Dynamic System Curve Determination for Heat Power System Efficiency
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Solution Overview
Problem
In heat power systems, especially those using thermodynamic cycles like the Rankine cycle, efficiently determining the current system curve is challenging due to the use of static system curves provided by manufacturers, which can lead to reduced efficiency, especially when operating with low temperature differences, and retrofitting with accurate sensors is expensive.
Innovation Solution
A method and controller that dynamically determine the current system curve by collecting sensor values with limited accuracy, identifying points on the curve through properties like fluttering values, and modeling it via linear interpolation between saved points, allowing the regulator output to follow the actual system curve closely without the need for expensive sensor upgrades.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If static system curves from manufacturers are used, then device complexity is reduced, but efficiency deteriorates due to inability to follow current system curve
Solution Approach 1:
The patent transforms the static system curve approach into a dynamic one by continuously determining the current system curve through iterative testing and sensor data collection. The controller dynamically adjusts regulator output to map the actual system curve, enabling real-time adaptation to changing operating conditions and eliminating energy losses associated with using outdated static curves.
Solution Approach 2:
The patent implements a feedback mechanism where sensor values are continuously collected and checked to determine if points on the current system curve have been reached. This feedback loop allows the controller to iteratively refine the system curve model by comparing actual sensor readings against expected values and adjusting accordingly, ensuring accurate tracking of the true system performance.
2Loss of energy
If accurate sensors are installed to follow system curve closely, then efficiency is improved, but cost increases due to sensor retrofitting
Solution Approach 1:
The patent enables the system to self-determine its own system curve using existing sensors with limited accuracy. The controller performs iterative testing and uses the collected sensor data to model the current system curve without requiring external intervention or expensive sensor upgrades. The system serves itself by using its own limited measurements to achieve accurate control.
Solution Approach 2:
The patent treats the system curve model as a temporary, computationally-generated representation rather than relying on permanent, expensive hardware upgrades. By using software-based curve determination with existing sensors, the system achieves accurate control without the cost of installing high-precision sensors, effectively replacing expensive physical components with inexpensive computational methods.
3Ease of operation
If manufacturer-provided system curves are used, then ease of operation is improved, but measurement precision deteriorates due to static vs dynamic curve mismatch
Solution Approach 1:
The patent performs preliminary system curve determination through iterative testing before actual operation begins. The controller pre-maps the system curve by collecting sensor data at various operating points, then uses this pre-determined curve for control operations. This preliminary action ensures that the most accurate current system curve is available before the system needs to operate, combining ease of operation with high measurement precision.
Data Source
AI summary
A method and controller of dynamically determining a current system curve in a heat power system, in which the heat power system comprises a regulator and sensors. The controller controls an output of the regulator to find the current system curve, collects and checks sensor values with limited accuracy to determine if properties of the sensor values indicate that a point of the current system curve has been reached. When at least two points are found the controller models the current system curve by linear interpolation between the first and second point of the current system curve.