Collaborative EV Charging System for Transformer Load Management
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increasing popularity of electric vehicles strains the existing power distribution infrastructure, as charging demands exceed the capacity of neighborhood step-down transformers, potentially leading to reduced transformer lifetime and temporary outages, while existing solutions are limited by Society of Automotive Engineers standards and compromise user comfort and privacy.
Innovation Solution
A method and system for collaborative electric vehicle charging that decentralizes power allocation among residences, identifying time-critical and time-flexible demands, and adjusting power distribution to avoid exceeding transformer limits, allowing for efficient charging by shedding or reducing amperage supply to electric vehicle batteries and HVAC systems, while maintaining user comfort and privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple electric vehicles are charged simultaneously at residential premises, then charging efficiency and user convenience are improved, but the transformer may be overloaded exceeding its upper power limit
Solution Approach 1:
The system dynamically adjusts power allocation to electric vehicle chargers based on real-time transformer load conditions. The controller continuously monitors the summation of power demands and modifies charging rates or temporarily suspends charging for individual vehicles to prevent exceeding the transformer's upper power limit, while resuming or increasing charging when capacity becomes available.
Solution Approach 2:
The system changes operational parameters of the charging process by adjusting charging rates, time slots, and power distribution among vehicles. It modifies the charging parameters (current, voltage, duration) based on transformer capacity, vehicle battery needs, and temporal patterns of residential power demand to optimize both charging efficiency and transformer safety.
2Reliability
If power is reduced or shed to prevent transformer overload, then transformer reliability is improved, but electric vehicle charging efficiency deteriorates
Solution Approach 1:
The system implements periodic charging cycles where vehicles are charged in alternating time slots rather than continuously simultaneously. The controller divides charging into periodic intervals, suspending charging for some vehicles during peak transformer load periods and resuming or intensifying charging during off-peak periods when transformer capacity is available, thus preventing overload while maintaining overall charging progress.
Solution Approach 2:
The system performs preliminary assessment of transformer capacity and vehicle charging needs before initiating charging. It predicts power demand patterns and pre-adjusts charging schedules to avoid situations where transformer overload would occur, allowing vehicles to charge at optimal rates during periods when transformer capacity permits.
3Productivity
If centralized control is used to manage power distribution, then power allocation efficiency is improved, but system complexity and infrastructure alteration requirements increase
Solution Approach 1:
The system introduces a communication network as an intermediary layer between the utility company and residential charging systems. This network enables centralized power allocation decisions to be transmitted to and executed by distributed charging controllers without requiring physical modifications to the transformer or electrical infrastructure. The communication network mediates the coordination between multiple vehicles, chargers, and the utility company.
Solution Approach 2:
The system replaces physical infrastructure modifications with communication-based control mechanisms. Instead of altering the electrical system hardware to enable centralized control, it uses communication networks and software algorithms to achieve efficient power allocation, substituting mechanical/electrical complexity with informational complexity that can be managed through existing communication infrastructures.
Data Source
AI summary
A system and method are provided for the collaborative charging of electric vehicles. The collaborative charging manages the disbursement of power from a neighborhood transformer so as to increase the efficiency of electric vehicle charging at the residences without significantly altering the existing power distribution and residential infrastructures. Time-flexible loads are shed in order to efficiently allocate energy distribution without compromising the comfort or security of the user. The identities of individual residential power demands can be concealed to protect the user's privacy or made available to further optimize power allocation. The power allocation negotiation may be performed in a residential local demand management client separate from the residential charging station.