Charging Station Power Allocation for Peak Vehicle Energy Exchange
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Solution Overview
Problem
Existing systems fail to efficiently manage energy distribution among vehicles, leading to inefficiencies during peak usage periods and inadequate charging or fueling at service stations.
Innovation Solution
A method and system that utilizes a charging station to prioritize vehicles needing charge and those capable of providing charge, optimizing their arrival times and energy exchange using blockchain consensus and smart contracts to ensure efficient energy allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a charging station serves multiple vehicles simultaneously without prioritization, then the station can accommodate more vehicles, but the energy distribution becomes inefficient and delays occur during peak usage periods
Solution Approach 1:
The system performs preliminary actions by determining and prioritizing vehicles before they arrive at the charging station. The processor identifies vehicles needing charge and vehicles capable of providing charge in advance, schedules their arrival times, and prepares the energy allocation plan before peak usage periods begin, thereby eliminating delays during actual charging operations
Solution Approach 2:
The system implements dynamic prioritization by continuously adjusting vehicle groups based on real-time conditions. The processor can reassign vehicles between priority groups, modify arrival times, and adapt energy allocation as vehicles arrive, depart, or change their charge needs, allowing the station to optimize energy distribution efficiency while minimizing delays during peak usage
2Productivity
If the charging station prioritizes vehicles in advance, then charging efficiency improves, but the system complexity increases due to scheduling and coordination requirements
Solution Approach 1:
Vehicles in the second group (capable of providing charge) autonomously contribute to the charging station's energy supply without requiring complex manual coordination. The system leverages the vehicles' own energy resources and their willingness to provide charge, reducing the need for complex external management while improving charging efficiency
Solution Approach 2:
The system employs feedback mechanisms where vehicles communicate their charge status, availability, and capabilities to the charging station processor. This continuous feedback loop allows the system to make informed prioritization decisions and adjust schedules dynamically, achieving high charging efficiency through relatively simple decision-making based on real-time vehicle data
3Reliability
If the station optimizes for peak period utilization, then energy allocation improves, but the coordination overhead between vehicles and station increases
Solution Approach 1:
The system segments vehicles into distinct groups based on their charge needs and capabilities. By categorizing vehicles into those needing charge and those capable of providing charge, the system simplifies coordination overhead while ensuring reliable energy allocation during peak periods, as each group can be managed with targeted strategies rather than individual vehicle-by-vehicle coordination
Data Source
AI summary
An example operation includes one or more of determining, by a station, a first group of transports in need of charge and a second group of transports capable of providing charge, prioritizing, by the station, at least one transport of the second group to come to the station at a time prior to when at least one transport of the first group comes to the station, receiving, at the station, a first amount of charge from the at least one transport of the second group, and providing, from the station, a second amount of charge to the at least one transport of the first group.