Adaptability of industrial-civil coupled energy systems under uncertain operating conditions

doi:10.3969/j.issn.2097-0706.2025.10.008

Abstract

Abstract:

The comprehensive utilization of industrial waste heat and energy by-products to supply energy for surrounding buildings is an important means of integrated cascade utilization of energy. However， industrial production schedules and building energy consumption are relatively independent， each dominated by different factors. This introduces new uncertainties beyond conventional source-load variations， making the boundary conditions for system design decisions even more complex. Taking an industrial-civil coupled energy system in an industrial park in Shanghai as a case study， typical uncertain operating conditions—including year-by-year meteorological variations， occupancy rates， and energy prices—were defined. Four typical system configuration schemes were selected to quantify the adaptability of the integrated energy supply system to these uncertainties. The calculation results showed that configuring fuel cell combined cooling， heating， and power equipment at 10%—20% of the total installed capacity could significantly enhance system adaptability， and its economic performance under variable scenarios was superior to that of all-electric heat pump systems.

Key words: industrial-civil coupled energy system, industrial waste heat, uncertainty, meteorological conditions, occupancy rate, energy price, fuel cell, combined cooling， heating， and power, heat pump

CLC Number:

TK01

HUANG Zishuo, DOU Zhenlan, CHEN Jiaying. Adaptability of industrial-civil coupled energy systems under uncertain operating conditions[J]. Integrated Intelligent Energy, 2025, 47(10): 69-76.

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剩余不确定性	状态	特点	分析方法
第1层次	情景清晰明确	可进行单一性预测	量化模型模拟分析决策工具
第2层次	有几种高度可能的情景	有限的、离散的情景	定性分析、定量评估、博弈论
第3层次	情景在一定范围内变化	未来情景在一定范围内变化，没有离散的情景	区间规划模型、概率模型
第4层次	情景模糊不清	无法预测未来情景，时间短暂	类比和类型确认、场景遍历、模糊决策

方案	地源热泵/MW	燃料电池系统/MW	氢、燃气锅炉/MW	水冷冷水机组/MW	投资回收期/a
1	3.88				9.22
2	1.90	0.21		1.76	9.16
3	1.69	0.42		1.76	9.89
4			2.11	3.88	7.74