为什么我们必须超越LCOE进行可再生能源设计

IF 13 Q1 ENERGY & FUELS
Eric Loth , Chris Qin , Juliet G. Simpson , Katherine Dykes
{"title":"为什么我们必须超越LCOE进行可再生能源设计","authors":"Eric Loth ,&nbsp;Chris Qin ,&nbsp;Juliet G. Simpson ,&nbsp;Katherine Dykes","doi":"10.1016/j.adapen.2022.100112","DOIUrl":null,"url":null,"abstract":"<div><p>The inherent intermittency of wind and solar energy challenges the relevance of Levelized Cost of Energy (LCOE) for their future design since LCOE neglects the time-varying price of electricity. The Cost of Valued Energy (COVE) is an improved valuation metric that takes into account time-dependent electricity prices. In particular, it integrates short-term (e.g., hourly) wind and solar energy “generation devaluation”, whereby high wind and/or solar energy generation can lead to low, and even negative, energy prices for grids with high renewable penetration. These aspects are demonstrated and quantified with examples of two large grids with high renewable shares using three approaches to model hourly price: (1) residual demand, (2) wind and solar generation, and (3) statistical price-generation correlation. All three approaches indicate significant generation devaluation. The residual demand approach provides the most accurate price information while statistical correlations show that generation devaluation is most pronounced for the Variable Renewable Energy (VRE) that dominates market share (e.g., solar for California and wind for Germany). In some cases, the cost of valued energy relative to levelized cost can be 43% higher for solar (CAISO) and 129% higher for wind (ERCOT). This indicates that COVE is a much more relevant metric than LCOE in such markets. This is because COVE is based on the annualized system costs relative to the annualized spot market revenue, and thus considers economic effects of costs vs. revenue as well as those of supply vs. demand. As such, COVE (instead of LCOE) is recommended to design and value next-generation renewable energy systems, including storage integration tradeoffs. However, more work is needed to develop generation devaluation models for projected grids and markets and to better classify grid characteristics as we head to a carbon-neutral energy future.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"8 ","pages":"Article 100112"},"PeriodicalIF":13.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792422000300/pdfft?md5=e6a6b7b159c443be41621352048b710e&pid=1-s2.0-S2666792422000300-main.pdf","citationCount":"16","resultStr":"{\"title\":\"Why we must move beyond LCOE for renewable energy design\",\"authors\":\"Eric Loth ,&nbsp;Chris Qin ,&nbsp;Juliet G. Simpson ,&nbsp;Katherine Dykes\",\"doi\":\"10.1016/j.adapen.2022.100112\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The inherent intermittency of wind and solar energy challenges the relevance of Levelized Cost of Energy (LCOE) for their future design since LCOE neglects the time-varying price of electricity. The Cost of Valued Energy (COVE) is an improved valuation metric that takes into account time-dependent electricity prices. In particular, it integrates short-term (e.g., hourly) wind and solar energy “generation devaluation”, whereby high wind and/or solar energy generation can lead to low, and even negative, energy prices for grids with high renewable penetration. These aspects are demonstrated and quantified with examples of two large grids with high renewable shares using three approaches to model hourly price: (1) residual demand, (2) wind and solar generation, and (3) statistical price-generation correlation. All three approaches indicate significant generation devaluation. The residual demand approach provides the most accurate price information while statistical correlations show that generation devaluation is most pronounced for the Variable Renewable Energy (VRE) that dominates market share (e.g., solar for California and wind for Germany). In some cases, the cost of valued energy relative to levelized cost can be 43% higher for solar (CAISO) and 129% higher for wind (ERCOT). This indicates that COVE is a much more relevant metric than LCOE in such markets. This is because COVE is based on the annualized system costs relative to the annualized spot market revenue, and thus considers economic effects of costs vs. revenue as well as those of supply vs. demand. As such, COVE (instead of LCOE) is recommended to design and value next-generation renewable energy systems, including storage integration tradeoffs. However, more work is needed to develop generation devaluation models for projected grids and markets and to better classify grid characteristics as we head to a carbon-neutral energy future.</p></div>\",\"PeriodicalId\":34615,\"journal\":{\"name\":\"Advances in Applied Energy\",\"volume\":\"8 \",\"pages\":\"Article 100112\"},\"PeriodicalIF\":13.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2666792422000300/pdfft?md5=e6a6b7b159c443be41621352048b710e&pid=1-s2.0-S2666792422000300-main.pdf\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Applied Energy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666792422000300\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Applied Energy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666792422000300","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 16

