Modeling and Operation Optimization of a Hydrogen‐Compressed Natural Gas‐Integrated Energy System With Variable Hydrogen Content and Flexible Thermal Load
Year: 2025
Type: article
Abstract: ABSTRACT In integrated energy systems (IESs) with high share of renewable energy, converting excess electrical energy into hydrogen (H2) and mixing it with natural gas (NG) offers numerous advantages and has become a key research focus. However, IES operations are influenced by various factors, such as equipment performance, energy flow dynamics, and load management, which are often overlooked in traditional optimization approaches. This study develops a novel hydrogen‐compressed natural gas (HCNG)‐IES model and operational strategy to address these challenges. An equivalence framework is established between electricity and hybrid gas, enabling the creation of an equivalent circuit model integrating electricity, heat, HCNG, H2, and NG. This model captures the intricate interactions and dependencies amongst energy equipment, multi‐energy flow, and consumption loads. An optimized operational strategy is proposed, leveraging variable H2 content in the gas mixture and adaptable thermal loads, while accounting for the energy inertia of H2 storage and building systems to maintain supply–demand balance. Case studies reveal that incorporating HCNG technology increases renewable resources utilization, reducing operational costs, carbon emissions, and primary energy consumption by 23%, 24%, and 23%, respectively. Moreover, compared to conventional NG‐IES optimization focused solely on equipment output, the proposed HCNG‐IES approach achieves reductions of 28.12% in costs, 24.36% in carbon emissions, and 39.13% in primary energy consumption.
Source: Energy Science & Engineering
DOI: 10.1002/ese3.70005
Authors: Jing Chen, Bo Sun
Institutions: Shandong Management University, Shandong University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,780
OpenAlex ID: W4407900337
