考虑两阶段P2G-CCS耦合和源-荷协同优化的电-热-气-氢-储综合能源系统低碳运行研究

邓丹; 吕游; 时一钧; 李泽洋; 季湛洋; 刘吉臻

doi:doi:10.19912/j.0254-0096.tynxb.2024-0927

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考虑两阶段P2G-CCS耦合和源-荷协同优化的电-热-气-氢-储综合能源系统低碳运行研究

更新时间：2025-12-17

- 考虑两阶段P2G-CCS耦合和源-荷协同优化的电-热-气-氢-储综合能源系统低碳运行研究
- Issue 10, Pages: 390-402(2025)
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- DOI：doi:10.19912/j.0254-0096.tynxb.2024-0927
  CLC： K513
- Published Online：31 October 2025，
  
  Published：31 October 2025
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邓丹, 吕游, 时一钧, et al. 考虑两阶段P2G-CCS耦合和源-荷协同优化的电-热-气-氢-储综合能源系统低碳运行研究[J]. 2025, (10): 390-402.
DOI：

邓丹, 吕游, 时一钧, et al. 考虑两阶段P2G-CCS耦合和源-荷协同优化的电-热-气-氢-储综合能源系统低碳运行研究[J]. 2025, (10): 390-402. DOI： doi:10.19912/j.0254-0096.tynxb.2024-0927.

摘要

为解决多种能源下源侧能量供给耦合转换和荷侧用能需求转移替代的协同优化问题

该文在阶梯碳交易机制和多能需求响应条件下提出电-热-气-氢-储系统源-荷协同优化调度模型。首先

源侧基于能量流模型构建灵活响应机制

设计热电比可调的氢能联产系统

通过电-氢-气多阶段转化实现分层能量优化

提升多能协同效率;其次

荷侧考虑柔性负荷特性

在阶梯碳交易机制下建立时空二维多能需求响应模型。最后

基于Frank-SJC-Copula处理不确定性后得到新能源出力及多能负荷曲线

以系统总运行成本最低为目标建立日前调度模型

在分时电价与气价基础上通过算例验证多场景、多能源配置下调度可行性

结果表明该文所提电-热-气-氢-储协同优化模型可有效优化系统低碳性与经济性并促进新能源消纳。

Abstract

To solve the collaborative optimization problem of source-side energy supply coupling conversion and load-side energy demand transfer substitution under various energy sources

this paper proposes a source-load collaborative optimal scheduling model for an electricity-heat-gas-hydrogen-storage system under a tiered carbon trading mechanism and multi-energy demand response conditions. Firstly

based on the energy flow model

a flexible response model is proposed on the source side

constructing a hydrogen-mixed combined heat and power unit model with an adjustable heat-to-power ratio

and utilizing a two-stage power-to-gas process for dual-layer energy optimization. Secondly

on the load side

considering the characteristics of flexible loads

a spatio-temporal two-dimensional multi-energy demand response model is established under a tiered carbon trading mechanism. Finally

by handling uncertainties using the Frank-SJC-Copula

renewable energy output and multi-energy load forecasting curves are obtained. A day-ahead scheduling model is established with the objective of minimizing the total operating cost of the system

and the feasibility of scheduling under multiple scenarios and multi-energy configurations is verified through case studies based on time-of-use electricity and gas prices. The results show that the proposed electricity-heat-gas-hydrogen-storage collaborative optimization model can effectively optimize the system’s low-carbon and economic performance and reduce wind and solar curtailment.

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