CN-121997796-A - Energy-saving steam turbine performance prediction system based on fluid mechanics

CN121997796ACN 121997796 ACN121997796 ACN 121997796ACN-121997796-A

Abstract

The invention relates to the field of performance prediction management, and discloses a fluid mechanics-based energy-saving turbine performance prediction system which is used for providing a solution for performance prediction and management of a turbine. The energy-saving steam turbine performance prediction system based on fluid mechanics comprises the steps of generating vortex dynamics characteristic data by acquiring geometric and working condition parameters of a steam turbine and utilizing a vortex evolution physical model, calculating entropy yield distribution by combining an entropy yield analysis model of physical coupling, and generating a quantized performance index based on a total entropy yield value. The quantitative performance index data provided by the invention provides a basis for the selection of the commercial operation mode, the energy efficiency assessment and the preventive maintenance plan formulation of the steam turbine, and greatly improves the working efficiency of the energy assessment and the commercial management of the steam turbine.

Inventors

XING SHENGLI
ZHANG JIAHAO
TU CHAO

Assignees

大唐蒲城第二发电有限责任公司

Dates

Publication Date: 20260508
Application Date: 20251212

Claims (9)

1. An energy efficient turbine performance prediction system based on fluid mechanics, comprising: The acquisition module is used for acquiring the geometric parameters and the preset operation condition parameters of the through-flow component of the target steam turbine, processing the geometric parameters and the operation condition parameters and generating input parameters; The evolution module is used for inputting the input parameters into a vortex evolution physical model to calculate and generating vortex dynamics characteristic data describing the strength and the distribution characteristics of a vortex structure in a multistage flow field inside the steam turbine; The analysis module is used for calculating through a pre-established entropy yield analysis model which is physically coupled with the vortex dynamics characteristic data to generate entropy yield distribution data; The quantization module is used for obtaining a total entropy production value reflecting the integral irreversible energy efficiency loss level of the system according to the entropy yield distribution data and obtaining quantization performance index data of the target steam turbine under a preset operation condition based on the total entropy production value and a preset performance standard; And the management module is used for taking the quantitative performance index data as a core decision basis and generating a business management output for guiding the selection of a business operation mode of the steam turbine, the assessment and evaluation of energy efficiency or the establishment of a preventive maintenance plan.
2. The hydrodynamically-based energy-efficient steam turbine performance prediction system of claim 1, comprising: Acquiring original geometric data of a through-flow component of a target turbine and original physical parameters under a preset operation condition; Determining and generating a system characteristic scale reference based on the inherent physical characteristics and the design operation conditions of the target turbine; Converting the original geometric data by utilizing the system characteristic scale standard to generate dimensionless geometric parameters describing the relative size and shape of the through-flow component; Converting the original physical parameters by using the system characteristic scale standard to generate dimensionless working condition parameters for describing the relative state of the operation working condition; and combining the dimensionless geometric parameters with the dimensionless working condition parameters to generate input parameters.
3. The hydrodynamically-based energy-efficient steam turbine performance prediction system of claim 2, comprising: Based on the input parameters, establishing a continuous calculation domain covering the steam turbine from a steam inlet domain to a steam outlet domain through a multi-stage through-flow component, and carrying out physical subregion division on the continuous calculation domain according to the geometric and flow characteristics of a flow channel to generate a multi-stage coupled flow field calculation architecture; In a multistage coupling flow field computing architecture, setting initial flow conditions and transmission boundary conditions between stages according to working condition parameters to generate a complete physical field initial value; Carrying out iterative solution under the multistage coupled flow field computing architecture and the complete physical field initial value, computing the vorticity vector of each point in the flow field and the change of the vorticity vector with time or space, and generating original vorticity field data; and carrying out feature extraction and post-processing on the original vortex flow field data, identifying and quantifying a key vortex structure, and generating vortex dynamics feature data.
4. A hydrodynamically-based energy-saving steam turbine performance prediction system according to claim 3, comprising: Deducing key speed gradient physical quantity related to viscous dissipation in a flow field according to vortex space structure and strength information described by the vortex dynamics characteristic data to generate speed gradient field data; generating original local entropy yield data according to physical relations which are defined in an entropy yield analysis model and reflect an irreversible dissipation process of fluid micro-groups based on the speed gradient field data; According to a vortex evolution path and a multi-stage flow field structure contained in the vortex dynamics characteristic data, carrying out space correlation and interstage transfer analysis on the original local entropy yield data, quantifying transport and accumulation effects of entropy products in a flow field, and generating entropy product transfer and distribution network data; Generating entropy yield distribution data according to the original local entropy yield data and the entropy yield transfer and distribution network data.
5. The hydrodynamically-based energy-efficient steam turbine performance prediction system according to claim 4, wherein the local entropy yield is set to Then: Where mu is the steam dynamic viscosity, T is the local temperature, The rate of change of the velocity components in the x, y, z directions in their own directions are indicated, respectively.
