Optimal Scheduling of Integrated Energy Systems Considering Source-load Uncertainty and Linear Carbon Trading

doi:10.16182/j.issn1004731x.joss.25-0521

Abstract

Abstract:

In order to overcome the impact of source-load uncertainty on the scheduling of integrated energy systems (IES) and reflect the flexibility of the carbon trading price with the change in trading volume, an optimal scheduling method for integrated energy systems considering source-load uncertainty and linear carbon trading was proposed. The equipment within the IES was modeled, and nonparametric kernel density estimation was used to obtain the probability density function for each time period, generating the set of scenes through Monte Carlo simulation and calculating the probability of each scene. For the time shift of wind and solar output peaks and fluctuations, the scene set was processed using a scene reduction method that integrated the dynamic time warping (DTW) distance and K-medoids clustering to obtain the typical scenes and probabilities.Alinear carbon trading mechanism was designed, which was derived from the ladder carbon trading mechanism, and an IES optimization scheduling model was established. The simulation results show that the proposed method can effectively promote the low-carbon operation of the IES.

Key words: integrated energy system, source-load uncertainty, carbon trading mechanism, nonparametric kernel density estimation method, dynamic time warping distance

CLC Number:

TP391.9

Zhong Huaping, Fan Yubo, Shui Jijun, Wang Danhao, Peng Daogang. Optimal Scheduling of Integrated Energy Systems Considering Source-load Uncertainty and Linear Carbon Trading[J]. Journal of System Simulation, 2025, 37(10): 2485-2499.

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现有研究	场景生成方法	初始场景概率	场景削减方法
文献[5]	拉丁超立方抽样	概率均等	Kantorovich距离
文献[24]	韦伯分布和贝塔分布、蒙特卡罗	概率均等	曼哈顿距离、概率距离
文献[29]	蒙特卡罗	概率均等	欧式距离、K-means、同步回代、FCM聚类
本文	核密度估计法、蒙特卡罗	非等概率	DTW、K-medoids聚类

分类	时段	价格/(元/kW·h)
峰	12:00—15:00	1.22
峰	18:00—21:00	1.22
平	07:00—12:00	0.69
	15:00—18:00
	21:00—22:00
谷	00:00—07:00	0.40
谷	22:00—24:00	0.40

设备类型	参数	数值
柴油发电机组 (DG)	油电转化系数	4.6
	额定功率/kW	1 000
	运维系数	0.05
	CO₂排放系数/(kg/kW·h)	0.74
热电联产机组 (CHP)	电\热比	0.6\0.35
	额定功率/kW	1000
	运维系数	0.04
	电功率排放系数/(kg/kW·h)	0.580
	单位热电功率排放比	0.6
燃气锅炉 (GB)	制热效率	0.72
	额定功率/kW	600
	运维系数	0.03
	CO₂排放系数/(kg/kW·h)	0.36
电转气设备 (P2G)	工作效率	0.6
	气电比/(m³/kW·h)	0.25
	额定功率/kW	600
	运维系数	0.028
电锅炉 (EB)	制热效率	0.95
	额定功率/kW	300
	运维系数	0.021

参数	储能柜	蓄热罐	储气罐
自损率	0.05	0.10	0.02
充\放能效率	0.92\0.90	0.95\0.85	0.95\0.95
最大充\放能功率/kW	400\300	350\300	300\250
充\放能运维系数	0.018\0.016	0.016\0.014	0.015\0.013
平均充放次数	12	—	12
爬坡上限/kW	500	400	500
最大容量/(kW·h)	1 000	800	1 000
最小安全容量/(kW·h)	100	50	100
最大安全容量/(kW·h)	950	750	950

场景	总成本/元	碳排放/kg	P2G消耗量/kg	免费碳配额/kg	碳交易量/kg
I	21 315.06	22 716.22	8 977.28	9 090.15	4 648.78
II	21 774.74	18 627.67	8 945.82	7 299.02	2 382.83
III	20 927.43	22 986.87	8 977.28	9 205.98	4 803.60