Ride-Sharing EV V2G Dispatch for Building Peak Power Demand
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Solution Overview
Problem
The increasing power consumption due to added facilities in buildings and the need to mitigate rising power bills and prevent power facility degradation in electric vehicles (EVs) are not adequately addressed by existing technologies, while the growing ride-sharing market presents an opportunity for integration.
Innovation Solution
An electric vehicle charging and discharging apparatus and method that links ride-sharing services with vehicle-to-grid (V2G) technology, utilizing EV batteries to optimize power usage by predicting building power demands, estimating travel demand, and setting efficient travel paths for EVs to discharge surplus power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If EV batteries are used for V2G discharging to reduce building power consumption, then power facility degradation is prevented and operating cost is reduced, but ride-sharing service availability may be compromised
Solution Approach 1:
The system dynamically adjusts the EV's function based on real-time conditions. The processor determines whether the EV should perform ride-sharing, V2G discharging, or charging based on predicted power consumption patterns, current battery state, and ride-sharing demand, allowing the vehicle to switch roles flexibly throughout the day
Solution Approach 2:
The system performs preliminary power consumption prediction for buildings and preliminary ride-sharing demand estimation before making dispatch decisions. This advance planning allows the system to schedule V2G discharging during periods of high power demand while ensuring ride-sharing availability during peak travel periods
2Use of energy by stationary object
If building power consumption is reduced through V2G discharging, then power bills are reduced, but additional power infrastructure capacity is required
Solution Approach 1:
The system continuously monitors actual power consumption data from buildings and compares it with predicted values. This feedback mechanism allows the system to learn from actual performance and optimize future V2G discharging schedules, ensuring that discharging operations actually reduce power bills while accounting for variations in building usage patterns
Solution Approach 2:
The system changes the operational parameters of the power infrastructure by utilizing the EV battery as a mobile power source. Instead of permanently increasing grid capacity, the system dynamically injects power from the EV battery during peak demand periods, effectively reducing the required permanent infrastructure capacity
3Productivity
If ride-sharing travel paths are optimized for profitability, then operating cost is reduced, but passenger service quality may be affected
Solution Approach 1:
The EV serves multiple functions simultaneously - it provides ride-sharing service, acts as a mobile power station for V2G discharging, and functions as a charging unit. This multi-functionality allows the system to optimize for profitability through V2G operations while maintaining adequate ride-sharing service through the universal nature of the vehicle
Solution Approach 2:
The system implements periodic cycles of ride-sharing service and V2G discharging/charging operations. The processor schedules periods of ride-sharing service alternating with periods of power discharging to the grid, creating a rhythmic pattern that balances profitability with service quality
Data Source
AI summary
An electric vehicle charging and discharging apparatus for linking ride-sharing service and vehicle-to-grid may include a processor and a memory storing software, when executed by the processor, causing the processor to collect power data of buildings, predict power consumption of the buildings based on the power data, respectively, calculate a time zone in which an additional power is required for each of the buildings and a required amount of electrical power based on the collected power data and the predicted power consumption, estimate a travel demand of a region where the buildings exist, and set a travel path of a ride-sharing vehicle for each time zone within the region based on the time zone requiring the additional power, the required amount of electrical power and the travel demand.