Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/118109
Title: Synergistic decarbonization strategies for high-density cities and their neighboring areas : a case for Hong Kong and Guangdong's power system
Authors: Peng, W 
Chen, Y
Wang, S 
Issue Date: 15-Oct-2025
Source: Applied energy, 15 Oct. 2025, v. 396, 126173
Abstract: To achieve carbon neutrality, high-density cities with limited natural resources are shifting from a fossil fuel-dominated generation structure to a more sustainable alternative. Regional cooperation emerges as a cost-effective solution for synergistic decarbonization, enabling mutual benefits between megacities and their hinterlands. This research investigates the potential benefits and challenges of such cooperation through a case analysis of Hong Kong and Guangdong's power systems. A novel power system evaluation framework based on real-world data at high spatiotemporal resolution is developed to analyze the supply-demand dynamics and explore suitable decarbonization scenarios for 2035. In this framework, the load demand of Hong Kong is initially introduced by simulating the electricity consumption patterns of typical buildings. Detailed modeling of 30 existing wind and solar power plants is conducted and optimal cross-border configurations are identified through supply-demand dynamics and economic performance. Scenario analysis demonstrates that enhanced regional cooperation can effectively reduce total system costs by 6.12 % to 9.73 % (approximately 2.37 to 8.56 billion USD) and annual carbon emissions by 43.66 % to 59.10 % (roughly 7479.89 to 10,125.39 ktCO₂), compared to reference trajectories. Challenges to deepening regional collaboration, including substantial upfront costs, technological uncertainties, and collaborative inefficiencies, are also discussed, offering actionable insights for policymakers and stakeholders to advance cross-border decarbonization partnerships.
Keywords: Decarbonization
Power sector
Regional cooperation
Scenario analysis
Spatiotemporal modeling
Publisher: Pergamon Press
Journal: Applied energy 
ISSN: 0306-2619
EISSN: 1872-9118
DOI: 10.1016/j.apenergy.2025.126173
Appears in Collections:Journal/Magazine Article

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