Demand response method for energy storage and electric vehicle cluster cooperative scheduling
A technology of electric vehicles and demand response, which is applied in the direction of electric vehicles, electric vehicle charging technology, vehicle energy storage, etc., and can solve the problems of not considering energy storage and the coordinated participation of electric vehicle clusters in demand response, etc.
Pending Publication Date: 2020-12-15
ZHEJIANG UNIV +2
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Finally, previous demand response strategies based on energy storage systems usually consider energy storage systems to participate in demand response, or electric vehicles to participate in demand response as energy storage. For clusters composed of multiple household users, the coordinated participation of energy storage and electric vehicle clusters is usually not considered. Demand Response Strategies
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[0102] The present invention will be further elaborated and illustrated below in conjunction with the accompanying drawings and specific embodiments. The technical features of the various implementations in the present invention can be combined accordingly on the premise that there is no conflict with each other.
[0103] Such as figure 1 As shown, it is a demand response method for coordinated scheduling of energy storage and electric vehicle clusters according to the present invention, which is specifically as follows:
[0104] S1: Establish a total cost model for residential user clusters, the formula is as follows:
[0105] C T =C S,all +C E =C S,1 +C S,2 +C E ,
[0106] Among them, C T is the total annual cost of the cluster; C S,all Calculate the average annual cost for the purchase of centralized energy storage equipment, including the converted average annual purchase cost of the energy storage system C S,1 and the converted average annual purchase cost of t...
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The invention discloses a demand response method for energy storage and electric vehicle cluster cooperative scheduling. The method specifically comprises the following steps: S1, building a residentuser cluster total cost model which comprises building of a converted annual average purchase cost model of an energy storage system, a converted annual average purchase cost model of an energy storage module in an electric vehicle battery replacement station, and a cluster annual total power consumption cost model; S2, establishing a cooperative response strategy of a plug-in electric vehicle andan energy storage system; S3, establishing a cooperative response strategy of a battery replacement type electric vehicle and the energy storage system; and S4, selecting the number of users in the cluster, the number of electric vehicles and the number of standby batteries in the battery swap station, and calculating a target function value by adopting the resident user cluster total cost modelestablished in the S1, thereby optimizing the DL, the EC and the PC. The method can be effectively applied to the guidance work of the demand response scheme based on energy storage and electric vehicles in future community development, and the total energy storage cost and the power consumption cost of the user cluster in the community are reduced.
Description
technical field [0001] The invention belongs to the field of power demand side management, and in particular relates to a demand response method for collaborative scheduling of energy storage and electric vehicle clusters. Background technique [0002] The charging problem is one of the problems restricting the rapid development of electric vehicles. There are three main modes of energy supplementation for electric vehicles: (1) plug-in mode, (2) battery swap mode and (3) wireless charging mode. The basic equipment of plug-in electric vehicles is a charging station, which is equipped with charging piles, and the electric vehicle is a stop service model. The charging method in this mode takes a long time. The charging time of an electric vehicle in the fast charging state is about 15-30 minutes, and the charging time in the normal charging mode will be as long as 6-10 hours. If the charging time is too long, it will cause mileage anxiety. Due to the randomness and uncertain...
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Login to View More IPC IPC(8): G06Q10/06G06F30/20B60L53/60B60L53/80G06F111/06
CPCG06Q10/06315G06F30/20B60L53/60B60L53/80G06F2111/06Y02T10/70Y02T10/7072Y02T90/12Y04S10/50
Inventor 郑梦莲孙聚伟赵俊雄田世明韩凝晖栾开宁杨世海曹晓冬
Owner ZHEJIANG UNIV