EV Charging Optimization via Demand Smoothing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The rapid growth of electric vehicle adoption is expected to significantly increase electricity demand, particularly during peak hours, leading to costly upgrades of generation and transmission systems, which will result in higher rates for all ratepayers and increased wholesale electricity costs.
Innovation Solution
A system that optimizes electric vehicle charging by using a server communicating with charge calculators and sensors within vehicles to estimate state-of-charge (SOC) and generate charging schedules that smooth electricity demand curves, reducing costs for ratepayers by optimizing when vehicles are charged.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If electric vehicle charging demand increases rapidly during peak hours, then more electric vehicles can be charged, but generation and transmission systems require costly upgrades and wholesale electricity costs increase
Solution Approach 1:
The system performs preliminary actions by predicting future electricity demand and renewable energy generation, then schedules charging in advance to occur during optimal times when electricity is cheaper and renewable generation is higher, avoiding peak demand periods and costly infrastructure upgrades
Solution Approach 2:
The charging schedule is made dynamic and adjustable based on real-time conditions. The system continuously monitors electricity prices, demand patterns, and renewable generation, then optimizes charging schedules adaptively to minimize costs while ensuring vehicles are charged when needed
2Productivity
If electric vehicle charging demand increases rapidly during peak hours, then more electric vehicles can be charged, but generation and transmission systems require substantial and costly upgrades
Solution Approach 1:
The system schedules charging activities in advance based on predicted demand patterns and infrastructure capacity constraints, distributing charging loads over time to avoid overwhelming the existing transmission and distribution systems, thereby deferring the need for costly infrastructure upgrades
Solution Approach 2:
The system changes the temporal parameters of charging operations by shifting charging from peak periods to off-peak periods, and adjusts charging rates dynamically based on grid conditions, transforming a static infrastructure challenge into a manageable operational parameter
3Loss of energy
If charging schedules are optimized to smooth electricity demand curve, then cost for ratepayers is reduced, but charging timing must be coordinated across multiple vehicles
Solution Approach 1:
The server performs multiple functions simultaneously: it predicts electricity demand, forecasts renewable generation, optimizes charging schedules for multiple vehicles, coordinates charging timing, and ensures individual vehicle charging needs are met. This multi-functionality consolidates complex coordination tasks into a single centralized system
Solution Approach 2:
The server acts as an intermediary between individual electric vehicles, the electricity grid, and renewable energy sources. It aggregates charging requests, smooths demand curves by coordinating schedules, and balances individual vehicle needs against overall system optimization, reducing coordination complexity through centralized mediation
Data Source
AI summary
A system for determining a state-of-charge (SOC) of an electric vehicle includes a housing that is supportable within the electric vehicle, one or more sensors supported by the housing, and a processor. The one or more sensors are configured to determine one or more values related to the electric vehicle, respectively. Each value of the one or more values represents a state of the electric vehicle or a state of an environment in which the electric vehicle is located. The processor is configured to estimate an SOC of the electric vehicle based on the one or more determined values related to the electric vehicle. The device also includes a wireless communication interface configured to transmit data representative of the estimated SOC of the electric vehicle and/or data representative of the one or more values related to the electric vehicle to the processor or to another processor.