Adaptive Parameter Optimization for Coal-Fired Power Systems
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Solution Overview
Problem
Coal-fired power generation systems face inefficiencies due to equipment-specific energy efficiency modules that are not adaptive and lack accuracy under varying load conditions, often relying on outdated parameters.
Innovation Solution
A method to determine optimal parameter settings automatically from historical power-related data, dividing it into segments based on load values, identifying feasible parameter ranges, and using linear regression to correlate energy efficiency with adjustable parameters, allowing for adaptive solutions across different load conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If equipment-specific energy efficiency modules are used for each equipment type, then the module can be specialized for that equipment, but the system lacks adaptability and comprehensiveness across different equipment types and load conditions
Solution Approach 1:
The patent creates a universal energy efficiency module that can analyze and optimize multiple types of equipment (boilers, turbines, condensers, etc.) and various load conditions through a single integrated system. This module uses historical data from diverse equipment types to generate optimized parameter settings applicable across the entire power generation system, eliminating the need for separate equipment-specific modules while maintaining comprehensive coverage.
2Measurement precision
If mechanism energy efficiency modules are established for rated operation conditions, then the module can be simplified for standard conditions, but the accuracy is compromised when operated at lower loading levels
Solution Approach 1:
The patent implements a dynamic optimization approach where the energy efficiency module adapts to different load conditions by using historical data spanning various operating levels. The system dynamically generates optimized parameter settings based on the current load condition, allowing accurate energy efficiency calculations across the full operating range from low to rated load conditions, rather than relying on static settings for rated conditions only.
Solution Approach 2:
The patent segments the operating range into different load conditions (low load, rated load, etc.) and generates optimized parameter settings for each segment based on historical data from corresponding operating conditions. This segmentation allows the system to maintain high accuracy for each specific load condition while providing comprehensive coverage across all operating levels through the unified module.
3Ease of manufacture
If equipment parameters from manufacturers are used, then the parameters are readily available, but they are inadequate or outdated for developing accurate mechanism modules
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously collects actual operating data and performance outcomes from the power generation equipment. This feedback loop allows the energy efficiency module to learn from real-world performance, update and refine parameter values, and improve the accuracy of its optimization recommendations over time, replacing outdated manufacturer parameters with empirically validated data.
Solution Approach 2:
The system performs self-updating by automatically collecting historical operating data, analyzing performance trends, and generating updated parameter settings without requiring manual intervention or external parameter updates. The module serves itself by continuously learning from its own operational experience and automatically refining its parameter database to maintain current and accurate information.
Data Source
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AI summary
The present disclosure relates to system, method and apparatuses for determining parameter settings for a power generation system and a tangible computer readable medium therefor. In an embodiment of the present disclosure, the system comprises at least one processor; and at least one memory storing computer executable instructions. The at least one memory and the computer executable instructions are configured to, with the at least one processor, cause the system to: divide historical power related data of the power generation system into a plurality of power load segments based on typical power load values and the number of the historical power related data; identify feasible parameter ranges for each of the plurality of power load segments; and determine optimal parameter settings for each of the plurality of power load segments, based on the identified feasible parameters ranges and correlations between system energy efficiency and relative parameters of each of the plurality of power load segments. The embodiments of the present disclosure provide a highly adaptive solution for determining optimal parameter settings instead of an equipment specific solution and it can be applied to different power generation systems, especially coal-fired power plant, as well as different operation conditions.