Energy efficiency evaluation method for ammonia-coal co-combustion power station boiler

Abstract

The invention discloses an energy efficiency evaluation method for an ammonia-coal co-combustion power station boiler, and belongs to the technical field of boiler energy efficiency analysis. Comprising the following steps: step 1, establishing an energy efficiency evaluation index system of the ammonia-coal co-combustion power station boiler; step 2, establishing a fuzzy matrix of the ammonia-coal co-combustion boiler; 3, determining a weight coefficient of an evaluation index in the energy efficiency evaluation index system by adopting an entropy weight method; step 4, performing step-by-step evaluation on the energy efficiency evaluation index system by adopting a multi-stage fuzzy comprehensive evaluation method, calculating a final score and determining an evaluation grade; according to the energy efficiency evaluation method for the ammonia-coal co-combustion power station boiler, multi-index and multi-factor conditions in the dynamic operation process of the ammonia-coal co-combustion power station boiler are fully considered, the ammonia-coal boiler can be scientifically and accurately evaluated, meanwhile, calculation is kept simple and convenient as much as possible, and a new evaluation criterion is provided for evaluating the overall operation effect of a boiler system.

Description

Technical Field

[0001] The invention relates to an energy efficiency evaluation method for an ammonia-coal co-firing power station boiler, belonging to the technical field of boiler energy efficiency analysis. Background Art

[0002] With the proposal of the "dual carbon" goal, zero-carbon fuel ammonia has received more and more attention in the power industry. Blending ammonia fuel in traditional coal-fired power plant boilers is a powerful means to achieve large-scale carbon emission reduction in my country's power industry. During the operation of ammonia-coal co-firing boilers, energy efficiency evaluation is one of the core tasks to understand the operating status of the boiler; by accurately evaluating the energy efficiency of the boiler, it is possible to effectively identify energy-saving potential, optimize energy utilization, reduce operating costs, and reduce environmental impact. However, the traditional power plant boiler energy efficiency evaluation method cannot adapt to the actual situation of ammonia-coal co-firing boilers, and the complex effects of the ammonia blending process on combustion efficiency and pollutant emissions cannot be quantitatively evaluated. Therefore, in order to solve the above problems, it is urgent to develop a more comprehensive and practical energy efficiency evaluation method to meet the challenges brought by the new combustion method of ammonia-coal co-firing. Summary of the invention

[0003] To solve the above problems, the present invention proposes an energy efficiency evaluation method for an ammonia-coal co-firing power plant boiler, which comprehensively considers multiple key indicators related to the operation of an ammonia-coal co-firing power plant boiler and provides a new evaluation criterion for the overall operation of the system.

[0004] The energy efficiency evaluation method of the ammonia-coal co-firing power station boiler of the present invention comprises the following steps: Step 1: Establish an energy efficiency evaluation index system for ammonia-coal co-firing power station boilers; Step 2: Establish the fuzzy matrix of ammonia-coal co-firing boiler; Step 3: Use the entropy weight method to determine the weight coefficients of the evaluation indicators in the energy efficiency evaluation index system; Step 4: Use the multi-level fuzzy comprehensive evaluation method to evaluate the energy efficiency evaluation index system step by step, calculate the final score and determine the evaluation level.

[0005] Furthermore, the energy efficiency evaluation index system of the ammonia-coal co-firing power plant boiler in step one includes a target layer, a criterion layer and a scheme layer; the target layer is the energy efficiency evaluation of the ammonia-coal co-firing power plant boiler; the criterion layer is the combustion index, environmental protection index, and economic index; the scheme layer is the coal powder burnout rate, the change value of the furnace outlet flue gas temperature, the CO2 reduction, the NO emission, the fuel cost increase, and the exergy efficiency.

[0006] Furthermore, the pulverized coal burnout rate and the flue gas temperature change at the furnace outlet are both combustion indicators; the CO2 reduction and NO emissions are both environmental protection indicators; the fuel cost increase and exergy efficiency are both economic indicators.

