Configuration optimization for coupled green electricity steam heating systems considering time-of-use steam pricing

doi:10.3785/j.issn.1008-973X.2025.09.015

Journal of ZheJiang University (Engineering Science)

2025, Vol. 59

Issue (9): 1911-1919 DOI: 10.3785/j.issn.1008-973X.2025.09.015

Configuration optimization for coupled green electricity steam heating systems considering time-of-use steam pricing

Qiming BO1,2(

),Meng YUAN1,Yuchao WANG3,Xiaojie LIN1,*(

),Pingyuan SHI1,Zhe DAI1,Wei ZHONG1,Lingkai ZHU4

1. College of Energy Engineering, Zhejiang University, Hangzhou 310027, China
2. China Huadian Corporation Ningxia Branch, Yinchuan 750002, China
3. Hefei Thermal Power Group Co. Ltd, Hefei 230061, China
4. State Grid Shandong Electric Power Research Institute, Jinan 250003, China

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Abstract

To address the challenges of high randomness on both the supply and demand sides, difficulties in integrating renewable resources, and low flexibility in industrial parks, a study on the optimal configuration of a steam heating system coupled with green electricity in industrial parks was conducted, considering time-of-use steam pricing. The aim was to enhance system economic efficiency and green electricity utilization level. A system demand response management strategy was developed based on the modeling of the steam heating system in a green electricity-coupled industrial park. By introducing time-of-use steam pricing, users were encouraged to adjust their steam usage behavior, thereby regulating user-side loads and improving system flexibility. Based on the optimized time-of-use pricing results, a bi-level optimal configuration model considering both planning and operation stages was established for the steam heating system in industrial parks. A case study based on a power plant in Zhejiang Province was conducted for validation. The comparative results showed that the proposed optimization method reduced the peak-valley load difference by 58.32%. Additionally, the optimized configuration scheme decreased the total system cost by 98200, 253700, and 182500 yuan under different scenarios with combined heat and power unit output limits of 70%, 60%, and 50%. This time-of-use steam pricing-based optimization approach provided valuable guidance for the low-carbon transition of steam heating systems in industrial parks.

Key words： steam heating system electric energy substitution demand response bi-level optimization configuration industrial park

Received: 27 September 2024 Published: 25 August 2025

CLC:

TK 11

Fund: 国家重点研发计划资助项目(2023YFE0108600)；国家自然科学基金资助项目(51806190).

Corresponding Authors: Xiaojie LIN E-mail: boqm@163.com;xiaojie.lin@zju.edu.cn

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	Qiming BO
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	Pingyuan SHI
	Zhe DAI
	Wei ZHONG
	Lingkai ZHU

Cite this article:

Qiming BO,Meng YUAN,Yuchao WANG,Xiaojie LIN,Pingyuan SHI,Zhe DAI,Wei ZHONG,Lingkai ZHU. Configuration optimization for coupled green electricity steam heating systems considering time-of-use steam pricing. Journal of ZheJiang University (Engineering Science), 2025, 59(9): 1911-1919.

URL:

https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2025.09.015 OR https://www.zjujournals.com/eng/Y2025/V59/I9/1911

计及分时汽价的耦合绿电蒸汽供热系统配置优化

为了应对工业园区源荷双侧随机性强、可再生资源整合困难和灵活性低的挑战，开展计及分时汽价的耦合绿电工业园区蒸汽供热系统优化配置研究，提升系统的经济性与绿电消纳水平. 基于耦合绿电工业园区蒸汽供热系统建模，开展系统需求响应管理研究，通过设置分时汽价引导用户改变用汽行为，调节用户侧负荷，提高系统灵活性. 基于分时汽价优化定价结果，建立考虑规划设计与运行调度2阶段的工业园区蒸汽供热系统双层优化配置模型. 浙江某发电厂的案例分析结果表明，本研究提出的计及分时汽价的系统优化配置方法能够使用户峰谷负荷差减少58.32%，在热电联产机组出力上限为70%、60%和50%的3种不同场景下，优化配置方案分别能够降低系统总成本9.82、25.37、18.25万元. 本研究提出的计及分时汽价的系统优化配置方法可为工业园区蒸汽供热系统低碳转型提供指导.

关键词： 蒸汽供热系统, 电能替代, 需求响应, 双层优化配置, 工业园区

Fig.1 Energy flow diagram of coupled green electricity industrial park steam heating system basic

Fig.2 Coupled green electricity industrial park steam heating system bi-level optimization configuration framework considering time-of-use steam pricing

Fig.3 Certain power plant steam heating system topology diagram

Fig.4 Clustering results of park steam loads

Tab.1 Load response parameter settings for different types of users

Tab.2 Typical day system heat source output and user load data

Fig.5 Peak-valley period division results

Fig.6 Pareto set of time-of-use steam pricing optimization objective function

Tab.3 Time-of-use steam pricing optimization results

Tab.4 Pollutant emission data from different sources (g·kW⁻¹·h⁻¹)

Tab.5 Related equipment parameters

Tab.6 Bi-level optimization configuration results considering time-of-use pricing-equipment capacity

Tab.7 Bi-level optimization configuration results considering time-of-use pricing-economic performance

Tab.8 Bi-level optimization configuration results-equipment capacity without considering time-of-use pricing-equipment capacity

Tab.9 Bi-level optimization configuration results-economic performance considering time-of-use pricing-economic performance


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