6. The energy-saving steam turbine performance prediction system based on fluid mechanics according to claim 4, wherein based on the entropy yield distribution data and the multistage coupled flow field calculation architecture, matching diagnosis is performed on a current entropy yield distribution mode by combining a preset entropy yield abnormal distribution feature library under a typical fault mode, and a flow field health state diagnosis report is generated; Performing association analysis on the high entropy production abnormal region identified in the flow field health state diagnosis report and the corresponding vortex structure described by the vortex dynamics characteristic data, determining specific vortex evolution behavior causing abnormal entropy production, and generating a vortex entropy production association analysis report; Reversely deducing key flow control parameters required for inhibiting the evolution of the harmful vortex or reducing the influence of the harmful vortex according to the fault physical mechanism disclosed by the vortex entropy production association analysis report, and generating a flow control parameter adjustment suggestion set; The flow control parameter adjustment proposal set is combined with the actual adjustable operation parameters of the steam turbine to carry out feasibility mapping and conversion to form a concrete operation instruction proposal scheme; And generating on-line flow regulation and health maintenance guide according to the flow field health state diagnosis report and the specific operation instruction proposal scheme.
7. The hydrodynamically-based energy-efficient steam turbine performance prediction system according to claim 4, comprising: Carrying out space domain integral calculation on the entropy yield distribution data in the covered full-through flow domain according to a multi-stage coupled flow field calculation architecture to obtain entropy yield component data of each component and each sub-region corresponding to each stage of through flow component and each flow sub-region respectively; summarizing entropy production component data of each component and each sub-region, and generating a total entropy production value of a physical system by combining the characteristic scale standard of the system; Calling preset performance reference data based on the total entropy production value of the physical system, obtaining an efficiency correction value caused by entropy production loss through coupling calculation, and generating predicted efficiency data of the target steam turbine under the preset operation working condition; Combining the predicted efficiency data with the part of the characteristic load and the energy input in the working condition parameters to generate multi-dimensional working condition point performance data, and repeating the process according to a plurality of preset variable working condition parameters to generate variable working condition performance curve data; And generating a quantized performance index data packet according to the prediction efficiency data, the multidimensional working condition point performance data and the variable working condition performance curve data.
8. The hydrodynamically-based energy-efficient steam turbine performance prediction system of claim 7, comprising: Identifying key components and high-loss areas with the largest energy efficiency loss in a through-flow system based on entropy yield component data and entropy yield distribution data of all components and subareas in the quantization performance index data packet, and generating a design optimization parameter suggestion set; based on the variable working condition performance curve data in the quantized performance index data packet, generating an economical optimal operation strategy packet by combining a preset commercial electricity price and fuel cost model; Starting a new design iteration and performance prediction process in a digital design platform of the steam turbine based on the design optimization parameter suggestion set, and utilizing updated quantized performance index data to evaluate the optimization effect so as to generate a final design improvement scheme; Based on the historical and current prediction efficiency data and the evolution trend of entropy production component data of each component in the quantized performance index data packet, a component level energy efficiency decline model is established, a performance decay path and the residual high-efficiency operation life of a key component are predicted, and a preventive maintenance priority list and a time plan are generated; And generating business management output according to the final design improvement scheme, the economic optimal operation strategy package, the preventive maintenance priority list and the time plan.
9. The hydrodynamically-based energy-saving steam turbine performance prediction system of claim 1, further comprising an evaluation module: Receiving geometric parameters and operation condition parameters of a through-flow component of at least one comparison turbine, and processing and generating quantized performance index data of the at least one comparison turbine; performing standard matching analysis on the quantized performance index data of the target steam turbine and the quantized performance index data of the at least one comparison steam turbine, extracting efficiency differences, entropy production distribution differences and vortex structure differences under the same or similar working condition parameters, and generating a multi-model standard matching analysis report; based on the multi-model benchmarking analysis report, a design criterion and an energy efficiency evaluation benchmark library of the turbine through-flow component are established by combining with a preset industry energy efficiency grade standard or design specification; Pre-evaluating geometric parameters of a new turbine scheme in a conceptual design stage by applying a design criterion and an energy efficiency evaluation reference library, screening a preliminary design scheme set meeting a target performance threshold, and generating a new scheme performance pre-evaluation report; and generating a comprehensive reference data product according to the multi-model benchmarking analysis report, the turbine through-flow component design criterion and the energy efficiency evaluation reference library and the new scheme performance pre-evaluation report.