[0007] Furthermore, the specific process of establishing the fuzzy matrix of the ammonia-coal co-firing boiler in step 2 is as follows: Firstly, the evaluation factor set of ammonia-coal co-firing boiler is established according to the evaluation index system in step 1; Secondly, a comment set is established corresponding to different states of boiler equipment; Again, calculate the relative degradation degree of each indicator; Finally, the membership function is determined and the fuzzy matrix is ​​established.

[0008] Furthermore, the specific process of using the entropy weight method in step 3 to determine the weight coefficient of the evaluation index in the energy efficiency evaluation index system is as follows: First, the original data matrix is ​​normalized to construct a normalized matrix; Secondly, calculate the information entropy of the normalized matrix; Finally, the weight value of each indicator is calculated based on the information entropy.

[0009] Furthermore, the specific process of using the multi-level fuzzy comprehensive evaluation method to evaluate the energy efficiency evaluation index system step by step, and calculating the final score and determining the evaluation level as described in step 4 is as follows: Firstly, the fuzzy matrix is ​​transformed into a fuzzy linear form to achieve the weighted synthesis of the weight vector and the fuzzy matrix. Secondly, through the fuzzy operator Calculation is performed to obtain the first-level fuzzy comprehensive evaluation result of the combustion index; Again, through the fuzzy operator Operation, to obtain the first-level fuzzy comprehensive evaluation results of environmental protection indicators; Again, through the fuzzy operator Operation, to obtain the first-level fuzzy comprehensive evaluation results of economic indicators; Finally, the secondary fuzzy comprehensive evaluation results are calculated.

[0010] Compared with the prior art, the energy efficiency evaluation method of the ammonia-coal co-firing power station boiler of the present invention fully considers the multi-indicator and multi-factor conditions in the dynamic operation process of the ammonia-coal co-firing power station boiler, can scientifically and accurately evaluate the ammonia-coal boiler while keeping the calculation as simple as possible, and provides a new evaluation criterion for evaluating the overall operation effect of the boiler system. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 It is a schematic diagram of the flow chart of the energy efficiency evaluation method of the present invention.

[0012] Figure 2 It is a schematic diagram of the energy efficiency evaluation index system of the ammonia-coal co-firing power station boiler established in the present invention. DETAILED DESCRIPTION

[0013] like Figure 1 and Figure 2 The energy efficiency evaluation method of the ammonia-coal co-firing power station boiler shown includes the following steps: Step 1: Establish an energy efficiency evaluation index system for ammonia-coal co-firing power station boilers; The energy efficiency evaluation index system of the ammonia-coal co-firing power station boiler includes a target layer, a criterion layer and a scheme layer; the target layer is the energy efficiency evaluation of the ammonia-coal co-firing power station boiler; the criterion layer is the combustion index, environmental protection index and economic index; the scheme layer is the coal powder burnout rate, the flue gas temperature change value at the furnace outlet, the CO2 reduction, the NO emission, the fuel cost increase and the exergy efficiency; the coal powder burnout rate and the flue gas temperature change value at the furnace outlet are both combustion indexes; the CO2 reduction and the NO emission are both environmental protection indexes; the fuel cost increase and the exergy efficiency are both economic indexes; Step 2: Establish the fuzzy matrix of ammonia-coal co-firing boiler; Firstly, the evaluation factor set of ammonia-coal co-firing boiler is established according to the evaluation index system in step 1; Secondly, a comment set is established corresponding to different states of boiler equipment; Again, calculate the relative degradation degree of each indicator; Finally, the membership function is determined and the fuzzy matrix is ​​established; Step 3: Use the entropy weight method to determine the weight coefficients of the evaluation indicators in the energy efficiency evaluation index system; First, the original data matrix is ​​normalized to construct a normalized matrix; Secondly, calculate the information entropy of the normalized matrix; Finally, the weight value of each indicator is calculated based on information entropy; Step 4: Use the multi-level fuzzy comprehensive evaluation method to evaluate the energy efficiency evaluation index system step by step, calculate the final score and determine the evaluation level; Firstly, the fuzzy matrix is ​​transformed into a fuzzy linear form to achieve the weighted synthesis of the weight vector and the fuzzy matrix. Secondly, through the fuzzy operator Calculation is performed to obtain the first-level fuzzy comprehensive evaluation result of the combustion index; Again, through the fuzzy operator Operation, to obtain the first-level fuzzy comprehensive evaluation results of environmental protection indicators; Again, through the fuzzy operator Operation, to obtain the first-level fuzzy comprehensive evaluation results of economic indicators; Finally, the secondary fuzzy comprehensive evaluation results are calculated.

