PyPSA-BD: A customized model to explore decarbonized energy transition for developing country

IF 4.2 Q2 ENERGY & FUELS Renewable Energy Focus Pub Date : 2024-11-26 DOI:10.1016/j.ref.2024.100655
Firuz Ahamed Nahid , Joyashree Roy
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Abstract

This article provides high-resolution, evidence-based insights towards power sector planning for a developing country. We consider the PyPSA-BD model as a cutting-edge contribution as it’s a fully customized adaptation of PyPSA-Earth for Bangladesh to identify challenges and opportunities for transitioning to a decarbonized power system through counterfactual validation of inputs from national official statistics with a spatial resolution of 30km x 30km and an hourly temporal resolution. Its open-source framework is helpful for future researchers and decision-makers in developing countries like Bangladesh to develop more scenarios to answer any policy-relevant questions as per national need. With 2019 as a reference year, scenarios for 2030, 2041, and 2050 align with national renewable energy integration and decarbonization targets revealing cost-effective generation expansions, diversification of installed capacity through renewable energy penetration, net employment generation, additional land and investment requirement. Model results show that the 2019 installed capacity of 18.94 GW will grow to 61.45 GW by 2030, 102.36 GW by 2041, and 281.52 GW by 2050. By 2050, a storage capacity of 28.5 GW will be required to maintain grid stability. This transition could create approximately 6.7 million jobs and reduce generation costs to 7.63 BDT/kWh by 2050, requiring 3690.85 sq.km of land. Achieving these outcomes will demand an annual investment of approximately 1.99% of Bangladesh’s 2023 GDP from 2025, underscoring the need for national and international finance mobilization. The results guide policymakers to develop sustainable energy transition strategies for Bangladesh that provide power supply security at both spatial and temporal scale.

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PyPSA-BD:探索发展中国家脱碳能源转型的定制模型
这篇文章为发展中国家的电力部门规划提供了高分辨率的、基于证据的见解。我们认为PyPSA-BD模型是一项前沿贡献,因为它是孟加拉国对PyPSA-Earth的完全定制化适应,通过对国家官方统计数据(空间分辨率为30公里× 30公里,每小时时间分辨率)的输入进行反事实验证,确定向脱碳电力系统过渡的挑战和机遇。它的开源框架有助于孟加拉国等发展中国家未来的研究人员和决策者根据国家需要开发更多的场景来回答任何与政策相关的问题。以2019年为参考年,2030年、2041年和2050年的情景与国家可再生能源整合和脱碳目标保持一致,揭示了具有成本效益的发电扩张、通过可再生能源渗透实现装机容量多样化、净就业、额外的土地和投资需求。模型结果显示,2019年的装机容量为18.94 GW,到2030年将增长到61.45 GW,到2041年将增长到102.36 GW,到2050年将增长到281.52 GW。到2050年,将需要28.5吉瓦的储能容量来维持电网的稳定。到2050年,这一转变将创造约670万个就业岗位,并将发电成本降至7.63 BDT/kWh,所需面积为3690.85平方英尺。千米的土地。实现这些成果需要从2025年起每年投资约占孟加拉国2023年GDP的1.99%,这凸显了动员国内和国际资金的必要性。研究结果指导决策者为孟加拉国制定可持续能源转型战略,在空间和时间尺度上提供电力供应安全。
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来源期刊
Renewable Energy Focus
Renewable Energy Focus Renewable Energy, Sustainability and the Environment
CiteScore
7.10
自引率
8.30%
发文量
0
审稿时长
48 days
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