Hybrid Energy Storage SoC Allocation Under Power Limit Constraints
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Solution Overview
Problem
Existing methods for allocating power in hybrid energy storage systems fail to control power amplitude and prevent simultaneous charging and discharging of different types of energy storage units, leading to efficiency and lifespan issues due to subjective frequency division points and lack of physical constraints.
Innovation Solution
A method and system for allocating hybrid energy storage capacity using an equal mileage incremental utility ratio, which calculates optimal charging and discharging mileages based on a sliding window algorithm and mathematical models considering physical constraints, ensuring safe operation and maximizing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If frequency-based decomposition method is used to allocate power among energy storage units, then power allocation points can be identified, but the power output of each energy storage unit may exceed its upper limit of charging and discharging power
Solution Approach 1:
The patent applies dynamic programming to create an optimized power allocation strategy that dynamically adjusts power distribution based on real-time system state and constraints. This resolves the contradiction by enabling flexible power allocation that adapts to changing conditions while ensuring power output limits are never exceeded, unlike static frequency-based methods.
Solution Approach 2:
The patent transforms the power allocation problem from frequency-domain decomposition to time-domain dynamic optimization, changing the fundamental parameter space. By using dynamic programming with state-of-charge (SOC) as the state parameter and power allocation as the control parameter, the system can precisely control power output within limits while maintaining allocation efficiency.
2Productivity
If original frequency decomposition method is used, then power allocation can be performed, but different types of energy storage may charge and discharge at the same time which violates physical constraints
Solution Approach 1:
The patent implements feedback control through dynamic programming that continuously monitors the SOC states of different energy storage units and adjusts power allocation accordingly. The algorithm incorporates physical constraints as feedback conditions, preventing simultaneous charging and discharging by checking constraint satisfaction at each decision step, thus resolving the contradiction between allocation capability and constraint compliance.
Solution Approach 2:
The patent performs preliminary verification of physical constraints before executing power allocation decisions. By pre-defining valid operation regions and checking constraint compliance in advance within the dynamic programming framework, the system prevents invalid operations (simultaneous charge/discharge) before they occur, rather than correcting them afterward.
3Ease of manufacture
If frequency division points are selected based on mathematical tools, then decomposition can be performed, but the selection is somewhat subjective and lacks interpretability of the real physical world
Solution Approach 1:
The patent replaces the mathematical frequency-domain decomposition approach with a physics-based time-domain dynamic optimization approach. Instead of using abstract frequency division points derived from mathematical transforms, the system uses physically meaningful parameters (SOC, power limits, efficiency curves) directly in the dynamic programming model, providing clear physical interpretability while maintaining implementation ease.
Data Source
AI summary
A method for allocating hybrid energy storage capacity is provided, including: determining a curve of an SoC with a maximum utility of the hybrid energy storage system in a predetermined time period as an objective function, with an SoC constraint and ES charging and discharging constraints as constraint conditions according to an power service utility signal; extracting an SoC value and a time point corresponding to each extreme point in the curve of the SoC; calculating a difference between adjacent SoC values to obtain a mileage sequence; obtaining a plurality of cycle processes and a mileage corresponding to each cycle process; constructing a mathematical model of a relationship between the mileage and an utility loss; calculating a mileage of each energy storage in a corresponding cycle process by applying an equal consumed energy increase ratio principle according to the mathematical model.