Movable Battery Grid Control for Predictive Power Allocation
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Solution Overview
Problem
Current electrical grid management systems face challenges in efficiently adjusting supply and demand due to the unpredictable nature of electrical power consumption and generation from mobile battery sources, leading to difficulties in accurately predicting and allocating electrical power resources.
Innovation Solution
A system that includes a network of stations and vehicles equipped with batteries, connected via a communication network, which uses predictive algorithms to estimate and allocate electrical power resources based on travel records, state of charge, and usage patterns, allowing for real-time adjustments to supply and demand by controlling charging and discharging operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If predictive algorithms are used to estimate electrical power resources from mobile battery sources, then the accuracy of predicting electrical power availability is improved, but the complexity of the system increases
Solution Approach 1:
The system performs preliminary actions by collecting travel records, state of charge data, and usage patterns before actual power allocation occurs. Predictive algorithms process this historical data in advance to estimate future power availability, enabling proactive resource allocation rather than reactive management.
Solution Approach 2:
The communication network serves as an intermediary that connects batteries, stations, and the allocation system. This intermediary enables data exchange and coordination without requiring direct physical connections between all components, thereby managing system complexity while maintaining prediction accuracy.
2Stability of the object's composition
If real-time adjustments to supply and demand are implemented by controlling charging and discharging operations, then the power supply and demand balance is improved, but the control system complexity increases
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring actual power consumption and generation from mobile batteries, comparing it with predicted values, and adjusting charging/discharging control accordingly. This closed-loop control maintains power balance while automating the adjustment process to manage complexity.
Solution Approach 2:
The control system dynamically adjusts charging and discharging operations based on real-time conditions and predictive estimates. Rather than using fixed schedules, the system adapts its control strategy to changing power supply and demand conditions, improving balance while maintaining manageable complexity through algorithmic decision-making.
Data Source
AI summary
A system comprising: a controlling module that provides an electric power grid with an electrical power resource by performing at least one of a first control for reducing power charging amounts for the multiple movable batteries, or a second control for increasing power supplying amounts from the multiple movable batteries to the outside, in response to a first request for requesting power consumption to be reduced; and an allocating unit that allocates control, among the first control and the second control, with which each of the multiple movable batteries provide the electric power grid with an electrical power resource in each of multiple timeframes in a future, wherein the first control is preferentially allocated over the second control.