Abstract
Climate change and rising temperatures represent a grave threat to modern civilization, with many of the key infrastructures across the world under risk. The energy sector is highly susceptible to anthropogenic warming, and many of its subsectors would be impacted by it. We use climate projections from climate models and use them to estimate the impact on demand, transmission, and generation in the country. An ANN-based approach utilizing historical demand patterns is used to estimate the impact on consumer demand, and it showed that most regions in the country would experience a drastic increase in demand. A thermal model of transmission lines showed that some transmission lines might lose 23.34% of their capacity. Data reveals that renewable energy sources boost energy efficiency. Hence, future national policies should include more of them. Thermal and PV power in the country have been compared to their resilience to rising temperatures. Without the implementation of more efficient technologies, demand-side management programs, or the upgrading of transmission infrastructure, CC impacts may overwhelm Pakistan's already weak grid system. Our applied models show the Highest forecasting efficiency to be 92.42%, 92.02% and 91.98% for PESCO, LESCO and IESCO.
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Data availability
The data is available from the corresponding author upon reasonable request.
Abbreviations
- CC:
-
Climate change
- GCM:
-
General circulation model
- CCGT:
-
Combined cycle gas turbine
- IPCC:
-
Intergovernmental Panel on Climate Change
- CMIP5:
-
Coupled Model Intercomparison Project Phase 5
- CCAM:
-
Conformal cubic atmospheric model
- IGCEP:
-
Indicative generation capacity expansion plan
- CORDEX:
-
Coordinated Regional Downscaling Experiment
- DISCO:
-
Distribution company
- RCM:
-
Regional climate model
- GT:
-
Gas turbine
- RCP:
-
Representative Concentration Pathway
- NTDC:
-
National Transmission and Distribution Company
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Acknowledgements
This work was supported and conducted at the United States-Pakistan Center of Advanced Studies in Energy (USPCAS-E) at the National University of Science and Technology (NUST) in Islamabad, Pakistan. The authors acknowledge the World Climate Research Programme’s Working Group on Regional Climate and the Working Group on Coupled Modelling, as well as the former coordinating body of CORDEX and the responsible panel for CMIP5. We also thank the climate modelling groups (listed in Table 1 of this paper) for producing and making available their model output. We also acknowledge the Earth System Grid Federation infrastructure, a global initiative led by the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison, the European Network for Earth System Modelling, and other partners in the Global Organisation for Earth System Science Portals (GO-ESSP).
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M Mahad Malik: Conceptualization, Investigation, Methodology, Writing & editing, Formatting. Hamza Waheed Asim: Software, Validation, Visualization, Roles/Writing—original draft, Syed Ali Abbas Kazmi: Review & editing, Supervision, Conceptualization, Investigation, Methodology, Software. Kamran Mujahid: Data curation, Formal analysis, Resources, Software. Muhammad Waleed Ansari: Investigation, Methodology, Conceptualization.
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Malik, M.M., Asim, H.W., Kazmi, S.A.A. et al. ANN and regression based quantification framework for climate change impact assessment on a weak transmission grid of a developing country across Horizon 2050 plus. Environ Dev Sustain (2024). https://doi.org/10.1007/s10668-024-04977-9
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DOI: https://doi.org/10.1007/s10668-024-04977-9