Inter-Regional Power-Generation Economic Exchange Analysis Model under Environmental Constraints

Abstract:

Article Preview

The rapid development of national economy has brought serious environmental pollution problems. The issue of emission reduction has become one of the most important missions in China. As one of the largest sources of energy consumption and pollution emission, the power generation industry plays an important role in the problem of emission reduction. According to Chinese actual conditions, this study takes into account the inter-regional difference between the tasks of environmental emission reduction and the corresponding costs due to various factors, and proposes an inter-regional power-generation economic exchange analysis model under environmental constraints. The model integrates the environmental constraints, as well as the transmission costs and transmission lines constraints, and provides the results of optimal exchange combinations. The analysis of an example indicates that the inter-regional economic power exchange can maximize inter-regional advantages and minimize the costs of economic dispatch, which requires a sound transmission system and transmission pricing system.

Info:

Periodical:

Advanced Materials Research (Volumes 361-363)

Edited by:

Qunjie Xu, Honghua Ge and Junxi Zhang

Pages:

1510-1523

DOI:

10.4028/www.scientific.net/AMR.361-363.1510

Citation:

Y. S. Shen et al., "Inter-Regional Power-Generation Economic Exchange Analysis Model under Environmental Constraints", Advanced Materials Research, Vols. 361-363, pp. 1510-1523, 2012

Online since:

October 2011

Export:

Price:

$35.00

[1] Lingfeng Wang, Chanan Singh. Reserve-constrained multi-area environmental/economic dispatch based on particle swarm optimization with local search[J]. Engineering Applications of Artificial Intelligence, 2009, 22(2): 298-307.

DOI: 10.1016/j.engappai.2008.07.007

[2] Hanzheng Duo, Hiroshi Sasaki, Takeshi Nagata, Hideki Fujita. A solution for unit commitment using Lagrangian relaxation combined with evolutionary programming[J]. Electric Power Systems Research, 1999, 51(1): 71-77.

DOI: 10.1016/s0378-7796(98)00153-9

[3] Ivo C. Silva Jr., Sandoval Carneiro Jr., Edimar J. de Oliveira, J.L.R. Pereira, Paulo A.N. Garcia, Andre L.M. Marcato. A Lagrangian multiplier based sensitive index to determine the unit commitment of thermal units [J]. International Journal of Electrical Power & Energy Systems, 2008, 30(9): 504-510.

DOI: 10.1016/j.ijepes.2008.04.004

[4] Vo Ngoc Dieu, Weerakorn Ongsakul. Ramp rate constrained unit commitment by improved priority list and augmented Lagrange Hopfield network[J]. Electric Power Systems Research, 2008, 78(3): 291-301.

DOI: 10.1016/j.epsr.2007.02.011

[5] Chung-Li Tseng, Shmuel S. Oren, Carol S. Cheng, Chao-an Li, Alva J. Svoboda, Raymond B. Johnson. A transmission-constrained unit commitment method in power system scheduling[J]. Decision Support Systems, 1999, 24(3-4): 297-310.

DOI: 10.1016/s0167-9236(98)00072-4

[6] V. Senthil Kumar, M.R. Mohan. Solution to security constrained unit commitment problem using genetic algorithm[J]. International Journal of Electrical Power & Energy Systems, Available online 7 July (2009).

DOI: 10.1016/j.ijepes.2009.06.019

[7] S. Jalilzadeh, H. Shayeghi, H. Hadadian. Integrating generation and transmission networks reliability for unit commitment solution[J]. Energy Conversion and Management, 2009, 50(3): 777-785.

DOI: 10.1016/j.enconman.2008.09.027

In order to see related information, you need to Login.