Study on CO2 Emission Constraint Based on New Energy Materials for Generation Permits Trade

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Abstract:

Generation permits trade plays a key role in the economic generation dispatch. The application of new energy materials has a positive influence on the generation fuel mix, which offers cleaner power option for generation permits trade. An optimization model on generation permits trade is established to promote the development of renewable energy and the lowest generation cost of a certain unit commitment. Power demand, ramp-up limit, real power of a unit, new energy materials, and a certain emission limit are applied as the constraints of the model. The process of generation permits trade is a cooperative game. An optimized profit allocation model is also established using Shapley value to effectively allocate the profits among the units participating in the generation permits trade.

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22-26

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October 2012

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] Tan Zhongfu, Chen Guangjuan, Zhao Jianbao, et al. Optimization model for designing peak-valley time-of-use power price of generation side and sale side at the direction of energy conservation dispatch[J]. Proceedings of the CSEE, 2009, 29(1): 55-60.

Google Scholar

[2] Abido M A. Environmental/economic power dispatch using multi-objective evolutionary algorithms[J]. IEEE Transactions on Power Systems, 2003, 18(4): 1529-1536.

DOI: 10.1109/tpwrs.2003.818693

Google Scholar

[3] Yu Jie, Li Yang, Xia Anbang. Distributed optimization of generation dispatch schedule considering environmental protection and economic profits[J]. Proceedings of the CSEE, 2009, 29(16): 63-68.

Google Scholar

[4] Peng Chunhua. Economic operation problem of generating side considering environmental protection and bidding risk[J]. Proceedings of the CSEE, 2008, 28(28): 97-102.

Google Scholar

[5] Tan Zhongfu, Li Li, Wang Jianjun, et al. A fuzzy bayesian learning model in agent-based electric power bilateral negotiation[J]. Proceedings of the CSEE, 2009, 29(7): 106-113.

Google Scholar

[6] Gao Ci-wei, LI Yang. Evolution of China's power dispatch principle and the new energy-saving power dispatch policy [J]. Energy Policy, 2010, 38(11): 7346-7357.

DOI: 10.1016/j.enpol.2010.08.011

Google Scholar

[7] Guiyin Fang, Hui Li, Zhi Chen, et. al. Preparation and properties of palmitic acid/SiO2 composites with flame retardant as thermal energy storage materials[J]. Solar Energy Materials and Solar Cells, 2011, 95 (7): 1875-1881.

DOI: 10.1016/j.solmat.2011.02.010

Google Scholar

[8] David Driver. Making a material difference in energy[J]. Energy Policy, 2008, 36(12): 4302-4309.

DOI: 10.1016/j.enpol.2008.09.061

Google Scholar

[9] Francis Agyenim, Neil Hewitt, Philip Eames, et. al. A review of materials, heat transfer and phase change problem formulation for latent heat thermal energy storage systems [J]. Renewable and Sustainable Energy Reviews, 2010, 14(2): 615-628.

DOI: 10.1016/j.rser.2009.10.015

Google Scholar