Optimization of Supply and Demand Balancing in Park-Level Energy Systems Considering Comprehensive Utilization of Hydrogen under P2G-CCS Coupling

The park-level integrated energy system (PIES) is essential for achieving carbon neutrality by managing multi-energy supply and demand while enhancing renewable energy integration. However, current carbon trading mechanisms lack sufficient incentives for emission reductions, and traditional optimization algorithms often face challenges with convergence and local optima in complex PIES scheduling. To address these issues, this paper introduces a low-carbon dispatch strategy that combines a reward-penalty tiered carbon trading model with P2G-CCS integration, hydrogen utilization, and the Secretary Bird Optimization Algorithm (SBOA). Key innovations include: (1) A dynamic reward-penalty carbon trading mechanism with coefficients (μ = 0.2, λ = 0.15), which reduces carbon trading costs by 47.2% (from $694.06 to $366.32) compared to traditional tiered models, incentivizing voluntary emission reductions. (2) The integration of P2G-CCS coupling, which lowers natural gas consumption by 41.9% (from $4117.20 to $2389.23) and enhances CO2 recycling efficiency, addressing the limitations of standalone P2G or CCS technologies. (3) The SBOA algorithm, which outperforms traditional methods (e.g., PSO, GWO) in convergence speed and global search capability, avoiding local optima and achieving 24.39% faster convergence on CEC2005 benchmark functions. (4) A four-energy PIES framework incorporating electricity, heat, gas, and hydrogen, where hydrogen fuel cells and CHP systems improve demand response flexibility, reducing gas-related emissions by 42.1% and generating $13.14 in demand response revenue. Case studies across five scenarios demonstrate the strategy’s effectiveness: total operational costs decrease by 14.7% (from $7354.64 to $6272.59), carbon emissions drop by 49.9% (from 5294.94 to 2653.39 kg), and renewable energy utilization increases by 24.39% (from 4.82% to 8.17%). These results affirm the model’s ability to reconcile economic and environmental goals, providing a scalable approach for low-carbon transitions in industrial parks.

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Publication Details

Journal
Energy Engineering
Published
2025-01-01
DOI
https://doi.org/10.32604/ee.2025.063178
Citations
1
Primary Topic
Power Systems and Renewable Energy
Type
article
Field-Weighted Citation Impact
0.53
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Optimization of Supply and Demand Balancing in Park-Level Energy Systems Considering Comprehensive Utilization of Hydrogen under P2G-CCS Coupling

Xinyu Li, Guangwu Zhang, Minghui Song, Z Zhang et al.
1 citations
Energy Engineering
Power Systems and Renewable Energy
0.53
article

Optimization of Supply and Demand Balancing in Park-Level Energy Systems Considering Comprehensive Utilization of Hydrogen under P2G-CCS Coupling

Xinyu Li, Guangwu Zhang, Minghui Song, Z Zhang, Ziren Wang, Yongjun Wu, Wei Li
article en
1 citations

Abstract

The park-level integrated energy system (PIES) is essential for achieving carbon neutrality by managing multi-energy supply and demand while enhancing renewable energy integration. However, current carbon trading mechanisms lack sufficient incentives for emission reductions, and traditional optimization algorithms often face challenges with convergence and local optima in complex PIES scheduling. To address these issues, this paper introduces a low-carbon dispatch strategy that combines a reward-penalty tiered carbon trading model with P2G-CCS integration, hydrogen utilization, and the Secretary Bird Optimization Algorithm (SBOA). Key innovations include: (1) A dynamic reward-penalty carbon trading mechanism with coefficients (μ = 0.2, λ = 0.15), which reduces carbon trading costs by 47.2% (from $694.06 to $366.32) compared to traditional tiered models, incentivizing voluntary emission reductions. (2) The integration of P2G-CCS coupling, which lowers natural gas consumption by 41.9% (from $4117.20 to $2389.23) and enhances CO2 recycling efficiency, addressing the limitations of standalone P2G or CCS technologies. (3) The SBOA algorithm, which outperforms traditional methods (e.g., PSO, GWO) in convergence speed and global search capability, avoiding local optima and achieving 24.39% faster convergence on CEC2005 benchmark functions. (4) A four-energy PIES framework incorporating electricity, heat, gas, and hydrogen, where hydrogen fuel cells and CHP systems improve demand response flexibility, reducing gas-related emissions by 42.1% and generating $13.14 in demand response revenue. Case studies across five scenarios demonstrate the strategy’s effectiveness: total operational costs decrease by 14.7% (from $7354.64 to $6272.59), carbon emissions drop by 49.9% (from 5294.94 to 2653.39 kg), and renewable energy utilization increases by 24.39% (from 4.82% to 8.17%). These results affirm the model’s ability to reconcile economic and environmental goals, providing a scalable approach for low-carbon transitions in industrial parks.

Energy EngineeringVol. 122(5)
Affordable and clean energy
Openalex Percentile: Top 32%
Power Systems and Renewable Energy
0.53
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