计及EV的综合能源系统双层优化调度策略

doi:10.16180/j.cnki.issn1007-7820.2024.11.012

Abstract

Abstract:

In order to solve the optimal scheduling problem of large-scale electric vehicles into the network, a two-layer optimal scheduling strategy of integrated energy system with electric vehicles is proposed in this study. The upper layer is the optimal dispatching layer, in which electric vehicle agents group electric vehicles into clusters according to the dispatchable time and upload the cluster information to the system dispatching center, which cooperates with electric vehicle clusters and energy systems and builds an economic dispatching model with the goal of minimizing the dispatching cost by considering integrated demand response and ladder-type carbon trading mechanism. The lower layer is the power allocation layer, where electric vehicle agents build a power allocation model with the goal of satisfying users' travel demand, and guide electric vehicles to participate in system scheduling in an orderly manner. The simulation algorithm is constructed and solved by using CPLEX solver. The simulation results show that the proposed strategy can not only effectively reduce the scheduling cost of integrated energy system, smooth the system load curves and reduce carbon emissions, but also significantly reduce the cost of electricity consumption of customers on the basis of securing their travel demand, thus achieving a win-win situation for both supply and demand.

Key words: electric vehicles, integrated energy system, integrated demand response, stepped carbon trading, orderly charging and discharging, time-of-use electricity price, optimal dispatch, V2G

CLC Number:

TP29

SHAO Wenfeng, HE Yu, WEN Yongjun, NIE Xianglun, ZHANG Tangqian, KAN Chao. Bi-Level Optimal Scheduling Strategy of Integrated Energy System Considering EV[J].Electronic Science and Technology, 2024, 37(11): 85-94.

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集群	不可调度时段	占比/%
1	7∶00~8∶00,17∶00~18∶00	12
2	7∶00~8∶00,18∶00~19∶00	18
3	7∶00~8∶00,19∶00~20∶00	23
4	8∶00~9∶00,17∶00~18∶00	10
5	8∶00~9∶00,18∶00~19∶00	21
6	8∶00~9∶00,19∶00~20∶00	16

设备	容量/kWh	充能效率	放能效率
蓄电池	1 000	0.95	0.95
蓄热槽	1 000	0.98	0.98

设备	功率上限/kW	功率下限/kW	爬坡限制/kW·h^-1
GT	800	0	160
GB	1 500	0	300
ER	150	0	-
AR	500	0	250
蓄电池	200	-200	200
蓄热槽	200	-200	200

设备	运维成本/元·(kWh)^-1
GT	0.168 50
GB	0.001 80
ER	0.010 40
AR	0.015 60
WT	0.012 60
PV	0.013 29

时段	购电价格/元·(kWh)^-1		售电价格/ 元·(kWh)^-1	购气价格/ 元·m^-3
时段	电网	EV	售电价格/ 元·(kWh)^-1	购气价格/ 元·m^-3
00∶00~07∶00	0.42	—	0.27	3.2
08∶00~11∶00 17∶00~20∶00	1.20	0.90	0.80	3.9
12∶00~16∶00 21∶00~23∶00	0.80	0.78	0.60	3.5

Bi-Level Optimal Scheduling Strategy of Integrated Energy System Considering EV

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成本	方案1	方案2	方案3
运维成本/元	2 251	2 090	2 362
燃料成本/元	13 989	13 433	14 045
电网交互成本/元	1 646	872	313
EV交互成本/元	-212	736	177
碳排放成本/元	-	-	-922
碳排放量/kg	8 421	9 062	7 760
总成本/元	17 674	17 131	15 975

成本	方案1	方案2	方案3
EV充电成本/元	212	1 038	549
EV放电收益/元	-	1 774	726
EV用户总成本/元	212	-736	-177

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集群	EV数量/辆	出行能量需求/kWh
1	12	48
2	18	83
3	23	147
4	10	41
5	21	89
6	16	91