摘要

风能和太阳能固有的间歇性挑战了能源平准化成本(LCOE)与未来设计的相关性,因为LCOE忽略了电力的时变价格。有价值能源成本(COVE)是一种改进的评估指标,它考虑了与时间相关的电价。特别是,它将短期(例如,每小时)风能和太阳能“发电贬值”结合起来,因此,风能和/或太阳能的高发电量可以导致可再生能源渗透率高的电网的能源价格较低,甚至为负。这些方面通过两个具有高可再生能源份额的大型电网的例子进行了演示和量化,使用三种方法来模拟小时价格:(1)剩余需求,(2)风能和太阳能发电,以及(3)统计价格-发电相关性。所有这三种方法都表明了显著的代际贬值。剩余需求方法提供了最准确的价格信息,而统计相关性显示,占市场份额的可变可再生能源(VRE)的发电贬值最为明显(例如,加州的太阳能和德国的风能)。在某些情况下,太阳能(CAISO)和风能(ERCOT)的价值能源成本相对于平准化成本可能高出43%和129%。这表明在这样的市场中,COVE是一个比LCOE更相关的指标。这是因为COVE是基于年化系统成本相对于年化现货市场收入,因此考虑了成本与收入的经济影响,以及供应与需求的经济影响。因此,COVE(而不是LCOE)被推荐用于设计和评估下一代可再生能源系统,包括存储集成权衡。然而,在我们迈向碳中和能源未来的过程中,需要做更多的工作来为预计的电网和市场开发发电量贬值模型,并更好地对电网特征进行分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Why we must move beyond LCOE for renewable energy design

Why we must move beyond LCOE for renewable energy design

The inherent intermittency of wind and solar energy challenges the relevance of Levelized Cost of Energy (LCOE) for their future design since LCOE neglects the time-varying price of electricity. The Cost of Valued Energy (COVE) is an improved valuation metric that takes into account time-dependent electricity prices. In particular, it integrates short-term (e.g., hourly) wind and solar energy “generation devaluation”, whereby high wind and/or solar energy generation can lead to low, and even negative, energy prices for grids with high renewable penetration. These aspects are demonstrated and quantified with examples of two large grids with high renewable shares using three approaches to model hourly price: (1) residual demand, (2) wind and solar generation, and (3) statistical price-generation correlation. All three approaches indicate significant generation devaluation. The residual demand approach provides the most accurate price information while statistical correlations show that generation devaluation is most pronounced for the Variable Renewable Energy (VRE) that dominates market share (e.g., solar for California and wind for Germany). In some cases, the cost of valued energy relative to levelized cost can be 43% higher for solar (CAISO) and 129% higher for wind (ERCOT). This indicates that COVE is a much more relevant metric than LCOE in such markets. This is because COVE is based on the annualized system costs relative to the annualized spot market revenue, and thus considers economic effects of costs vs. revenue as well as those of supply vs. demand. As such, COVE (instead of LCOE) is recommended to design and value next-generation renewable energy systems, including storage integration tradeoffs. However, more work is needed to develop generation devaluation models for projected grids and markets and to better classify grid characteristics as we head to a carbon-neutral energy future.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Advances in Applied Energy
Advances in Applied Energy Energy-General Energy
CiteScore
23.90
自引率
0.00%
发文量
36
审稿时长
21 days
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信