计及多重不确定性的综合能源系统两阶段鲁棒低碳优化调度

杨胡萍; 龚家宁; 程明; 李向军; 刘常禄; 张扬

doi:10.11930/j.issn.1004-9649.202507022

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计及多重不确定性的综合能源系统两阶段鲁棒低碳优化调度

高比例新能源区域综合能源系统调度、控制与可靠性研究 | 更新时间：2025-12-20

- 计及多重不确定性的综合能源系统两阶段鲁棒低碳优化调度
- Two-stage Robust Low-carbon Optimal Scheduling for Integrated Energy Systems Considering for Multiple Uncertainties
- 中国电力 2025年58卷第11期页码：101-110
- 作者机构：
  
  1. 南昌大学智能系统与人机交互江西省重点实验室,江西,南昌,330031
  2. 国网江西省电力有限公司赣州供电分公司,江西,赣州,341000
  3. 国网江西省电力有限公司信息通信分公司,江西,南昌,330031
  4. 南昌大学数学与计算机学院,江西,南昌,330031
- 作者简介：
- 基金信息：
  
  国家自然科学基金资助项目（62562047）。
- DOI：10.11930/j.issn.1004-9649.202507022
  中图分类号：
- 网络出版：2025-12-01，
  
  纸质出版：2025-12-01
- 稿件说明：
移动端阅览
杨胡萍, 龚家宁, 程明, 李向军, 刘常禄, 张扬. 计及多重不确定性的综合能源系统两阶段鲁棒低碳优化调度[J]. 中国电力, 2025, 58(11): 101-110, 121.

YANG Huping, GONG Jianing, CHENG Ming, et al. Two-stage Robust Low-carbon Optimal Scheduling for Integrated Energy Systems Considering for Multiple Uncertainties[J]. 2025, 58(11): 101-110.
杨胡萍, 龚家宁, 程明, 李向军, 刘常禄, 张扬. 计及多重不确定性的综合能源系统两阶段鲁棒低碳优化调度[J]. 中国电力, 2025, 58(11): 101-110, 121. DOI： 10.11930/j.issn.1004-9649.202507022.

YANG Huping, GONG Jianing, CHENG Ming, et al. Two-stage Robust Low-carbon Optimal Scheduling for Integrated Energy Systems Considering for Multiple Uncertainties[J]. 2025, 58(11): 101-110. DOI： 10.11930/j.issn.1004-9649.202507022.

摘要

针对综合能源系统电、热、气等多种能源耦合，受到多重不确定性因素扰动的问题，构建了一种考虑可再生能源和设备多重不确定性的两阶段鲁棒优化调度模型。首先，构建了涵盖电、热、气的综合能源系统模型。其次，引入阶梯式碳交易机制来约束系统的碳排放量，建立以系统的经济性、鲁棒性和低碳性为目标的两阶段鲁棒低碳优化调度模型。最后，设置了5种场景，通过列-约束生成算法进行求解。仿真结果表明该模型能够在保证系统鲁棒性的同时，有效降低系统调度方案的碳排放量，提升调度方案的合理性。

Abstract

To address the challenges of electricity-heat-gas coupling in integrated energy systems under multiple uncertainties

a two-stage robust optimization scheduling model is constructed that considers the multiple uncertainties from both renewable energy and equipment. Firstly

an integrated energy system model encompassing electricity

heat

and gas is established. Subsequently

with the objectives of system economy

robustness

and low-carbon performance

a two-stage robust low-carbon optimal scheduling model is established by introducing a tiered carbon trading mechanism to constrain carbon emissions. Finally

five scenarios are designed and solved using the column-and-constraint generation algorithm. Simulation results demonstrate that the proposed model effectively reduces carbon emissions of the system scheduling scheme while ensuring system robustness

thereby significantly enhancing the rationality of the scheduling scheme.

关键词

Keywords

references

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