dong, ZY, Wu, Y, Meng, K, Wong, KP & Xu, Y 2012, Optimal decision making model for GENCO under the Emission Trading Scheme. in 2012 IEEE Power and Energy Society General Meeting, PES 2012., 6345267, IEEE Power and Energy Society General Meeting, 2012 IEEE Power and Energy Society General Meeting, PES 2012, San Diego, CA, United States, 22/07/12. https://doi.org/10.1109/PESGM.2012.6345267

Optimal decision making model for GENCO under the Emission Trading Scheme. / Li, X. R.; Yu, C. W.; Luo, F. J. et al.
2012 IEEE Power and Energy Society General Meeting, PES 2012. 2012. 6345267 (IEEE Power and Energy Society General Meeting).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Optimal decision making model for GENCO under the Emission Trading Scheme

AU - Li, X. R.

AU - Yu, C. W.

AU - Luo, F. J.

AU - Ren, S. R.

AU - Dong, Z. Y.

AU - Wu, Y.

AU - Meng, K.

AU - Wong, K. P.

AU - Xu, Y.

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 - 2012

Y1 - 2012

N2 - Emission Trading Schemes(ETS) has been implemented in electricity industrial activities. A large number of existing and potential GENCO are subject to ETS and targeted for emission reduction. A dynamic decision making model is proposed to deal with the multimarket trading problem for GENCO. During each trading period, the operation of GENCO is divided into production process and trading process. These two processes are considered dynamic and stochastic so that the results of decision making are given process by process for each planning period. To solve the multi-period stochastic optimization problem, Differential Evolution(DE) algorithm is adopted to give the results of each period. Comparisons between different scenarios show that the proposed model can provide good tradeoff between profit-making and emission reduction. © 2012 IEEE.

AB - Emission Trading Schemes(ETS) has been implemented in electricity industrial activities. A large number of existing and potential GENCO are subject to ETS and targeted for emission reduction. A dynamic decision making model is proposed to deal with the multimarket trading problem for GENCO. During each trading period, the operation of GENCO is divided into production process and trading process. These two processes are considered dynamic and stochastic so that the results of decision making are given process by process for each planning period. To solve the multi-period stochastic optimization problem, Differential Evolution(DE) algorithm is adopted to give the results of each period. Comparisons between different scenarios show that the proposed model can provide good tradeoff between profit-making and emission reduction. © 2012 IEEE.

KW - Carbon Market

KW - Differential Evolution(DE)

KW - Electricity market

KW - Emission Trading Schemes (ETS)

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DO - 10.1109/PESGM.2012.6345267

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781467327275

T3 - IEEE Power and Energy Society General Meeting

BT - 2012 IEEE Power and Energy Society General Meeting, PES 2012

T2 - 2012 IEEE Power and Energy Society General Meeting, PES 2012

Y2 - 22 July 2012 through 26 July 2012

ER -

Optimal decision making model for GENCO under the Emission Trading Scheme

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Research Keywords

Access Output

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