A steam turbine efficiency optimization system and optimization method thereof

Abstract

The invention discloses a steam turbine efficiency optimization system, comprising a steam turbine operating parameter acquisition module for acquiring steam turbine operating parameters; a sliding pressure curve generation module for generating a sliding pressure curve of steam turbine operation; and a sliding pressure curve optimization module for optimizing the sliding pressure curve. The invention can improve the deficiencies of the prior art and improve the accuracy of steam turbine tea curve optimization.

Description

Technical Field

[0001] The invention relates to the technical field of steam turbine efficiency optimization, in particular to a steam turbine efficiency optimization system and an optimization method thereof. Background Art

[0002] In the prior art, thermal power plants usually operate the steam turbine in a "constant pressure-sliding pressure" alternating mode to achieve higher operating efficiency under different working conditions. Since there are many unit operating parameters involved in the sliding pressure operation process, there are obvious errors in the optimization of the sliding pressure operation curve due to parameter measurement errors and calculation accuracy. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a steam turbine efficiency optimization system and an optimization method thereof, which can solve the deficiencies of the prior art and improve the accuracy of steam turbine scented tea curve optimization.

[0004] In order to solve the above technical problems, the technical solutions adopted by the present invention are as follows.

[0005] A steam turbine efficiency optimization system, comprising:

[0006] Steam turbine operating parameter collection module, used to collect steam turbine operating parameters;

[0007] A sliding pressure curve generation module is used to generate a sliding pressure curve for steam turbine operation;

[0008] The sliding pressure curve optimization module is used to optimize the sliding pressure curve.

[0009] An optimization method for the above-mentioned steam turbine efficiency optimization system comprises the following steps:

[0010] A. The steam turbine operating parameter acquisition module acquires the steam turbine operating parameters, and then sends the steam turbine operating parameters to the sliding pressure curve generation module;

[0011] B. The sliding pressure curve generation module classifies the steam turbine operating parameters according to parameter categories, and then traverses all parameter categories, deletes one category of steam turbine operating parameters each time, calculates the sliding pressure curve using the remaining steam turbine operating parameters of other categories, and then sends all the generated sliding pressure curves to the sliding pressure curve optimization module;

[0012] C. The sliding pressure curve optimization module performs simulation experiments on each sliding pressure curve in turn to obtain the average efficiency of the steam turbine corresponding to each sliding pressure curve;

[0013] D. The sliding pressure curve optimization module selects the sliding pressure curve with the highest average efficiency of the steam turbine as the optimization object, and corrects the steam turbine operating parameters deleted when generating the optimization object;

[0014] E. The sliding pressure curve generation module uses the turbine operating parameters corrected in step D to perform secondary calculation optimization on the optimization object to obtain the optimized sliding pressure curve.

[0015] Preferably, the turbine operating parameters include main steam pressure, main steam temperature, reheat temperature, high-pressure cylinder exhaust pressure, and high-pressure cylinder exhaust temperature.

[0016] Preferably, in step D, correcting the turbine operating parameters comprises the following steps:

[0017] D1. Use the existing parameter discrete numerical fitting to establish the correlation curve between the parameter category to be corrected and other parameter categories on the time coordinate axis;

[0018] D2, synchronously traverse all the associated curves, and mark the discrete parameter points whose total deviation from the associated curve is greater than the set threshold;

[0019] D3, the discrete parameter point marked in step D2 is deleted, and other discrete parameter points adjacent to the deleted parameter point are used for weighted averaging. The weighted average value is used as the corrected discrete parameter point, and the weighted value is proportional to the deviation between its parameter value and the parameter value of the deleted parameter point.

[0020] Preferably, in step D2, the total deviation between the discrete parameter points and the associated curve is the sum of the minimum distances from the discrete parameter points to the associated curve.

[0021] Preferably, in step E, performing secondary calculation optimization on the optimization object includes the following steps:

[0022] The corrected turbine operating parameters are added to the turbine operating parameters of other categories, and the sliding pressure curve is calculated using the same calculation method as step B. The sliding pressure curve after the secondary calculation optimization is compared with the optimization object. If its linear correlation is greater than the preset threshold, the optimization is completed. Otherwise, the sliding pressure curve after the secondary calculation optimization is adjusted so that its linear correlation with the optimization object is greater than the preset threshold.

[0023] The beneficial effects brought about by adopting the above technical solution are: the present invention changes the existing optimization method of the sliding pressure curve, obtains multiple groups of sliding pressure curves by matching different types of operating parameters, and then uses the characteristics between different sliding pressure curves to realize the recognition of parameter accuracy, and then corrects the parameters with large errors. By improving the correction process, there is no need for additional measurement and data collection, which greatly simplifies the parameter correction process. Finally, the corrected parameters are used to optimize the sliding pressure curve to obtain the final sliding pressure curve. The entire optimization process relies on the intrinsic connection between different parameters and sliding pressure curves, and there is no need to upgrade the hardware of the parameter measurement equipment, and there is no need to use complex data processing algorithms for error correction, which is very suitable for upgrading and transformation in existing systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a schematic diagram of a specific implementation mode of the present invention. DETAILED DESCRIPTION

[0025] Reference Figure 1 , a specific embodiment of the present invention includes,

[0026] The steam turbine operating parameter acquisition module 1 is used to acquire the steam turbine operating parameters; the steam turbine operating parameters include main steam pressure, main steam temperature, reheat temperature, high-pressure cylinder exhaust pressure, and high-pressure cylinder exhaust temperature;

[0027] The sliding pressure curve generating module 2 is used to generate the sliding pressure curve of the steam turbine operation;

[0028] The sliding pressure curve optimization module 3 is used to optimize the sliding pressure curve.

