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A Model for Analyzing the Impact of Production Tax Credit on Renewable Electricity Production

机译:生产税收抵免对可再生电力生产影响的分析模型

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This paper provides an optimization model that captures the impact of policies, such as the production tax credit (PTC), on the production of renewable electricity. The paper is focused on using biomass for co-firing in coal-fired power plants. Co-firing is a strategy that can be used to reduce greenhouse gas emissions at coal plants. Co-firing is a practice that impacts logistics-related costs, capital investments, plant efficiency, and tax credit collected. The nonlinear optimization model we develop captures the relationship that exists between biomass usage and the corresponding costs and savings due to production of renewable energy. We test the performance of the model proposed on a case study developed using data from the State of Mississippi. Some of the lessons learned from our numerical analyses are: (a) Tax credits are necessary in order to increase the production of the renewable electricity, (b) Tax credit should not be "one size fits all"; instead, tax credits should be a function of the amount of renewable electricity produced, (c) Biomass availability in the USA differs by region; to optimize renewable energy production, the tax rate/production amount should be customized by region.
机译:本文提供了一个优化模型,该模型可以捕获政策(例如生产税抵免(PTC))对可再生电力生产的影响。该论文的重点是将生物质用于燃煤电厂的联合燃烧。共燃是一种可用于减少燃煤电厂温室气体排放的策略。共燃是一种影响物流相关成本,资本投资,工厂效率和税收抵免的做法。我们开发的非线性优化模型可捕获生物量使用与因可再生能源生产而产生的相应成本和节省之间的关系。我们使用来自密西西比州的数据开发的案例研究测试了该模型的性能。从我们的数值分析中学到的一些教训是:(a)税收抵免是增加可再生电力生产所必需的;(b)税收抵免不应“一刀切”。取而代之的是,税收抵免应该是可再生电力生产量的函数。(c)美国的生物质可利用性因地区而异;为了优化可再生能源的生产,应按地区定制税率/产量。

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