Economic and low-carbon coordinated optimization scheduling of hydrogen-integrated multi-energy system based on NSGA-Ⅱ

QIU Wenting; DONG Jiale; WU Di; SU Wenjing; ZONG Yi

doi:10.3969/j.issn.2097-0706.2025.10.004

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Economic and low-carbon coordinated optimization scheduling of hydrogen-integrated multi-energy system based on NSGA-Ⅱ

Electrochemical Energy Storage | 更新时间：2025-11-03

- Economic and low-carbon coordinated optimization scheduling of hydrogen-integrated multi-energy system based on NSGA-Ⅱ
- BLASTING Vol. 47, Issue 10, Pages: 34-44(2025)
- 作者机构：
  
  1.武汉工程大学电气信息学院，武汉 430200
  2.丹麦技术大学风力与能源系统，罗斯基勒 4000
- 作者简介：
- 基金信息：
  
  Graduate Innovative Fund of Wuhan Institute of Technology(CX2023575)
- DOI：10.3969/j.issn.2097-0706.2025.10.004
  CLC： TK 01⁺9
- Received：06 November 2024，
  
  Revised：2024-12-06，
  
  Published Online：21 January 2025，
  
  Published：25 October 2025
- 稿件说明：
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邱文婷,董家乐,吴笛等.基于NSGA-Ⅱ的含氢多能源系统经济与低碳协同优化调度[J].综合智慧能源,2025,47(10):34-44.

QIU Wenting,DONG Jiale,WU Di,et al.Economic and low-carbon coordinated optimization scheduling of hydrogen-integrated multi-energy system based on NSGA-Ⅱ[J].BLASTING,2025,47(10):34-44.
邱文婷,董家乐,吴笛等.基于NSGA-Ⅱ的含氢多能源系统经济与低碳协同优化调度[J].综合智慧能源,2025,47(10):34-44. DOI： 10.3969/j.issn.2097-0706.2025.10.004.

QIU Wenting,DONG Jiale,WU Di,et al.Economic and low-carbon coordinated optimization scheduling of hydrogen-integrated multi-energy system based on NSGA-Ⅱ[J].BLASTING,2025,47(10):34-44. DOI： 10.3969/j.issn.2097-0706.2025.10.004.

摘要

为应对电-热-氢多能源系统（MES）中电制氢设备运行安全问题以及运行调度难以兼顾经济性和低碳性的问题，提出一种结合电解槽非线性动态模型和非支配遗传算法Ⅱ（NSGA-Ⅱ）的优化调度策略，以实现MES的多目标优化。为确保电制氢过程在安全温度范围内，构建了一个考虑堆温对电解效率非线性影响的碱性电解槽动态模型；为利用MES中各类能源的强耦合关系和负荷的可调度性，引入综合需求响应机制和碳交易机制以提高系统的经济性和低碳运行能力；融合电解槽的复杂非线性模型，提出了基于NSGA-Ⅱ的多目标优化算法，并使用优劣解距离法综合评价出最优解，以实现对MES的优化调度。通过不同算例的仿真试验，对MES的日总运行成本和碳排放量进行比较分析。结果表明，结合了NSGA-Ⅱ的多目标优化方法可显著降低系统的日总运行成本和碳排放总量，相较于单一优化系统经济成本，系统的日总成本和碳排放分别减少33.5%和57.7%，验证了所提策略在提升电-热-氢MES经济性与低碳性方面的有效性。

Abstract

To address the operational safety issues of hydrogen production equipment in electricity-heat-hydrogen multi-carrier energy systems（MES） and the challenge of balancing economic efficiency with low-carbon operation in scheduling， an optimized scheduling strategy was proposed， integrating the nonlinear dynamic model of the electrolyzer with the non-dominated sorting genetic algorithm-Ⅱ（NSGA-Ⅱ） for multi-objective optimization of the MES. To ensure that the hydrogen production process operates within a safe temperature range， a dynamic model of alkaline electrolyzer was developed， considering the nonlinear effect of stack temperature on electrolysis efficiency. To make use of the strong coupling relationships among various energy resources and the dispatchability of loads in the MES， an integrated demand response mechanism and carbon trading mechanism were introduced to improve the system's economic efficiency and low-carbon operational performance. By integrating the complex nonlinear model of the electrolyzer， a multi-objective optimization algorithm based on NSGA-Ⅱ was proposed， and the optimal solution was comprehensively evaluated using the technique for order preference by similarity to ideal solution to achieve the optimization scheduling of the MES. Through simulation experiments under different scenarios， the daily total operating costs and carbon emissions of MES were compared and analyzed. The results showed that the multi-objective optimization method combined with NSGA-Ⅱ could significantly reduce the daily total operating costs and carbon emissions of the system. Compared with optimizing the system's economic costs alone， the daily total costs and carbon emissions of the system were reduced by 33.5% and 57.7%， respectively. This validated the effectiveness of the proposed strategy in improving the economic efficiency and low-carbon operation of the electricity-heat-hydrogen MES.

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references

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