EV Charging Station Battery Sizing From Fuel Demand Conversion
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Solution Overview
Problem
The challenge of sizing electric charging stations for future demand, particularly in locations previously used as fuel stations, where there is a need to balance the number of charging points and electrical network capacity to avoid overload and ensure efficient charging operations.
Innovation Solution
A method and device that convert historical fuel consumption data into equivalent electric charging sessions, using probability distributions for charging power based on vehicle categories, to determine the optimal number of electric charging points and compensation battery sizing for a charging station, ensuring it can meet future demand without exceeding electrical network capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the number of charging points is increased to meet future electric vehicle demand, then the charging station can serve more vehicles and reduce waiting times, but the electrical network capacity may be exceeded causing overload
Solution Approach 1:
The patent performs preliminary sizing calculations before the charging station is operational. Historical fuel consumption data is analyzed and converted to equivalent electric charging sessions to predict future demand patterns. This advance planning allows the electrical network capacity to be properly sized before peak loads occur, preventing overload while ensuring sufficient charging capacity.
Solution Approach 2:
The patent transforms parameters from the fuel station context to the electric vehicle charging context. Fuel consumption volumes are converted to equivalent charging energy requirements using conversion factors. This parameter transformation enables accurate prediction of charging demand based on historical fuel usage patterns, allowing proper sizing of both charging points and electrical network capacity.
2Productivity
If the number of charging points is optimized based on accurate demand prediction, then waiting times and energy not delivered are minimized, but complex calculations and data processing are required
Solution Approach 1:
The patent creates a simplified model by copying historical fuel consumption patterns and transforming them into equivalent charging sessions. Instead of complex real-time simulations, the system uses a straightforward conversion approach where fuel volume data is multiplied by conversion factors to estimate charging energy needs. This copied and transformed data provides sufficient accuracy for sizing decisions without requiring complex computational models.
Data Source
Figure 1
Figure 2a~2b
Figure 2c~2d
AI summary
The present disclosure relates to a method for sizing a charging station for electric vehicles, in view of operating the charging station at a future period of time T, the charging station being installed at the location of a fuel station operated over a past or current period of time N, said charging station comprising at least one electric charging point and being connected to an electrical network, the method being implemented by a device comprising a circuit and a memory, the memory comprises consumption data specific to the previously operated fuel station for the period of time N comprising a set of fuel consumption sessions, and at least one charging power probability distribution as a function of vehicle categories; the method comprises: /a/ converting fuel consumption sessions into a set of equivalent electric charging sessions; Ibl for each equivalent electric charging session, determining an average charging power based on the charging power probability distribution and the equivalent electric charging session; /c/ determining (320) a sizing of the at least one compensation battery of the charging station from the average charging powers of the equivalent electric charging sessions determined for the period T, so that the compensation battery allows to temporally increase the maximum load capacity of the electrical network when an electrical load demand of the charging station is superior to the maximum load capacity of the electrical network.