Description

Energy-saving steam turbine performance prediction system based on fluid mechanics Technical Field The invention relates to the field of performance prediction management, in particular to an energy-saving steam turbine performance prediction system based on fluid mechanics. Background Under the big background that the global energy crisis is increasingly severe, energy conservation and emission reduction become global consensus, the power industry is taken as a large household of energy consumption and carbon emission, and is faced with huge energy conservation and emission reduction pressure. As a core device in power generation, a steam turbine has an operation efficiency directly related to the utilization efficiency of energy and the power generation cost. The performance of the steam turbine is improved, the energy loss in the operation process is reduced, and the method has important significance for improving the overall energy efficiency and reducing the carbon emission of the power industry. In aspects of commercial operation mode selection, energy efficiency assessment and preventive maintenance planning and the like of the steam turbine, the prior art often cannot provide accurate and quantized performance index data as decision basis. When making relevant decisions, enterprises mainly rely on experience judgment and qualitative analysis, lack of scientificity and objectivity, and easily cause decision errors, so that economic losses are brought to the enterprises; In the aspect of steam turbine performance prediction and management, the prior art only focuses on the performance of single equipment or single link, and lacks the view angle of optimizing from the whole system. In the operation management process of the steam turbine, the high-efficiency utilization of energy and the improvement of the overall energy efficiency are difficult to realize, and the requirements of energy conservation, emission reduction and sustainable development of enterprises cannot be met; conventional turbine performance prediction methods typically require extensive experimentation and simulation calculations, which are complex and time consuming. In practical application, it is difficult to rapidly and accurately predict the performance of the steam turbine under different operation conditions, and the requirements of enterprise real-time monitoring and optimizing operation cannot be met; Because the prior art has defects in accuracy and efficiency of performance prediction, the prior art is limited to a certain extent in the commercial application of the steam turbine, and enterprises cannot fully utilize the performance prediction technology when selecting the commercial operation mode of the steam turbine, performing energy efficiency assessment and making a preventive maintenance plan, so that the maximization of commercial interests and the minimization of operation cost are difficult to realize. Therefore, we propose a fluid mechanics based energy efficient turbine performance prediction system to solve the above problems. Disclosure of Invention The invention provides a fluid mechanics-based energy-saving turbine performance prediction system, which is used for providing a solution for turbine performance prediction and management. The invention provides a fluid mechanics-based energy-saving steam turbine performance prediction system, which comprises an acquisition module, an evolution module, an analysis module and a quantization module, wherein the acquisition module is used for acquiring geometric parameters of a through-flow component of a target steam turbine and preset operation condition parameters, processing the geometric parameters and the operation condition parameters to generate input parameters, the evolution module is used for inputting the input parameters into a vortex evolution physical model to calculate so as to generate vortex dynamics characteristic data for describing the strength and the distribution characteristics of a vortex structure in a multistage flow field inside the steam turbine, the analysis module is used for calculating through a pre-established entropy yield analysis model which is physically coupled with the vortex dynamics characteristic data so as to generate entropy yield distribution data, the quantization module is used for obtaining a total entropy yield value reflecting the irreversible energy efficiency loss level of the whole system according to the entropy yield distribution data and obtaining quantized performance index data of the target steam turbine under the preset operation condition based on the total entropy yield value and the preset performance standard, and the management module is used for taking the quantized performance index data as a core decision basis to generate a business decision-making basis for guiding business operation mode selection, energy efficiency assessment or preventive maintenance management plan of the steam turbine. Optio