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Quantifying the value of investing in distributed natural gas and renewable electricity systems as complements: Applications of discounted cash flow and real options analysis with stochastic inputs

机译:量化作为补充的分布式天然气和可再生电力系统的投资价值:现金流量折现法和带有随机输入的实物期权分析的应用

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摘要

One energy policy objective in the United States is to promote the adoption of technologies that provide consumers with stable, secure, and clean energy. Recent work provides anecdotal evidence of natural gas (NG) and renewable electricity (RE) synergies in the power sector, however few studies quantify the value of investing in NG and RE systems together as complements. This paper uses discounted cash flow analysis and real options analysis to value hybrid NG-RE systems in distributed applications, focusing on residential and commercial projects assumed to be located in the states of New York and Texas. Technology performance and operational risk profiles are modeled at the hourly level to capture variable RE output and NG prices are modeled stochastically as geometric Ornstein-Uhlenbeck (OU) stochastic processes to capture NG price uncertainty. The findings consistently suggest that NG-RE hybrid distributed systems are more favorable investments in the applications studied relative to their single technology alternatives when incentives for renewables are available. In some cases, NG-only systems are the favorable investments. Understanding the value of investing, in NG-RE hybrid systems provides insights into one avenue towards reducing greenhouse gas emissions, given the important role of NG and RE in the power sector. (C) 2016 Published by Elsevier Ltd.
机译:美国的能源政策目标之一是促进采用能够为消费者提供稳定,安全和清洁能源的技术。最近的工作提供了电力部门天然气(NG)和可再生电力(RE)协同作用的传闻证据,但是很少有研究量化对NG和RE系统的投资作为补充的价值。本文使用折现现金流量分析和实物期权分析来评估分布式应用中的混合NG-RE系统的价值,重点关注假定位于纽约州和德克萨斯州的住宅和商业项目。以小时为单位对技术性能和操作风险状况进行建模,以捕获可变的RE产出,将NG价格随机建模为几何Ornstein-Uhlenbeck(OU)随机过程,以捕获NG价格的不确定性。研究结果始终表明,与NG-RE混合分布式系统相比,在可获得可再生能源激励的情况下,相对于其单一技术替代方案,在所研究的应用中更有利。在某些情况下,纯NG系统是有利的投资。鉴于NG和RE在电力行业中的重要作用,了解NG-RE混合系统投资的价值可为减少温室气体排放的一种途径提供见识。 (C)2016由Elsevier Ltd.出版

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