将电网发展纳入产能扩张优化 - 印度尼西亚案例研究

IF 10.1 1区 工程技术 Q1 ENERGY & FUELS Applied Energy Pub Date : 2024-11-16 DOI:10.1016/j.apenergy.2024.124837
Bintang Yuwono , Lukas Kranzl , Reinhard Haas , Retno Gumilang Dewi , Ucok Welo Risma Siagian , Florian Kraxner , Ping Yowargana
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引用次数: 0

摘要

产能扩张优化是一种广泛应用的技术经济分析方法,尤其是在与减缓气候变化和可再生能源转型相关的课题上。在可能需要大量电网基础设施建设的地区,使用优化模型来研究扩容问题需要在优化过程中考虑电网扩容问题。本研究介绍了 SELARU 的开发情况,这是一个空间显式优化模型,它利用背景地理特征将电网扩张的规模经济纳入模型的高分辨率空间单元。该模型利用各种空间处理方法对印度尼西亚的案例进行了研究,以展示电网扩张的详细空间描述所产生的影响。结果显示,高分辨率的电网扩展空间描述与非空间明确的能源系统优化相比,在可再生能源部署轨迹上存在明显差异(新增发电能力最多可增加 2272%)。由于具有高分辨率,SELARU 还能生成有关电网扩展要求的地理范围的详细信息,从而为可再生能源转型的治理挑战提供更现实的见解。当优化模型用于评估可再生能源部署或气候变化减缓等技术选择方案时,仔细考虑空间表示至关重要。
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Incorporating grid development in capacity expansion optimisation - a case study for Indonesia
Capacity expansion optimisation is a widely used techno-economic analysis particularly on topics related to climate change mitigation and renewable energy transition. Using optimisation models to investigate capacity expansion in regions that potentially require significant grid infrastructure development requires incorporation of grid expansion problem within the optimisation. This study presents the development of SELARU, a spatially explicit optimisation model that incorporates the economies of scale of grid expansion using contextualized geographical feature to form the model's high-resolution spatial units. The model is used to investigate the case study of Indonesia using various spatial treatments to demonstrate the impact of detailed spatial depiction of grid expansion. Results reveal significant difference in renewable energy deployment trajectory (up to 2272 % increase in new generation capacity) between high-resolution spatial depiction of grid expansion vis-à-vis non spatially explicit energy system optimisation. Due to its high-resolution, SELARU also generates detailed information on the geographical extent of grid expansion requirement, which provides more realistic insights on governance challenges of renewable energy transition. Careful consideration of spatial representation is crucial when optimisation model is used to evaluate scenarios that concern technology selection such as renewable energy deployment or climate change mitigation.
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来源期刊
Applied Energy
Applied Energy 工程技术-工程:化工
CiteScore
21.20
自引率
10.70%
发文量
1830
审稿时长
41 days
期刊介绍: Applied Energy serves as a platform for sharing innovations, research, development, and demonstrations in energy conversion, conservation, and sustainable energy systems. The journal covers topics such as optimal energy resource use, environmental pollutant mitigation, and energy process analysis. It welcomes original papers, review articles, technical notes, and letters to the editor. Authors are encouraged to submit manuscripts that bridge the gap between research, development, and implementation. The journal addresses a wide spectrum of topics, including fossil and renewable energy technologies, energy economics, and environmental impacts. Applied Energy also explores modeling and forecasting, conservation strategies, and the social and economic implications of energy policies, including climate change mitigation. It is complemented by the open-access journal Advances in Applied Energy.
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