EV Charging Booking Control for Predictive Grid Power Allocation
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Solution Overview
Problem
The increasing adoption of electric vehicles poses unpredictability in electricity consumption patterns, leading to imbalances in electrical grids, necessitating a method to predict and manage energy flows effectively for optimal grid operation and cost-efficient energy distribution.
Innovation Solution
A method and system for managing energy flows that involve defining a control and management system for electric vehicle charging, associating it with a supervision and control unit, and configuring the electrical grid based on anticipated energy consumption by calculating demand across geographic regions and adjusting in real-time, ensuring optimal power allocation and usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If electric vehicle charging demand increases, then more electric power must be produced and distributed, but this leads to unpredictable consumption patterns and grid imbalance
Solution Approach 1:
The system performs preliminary actions by collecting booking data from charging facilities in advance, calculating anticipated energy consumption before actual charging occurs, and configuring the electrical grid proactively based on these predictions. This allows the grid to be prepared for upcoming demand spikes rather than reacting to them, thereby maintaining reliability while accommodating increased power production.
Solution Approach 2:
The system establishes a feedback loop where booking data from charging facilities is continuously collected, processed to calculate anticipated consumption, and used to adjust grid configuration. This feedback mechanism enables the system to adapt to changing charging demands dynamically, ensuring grid balance is maintained even as electric vehicle adoption increases.
2Power
If charging facilities are equipped with high power capacity to meet peak demand, then rapid charging can be provided, but power may not be completely utilized during low consumption periods
Solution Approach 1:
The system makes the charging infrastructure dynamic by configuring grid power allocation based on anticipated consumption calculated from actual booking data. Instead of static high-power capacity that sits unused during low demand, the grid configuration adapts to match expected charging needs, allowing facilities to access high power when needed while reducing allocated power during low consumption periods, thereby minimizing energy loss from unused committed power.
3Reliability
If the electrical grid is configured to handle maximum anticipated consumption, then sufficient power is available for all charging operations, but this increases infrastructure costs and complexity
Solution Approach 1:
The system calculates anticipated energy consumption in advance based on collected booking data and uses this information to configure the electrical grid appropriately. This preliminary calculation allows the grid to be configured for the actual expected load rather than maximum potential load, reducing infrastructure complexity and costs while maintaining sufficient power availability for all booked charging operations.
4Productivity
If real-time monitoring and configuration of the electrical grid is implemented, then optimal power allocation is achieved, but system complexity and implementation cost increase
Solution Approach 1:
The system achieves optimal power allocation by implementing a multi-functional control architecture where a single control entity performs multiple functions: collecting booking data from charging facilities, calculating anticipated energy consumption, and configuring the electrical grid based on these calculations. This universal approach consolidates what could be separate complex systems into one integrated solution, improving power allocation efficiency while managing complexity through functional integration.
Data Source
Figure 1
AI summary
A method for management and planning of energy flows intended for charging electric vehicles (2) in an electrical grid, which consists of defining a system (1) for control and management of the charging of electric vehicles (2) that is suitable for the booking of each individual electric power delivery point of at least one charging facility (3) for electric vehicles (2), by a respective user account; associating with a main server (4) of the system (1) at least one first supervision and control unit (5) which is functionally associated with at least one supplier of electric power (6); acquiring from the system (1) strings of data relating to the bookings of future charging operations and transmitting them to the at least one first supervision and control unit (5); configuring the electrical grid as a function of the expected energy consumption in relation to the booked charging operations.