计及㶲效率和多重不确定性的区域综合能源系统双层优化

doi:10.11930/j.issn.1004-9649.202404018

中国电力 ›› 2025, Vol. 58 ›› Issue (1): 128-140.DOI: 10.11930/j.issn.1004-9649.202404018

计及㶲效率和多重不确定性的区域综合能源系统双层优化

鲁玲¹^,²(), 苑涛¹(), 杨波³(), 李欣¹^,²(), 鲁洋¹, 蒲秋平¹, 张鑫¹

1. 三峡大学电气与新能源学院，湖北宜昌　443002
2. 三峡大学智慧能源技术湖北省工程研究中心，湖北宜昌　443002
3. 国网武汉供电公司，湖北武汉　430015

收稿日期:2024-04-01 出版日期:2025-01-28 发布日期:2025-01-23
作者简介:鲁玲（1979—），女，通信作者，硕士，副教授，从事综合能源系统运行与规划、电力设备状态监测与智能决策研究，E-mail：luling@ctgu.edu.cn
苑涛（1998—），男，硕士研究生，从事区域综合能源系统运行与调度优化研究，E-mail：1213576804@qq.com
基金资助:
国家自然科学基金资助项目（基于集成-深度学习的高比例新能源大规模电力系统动态安全评估研究，52107107）。

Two-Layer Optimization of Regional Integrated Energy System Considering Exergy Efficiency and Multiple Uncertainties

Ling LU¹^,²(), Tao YUAN¹(), Bo YANG³(), Xin LI¹^,²(), Yang LU¹, Qiuping PU¹, Xin ZHANG¹

1. College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, China
2. Hubei Provincial Engineering Center for Intelligent Energy Technology, China Three Gorges University, Yichang 443002, China
3. State Grid Wuhan Power Supply Company, Wuhan 430015, China

Received:2024-04-01 Online:2025-01-28 Published:2025-01-23
Supported by:
This work is supported by National Natural Science Foundation of China (Research on Dynamic Safety Assessment of High-Proportion Renewable Energy Large-Scale Power System Based on Ensemble-Deep Learning, No.52107107).

摘要/Abstract

摘要：

为实现能量高质量、高效率的利用，同时提高系统供能可靠性，针对含高比例的可再生能源的区域综合能源系统，引入“㶲”的概念，提出了一种计及㶲效率和多重不确定性的双层优化方法。首先，建立了区域综合能源系统的多能耦合模型，进行㶲分析和多重不确定性分析，并且针对风光不确定性、负荷和能源价格波动的不同特点，分别采取多场景随机规划和区间优化的方法进行处理。然后，建立了上层以㶲效率和经济性为优化目标，下层以运行成本最低为优化目标，兼顾系统容量规划和调度运行的双层协同优化模型。最后，选取某园区进行算例分析，验证了所提方法的有效性，与其他不确定因素相比，电负荷的波动对系统的经济和㶲效率影响更大。

关键词: 区域综合能源系统, 可再生能源, ?效率, 多重不确定性, 双层优化

Abstract:

In order to realize high quality and efficiency utilization of energy while improving the reliability of system energy supply, the concept of exergy is introduced into regional integrated energy system containing a high proportion of renewable energy, and a two-layer optimization method is proposed considering exergy efficiency and multiple uncertainties. Firstly, a multi-energy coupling model of regional integrated energy system is established for exergy and multi-uncertainties analysis. Multi-scene random planning and range optimization methods are adopted to deal with exergy for different characteristics of solar and wind power uncertainty, along with load and energy price fluctuations. Then, a two-layer collaborative optimization model balances system capacity planning and scheduling operations is constructed, with both exergy efficiency and economy as the optimization goal in the upper layer, and the lowest operating cost as the optimization goal in the lower layer. Finally, an industrial park is selected for example analysis to verify the effectiveness of the proposed method in this paper. Compared with other uncertain factors, the fluctuation of electrical load has a greater impact on the economy and exergy efficiency of the system.

Key words: regional integrated energy system, renewable energy, exergy efficiency, multiple uncertainties, two-layer optimization

鲁玲, 苑涛, 杨波, 李欣, 鲁洋, 蒲秋平, 张鑫. 计及㶲效率和多重不确定性的区域综合能源系统双层优化[J]. 中国电力, 2025, 58(1): 128-140.

Ling LU, Tao YUAN, Bo YANG, Xin LI, Yang LU, Qiuping PU, Xin ZHANG. Two-Layer Optimization of Regional Integrated Energy System Considering Exergy Efficiency and Multiple Uncertainties[J]. Electric Power, 2025, 58(1): 128-140.

