Brayton Cycle Control via Iterative Thermodynamic Modeling
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Solution Overview
Problem
There is a need for a method to predict and optimize the balanced steady-state operating conditions of a split flow recompression Brayton cycle power generation system, particularly for supercritical CO2 systems, as existing methods lack the capability to achieve stable start-up and efficient operation.
Innovation Solution
A method involving a thermodynamic and mass flow model is developed, which iteratively adjusts input conditions such as mass flow split between compressors and recuperator temperatures to achieve balanced operating points, using a non-transitory machine-readable medium to determine operating parameters like TAC speeds and heat rejection amounts, ensuring stable start-up and steady-state operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a closed split flow recompression Brayton cycle system is operated without a predictive control method, then the system structure remains simple, but the steady-state operating conditions cannot be optimized and start-up stability is compromised
Solution Approach 1:
The patent applies preliminary action by pre-calculating balanced steady-state operating conditions through iterative computation before actual system operation. The control method predicts optimal operating parameters (mass flow rates, temperatures, pressures) in advance, allowing the system to start up and transition to steady state without real-time trial-and-error adjustments, thereby ensuring start-up stability without requiring complex real-time control hardware
Solution Approach 2:
The patent replaces complex mechanical control systems with a computational model-based approach. Instead of using complex physical control mechanisms and sensors to maintain steady-state conditions, the invention uses thermodynamic and mass flow models to predict optimal operating conditions, substituting mechanical complexity with algorithmic computation that can be implemented with simpler control hardware
2Productivity
If iterative adjustment of operating parameters is performed to achieve balanced steady-state conditions, then power conversion efficiency is maximized, but computational time and control complexity increase
Solution Approach 1:
The patent performs iterative calculations of balanced steady-state operating conditions in advance, before actual system operation. By pre-computing optimal mass flow rates, temperatures, and pressures that maximize power conversion efficiency, the system avoids real-time iterative adjustments during operation, thereby achieving maximum efficiency without incurring computational time delays during critical operational phases
Solution Approach 2:
The patent implements a feedback mechanism where calculated operating conditions from the thermodynamic and mass flow models are compared with actual system performance. This feedback loop allows the system to verify and adjust operating parameters to maintain optimal efficiency, ensuring that the pre-calculated balanced conditions are accurately achieved and sustained during steady-state operation
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method effectively predicts and optimizes the operating conditions of a closed split flow recompression Brayton cycle, enhancing power conversion efficiency and stability by iteratively refining input parameters to match calculated and estimated values, thereby maximizing efficiency and operational stability.
Implementation Method 1
Method for controlling start-up and steady state performance of a closed split flow recompression brayton cycle
Implementation Method 2
efficiencies that meet or exceed efficiencies of conventional power generation systems utilizing a single-phase fluid operating near the critical temperature and pressure of such fluid
Implementation Method 3
a first step of providing a thermodynamic and mass flow model of a closed split flow recompression Brayton cycle power generation system
Implementation Method 4
a sixth step of comparing the fluid pressure at the secondary compressor outlet calculated in the fifth step to the fluid pressure on the high pressure side at the LT recuperator outlet
Data Source
AI summary
A method of resolving a balanced condition that generates control parameters for start-up and steady state operating points and various component and cycle performances for a closed split flow recompression cycle system. The method provides for improved control of a Brayton cycle thermal to electrical power conversion system. The method may also be used for system design, operational simulation and/or parameter prediction.