EV Charger Load Shedding for Transformer Overload
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Solution Overview
Problem
The increasing demand for electric vehicle charging in residential areas often leads to transformer overload during peak hours, as multiple vehicles attempt to charge simultaneously, causing strain on the electrical distribution system and potentially resulting in transformer overload, which is costly to mitigate with higher capacity transformers or additional infrastructure.
Innovation Solution
Implementing an electric vehicle charging device with control circuitry that estimates charging time, delays charging until off-peak hours, and employs a load shedding algorithm to prioritize charging based on vehicle priority ranks, thereby smoothing the peak load and reducing the risk of transformer overload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple electric vehicles charge simultaneously at residences during peak hours, then the charging service is provided efficiently to users, but the transformer becomes overloaded and cannot meet power demands
Solution Approach 1:
The patent implements periodic action by scheduling EV charging to occur during off-peak hours rather than continuously during peak demand periods. The system monitors transformer load and activates charging only when load conditions are favorable, creating a periodic charging pattern that avoids sustained peak loading and prevents transformer overload while still providing charging services to multiple vehicles.
Solution Approach 2:
The patent applies dynamics by making the charging system adaptive and flexible rather than static. The charging device continuously monitors transformer load conditions and dynamically adjusts charging parameters including power level, charging rate, and duration. This dynamic adjustment allows the system to optimize charging efficiency while responding to real-time transformer capacity constraints, preventing overload while maximizing productivity.
2Reliability
If the transformer capacity is increased or additional transformers are added to service more residences, then the transformer overload problem is solved, but the cost of infrastructure replacement or expansion becomes very expensive
Solution Approach 1:
The patent applies parameter changes by modifying the operational parameters of the existing transformer rather than changing the physical infrastructure. The system adjusts charging power levels, voltage, and current parameters dynamically based on transformer load conditions. This allows the existing transformer to handle EV charging demands safely without requiring capacity upgrades or additional infrastructure, avoiding the high costs associated with transformer replacement or expansion.
Solution Approach 2:
The patent implements self-service by enabling the charging system to automatically monitor transformer load conditions and adjust charging parameters without human intervention. The intelligent charging device autonomously determines when to activate charging, at what power level, and for how long based on real-time transformer capacity assessment. This self-regulating mechanism ensures reliable operation within transformer limits while eliminating the need for costly infrastructure upgrades.
3Reliability
If electric vehicles are charged during off-peak hours with delayed start times, then the peak load on transformers is reduced, but the charging time for individual vehicles is extended
Solution Approach 1:
The patent applies partial action by providing charging services to only those vehicles whose charging can be completed within acceptable time frames under off-peak conditions. The system assesses each vehicle's charging needs and prioritizes those that can be fully charged during off-peak hours, while potentially deferring or reducing charging for vehicles with tighter time constraints. This selective approach reduces peak load while minimizing the time loss for individual users.
Solution Approach 2:
The patent implements preliminary action by pre-scheduling and pre-coordinating charging sessions during off-peak hours. The system anticipates charging needs and plans charging sessions in advance during periods of low transformer load, allowing vehicles to be charged when conditions are favorable. This preliminary scheduling approach enables the system to reduce peak load while providing advance notice to users about charging timing, minimizing unexpected time delays.
Data Source
AI summary
An electric vehicle charging device includes a processing unit having a memory with a routine stored therein which, when executed by the processing unit causes the processing unit to control circuitry to prevent the electric vehicle charging device from charging an electric vehicle for a random delay period and to allow the electric vehicle charging device to charge the electric vehicle starting when the random delay period ends, wherein the random delay period starts at a predetermined start time and lasts a random delay length of time. The random delay reduces the peak load on a transformer that the electric vehicle charging device and other electric vehicle charging devices receive power from.