EV Charging Load Modeling for Grid Optimization
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Solution Overview
Problem
Current electric vehicle charging systems lack the ability to communicate and respond to optimal charging needs, failing to incorporate disparate data streams that could optimize power grid objectives such as energy balancing, revenue maximization, and environmental goals, due to binary communication limitations and lack of data processing capabilities.
Innovation Solution
A computerized system that aggregates and analyzes various data types, including power grid data, user behavior, and environmental conditions, to determine optimal charging patterns for electric vehicle charging stations, enabling control of charging operations to align with grid needs through a cloud server and communication module.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If binary communication is used for charging control, then device complexity is reduced, but loss of information occurs due to inability to convey optimal charging needs and grid objectives
Solution Approach 1:
The patent transitions from binary communication to multi-parameter communication, enabling the transmission of detailed charging control information including optimal charging times, power levels, and grid objective parameters. This allows the charging system to convey comprehensive control data without increasing fundamental system complexity.
2Productivity
If charging power is increased to meet driver requirements, then productivity is improved, but loss of energy occurs due to lack of optimization with grid conditions
Solution Approach 1:
The system implements feedback mechanisms where charging control information is continuously adjusted based on grid conditions, driver needs, and optimal charging algorithms. This feedback loop enables the system to optimize charging power delivery, ensuring high productivity while minimizing energy loss through intelligent control.
Solution Approach 2:
The patent introduces dynamic charging control where power delivery is continuously adapted based on real-time grid conditions and driver requirements. This dynamic adjustment allows the system to maintain high charging productivity while optimizing energy efficiency through variable power levels rather than fixed high-power delivery.
3Adaptability or versatility
If distributed generation and storage are incorporated, then adaptability is improved, but device complexity increases due to multiple stakeholders and data streams
Solution Approach 1:
The patent creates a universal charging control framework that can handle multiple stakeholders, distributed generation sources, and storage systems through a single integrated communication protocol. This multi-functional approach enables the system to adapt to various grid configurations and stakeholder requirements without proportionally increasing complexity.
Data Source
AI summary
A system configured to receive and automatically analyze various types of information, including, without limitation, information from energy generators, information from non-generation resources, information on the facility status, information on user behavior, information on user's short-term energy needs (e.g. over-ride any algorithm due to immediate charging need), information on renewable generation, including, without limitation, solar, wind, biomass and/or hydro, and information on environmental conditions including, without limitation, barometric pressure, temperature, ambient light intensity, humidity, air speed, and air quality. In one or more embodiments, a sole novel charging station or selected, aggregated groupings of the aforesaid novel charging stations are configured to start, modulate or stop charging, or start, modulate (down) or stop discharging over specific time intervals based on the electrical grid needs as automatically determined based on the totality of the received diverse information. To this end, a system and an associated method are provided to perform complete electrical charging load modeling to optimize power grid objectives.