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Optimally Designed Subsidies for Achieving Carbon Emissions Targets in Electric Power Systems

机译:为实现电力系统中的碳排放目标而优化设计的补贴

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One of the major contributors to global warming is the amount of carbon dioxide (CO2) released from burning fossil fuel (primarily coal) as a by-product of the production of electric energy. Imposing carbon taxes to mitigate the emissions from the electricity sector is a well-established method to counteract the detrimental effects of CO2 on the environment. This added tax, however, has a negative impact on the economy and wholesale electricity prices. A fact that is more evident when regulating authorities set higher reduction targets which require a higher tax rate. This paper proposes a framework in which regulating authorities can use the revenue from the levied taxes to subsidize more expensive producers that have lower CO2 emissions, allowing them to be more competitive in the day-ahead energy market. The problem is formulated as a bilevel optimization in which the upper level represents the regulating authority whose objective function is to minimize the total cost of subsidies given to producers and the lower level represents the day-ahead market clearing process. This nonlinear bilevel model is then transformed into a mixed-integer linear programming problem that can be solved using commercial tools. Numerical studies demonstrate that implementing the proposed approach would make it possible to achieve any feasible emissions target at a much lower tax rate.
机译:导致全球变暖的主要因素之一是二氧化碳(CO 2 )从燃烧化石燃料(主要是煤炭)中释放出来,作为电能生产的副产品。征收碳税以减轻电力部门的排放是一种成熟的方法,可以抵消二氧化碳的不利影响 2 在环境上。但是,这种附加税对经济和批发电价具有负面影响。当监管机构设定更高的减排目标并要求更高的税率时,这一事实更加明显。本文提出了一个框架,在该框架中,监管机构可以使用征收的税收来补贴二氧化碳价格较低的价格更高的生产商 2 排放量,使它们在日复一日的能源市场中更具竞争力。该问题被表述为双层优化,其中上级代表监管机构,其目标功能是使提供给生产者的补贴总成本最小化,而下级则代表日前的市场清理过程。然后将此非线性双层模型转换为可以使用商业工具解决的混合整数线性规划问题。数值研究表明,实施建议的方法将有可能以低得多的税率实现任何可行的排放目标。

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