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Tradable Renewable Quota vs. Feed-In Tariff vs. Feed-In Premium under Uncertainty

机译:可交易可再生配额与上网电价相比与不确定性下的上网电价

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摘要

We study the performance under uncertainty of three renewable energy policy instruments: Tradable Renewable Quota (TRQ), Feed-In-Tariff (FIT), and Feed-In-Premium (FIP). We develop a stylized model of the electricity market, where renewables are characterized by a positive learning externality, which the regulator aims to internalize. Assuming shocks on the fossil-based electricity supply, renewables supply, or on total electricity demand, we analytically derive the conditions determining the instruments\u92 relative welfare ranking. Although we generally confirm the key role of the slopes of marginal benefits and costs associated with the policy, the specific ranking depends on which type of uncertainty is considered, and whether shocks are permanent or transitory. However, a high learning rate generally favours the FIT, while TRQ is mostly dominated by the other two instruments. These results are confirmed in a numerical application to the US electricity market, in which the FIP emerges as the most and TRQ as the least robust overall choice.
机译:我们研究了三种可再生能源政策工具在不确定性下的绩效:可交易可再生配额(TRQ),上网电价(FIT)和上网电价(FIP)。我们开发了一个电力市场的程式化模型,其中可再生能源的特征是积极的学习外部性,监管机构旨在内部化。假设对基于化石的电力供应,可再生能源供应或总电力需求造成冲击,我们通过分析得出确定工具相对福利等级的条件。尽管我们通常确认与政策相关的边际收益和成本斜率的关键作用,但具体的排名取决于所考虑的不确定性类型以及冲击是永久性的还是暂时性的。但是,较高的学习率通常有利于FIT,而TRQ主要由其他两种工具主导。这些结果在美国电力市场的数值应用中得到了证实,其中FIP出现最多,而TRQ出现最少的总体选择。

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