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https://www.electricpower.com.cn/CN/Y2025/V58/I1/128

图/表 20

图 1 区域综合能源系统基本结构

Fig.1 Basic structure of regional integrated energy system

表 1 能量品质系数

Table 1 Energy quality coefficient

能量类型		品质系数
电能		1.00
天然气		0.51
热能		0.10~0.20
冷能		0.05~0.08

图 2 㶲分析模型

Fig.2 Exergy analysis model

图 3 场景缩减流程

Fig.3 Scene reduction process

图 4 RIES双层优化模型

Fig.4 Two-layer optimization model for RIES

图 5 双层优化模型求解流程

Fig.5 The solution process of two-layer optimization model

表 2 价格参数

Table 2 Price parameters

时段	电价/ (元·(kW·h)^–1)	天然气价格/ (元·m^–3)	碳税/ (元·(kgCO₂)^–1)
10:00—14:00	1.040	2.37	0.23
19:00—22:00	1.040
00:00—07:00	0.315
23:00—24:00	0.315
其他	0.630

表 3 设备参数

Table 3 Parameters of equipment

设备	能源转换效率	㶲效率	单位成本/ (元·(kW)^–1)	运维成本/ (元·(kW·h)^–1)
WT	0.32	1.000	8000	0.030
PV	0.16	1.000	5000	0.030
STC	0.60	1.000	5600	0.030
CCHP	0.88	0.745	7000	0.300
PtG	0.60	0.306	5500	0.150
EB	0.95	0.190	1000	0.032
GB	0.85	0.283	850	0.020
AC	0.85	0.295	1200	0.042
EC	3.00	0.245	1470	0.077

图 6 典型日负荷和可再生能源预测出力

Fig.6 Typical daily load and renewable energy forecast output

表 4 不同方案下经济性和能效对比

Table 4 Comparison of economy and energy efficiency under different schemes

项目	方案1	方案2	方案3	方案4
运维成本/元	20112	32215	76343	30110
能耗成本/元	263890	301490	250450	241670
碳排放成本/元	11108	14415	9437	10325
运行成本/元	295110	348120	336230	282105
投资成本/元	63650	34420	111100	106245
总成本/元	358760	382540	447330	388350
㶲效率/%	63.59	60.42	69.59	66.89
能源利用效率/%	80.79	87.85	83.04	87.03

图 7 上限子模型电能调度

Fig.7 Upper limit sub-model power scheduling

图 8 下限子模型电能调度

Fig.8 Lower limit sub-model power scheduling

表 5 区间优化运行经济结果

Table 5 Economic results of interval optimization operation

成本类型	区间/元	区间平均值/元	区间宽度/ 元	相对区间差/%
碳排放成本	[7540, 13323]	10431.5	5783	43.4
能耗成本	[194920, 309540]	252230.0	114620	37.0
运维成本	[404450, 48228]	44336.5	7783	16.1
运行成本	[250690, 363310]	307000.0	112620	31.0
投资成本	[83341, 79384]	81344.5	3993	4.8
总成本	[334030, 442660]	388345.0	108630	24.5

表 6 区间优化运行能效结果

Table 6 Energy efficiency results of interval optimization operation 单位：%

项目	区间	区间平均值	区间宽度	相对区间差
能源利用效率	[86.52, 87.53]	87.025	1.01	1.15
㶲效率	[64.19, 67.78]	65.985	3.59	5.30

图 9 不同波动比例下设备容量的配置

Fig.9 Device capacity configuration under different fluctuation ratios

图 10 多种不确定因素不同波动比例下的区间平均值

Fig.10 The interval average value under different fluctuation ratio of multiple uncertain factors

图 11 多种不确定因素不同波动比例下的区间宽度

Fig.11 The interval width under different fluctuation ratio of multiple uncertain factors

图 12 多种不确定因素不同波动比例下的区间相对差

Fig.12 The interval relative difference under different fluctuation ratio of multiple uncertain factors

表 7 单一不确定因素波动下的相对区间差

Table 7 The relative interval difference under the fluctuation of one single uncertain factor 单位：%

波动类型	碳排放成本	能耗成本	运维成本	运行成本	投资成本	总成本	㶲效率
电价波动EP	0.69	8.86	1.88	7.60	0.28	6.09	0.23
电负荷波动EL	18.24	14.26	1.60	12.74	0.55	10.06	7.39
气价波动GP	0.68	5.38	1.56	4.29	0.15	3.42	0.06
气负荷波动GL	3.45	2.32	6.00	1.24	0.72	0.43	0.37

图 13 不同电负荷波动比例下的区间相对差

Fig.13 The relative interval difference of the interval under different electric load fluctuation ratio

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计及㶲效率和多重不确定性的区域综合能源系统双层优化

Two-Layer Optimization of Regional Integrated Energy System Considering Exergy Efficiency and Multiple Uncertainties

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计及㶲效率和多重不确定性的区域综合能源系统双层优化

Two-Layer Optimization of Regional Integrated Energy System Considering Exergy Efficiency and Multiple Uncertainties

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PDF (PC)

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参考文献 28

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