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Interview – Modelling Energy Systems for Low-Carbon Pathways


Interviewee: Meng Yuan

Energy Review, Vol 4. Issue 10. 2022

Energy Review: Based on your research and experience in energy systems modelling, what do you think are some peculiar challenges faced while modelling effective low-carbon pathways for developing economies, such as those in Asia, where conventional fossil fuels substantially dominate the energy mix? Dr. Yuan: Energy system modelling is a broad concept in terms of both the spatial and temporal scope. From the perspective of the geographical scope, it could include the international level (e.g., pan-EU), national level, regional level, city/municipal level, local/district level, and even the plant level with the technical detail focus. To model the transition pathway of an energy system, the reference system in the historical years, preferably up to date, based on the detailed depiction of the current status is set as the baseline and starting point of an energy system model. And then, we look into the future scenarios by modelling the future energy systems based on the knowledge of potential technical alternative solutions. We, as energy planners who use the energy system model as the tool, face different challenges at different stages. For developing economies, data scarcity is commonly one of the biggest challenges during all stages. This is commonly found that the statistical data is inadequate, unclear, or simply too rough. Such as the potential of renewable energy sources by type and location, the hourly distribution of electricity and heating demand, and the building areas by type. Also, it is often more difficult to model the local level system (province/city/municipality) while only the national data is available. When modelling the future scenario, the less ambitious political will in terms of climate targets is another main challenge, which is often derived from the country's historical development and energy structure. ER: Your analysis on the feasibilities of energy transition in the Beijing-Tianjin-Hebei Region has underscored the importance of regional integrated planning. Can you elaborate on the advantages of cross-regional integrated energy modelling over independent planning? Dr. Yuan: Glad to know that my study “The first feasible step towards clean heating transition in urban agglomeration: A case study of Beijing-Tianjin-Hebei region” raises your interest and stimulates further discussions. In this work, the energy systems of three spatially connected geographic units consisting of two giant cities (Beijing and Tianjin) and one province (Hebei) in China were studied, which falls within the (inter-) regional level energy system modelling. The significant differences among the three regions in the local potential of renewable energy resources as well as the uneven distribution of energy demand make the integrated planning outperform the independent planning. In this certain case, implementing integrated energy planning by considering the three regions as a holistic unit promotes energy cooperation among regions to expand the penetration of renewable energy as well as maximize mutual benefits, which is less feasible when using independent planning for each region. However, whether adopting the idea of integrated planning or not for a specific region should be analysed case by case because the context, purpose, and objective of energy planning are different. For instance, for neighbour regions with similar resource endowment and demand structures, the choice of independent planning may also enjoy the advantage of practicality. Another example is the planning of a national-level energy system. In such cases, energy security and energy independence are commonly the priority, especially in the current uncertain world, in which independent planning can be considered a better way. It should be noted that independent energy planning does not necessarily deliver an island-mode system, which could also consider the energy exchange beyond the border. ER: While individual countries are inclined to cost-effective transition pathways, we see increasing policy support and attention towards open-source energy modelling. What role does open energy data play in accelerating the decarbonization pathways of countries? Dr. Yuan: Thanks for the interesting question. A small word in the beginning, actually, I don’t see a conflict between cost-effective solutions and open-source energy system modelling, because the cost is one of the most common decision factors of the energy system models. As discussed before in the first question, data scarcity is one of the biggest challenges in macro energy system modelling. From the perspective of energy system modelling, there is no doubt that the open energy data will play an important and significant role in promoting the top-level design of the energy structure, which in turn will stimulate green investment and affect further project implementation, which as a result will contribute to accelerating the process of sustainable transition. Under an open data environment, a region that is struggling with missing data may get inspired by the open data of its neighbour or another region in similar status. (Dr. Meng Yuan is a postdoc in the Sustainable Energy Planning Research Group at Aalborg University in Denmark. Her research interests include energy system modelling and analysis, sustainable energy transition, and energy policy under the smart energy systems context.) ■□■

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