Considering Adaptive Power System Planning for Indonesia in the Face of Climate Uncertainties

Conference Paper (2025)
Author(s)

H. Aji (TU Delft - System Engineering, PT. PLN (Persero) )

N. Goyal (TU Delft - Organisation & Governance)

Stefan Pfenninger (TU Delft - Energy and Industry)

I. Nikolic (TU Delft - System Engineering)

Research Group
System Engineering
DOI related publication
https://doi.org/10.1109/ICT-PEP67281.2025.11232371
More Info
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Publication Year
2025
Language
English
Research Group
System Engineering
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository as part of the Taverne amendment. More information about this copyright law amendment can be found at https://www.openaccess.nl. Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Pages (from-to)
143-148
ISBN (electronic)
9798331554835
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Abstract

Climate change impacts the power system globally. It also creates a challenge for Indonesia's energy transition, which aims for net-zero emissions by 2060. Aside from decarbonization efforts, planning for this transition adds a challenge due to the deeply uncertain nature of climate change. This refers to a condition where planners cannot agree on models, probabilities, or even which variables to prioritize. That degree of climate uncertainty has not yet been addressed in Indonesia's current power systems planning approach. Failure to address these uncertainties could bring significant vulnerabilities to Indonesia's future power system. Furthermore, only a small number of studies on power systems planning in Indonesia have addressed these climate uncertainties, and even then, only in a limited way. This paper offers a conceptual recommendation of an adaptive planning approach as one potential method to address these uncertainties. The approach is based on Dynamic Adaptive Pathways Planning (DAPP), which comes from the decision-making under deep uncertainty (DMDU) taxonomy. It supports planners in exploring a range of possible futures, considering policies and uncertainties, and enabling more robust decision-making.

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