Leveraging Power-to-X for Renewable Integration: A Strategic Approach to Decarbonization

The urgency to reduce global carbon emissions has accelerated the transition to renewable energy, with P2X technologies offering promising solutions for storing and utilizing renewable electricity across sectors. However, optimal deployment of renewables in P2X systems remains underexplored, particularly under system-level uncertainties. Therefore, this study proposes a novel, uncertainty-aware framework for renewable-to-P2X allocation, integrating Monte Carlo simulation, conditional value-at-risk (CVaR), and sensitivity analysis to identify low-risk deployment strategies. This study also explicitly considers China’s ultrahigh-voltage (UHV) transmission infrastructure, distinguishing renewable exporters and importers based on decarbonization potential, demand, and grid connectivity. A case study involving 10 provinces shows that achieving the national emissions reduction goal requires an additional 2693.08 TWh of renewable energy and that inter-region optimization reduces the required increment ratio by approximately 11.77% (approximately 280 TWh) compared to in-region expansion, supported by infrastructure connectivity between provinces. The results underscore the need for risk-aware, transmission-feasible planning in future P2X deployment strategies to support national decarbonization goals.

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Publication Details

Journal
Industrial & Engineering Chemistry Research
Published
2025-09-25
DOI
https://doi.org/10.1021/acs.iecr.5c01674
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Leveraging Power-to-X for Renewable Integration: A Strategic Approach to Decarbonization

Zuwei Liao, Jingdai Wang, Yongrong Yang, Xiaodong Hong et al.
Industrial & Engineering Chemistry Research
Integrated Energy Systems Optimization
article

Leveraging Power-to-X for Renewable Integration: A Strategic Approach to Decarbonization

Zuwei Liao, Jingdai Wang, Yongrong Yang, Xiaodong Hong, Karen Gah Hie Kong
article en

Abstract

The urgency to reduce global carbon emissions has accelerated the transition to renewable energy, with P2X technologies offering promising solutions for storing and utilizing renewable electricity across sectors. However, optimal deployment of renewables in P2X systems remains underexplored, particularly under system-level uncertainties. Therefore, this study proposes a novel, uncertainty-aware framework for renewable-to-P2X allocation, integrating Monte Carlo simulation, conditional value-at-risk (CVaR), and sensitivity analysis to identify low-risk deployment strategies. This study also explicitly considers China’s ultrahigh-voltage (UHV) transmission infrastructure, distinguishing renewable exporters and importers based on decarbonization potential, demand, and grid connectivity. A case study involving 10 provinces shows that achieving the national emissions reduction goal requires an additional 2693.08 TWh of renewable energy and that inter-region optimization reduces the required increment ratio by approximately 11.77% (approximately 280 TWh) compared to in-region expansion, supported by infrastructure connectivity between provinces. The results underscore the need for risk-aware, transmission-feasible planning in future P2X deployment strategies to support national decarbonization goals.

Industrial & Engineering Chemistry ResearchVol. 64(40)
Zhejiang University of Science and Technology (CN), Zhejiang Lab (CN), State Key Laboratory of Chemical Engineering (CN), Zhejiang University (CN)
Openalex Percentile: Top 74%
Integrated Energy Systems Optimization
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