Optimizing storage capacity in 100 % renewable electricity supply: A GIS-based approach for Italy

IF 5.4 Q2 ENERGY & FUELS
Vittoria Battaglia , Aseed Ur Rehman , Laura Vanoli
{"title":"Optimizing storage capacity in 100 % renewable electricity supply: A GIS-based approach for Italy","authors":"Vittoria Battaglia ,&nbsp;Aseed Ur Rehman ,&nbsp;Laura Vanoli","doi":"10.1016/j.segy.2025.100177","DOIUrl":null,"url":null,"abstract":"<div><div>The sustainability of energy systems relies on the integration of renewable local sources. This study aimed to optimize Italy's electricity supply by leveraging a hybrid PV-wind energy system, employing advanced optimization techniques. The primary goal was pinpointing the minimum storage capacity necessary for Italy's power grid in a scenario completely reliant on PV and wind energy. To achieve this, the potential of both PV and wind energy was evaluated through a GIS-based analysis, while dynamic simulation was used to estimate power generation across regions. The Mixed-integer linear programming algorithm underwent a three-step process: computing the hourly residual load for diverse PV and wind capacity combinations, determining the hourly storage requirements and ultimately identifying the mix with the least storage capacity. Applying Mixed-integer linear programming to Italy's complete PV and wind energy potential revealed a necessity for 33 TWh of storage capacity. To decrease the required storage capacity, two new scenarios were proposed: the island scenario, in which the total annual electricity production from solar and wind energy is equal to the annual electricity demand, and the peak hour scenario, where generation from PV and wind is matched to the consumption in peak hour electric demand. The economic analysis of the proposed scenarios shows that although hydrogen can be used to store enormous amounts of energy, the inefficiencies in the conversion processes make it less cost-effective compared to other technologies. Pumped-hydro storage is the most cost-effective option for energy storage. The results show that the most economically viable scenario is the island scenario with an optimal mix of 16.9 % PV and 83.1 % wind, requiring a storage capacity of 7.04 TWh and a 3.34 trillion euro investment for pump-hydro storage.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"18 ","pages":"Article 100177"},"PeriodicalIF":5.4000,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart Energy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S266695522500005X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0

Abstract

The sustainability of energy systems relies on the integration of renewable local sources. This study aimed to optimize Italy's electricity supply by leveraging a hybrid PV-wind energy system, employing advanced optimization techniques. The primary goal was pinpointing the minimum storage capacity necessary for Italy's power grid in a scenario completely reliant on PV and wind energy. To achieve this, the potential of both PV and wind energy was evaluated through a GIS-based analysis, while dynamic simulation was used to estimate power generation across regions. The Mixed-integer linear programming algorithm underwent a three-step process: computing the hourly residual load for diverse PV and wind capacity combinations, determining the hourly storage requirements and ultimately identifying the mix with the least storage capacity. Applying Mixed-integer linear programming to Italy's complete PV and wind energy potential revealed a necessity for 33 TWh of storage capacity. To decrease the required storage capacity, two new scenarios were proposed: the island scenario, in which the total annual electricity production from solar and wind energy is equal to the annual electricity demand, and the peak hour scenario, where generation from PV and wind is matched to the consumption in peak hour electric demand. The economic analysis of the proposed scenarios shows that although hydrogen can be used to store enormous amounts of energy, the inefficiencies in the conversion processes make it less cost-effective compared to other technologies. Pumped-hydro storage is the most cost-effective option for energy storage. The results show that the most economically viable scenario is the island scenario with an optimal mix of 16.9 % PV and 83.1 % wind, requiring a storage capacity of 7.04 TWh and a 3.34 trillion euro investment for pump-hydro storage.

Abstract Image

在100%可再生电力供应中优化存储容量:意大利基于gis的方法
能源系统的可持续性依赖于当地可再生能源的整合。本研究旨在通过采用先进的优化技术,利用混合光伏-风能系统来优化意大利的电力供应。主要目标是在完全依赖光伏和风能的情况下,确定意大利电网所需的最小存储容量。为了实现这一目标,通过基于gis的分析评估了光伏和风能的潜力,同时使用动态模拟来估计区域间的发电量。混合整数线性规划算法经历了三个步骤:计算不同光伏和风能容量组合的每小时剩余负荷,确定每小时存储需求,最终确定存储容量最小的组合。将混合整数线性规划应用于意大利完整的光伏和风能潜力,发现需要33太瓦时的存储容量。为了减少所需的存储容量,提出了两种新的情景:孤岛情景,其中太阳能和风能的年总发电量等于年电力需求;高峰时段情景,其中光伏和风能的发电量与高峰时段电力需求的消费量相匹配。对提议方案的经济分析表明,尽管氢可以用来储存大量的能量,但与其他技术相比,转换过程中的低效率使其成本效益较低。抽水蓄能是能源储存最具成本效益的选择。结果表明,经济上最可行的方案是岛屿方案,其最佳组合为16.9%的光伏和83.1%的风能,需要7.04太瓦时的存储容量和3.34万亿欧元的抽水蓄能投资。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Smart Energy
Smart Energy Engineering-Mechanical Engineering
CiteScore
9.20
自引率
0.00%
发文量
29
审稿时长
73 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