计及多生物质能与综合需求响应的低碳综合能源系统鲁棒优化

颜湘武; 张育铭; 张仁博; 贾焦心; 王庆澳

doi:doi:10.19912/j.0254-0096.tynxb.2024-1008

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计及多生物质能与综合需求响应的低碳综合能源系统鲁棒优化

更新时间：2026-02-06

- 计及多生物质能与综合需求响应的低碳综合能源系统鲁棒优化
- Vol. 47, Issue 1, Pages: 214-226(2026)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：doi:10.19912/j.0254-0096.tynxb.2024-1008
  CLC： TM732
- Online First：05 February 2026，
  
  Published：05 February 2026
- 稿件说明：
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颜湘武, 张育铭, 张仁博, et al. 计及多生物质能与综合需求响应的低碳综合能源系统鲁棒优化[J]. 2026, 47(1): 214-226.
DOI：

颜湘武, 张育铭, 张仁博, et al. 计及多生物质能与综合需求响应的低碳综合能源系统鲁棒优化[J]. 2026, 47(1): 214-226. DOI： doi:10.19912/j.0254-0096.tynxb.2024-1008.

摘要

为实现农业区域综合能源系统（RIES）多能互补及能源高效利用的低碳发展

提出一种计及多生物质能与综合需求响应的农业综合能源低碳调度模型。首先

基于农业区域的生物质能特点

将其分为可燃性生物质能和不可燃性生物质能

分别用不同机组供能。同时

对综合需求响应进行建模

考虑可削减、可转移及可替代3种类型负荷

实现负荷在时间及类型上的转移

深度挖掘需求侧潜力。其次

考虑到源侧和负荷侧的不确定性

建立农业区域综合能源系统（RIES）两阶段鲁棒优化模型

并引入阶梯式碳交易机制降低系统碳排放量

达到低碳运行目的。最后

通过列约束生成算法对该模型求解

算例分析表明

所提优化方案在调度成本降低4.65%、碳排放量下降5.36%的同时使系统鲁棒性与灵活性得到提升

实现农业区域多能协同互补

提高农业区域综合能源系统的整体效益。

Abstract

To achieve low-carbon development of regional integrated energy systems （RIES） with multi-energy complementarity and efficient energy utilization

a low-carbon scheduling model for agricultural integrated energy is proposed

whichconsidersmultiple biomass energy sources and comprehensive demand response. Firstly

based on the characteristics of biomass energy in agricultural regions

it is divided into combustible biomass energy and non-combustible biomass energy

which are supplied by different assembling unit. At the same time

the comprehensive demand response is modeled

considering three types of loads that can be reduced

transferred

and replaced

to achieve the transfer of loads in terms of time and type

and deeply explore the potential of the demand side. Secondly

considering the uncertainty of the source and load sides

a two-stage robust optimization model for the agricultural regional integrated energy system （RIES） is established

and a stepped carbon trading mechanism is introduced to reduce the system's carbon emissions and achieve low-carbon operation. Finally

the model is solved using the column constraint generation algorithm. Case analysis shows that the proposed optimization scheme not only reduces scheduling costs by 4.65% and carbon emissions by 5.36%

but also improves system robustness and flexibility

achieving multi energy synergy and complementarity in agricultural regions

and improving the overall efficiency of the agricultural regional comprehensive energy system.

关键词

Keywords

references

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