Low Carbon Economy Optimization of Integrated Energy System Considering Electric Vehicle Charging Mode and Multi-Energy Coupling

doi:10.16183/j.cnki.jsjtu.2022.364

Abstract

Abstract:

In order to enable a multi-energy coupling integrated energy system (IES) to meet the needs of load diversity in low-carbon economic operation, a bi-level optimal configuration method for low-carbon economic operation of multi-energy coupling IES in different charging modes of electric vehicles (EVs) is proposed. First, an IES including cold-thermal-electric-gas coupling is established. Then, in the day-to-day operation stage, factors such as hierarchical carbon trading mechanism and different charging modes of EVs are considered to achieve the lowest daily scheduling cost. In the configuration planning stage, based on the daily operation cost, the equipment capacity is configured with the lowest equipment investment cost and annual operation cost. Finally, Cplex is used to solve the above two-stage objective functions and obtain the optimal configuration scheme and scheduling results through mutual iteration. The results show that the charging method considering the remaining charge of EVs and carbon trading mechanism can significantly reduce carbon emissions and operating costs of the system. The proposed configuration approach can well realize low-carbon economic operation of the multi-energy coupling IES.

Key words: integrated energy system (IES), electric vehicle (EV), bi-level optimization, configuration, low-carbon dispatch

CLC Number:

TM732

ZHANG Cheng, KUANG Yu, CHEN Wenxing, ZHENG Yang. Low Carbon Economy Optimization of Integrated Energy System Considering Electric Vehicle Charging Mode and Multi-Energy Coupling[J]. Journal of Shanghai Jiao Tong University, 2024, 58(5): 669-681.

Figures/Tables 20

Fig.1

Fig.2

Fig.3

Tab.1

Tab.2

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

Fig.9

Fig.10

Tab.3

季节	C_DR	C_GN	C_M	$C C O 2$	C_CCS	F₁
冬季	242	20141	348	2210	128	23069
过渡季	266	17537	329	2065	343	20540
夏季	428	19005	408	2720	718	23279

Tab.3

Fig.11

Tab.4

Tab.5

Tab.6

场景	C_DR	C_GN	C_M	$C C O 2$	C_CCS	F_inv
1	142051	7439914	141550	1114890	206504	2580400
2	131559	7163903	133932	959132	184592	2486810
3	110846	6776861	129983	840743	147061	2365655
4	109834	6770421	129063	827035	140345	2280380

Tab.6

Tab.7

场景	C_DR	C_GN	C_M	$C C O 2$	C_CCS	F₂
5	110235	6785386	120879	1167834	0	10348724
6	110846	6778248	128699	1117250	0	10281593
7	109834	6770421	129063	827035	140345	10257078

Tab.7

Fig.12

Fig.13

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时段	具体时间	电价/(元·kW^-1·h^-1)
峰时段	8:00—11:00,18:00—21:00	0.804
平时段	6:00—7:00,12:00—17:00	0.550
谷时段	1:00—5:00,22:00—24:00	0.295

能源设备	寿命/a	投资成本/ (元·kW^-1)	维护成本/ (元·kW^-1)	效率
WT	25	10000	0.01
PV	25	12000	0.01
GB	20	8000	0.01	0.9
AC	15	1000	0.01	0.99
EC	15	1500	0.02	3
ES	20	800	0.15	0.9
HS	20	50	0.05	0.95
CS	20	100	0.05	0.95
WHB	15	200	0.05	0.4
HST	20	600	0.15	0.95
GT	15	7800	0.01	0.7
EB	15	7500	0.01	0.9
EW	15	13500	0.01	0.8
MET	15	15000	0.01	0.8

季节	峰谷差/kW
季节	初始	优化后	考虑EV
夏季	579.1	415.0	493.2
冬季	341.0	242.5	272.1
过渡季	378.9	254.0	310.0

负荷类型	配置容量/(kW·h)
负荷类型	场景1	场景2	场景3	场景4
WT	290	290	290	280
PV	290	280	277	272
GB	13	24	25	26
AC	104	104	75	66
EC	225	224	223	227
ES	125	126	127	107
HS	364	397	383	243
CS	304	243	266	200
WHB	106	96	85	74
HST	271	260	262	263
GT	837	722	631	536
EB	257	262	264	270
EW	102	103	90	92
MET	440	443	423	423