Patent ID: 11878602
Assignee: STATE GRID FUJIAN ELECTRIC POWER COMPANY LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC B  H  G  Y | IPC B  G  H

Claim 0:
1. A method for establishing an active distribution network planning model considering location and capacity determination of an electric vehicle charging station, comprising the following steps:
step S1: establishing a traffic network, and establishing, based on an M/M/s queuing model and a flow capturing location model, a traffic network comprising an electric vehicle charging station;
step S2: establishing an active distribution network model, and establishing a distributed generation and load time-series model based on a time series method; and establishing an energy storage model based on an equivalent load principle; and
step S3: converting a traffic flow of electric vehicles into an equivalent load of an equivalent charging station, coupling the traffic network with a power grid, and establishing an active distribution network nested planning model considering the traffic network;
wherein step S1 particularly comprises:
step S11: calculating an EV charging capacity demand;
calculating a battery pack quantity demand;, N
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in the formula: NB is a daily demand for battery packs; NEVi is a stock of an ith-type EV: Ld and L0i are respectively an average daily mileage of the ith-type EV and a distance at which the ith-type EV travels on a full charge; and ai, bi, and KEVdi are respectively attendance rates, a battery replacement ratio, and the number of battery packs per vehicle for the ith-type EV;
the charging capacity demand is:

WB=NBPCtcharge/(ηtranηcharge)  (2)

in the formula: ηtran is transformer efficiency; ηcharge is charger efficiency; Pc denotes an average charge power; and tcharge denotes a charging time;
step S12: establishing a charging station location and capacity determination model;
calculating a traffic flow FCS annually intercepted by a system-wide charging station by using a gravity space interaction model in combination with a Floyd algorithm; of which a calculation formula is as follows; and
calculating a traffic flow intercepted by a single charging station according to the following formulas:, f
            
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in the formula (3): fk,tread denotes a per-unit value of a one-way traffic flow demand of the shortest path k in a period t: ωko and ωkd are traffic demand weights of a starting point and an ending point of the path k respectively, used to indicate busyness degrees of traffic nodes; Dk is a per-unit value of the length of the path k; σt and σRH are travel ratios of EV users in a period t and a peak hour h respectively; Ωod is a set of shortest paths from any starting point o to any ending point d in the traffic network and is obtained according to the Floyd algorithm; T is a set of periods; and xkload indicates a binary variable of whether a flow on the path k can be intercepted by a charging station, if the path k passes through the charging station, the variable is l, and otherwise, the variable is 0;
calculating an equivalent charging load according to the traffic flow intercepted by the single charging station in the following calculation manners;, f
            
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in the formula (5), fi,tCS is a traffic flow intercepted by a node i in a period t; xk,iroad is a binary variable of whether the path k passes through the node i; xiCS is a binary variable of whether a charging station is constructed at the node i; Ω is a set of network nodes: λi,t is the number of electric vehicles arriving at the charging station located at the node i at time t to receive a charging service; in the formula (6), Pi,tCS is a charge power of the node i at the time t; λtRH is an average arrival rate of to-be-charged vehicles at the node i during rush hours, i.e. the number of EVs arriving at the charging station to receive the charging service per unit of time; {tilde over (F)}CS is a total daily charging frequency demand of an EV charging station and needs to be calculated according to WB in the formula (2): {tilde over (F)}CS=WB/preset maximum battery pack capacity; WB is a charging capacity: in the formula (7), pCS is a charge power of a single charging device; and μ is an average service rate of a single device, in units of vehicles per hour; and
step S13: transforming, based on the M/M/s queuing model, a capacity determination problem of a charging station into the following nonlinear integer planning problems:, min
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in the formulas: ziCS is the number of charging devices configured for the node i, which is multiplied by pCS to obtain the capacity of the charging station at node i; WiRH and Wallowed are an average waiting time for receiving a charging service during rush hours and a threshold thereof respectively; Pinon is the probability that charging station devices at the node i are all idle; and ρtRH is an average device usage rate of the node i during rush hours.