Energy Storage Simplified Model for Real-Time Setpoint Control
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Solution Overview
Problem
Existing energy storage systems require computationally intensive simulations with time steps much lower than the driving time step to achieve accurate setpoints, leading to inefficiencies in computational power and memory usage.
Innovation Solution
A simplified model is developed using a method that involves multiple simulations with a time step of the same order as the driving time step, generating tables for state of charge variation and power, allowing for accurate setpoints with reduced computational requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a complex model with much lower time step is used for simulation, then accuracy of simulated results is improved, but computational power requirements increase
Solution Approach 1:
The patent segments the simulation process into two distinct phases: an offline phase where a complex model with fine time steps is used to generate lookup tables, and an online phase where a simplified model with coarse time steps uses these tables for rapid simulation. This segmentation allows the computationally intensive accuracy-enhancing simulations to be performed only once offline, while online operations benefit from reduced computational requirements.
Solution Approach 2:
The patent performs preliminary simulations using the complex model with fine time steps to pre-calculate and store state of charge variations and power values in lookup tables before the actual control operation. This preliminary action eliminates the need to perform computationally intensive simulations in real-time, thereby reducing online computational power requirements while maintaining accuracy.
2Measurement precision
If a complex model with much lower time step is used for simulation, then accuracy of simulated results is improved, but simulation time increases
Solution Approach 1:
The patent divides the simulation task into offline pre-computation (using complex model with fine time steps to build lookup tables) and online execution (using simplified model with coarse time steps and the pre-built tables). This segmentation transfers the time-consuming accurate simulations to the offline phase, enabling real-time or near-real-time control with the simplified online model.
Solution Approach 2:
The patent performs the accurate but time-consuming simulations in advance to populate lookup tables with state of charge variations and power values. By performing this preliminary action offline, the system avoids repeating these simulations during online operation, thereby dramatically reducing simulation time for actual control operations while preserving accuracy through the pre-computed data.
3Power
If a simplified model with larger time step is used for simulation, then computational power requirements are reduced, but accuracy of simulated results deteriorates
Solution Approach 1:
The patent introduces lookup tables as an intermediary between the simplified model and the complex model. These tables, pre-filled with accurate data from complex model simulations, allow the simplified model to achieve accuracy comparable to the complex model without requiring its computational intensity. The lookup tables act as a mediator that transfers accuracy benefits to the computationally efficient simplified model.
Solution Approach 2:
The patent creates a simplified model that copies the essential input-output relationships of the complex model by using lookup tables derived from complex model simulations. Instead of directly using the complex model online, the system creates a lightweight copy that replicates the complex model's accuracy characteristics through pre-computed data, enabling fast execution without sacrificing precision.
4Productivity
If a simplified model with larger time step is used for simulation, then computational efficiency is improved, but reliability of setpoint generation deteriorates
Solution Approach 1:
The lookup tables serve as an intermediary that ensures the simplified model produces reliable setpoints by incorporating accurate data from complex model simulations. The tables contain pre-computed state of charge variations and power values that guarantee the reliability normally associated with complex models, while the simplified model structure maintains computational efficiency.
Data Source
AI summary
A method for determining parameters of a simplified model of an energy storage system, including an energy storage device and a conversion device, the system being modelled by a complex model including models of the energy storage and conversion devices; the complex model receiving a setpoint power Pac_sp and a state of charge SOCp at input and providing the state of charge SOC of the storage device and the power Pac at the output of the storage device at output; the method including implementing simulations of the energy storage system using the complex model; calculating (a) a table of the variation in the state of charge of the system as a function of the setpoint power and of a state of charge, (b) a table of maximum power as a function of the state of charge; (c) a table of minimum power as a function of the state of charge.