[0029] An optimization method for the above-mentioned steam turbine efficiency optimization system comprises the following steps:

[0030] A. The steam turbine operating parameter acquisition module 1 acquires the steam turbine operating parameters, and then sends the steam turbine operating parameters to the sliding pressure curve generation module 2;

[0031] B. The sliding pressure curve generation module 2 classifies the steam turbine operating parameters according to parameter categories, and then traverses all parameter categories, deletes one category of steam turbine operating parameters each time, calculates the sliding pressure curve using the remaining steam turbine operating parameters of other categories, and then sends all the generated sliding pressure curves to the sliding pressure curve optimization module 3;

[0032] C. The sliding pressure curve optimization module 3 performs simulation experiments on each sliding pressure curve in turn to obtain the average efficiency of the steam turbine corresponding to each sliding pressure curve;

[0033] D. The sliding pressure curve optimization module 3 selects the sliding pressure curve with the highest average efficiency of the steam turbine as the optimization object, and corrects the steam turbine operating parameters deleted when generating the optimization object; the correction of the steam turbine operating parameters includes the following steps:

[0034] D1. Use the existing parameter discrete numerical fitting to establish the correlation curve between the parameter category to be corrected and other parameter categories on the time coordinate axis;

[0035] D2. Synchronously traverse all associated curves and mark the discrete parameter points whose total deviation between the discrete parameter points and the associated curve is greater than the set threshold; the total deviation between the discrete parameter points and the associated curve is the sum of the minimum distances from the discrete parameter points to the associated curve;

[0036] D3, deleting the discrete parameter point marked in step D2, and using other discrete parameter points adjacent to the deleted parameter point for weighted averaging, the weighted average value calculated is used as the corrected discrete parameter point, and the weighted value is proportional to the deviation between its parameter value and the parameter value of the deleted parameter point;

[0037] E. The sliding pressure curve generation module 2 uses the turbine operating parameters corrected in step D to perform secondary calculation optimization on the optimization object to obtain an optimized sliding pressure curve; performing secondary calculation optimization on the optimization object includes the following steps:

[0038] The corrected turbine operating parameters are added to the turbine operating parameters of other categories, and the sliding pressure curve is calculated using the same calculation method as step B. The sliding pressure curve after the secondary calculation optimization is compared with the optimization object. If its linear correlation is greater than the preset threshold, the optimization is completed. Otherwise, the sliding pressure curve after the secondary calculation optimization is adjusted so that its linear correlation with the optimization object is greater than the preset threshold.

[0039] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for optimizing steam turbine efficiency, characterized in that The following steps are involved: A. The steam turbine operating parameter acquisition module (1) acquires the steam turbine operating parameters and then sends the steam turbine operating parameters to the sliding pressure curve generation module (2); B. The sliding pressure curve generation module (2) classifies the steam turbine operating parameters according to parameter categories, then traverses all parameter categories, deletes one category of steam turbine operating parameters each time, calculates the sliding pressure curve using the remaining steam turbine operating parameters of other categories, and then sends all the generated sliding pressure curves to the sliding pressure curve optimization module (3); C. Sliding pressure curve optimization module (3) performs simulation experiments on each sliding pressure curve in turn to obtain the average efficiency of the steam turbine corresponding to each sliding pressure curve; D. Sliding pressure curve optimization module (3) selects the sliding pressure curve with the highest average efficiency of the steam turbine as the optimization object, and corrects the steam turbine operating parameters deleted when generating the optimization object; the correction of the steam turbine operating parameters includes the following steps: D1. Use the existing parameter discrete numerical fitting to establish the correlation curve between the parameter category to be corrected and other parameter categories on the time coordinate axis; D2, synchronously traverse all the associated curves, and mark the discrete parameter points whose total deviation from the associated curve is greater than the set threshold; The total deviation between the discrete parameter point and the associated curve is the sum of the minimum distances from the discrete parameter point to the associated curve; D3, deleting the discrete parameter point marked in step D2, and using other discrete parameter points adjacent to the deleted parameter point for weighted averaging, the weighted average value calculated is used as the corrected discrete parameter point, and the weighted value is proportional to the deviation between its parameter value and the parameter value of the deleted parameter point; E. Sliding pressure curve generation module (2) uses the turbine operating parameters corrected in step D to perform secondary calculation optimization on the optimization object to obtain an optimized sliding pressure curve; performing secondary calculation optimization on the optimization object includes the following steps: The corrected turbine operating parameters are added to the turbine operating parameters of other categories, and the sliding pressure curve is calculated using the same calculation method as step B. The sliding pressure curve after the secondary calculation optimization is compared with the optimization object. If its linear correlation is greater than the preset threshold, the optimization is completed. Otherwise, the sliding pressure curve after the secondary calculation optimization is adjusted so that its linear correlation with the optimization object is greater than the preset threshold.

2. The method for optimizing steam turbine efficiency according to claim 1, characterized in that: The steam turbine operating parameters include main steam pressure, main steam temperature, reheat temperature, high-pressure cylinder exhaust pressure, and high-pressure cylinder exhaust temperature.

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