Movable Battery Charging Control for Grid Demand Fluctuations
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Solution Overview
Problem
Current electrical grid management systems face challenges in efficiently adjusting supply and demand, particularly with the integration of electric vehicle batteries, which complicates the prediction and allocation of electrical power resources to meet demand fluctuations.
Innovation Solution
A system that includes a network of stations and vehicles equipped with batteries, connected through a communication network, which uses predictive algorithms to manage charging and discharging operations based on demand requests, optimizing power supply and demand by allocating control strategies such as first, second, third, and fourth controls to balance grid requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If electric vehicle batteries are integrated into the electrical grid for supply-demand adjustment, then the grid's ability to manage demand fluctuations is enhanced, but the complexity of predicting and allocating electrical power resources increases
Solution Approach 1:
The patent segments the power resource allocation problem by classifying control methods into four distinct types (first control for charging, second control for discharging, third control for idle charging, fourth control for idle discharging) and allocating them to different batteries based on their states. This segmentation simplifies the complex allocation task by providing a structured framework for managing multiple batteries with different conditions.
Solution Approach 2:
The system performs preliminary prediction of electrical power resources that can be provided by each battery before allocation. The prediction unit forecasts available power based on battery states and usage patterns, allowing the system to plan and allocate resources in advance rather than reacting to fluctuations in real-time, thereby reducing allocation complexity.
2Productivity
If predictive algorithms are used to manage charging and discharging operations, then power supply and demand optimization is improved, but the computational requirements and system complexity increase
Solution Approach 1:
The prediction unit serves multiple functions: it predicts electrical power resources for allocation, provides data for control method selection, and supports decision-making for charge/discharge operations. This multi-functionality improves power allocation efficiency without requiring separate complex systems for each function, thereby limiting the increase in overall system complexity.
3Manufacturing precision
If multiple control methods are allocated to different batteries based on their states, then the precision of meeting demand fluctuations is improved, but the difficulty of detecting and measuring battery states increases
Solution Approach 1:
The system applies different control methods to different batteries based on their local states (charging, discharging, idle, SOC levels). Each battery receives a tailored control approach appropriate to its current condition, which improves the precision of meeting demand fluctuations while using simple state-based classification rather than complex continuous monitoring.
Data Source
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 state of charges 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, 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.