Electric Vehicle Charging Control for Grid Peak Load Balancing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Electric grids face challenges in maintaining optimal balance and efficiency due to fluctuations in power demand and supply, which can lead to sub-optimal conditions such as unbalanced loads and peak demand issues.
Innovation Solution
A grid-to-vehicle (g2v) system that selectively controls the charging operations of electric vehicles connected to the grid based on grid conditions, such as load balancing and cost considerations, to assist in balancing the grid and optimizing energy usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If electric vehicles charge continuously from the grid, then vehicle batteries are kept charged, but grid load increases during peak demand periods
Solution Approach 1:
The system dynamically adjusts the charging rate of electric vehicles based on real-time grid conditions. During off-peak periods with excess supply, charging is accelerated; during peak periods with high demand, charging is reduced or paused. This dynamic control resolves the contradiction by making the charging process adaptive rather than static.
Solution Approach 2:
The system implements periodic charging cycles that alternate between high-charging periods (off-peak) and low-charging periods (peak). This periodic action allows vehicles to accumulate charge during low-demand periods without contributing to peak demand, thereby resolving the contradiction between maintaining battery charge levels and avoiding grid energy waste.
2Stability of the object's composition
If demand response systems are implemented to balance the grid, then grid stability improves, but system complexity increases
Solution Approach 1:
The demand response system automatically monitors grid conditions and adjusts vehicle charging operations without requiring complex manual intervention or centralized control infrastructure. Each vehicle's onboard system makes local decisions based on grid signals, simplifying the overall system architecture while maintaining grid stability.
Solution Approach 2:
The system uses existing vehicle battery infrastructure and communication protocols to achieve multiple functions: energy storage, load balancing, and demand response. By making the battery system multi-functional, the solution avoids adding separate complex infrastructure while still achieving grid stability.
Data Source
AI summary
A grid to vehicle system is described. In some examples, the system selectively controls one or more electric vehicles connected to an electric grid based on conditions associated with the electric grid. For example, the system may control charging operations of the electric vehicles based on load balancing conditions associated with the electric grid, based on cost conditions associated with electric power provided by the electric grid, and so on.