Transport Climate Control Power Scheduling Across Multi-Station Supply
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Solution Overview
Problem
Existing power distribution systems for electrically powered accessories in vehicles and transport containers face challenges in optimizing power usage to minimize costs and ensure continuous operation, especially during peak demand periods and varying infrastructure capacities.
Innovation Solution
A method and system for optimizing power distribution by using infrastructure, vehicle, and external data to generate a scheduling model that coordinates power distribution across multiple electrical supply equipment stations, incorporating a power converter stage, transfer switch matrix, and a power distribution controller to manage power sources and demand dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If power is distributed to multiple electrically powered accessories simultaneously, then the accessories can operate continuously, but the power demand rate increases and costs increase
Solution Approach 1:
The system performs preliminary actions by charging accessories' energy storage devices before peak demand periods or when power rates are lower. The optimization controller schedules power distribution to charge batteries or capacitors in advance, allowing accessories to operate from stored energy during high-cost periods, thus reducing instantaneous power demand rates while maintaining continuous operation.
Solution Approach 2:
The system dynamically adjusts power distribution schedules based on real-time conditions including power demand rates, accessory operational needs, and energy storage status. The optimization controller continuously modifies the power distribution plan to balance reliability requirements with cost minimization, adapting to changing conditions in the electrical environment.
2Reliability
If power distribution capacity is increased to handle peak demand, then accessories can operate without interruption, but the infrastructure cost and capacity strain increase
Solution Approach 1:
Energy storage devices serve as intermediary elements between the power distribution system and the electrically powered accessories. These intermediaries store excess power when available and release it during peak demand, decoupling the instantaneous power demand from the infrastructure capacity requirements. This allows the system to maintain reliability without proportionally increasing infrastructure capacity.
Solution Approach 2:
The system changes the temporal distribution parameter of power delivery by shifting power transfer to off-peak periods. Instead of delivering power uniformly when needed, the system varies the timing of power transfer, accumulating energy during low-demand periods and releasing it during high-demand periods, thereby reducing the required instantaneous capacity.
3Use of energy by stationary object
If power distribution is optimized to minimize costs, then operational costs decrease, but the risk of insufficient power for accessories increases
Solution Approach 1:
The optimization controller implements feedback mechanisms by continuously monitoring accessory operational requirements, energy storage status, and power distribution outcomes. This feedback allows the system to learn from past performance and adjust future power distribution schedules to ensure sufficient power availability while maintaining cost optimization, preventing both over-provisioning and under-provisioning of power.
Solution Approach 2:
The system performs preliminary assessment of accessory power requirements and schedules power distribution accordingly. By analyzing forecasted operational needs and historical data, the system pre-plans power delivery schedules that ensure sufficient power availability while minimizing costs, rather than reacting to power shortages after they occur.
4Adaptability or versatility
If multiple ESE stations are used for power distribution, then flexibility and capacity adjustment improve, but the system complexity and coordination requirements increase
Solution Approach 1:
The system merges the control functions of multiple ESE stations into a unified optimization controller that manages all stations centrally. This consolidation reduces coordination complexity by providing a single point of decision-making that considers the collective status and capabilities of all ESE stations, while still allowing individual stations to operate semi-independently for local flexibility.
Solution Approach 2:
Each ESE station is designed with universal capabilities to handle multiple types of electrically powered accessories and various power delivery modes. This multi-functionality reduces the need for specialized coordination protocols for different station types, simplifying the overall system architecture while maintaining the flexibility to accommodate diverse power distribution requirements.
Data Source
AI summary
A method for optimizing power distribution amongst one or more electrical supply equipment stations at a power distribution site is provided. The method includes obtaining infrastructure data about the power distribution site, obtaining vehicle/transport climate control system data from one or more transport climate control systems and one or more vehicles demanding power from the one or more electrical supply equipment, and obtaining external data from an external source that can impact power demand from the one or more transport climate control systems. Each of the one or more transport climate control systems configured to provide climate control within a climate controlled space. The method also includes generating an optimized power distribution schedule based on the infrastructure data, the vehicle/transport climate control system data and the external data, and distributing power to the one or more transport climate control systems based on the optimized power distribution schedule.