[0014] Embodiment 1: The energy efficiency evaluation method of the ammonia-coal co-firing power station boiler of the present invention comprises the following steps: Step 1: Establish an energy efficiency evaluation index system for ammonia-coal co-firing power station boilers; First, it is necessary to analyze the complex problem hierarchically, decompose the problem into its components, and construct a hierarchical model; by analyzing the interrelationships and attributes between the elements, the decomposition is carried out step by step to ensure that the elements of each level are based on the standards of the previous level; specifically, the gas boiler energy efficiency evaluation system constructed by this method adopts a three-level structure, including the target layer, the criterion layer, and the scheme layer; the criterion layer covers the indicators of combustion, environmental protection, and economy, and each criterion is further subdivided into 6 secondary indicators, as shown in Table 1; the system comprehensively covers all factors affecting the boiler energy efficiency evaluation, and has good hierarchy and systematicity; Table 1 Hierarchical structure of comprehensive evaluation indicators

[0015] Step 2: Establish the fuzzy matrix of ammonia-coal co-firing boiler; Firstly, the evaluation factor set of ammonia-coal co-firing boiler is established according to the evaluation index system in Table 1; the three primary indicators and six secondary indicators together constitute the evaluation factor set U={U1, U2, U3}; among which U1={U 11 , U 12},U2={U 21 , U 22},U3={U 31 , U 32}; Secondly, corresponding to the different states of the boiler equipment, the comments of the evaluation indicators are divided into 4 categories, the comment set V = {v1, v2, v3, v4} = {excellent, good, medium, poor}, the specific description is shown in Table 2; Table 2 Description of comment set

[0016] Secondly, the relative degradation degree of each indicator is calculated and the relative degradation degree formula is introduced to eliminate the influence of different indicator types, physical meanings and quantitative units, and to show the difference between the current evaluation indicator and the target value; In order to comprehensively evaluate the ammonia-coal co-firing power plant boiler, Table 3 lists the specific parameter values ​​of ten operating conditions; in each operating condition, the heat input and total excess air coefficient remain unchanged; Table 3 Working condition specific parameters The calculated values ​​of each secondary index are statistically shown in Table 4; the upper and lower limits a and b of each index are determined by data statistics and empirical judgment; Table 4 Values ​​of secondary evaluation indicators under various working conditions

[0017] Taking working condition 3 as an example, the relative degradation degree of each evaluation index of this working condition is calculated as shown in Table 5: Table 5 Relative degradation of each index under working condition 3

