Low-Carbon Economic Scheduling of Virtual Power Plants With Hydrogen-Blended Gas and Liquid-Storage CCS Coupled P2G

doi:10.12096/j.2096-4528.pgt.260214

Abstract

Abstract:

Objectives In the process of achieving the “dual carbon” goals, virtual power plants, as a new energy management system, can enhance the flexibility and energy efficiency of the power grid. Issues such as the failure of coupling between power-to-gas (P2G) and carbon capture system (CCS), low energy utilization efficiency, high volatility of renewable energy, and insufficient incentives from emission reduction policies have affected the economic viability of virtual power plants. Therefore, an optimized scheduling model that balances low-carbon and economic considerations is proposed based on liquid storage CCS and gas hydrogen blending equipment. Methods From the two perspectives of innovative low-carbon equipment and carbon trading policy, mathematical models are first established for the liquid-storage carbon capture system coupled with power-to-gas equipment, gas turbines, electric heating furnaces, and energy storage equipment. Secondly, tiered carbon trading prices are designed for different carbon emission levels, and price compensation factors and price growth factors are introduced to incentivize virtual power plants to reduce emissions. Optimized scheduling strategies with economic and low-carbon objectives as the target functions are proposed. Finally, the model is processed using a linearization method for efficient solution. Case analysis sets different hydrogen blending ratio scenarios, different coupled equipment scenarios, and different carbon trading mechanism scenarios to validate the effectiveness of the proposed model. Results Compared with the virtual power plant before modification, variable hydrogen blending operation and the liquid-storage P2G-CCS coupling equipment reduce operating costs by 6.21% and 12.62%, respectively, and the tiered carbon trading price reduces carbon emissions of the virtual power plant by 12.96%. Conclusions The proposed scheduling model can effectively achieve low-carbon emissions, enhance wind power integration capability, and reduce operating costs of virtual power plants.

Key words: virtual power plants, low-carbon scheduling, carbon capture, tiered carbon trading, hydrogen-blended gas

CLC Number:

TK 01

Yaoyao HE, Yasheng WANG. Low-Carbon Economic Scheduling of Virtual Power Plants With Hydrogen-Blended Gas and Liquid-Storage CCS Coupled P2G[J]. Power Generation Technology, 2026, 47(2): 370-382.

Figures/Tables 13

Fig. 1 VPP structure of liquid storage CCS-P2G and hydrogen-blended gas

Fig. 2 Liquid-storage carbon capture system

Tab. 1 Parameter settings

设备	参数	数值
火电机组	最大(最小)发电功率/MW	85(0)
火电机组	爬坡功率上限(下限)/MW	100(-100)
电转气机组	甲烷化效率	0.75
	电转氢效率	0.85
	最大(最小)耗电功率/MW	125(0)
碳捕集设备	最大耗电功率/MW	135
	贫液存储设备最大(最小)容量/m³	27 000(0)
	富液存储设备最大(最小)容量/m³	27 000(0)
燃气轮机	最大(最小)发电功率/MW	350(0)
	最大(最小)产热功率/MW	300(0)
	爬坡功率上限(下限)/MW	150(-150)
	产电(热)效率	0.5(0.45)
燃气锅炉	最大(最小)产热功率/MW	80(0)
燃气锅炉	爬坡功率上限(下限)/MW	25(-25)
电热炉	最大(最小)产热功率/MW	45(0)
电热炉	爬坡功率上限(下限)/MW	10(-10)
其他	燃煤价格/(元/t)	500
	碳封存成本/(元/t)	50
	天然气价格/(元/m³)	3.5
	初始碳价/(元/t)	205
	再生塔处理CO₂能耗系数/(MW⋅h/t)	0.269

Tab. 2 Scheduling results under different hydrogen blending scenarios

成本	场景1	场景2	场景3
总成本	502.12	484.54	472.76
启停成本	15.62	15.52	15.01
购气成本	419.28	412.18	410.06
碳交易成本	1.76	-2.55	-10.49
碳封存成本	0	1.02	2.38
弃风成本	25.02	16.21	11.42
燃煤成本	40.44	42.16	44.38

Tab.3 Equipment output under different hydrogen blending scenarios

机组设备出力	场景1	场景2	场景3
火电机组功率/MW	1 228.09	1 346.99	1 382.05
燃气轮机电功率/MW	3 809.51	3 789.344	4 102.06
燃气轮机热功率/MW	4 353.72	4 326.67	4 330.69
燃气锅炉热功率/MW	1 910.49	1 913.14	1 920
电热炉电功率/MW	920.21	940.839	934.13
CCS设备消耗电功率/MW	110.39	113.51	177.39
P2G设备消耗电功率/MW	1 564.12	1 636.59	1 456.56

Fig. 3 Hydrogen consumption power under different hydrogen blending ratios

Fig. 4 Scheduling results under different equipment scenarios

Fig. 5 CO2 emissions and total costs under a tiered carbon trading system

Fig. 6 CO2 emissions and total costs under a fixed carbon trading system

Tab. 4 Variation in carbon emission sources and their quantities under different carbon trading prices

碳价格/元	阶梯式		固定式
碳价格/元	$m t C O 2, g a s$ /t	$m t C O 2, C C S, g a s$ /t	$m t C O 2, g a s$ /t	$m t C O 2, C C S, g a s$ /t
140	3 232.47	53.21	3 289.21	54.34
160	3 204.23	52.35	3 285.14	54.32
180	3 198.24	53.98	3 283.96	55.48
200	3 087.24	49.21	3 271.04	52.19
220	3 012.65	48.82	3 182.34	52.22
240	2 823.25	48.82	3 166.12	52.23
260	2 822.98	48.83	3 163.08	51.75
280	2 820.76	48.81	3 161.28	52.72

Tab. 4 Variation in carbon emission sources and their quantities under different carbon trading prices

碳价格/元	阶梯式		固定式
碳价格/元	$m t C O 2, g a s$ /t	$m t C O 2, C C S, g a s$ /t	$m t C O 2, g a s$ /t	$m t C O 2, C C S, g a s$ /t
140	3 232.47	53.21	3 289.21	54.34
160	3 204.23	52.35	3 285.14	54.32
180	3 198.24	53.98	3 283.96	55.48
200	3 087.24	49.21	3 271.04	52.19
220	3 012.65	48.82	3 182.34	52.22
240	2 823.25	48.82	3 166.12	52.23
260	2 822.98	48.83	3 163.08	51.75
280	2 820.76	48.81	3 161.28	52.72

Fig. 7 Carbon trading volumes and trading intervals under a tiered carbon trading system

Fig. 8 Effect of base price and price growth rate on carbon emissions

Fig. 9 Effect of base price and compensation coefficient on carbon emissions

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