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估算和预测气候变化、非正规经济及部门效率低下情况下加纳被抑制的电力需求。

Estimating and forecasting suppressed electricity demand in Ghana under climate change, the informal economy and sector inefficiencies.

作者信息

Dramani John Bosco, Ofori-Mensah Kwame Ansere, Otchere Nathaniel Oppong, Frimpong Prince Boakye, Adu-Poku Akwasi, Kemausuor Francis, Yazdanie Mashael

机构信息

Department of Economics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.

The Brew Hammond Energy Centre, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.

出版信息

Heliyon. 2024 Aug 10;10(16):e36001. doi: 10.1016/j.heliyon.2024.e36001. eCollection 2024 Aug 30.

DOI:10.1016/j.heliyon.2024.e36001
PMID:39247376
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11380181/
Abstract

Suppressed demand arises from inadequate energy access, resulting in unmet basic needs. Therefore, this study investigates the impact of the informal economy, rising temperatures, and electricity transmission losses on suppressed demand in Ghana from 2000 to 2020, using a quantile autoregressive distributed lag (QARDL) approach. The study forecasts suppressed demand using Shared Socioeconomic Pathway (SSP) scenarios, offering insights for energy system planning. The results indicate that all the variables significantly affect suppressed demand in the mid-quantiles. Notably, transmission losses and growth of informal economy variables significantly impact suppressed demand within the 50th to 75th quantiles but have minimal impact before the 50th and after the 75th quantiles in the long run. Additionally, rising temperatures substantially increase suppressed demand by increasing electricity demand for cooling. All future scenarios project this growth trend will continue through 2050, albeit at varying rates. In the business-as-usual (BAU) case, suppressed demand is expected to steadily increase from 1782 MW in 2020 to 8636 MW in 2050. This trajectory aligns well with historical growth trends, which saw suppressed demand increase from 659 GWh to 1782 GWh between 2000 and 2020. SSP scenarios suggest that suppressed demand could grow substantially through 2050, driven by high losses and informal sector growth. Despite sustainable development narratives like SSP1, suppressed demand remains high without major grid and governance improvements. Comparing the results with past studies shows that our findings align with previous research but provide more nuanced insights by incorporating the effects of the informal economy and using advanced forecasting techniques. Practical policy implications include investing in green infrastructure, upgrading grid infrastructure, and formalising the informal economy to alleviate suppressed demand. These actions are critical for sustainable energy access and meeting future electricity needs effectively.

摘要

能源获取不足导致需求抑制,进而造成基本需求无法满足。因此,本研究采用分位数自回归分布滞后(QARDL)方法,调查2000年至2020年期间加纳非正规经济、气温上升和电力传输损耗对需求抑制的影响。该研究使用共享社会经济路径(SSP)情景预测需求抑制情况,为能源系统规划提供见解。结果表明,所有变量在中位数分位数上对需求抑制有显著影响。值得注意的是,传输损耗和非正规经济变量的增长在第50至75分位数内对需求抑制有显著影响,但从长期来看,在第50分位数之前和第75分位数之后影响极小。此外,气温上升通过增加制冷用电需求大幅增加了需求抑制。所有未来情景都预测,这种增长趋势将持续到2050年,尽管速度有所不同。在照常营业(BAU)的情况下,预计需求抑制将从2020年的1782兆瓦稳步增加到2050年的8636兆瓦。这一轨迹与历史增长趋势非常吻合,在2000年至2020年期间,需求抑制从659吉瓦时增加到1782吉瓦时。SSP情景表明,受高损耗和非正规部门增长的推动,到2050年需求抑制可能大幅增长。尽管有像SSP1这样的可持续发展设想,但如果不进行重大的电网和治理改进,需求抑制仍然很高。将结果与过去的研究进行比较表明,我们的发现与先前的研究一致,但通过纳入非正规经济的影响并使用先进的预测技术,提供了更细致入微的见解。实际政策含义包括投资绿色基础设施、升级电网基础设施以及将非正规经济正规化,以缓解需求抑制。这些行动对于可持续能源获取和有效满足未来电力需求至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31b1/11380181/27d62bd48abe/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31b1/11380181/f6c9f690e428/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31b1/11380181/a813f08afcd0/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31b1/11380181/ade3769b5657/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31b1/11380181/2f0d9c6b534f/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31b1/11380181/c9efdbf7a431/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31b1/11380181/feed18f714e2/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31b1/11380181/27d62bd48abe/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31b1/11380181/f6c9f690e428/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31b1/11380181/a813f08afcd0/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31b1/11380181/ade3769b5657/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31b1/11380181/2f0d9c6b534f/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31b1/11380181/c9efdbf7a431/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31b1/11380181/feed18f714e2/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31b1/11380181/27d62bd48abe/gr7.jpg

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