Movable Battery Charge Forecasting for Grid Demand Response
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Solution Overview
Problem
Existing systems face challenges in effectively utilizing batteries for energy conservation, particularly in managing power supply and demand in electrical grids, as they struggle to predict and optimize battery state of charge and usage patterns to meet grid requirements efficiently.
Innovation Solution
A computer system that includes a controlling module and an estimating module to perform charging increment or reduction controls based on predicted usage situations of movable batteries, ensuring the state of charge does not exceed predefined values, thereby optimizing power supply to the electrical grid.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If charging amounts for movable batteries are increased to meet power consumption requests, then the power consumption increment request is satisfied, but the state of charge may exceed predefined values causing battery deterioration
Solution Approach 1:
The estimating module predicts future usage situations and state of charge levels before charging occurs, allowing the controlling module to pre-calculate safe charging increments that won't exceed predefined thresholds. This preliminary estimation enables proactive power consumption increment responses while maintaining battery safety.
Solution Approach 2:
The system continuously monitors actual usage situations against predicted values and adjusts charging increment calculations accordingly. The controlling module uses feedback from the estimating module about predicted state of charge levels to dynamically adjust charging amounts, ensuring predefined thresholds are never exceeded while maximizing power consumption response capability.
2Reliability
If charging amounts are limited to prevent state of charge from exceeding predefined values, then battery reliability is maintained, but the ability to respond to power consumption increment requests is reduced
Solution Approach 1:
The system dynamically adjusts charging increment limits based on predicted usage situations. Rather than using a static charging limit, the controlling module calculates time-varying charging increments that adapt to forecasted battery usage patterns, allowing maximum charging when future usage is low and reduced charging when future usage is expected to be high.
Solution Approach 2:
The system changes the charging increment parameter dynamically based on predicted state of charge trajectories. The controlling module adjusts the charging rate parameter in real-time according to predictions from the estimating module, optimizing the balance between responding to power requests and maintaining reliability thresholds.
3Productivity
If battery usage patterns are predicted accurately, then charging optimization is improved, but the complexity of prediction algorithms increases
Solution Approach 1:
The estimating module focuses on predicting only the critical parameters needed for charging optimization (state of charge trajectories and usage patterns) rather than comprehensive battery behavior. This partial prediction approach achieves sufficient optimization efficiency without requiring overly complex algorithms that would predict every aspect of battery usage.
Data Source
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AI summary
A system includes: a controlling module that provides an electric power grid with an electrical power resource by performing a charging increment control for increasing power charging amounts for the multiple movable batteries, in response to a power consumption increment request for requesting power consumption to be increased; and an estimating module that estimates, based on predicted usage situations of the multiple movable batteries, an amount of electrical power resources that can be provided to the electric power grid by each of the multiple movable batteries by the charging increment control, wherein the predicted usage situations of the multiple movable batteries include a predicted state of charge of the multiple movable batteries, and the estimating module estimates the amount of electrical power resources that can be provided to the electric power grid by each of the multiple movable batteries by the charging increment control such that the state of charge of each of the multiple movable batteries does not exceed a predefined value.