FORECASTING ANALYSIS ON ELECTRICITY DEMAND IN THE SPECIAL REGION OF YOGYAKARTA UNDER THE IMPACT OF THE COVID-19 PANDEMIC

Feikal Aprieza, M. K. Ridwan, W. Wilopo
{"title":"FORECASTING ANALYSIS ON ELECTRICITY DEMAND IN THE SPECIAL REGION OF YOGYAKARTA UNDER THE IMPACT OF THE COVID-19 PANDEMIC","authors":"Feikal Aprieza, M. K. Ridwan, W. Wilopo","doi":"10.22146/ajse.v6i1.75149","DOIUrl":null,"url":null,"abstract":"The COVID-19 pandemic as a global pandemic on 2020 has encouraged the Indonesian Government to establish pandemic response policies in many provinces. The policies that had been restricting mobility during the pandemic showed significant impacts in many aspects in the Special Region of Yogyakarta. A shifting pattern in electricity consumption can be seen as the growth of economic sectors in the GDP encountered contraction after the decline of community mobility. Electricity demand forecasting is required to analyze the impact of the COVID-19 pandemic by applying three scenarios, specifically an unlikely pandemic scenario or Business As Usual (BAU), moderate scenario (MOD), and optimistic scenario (OPT). Also, the household, industrial, business, social, and public sectors are analyzed in order to see the shifting pattern in electricity consumption through the scenarios that have been given. Energy modeling is conducted with Low Emission Analysis Platform (LEAP) software to analyze electricity demand forecasting from 2019 to 2030 based on the three scenarios. The results show that the electricity demand in 2030, according to BAU, MOD, and OPT scenarios, in the amount of 5,301.58 GWh, 4,489.11 GWh, and 4,648.12 GWh, respectively. According to the MOD and OPT scenarios, the electricity demands of the household and industrial sectors will increase relative to the BAU scenario. Meanwhile, according to both scenarios, the electricity demands of the business and social sectors will decrease. In the public sector, the MOD scenario shows the decline of electricity demand relative to the BAU scenario, while OPT scenario shows the opposite.","PeriodicalId":280593,"journal":{"name":"ASEAN Journal of Systems Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ASEAN Journal of Systems Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22146/ajse.v6i1.75149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The COVID-19 pandemic as a global pandemic on 2020 has encouraged the Indonesian Government to establish pandemic response policies in many provinces. The policies that had been restricting mobility during the pandemic showed significant impacts in many aspects in the Special Region of Yogyakarta. A shifting pattern in electricity consumption can be seen as the growth of economic sectors in the GDP encountered contraction after the decline of community mobility. Electricity demand forecasting is required to analyze the impact of the COVID-19 pandemic by applying three scenarios, specifically an unlikely pandemic scenario or Business As Usual (BAU), moderate scenario (MOD), and optimistic scenario (OPT). Also, the household, industrial, business, social, and public sectors are analyzed in order to see the shifting pattern in electricity consumption through the scenarios that have been given. Energy modeling is conducted with Low Emission Analysis Platform (LEAP) software to analyze electricity demand forecasting from 2019 to 2030 based on the three scenarios. The results show that the electricity demand in 2030, according to BAU, MOD, and OPT scenarios, in the amount of 5,301.58 GWh, 4,489.11 GWh, and 4,648.12 GWh, respectively. According to the MOD and OPT scenarios, the electricity demands of the household and industrial sectors will increase relative to the BAU scenario. Meanwhile, according to both scenarios, the electricity demands of the business and social sectors will decrease. In the public sector, the MOD scenario shows the decline of electricity demand relative to the BAU scenario, while OPT scenario shows the opposite.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
2019冠状病毒病大流行影响下日惹特殊地区电力需求预测分析
2019冠状病毒病大流行作为2020年的全球大流行,促使印度尼西亚政府在许多省份制定大流行应对政策。在大流行病期间限制流动的政策在日惹特区的许多方面显示出重大影响。电力消费模式的转变可以看作是在社区流动性下降后,经济部门的增长在GDP中遇到了收缩。为了分析新冠肺炎大流行的影响,需要进行电力需求预测,具体应用三种情景,即不太可能发生的大流行情景或一切照常(BAU)、中等情景(MOD)和乐观情景(OPT)。此外,还分析了家庭、工业、商业、社会和公共部门,以便通过所给出的情景看到电力消费的变化模式。利用低排放分析平台(Low Emission Analysis Platform, LEAP)软件进行能源建模,分析2019 - 2030年三种情景下的电力需求预测。结果表明:2030年,根据BAU、MOD和OPT情景,电力需求分别为5,301.58 GWh、4,489.11 GWh和4,648.12 GWh。根据MOD和OPT情景,家庭和工业部门的电力需求将相对于BAU情景增加。同时,根据这两种情况,商业和社会部门的电力需求将减少。在公共部门,MOD情景显示相对于BAU情景的电力需求下降,而OPT情景显示相反的情况。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
FACTOR ANALYSIS OF HEALTHY FOOD PHOTOGRAPH BIOREMEDIATION OF TOFU INDUSTRY LIQUID WASTE USING EFFECTIVE MICROORGANISM-4 (EM4) SOLUTION (CASE STUDY OF TOFU SENTOSA INDUSTRY, YOGYAKARTA) FORECASTING ANALYSIS ON ELECTRICITY DEMAND IN THE SPECIAL REGION OF YOGYAKARTA UNDER THE IMPACT OF THE COVID-19 PANDEMIC POROUS CARBON FROM PINEAPPLE PEEL AS ELECTRODE MATERIAL OF SUPERCAPACITOR IMPLEMENTATION OF IMAGE CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORK (CNN) ALGORITHM ON VEHICLES IMAGES
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1