Nature Energy intl_tech D1

发布：2026-05-27 · 事件：2026-05-27

Subjects Energy policy Energy supply and demand Abstract Energy modelling tools guide energy transition planning, yet critical questions persist regarding their application in low- and middle-income c...

Subjects Energy policy Energy supply and demand Abstract Energy modelling tools guide energy transition planning, yet critical questions persist regarding their application in low- and middle-income countries (LMICs). These countries face the complex challenge of meeting growing energy needs in ways that are affordable, sustainable and resilient, while also advancing broader, long-term development goals in uncertain financial, geopolitical and climatic contexts. Here we highlight that innovation in modelling practice is required to adequately analyse current planning challenges and avoid the risks of misaligned policy advice. Framed through three features of modelling practice—choice of paradigm, modelling process and pluralism of expertise—we identify priority areas for methodological advancement. This means innovation across energy planning related to context-specificity, system dynamics and uncertainties, as well as integration with connected systems. To mainstream innovation, we propose a focus on ensuring data and modelling availability, prioritizing support for modelling in low-planning-capacity contexts, and expanding networks of practice that support LMIC modelling. Access through your institution Buy or subscribe This is a preview of subscription content, access via your institution Access options Access through your institution Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription 27,99 € / 30 days cancel any time Learn more Subscribe to this journal Receive 12 digital issues and online access to articles 111,21 € per year only 9,27 € per issue Learn more Buy this article Purchase on SpringerLink Instant access to the full article PDF. 39,95 € Prices may be subject to local taxes which are calculated during checkout Fig. 1: Country-level energy modelling risks in LMICs. The alternative text for this image may have been generated using AI. Similar content being viewed by others Development transitions for fossil fuel-producing low and lower–middle income countries in a carbon-constrained world Article 08 February 2024 Identifying energy model fingerprints in mitigation scenarios Article Open access 06 November 2023 Global properties of the energy landscape: a testing and training arena for machine learned potentials Article Open access 04 December 2025 References Fuso Nerini, F. et al. Mapping synergies and trade-offs between energy and the Sustainable Development Goals. Nat. Energy 3 , 10–15 (2018). Article Google Scholar Plazas-Niño, F., Tan, N., Howells, M., Foster, V. & Quirós-Tortós, J. Uncovering the applications, developments and future research directions of the open-source energy modelling system (OSeMOSYS): a systematic literature review. Energy Sustain. Dev. 85 , 101629 (2025). Article Google Scholar Waisman, H. et al. A pathway design framework for national low greenhouse gas emission development strategies. Nat. Clim. Change 9 , 261–268 (2019). Article Google Scholar Tesfamichael, M. & Fuchs, J. Navigating complexity: integrating political realities into energy system modelling for effective policy in sub-Saharan Africa. Prog. Energy 6 , 043001 (2024). Article Google Scholar Mulugetta, Y. et al. Africa needs context-relevant evidence to shape its clean energy future. Nat. Energy 7 , 1015–1022 (2022). Article Google Scholar Fuchs, J. L., Tesfamichael, M., Clube, R. & Tomei, J. How does energy modelling influence policymaking? Insights from low- and middle-income countries. Renew. Sustain. Energy Rev. 203 , 114726 (2024). Article Google Scholar Süsser, D. et al. Why energy models should integrate social and environmental factors: assessing user needs, omission impacts and real-word accuracy in the European Union. Energy Res. Soc. Sci. 92 , 102775 (2022). Article Google Scholar Dioha, M. O., Montgomery, M., Almada, R., Dato, P. & Abrahams, L. Beyond dollars and cents: why socio-political factors matter in energy system modeling. Environ. Res. Lett. 18 , 121002 (2023). Article Google Scholar Bergman, M. et al. Guidelines for inclusive and equitable energy and transport modeling. iScience 28 , 113218 (2025). Article Google Scholar Trotter, P. A. Rural electrification, electrification inequality and democratic institutions in sub-Saharan Africa. Energy Sustain. Dev. 34 , 111–129 (2016). Article Google Scholar Mengisteab, K. Traditional institutions of governance in Africa. Oxford Research Encyclopedia of Politics https://doi.org/10.1093/acrefore/9780190228637.013.1347 (2019). Dioha, M. O. & Mutiso, R. Generating meaningful energy systems models for Africa. Issues Sci. Technol. 39 , 54–57 (2023). Article Google Scholar Blimpo, M. P., Dato, P., Mukhaya, B. & Odarno, L. Climate change and economic development in Africa: a systematic review of energy transition modeling research. Energy Policy 187 , 114044 (2024). Article Google Scholar Lonergan, K. E. et al. Improving the representation of cost of capital in energy system models. Joule 7 , 4