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基于低碳激励型出清的跨省区发电权交易双层优化模型 被引量:16

Bi-optimal model for trans-provincial power generation trading based on low-carbon incentive clearing method
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摘要 为打破省间交易壁垒,在经济发展的同时,促进清洁能源在全国范围内的优化配置,建立了基于低碳激励型出清的清洁能源跨省区交易双层优化模型。针对传统出清方式未充分考虑常规能源发电的环境负外部性,文章提出了一种低碳激励型出清方式,并以最大化交易的经济和环境效益为目标构建了交易中心出清模型。模型上层引入碳交易机制,将碳排放外部成本内部化;基于利润最大化建立了各发电商交易竞价决策模型;通过算例仿真,从多个角度验证了所提模型的有效性。研究结果表明,该模型不仅能够调动常规能源发电商的积极性,促进清洁能源发电的大范围消纳,还能够满足各发电主体的利益诉求,实现多方共赢。 In order to break the interprovincial trade barriers and achieve the optimal country-wide configuration of clean energy in the development of economy, a bi-level optimization model for trans-provincial trade of clean energy based on low-carbon incentive is proposed. In the bottom level, a low-carbon incentive clearing method is proposed to overcome the weakness of the traditional clearing method that gives insufficient consideration on the environment negative externality of conventional power. Still in this level, a two-objectives clearing model of the transaction center is built to maximize the economic and environmental benefits of the transaction.In the upper level,the carbon trading mechanism is introduced to internalize the external costs of carbon emissions, meanwhile a bidding model of the two parties is built based on the maximum profit of each generation. Finally, the model is verified from multiple perspectives by numerical simulations of real examples. The results show that the model not only arouse the initiatives of conventional power and promote the wide range utilization of clean energy, but also meet the interest demand of a wide range of power generation entities and realize win-win situations.
作者 王辉 陈波波 廖昆 Wang Hui;Chen Bobo;Liao Kun(College of Economics and Management,Shanghai University of Electric Power,Shanghai 200090,China)
出处 《可再生能源》 CAS 北大核心 2019年第12期1842-1849,共8页 Renewable Energy Resources
基金 国家自然科学基金资助项目(71403163) 教育部人文社会科学研究一般项目(18YJAZH138)
关键词 清洁能源 跨省区交易 碳减排效益 低碳激励型出清 双层优化 clean energy trans-provincial trade benefit of carbon emission reduction low carbon incentive clearing bi-level optimization
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