ESS Efficiency Optimization via Dynamic Power Distribution
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Solution Overview
Problem
Energy storage systems (ESS) composed of multiple unit-BESSs face inefficiencies due to varying power conversion system (PCS) and battery efficiencies, which change with output and state of charge (SOC), requiring an optimized method for charge/discharge power distribution.
Innovation Solution
A method that collects and linearizes charge/discharge efficiency data of PCS and batteries, determining optimal charge/discharge levels for each unit-BESS to satisfy input/output power values, using a Maximum Energy Efficiency Tracking (MEET) algorithm to optimize output distribution and extend battery life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If charge/discharge power is distributed without optimization in ESS with multiple unit-BESSs, then system operation is simple, but efficiency is reduced due to varying PCS and battery efficiencies
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting charge/discharge power distribution based on varying efficiency parameters of PCS and batteries. The system collects efficiency data, linearizes it through mathematical transformation, and uses these transformed parameters to optimize power allocation, thereby resolving the contradiction between energy efficiency and system complexity
Solution Approach 2:
The patent implements feedback mechanisms by continuously collecting charge/discharge efficiency data from PCS and batteries, processing this data through linearization algorithms, and using the results to adjust power distribution in real-time. This closed-loop feedback system optimizes energy efficiency while maintaining manageable complexity through automated control
2Measurement precision
If efficiency data is not linearized and segmented, then data processing is simpler, but optimization accuracy is insufficient due to non-linear efficiency variations
Solution Approach 1:
The patent applies segmentation by dividing the continuous efficiency data into discrete sections and applying linearization to each segment. This approach transforms complex non-linear efficiency variations into manageable linear segments, improving measurement accuracy while keeping data processing complexity at acceptable levels through systematic segmentation
Solution Approach 2:
The patent transforms efficiency parameters through mathematical linearization, changing the parameter representation from non-linear to linear form. This parameter transformation enables more accurate efficiency measurement and optimization while maintaining tractable data processing through standardized mathematical operations
3Adaptability or versatility
If fixed power distribution is used in unit-BESSs, then control is simpler, but adaptability is reduced when PCS or batteries are added or removed
Solution Approach 1:
The patent applies dynamics by implementing a dynamic power distribution system that automatically adjusts to changing system configurations. When PCS or batteries are added or removed, the system dynamically recalculates efficiency parameters and redistributes power optimally, providing high adaptability while maintaining controlled complexity through automated dynamic adjustment
Data Source
AI summary
A method of operating an ESS with optimal efficiency includes: collecting charge/discharge efficiency data of a PCS; collecting charge/discharge efficiency data of a battery depending on current state of charge of the battery; creating charge/discharge efficiency data of a unit BESS including the PCS and the battery by using the collected data; determining optimal charge/discharge levels of at least two unit-BESSs included in the ESS by using charge/discharge efficiency data of the at least two unit-BESSs to satisfy commanded input/output power values of the whole ESS at a current point of time; and charging or discharging the at least two unit-BESSs depending on the determined optimal charge/discharge power values.