[0018] Finally, the membership function is determined and the fuzzy matrix is ​​established. When determining the membership function, the optimal performance of the factor is set to membership μ=1, and the worst performance is μ=0. When the relative degradation degree of the indicator is u, the membership function of the relevant comment status v1 to v4 is expressed as follows: , , , ; Use the membership function established above to calculate each index U i Corresponding to each comment V j The membership degree r ij , then the fuzzy matrix R can be constructed pq =(r ij ) ni×s , where p is the working condition number, q represents the secondary index, ni is the number of corresponding indicators at different levels, and s is the number of comments; the fuzzy matrix is ​​constructed as follows: , , ; Step 3: Use the entropy weight method to determine the weight coefficients of the evaluation indicators in the energy efficiency evaluation index system; First, normalize the original data matrix and construct a normalized matrix; construct the matrix ; Where m is the number of actual working condition groups, which is 10; n is the number of secondary evaluation indicators contained in the primary indicator set, which is 2; Normalize the P matrix to get the new matrix Q. The calculation process is: For the bigger-is-better metric: ; For smaller is better indicators: ; Among them, p max With p min They are the maximum and minimum values ​​of the measured indicators under different working conditions; The three matrices are: ; Normalize the three matrices to get the new matrix Q, and we get: ; Secondly, the information entropy of the normalized matrix is ​​calculated; the information entropy formula for calculating each indicator is: , ; And define hour, ; The matrix F is as follows: ; Finally, the weight value of each indicator is calculated based on the information entropy; The weights of the secondary indicators are obtained: the weight of the combustion indicator w1={0.4721, 0.5279}, the weight of the environmental protection indicator w2={0.5319, 0.4681}, and the weight of the economic indicator w3={0.5309, 0.4691}; Similarly, we can get: the weight of the first-level index W = {0.3264, 0.3172, 0.3564}; Step 4: Use the multi-level fuzzy comprehensive evaluation method to evaluate the energy efficiency evaluation index system step by step, calculate the final score and determine the evaluation level; First, through the fuzzy operator Calculation is performed to obtain the first-level fuzzy comprehensive evaluation result of the combustion index; Specifically, the generalized fuzzy operator is used to calculate the first-level fuzzy comprehensive evaluation of the combustion index of working condition 3: ; According to the maximum membership principle, the "good" in the final evaluation result has the largest membership, and the combustion index is judged as "good"; Secondly, through the fuzzy operator Operation, to obtain the first-level fuzzy comprehensive evaluation results of environmental protection indicators; Specifically, the generalized fuzzy operator is used to calculate the first-level fuzzy comprehensive evaluation of the environmental protection index of working condition 3: ; According to the maximum membership principle, the "medium" in the final evaluation result has the largest membership, and the environmental protection index is judged as "medium"; Again, through the fuzzy operator Operation, to obtain the first-level fuzzy comprehensive evaluation results of economic indicators; The first-level fuzzy comprehensive evaluation of economic indicators of working condition 3 is calculated using generalized fuzzy operators: ; According to the maximum membership principle, the "excellent" membership in the final evaluation result is the largest, and the economic indicators are judged as "excellent"; Finally, the secondary fuzzy comprehensive evaluation results are calculated; The evaluation results of each index in working condition 3 are: B 31 = (0, 0.4721, 0.4038, 0.1240), B 32 = (0.3253, 0.1427, 0.5319, 0), B 33 =(0.4691,0,0.2919,0.2389), so the secondary comprehensive judgment matrix of the evaluation factor set U is: ; The final evaluation result is According to the maximum membership principle, this ammonia-coal co-firing power station boiler can be identified as "medium".

[0019] The energy efficiency evaluation method of the ammonia-coal co-firing power station boiler of the present invention fully considers the multi-indicator and multi-factor conditions during the dynamic operation of the ammonia-coal co-firing power station boiler, can scientifically and accurately evaluate the ammonia-coal boiler while keeping the calculation as simple as possible, and provides a new evaluation criterion for evaluating the overall operation effect of the boiler system.

[0020] The above embodiments are only preferred implementations of the present invention, so all equivalent changes or modifications made according to the structures, features and principles described in the scope of the patent application of the present invention are included in the scope of the patent application of the present invention.

Claims

1. A method for evaluating the energy efficiency of an ammonia-coal co-firing power station boiler, characterized in that: The following steps are involved: Step 1: Establish an energy efficiency evaluation index system for ammonia-coal co-firing power station boilers; Step 2: Establish the fuzzy matrix of ammonia-coal co-firing boiler; Step 3: Use the entropy weight method to determine the weight coefficients of the evaluation indicators in the energy efficiency evaluation index system; Step 4: Use the multi-level fuzzy comprehensive evaluation method to evaluate the energy efficiency evaluation index system step by step, calculate the final score and determine the evaluation level.

2. The energy efficiency evaluation method for ammonia-coal co-firing power station boiler according to claim 1, characterized in that: The energy efficiency evaluation index system of the ammonia-coal co-firing power plant boiler described in step one includes a target layer, a criterion layer and a scheme layer; the target layer is the energy efficiency evaluation of the ammonia-coal co-firing power plant boiler; the criterion layer is the combustion index, environmental protection index, and economic index; the scheme layer is the coal powder burnout rate, the change value of the furnace outlet flue gas temperature, the CO2 reduction, the NO emission, the fuel cost increase, and the exergy efficiency.

3. The energy efficiency evaluation method for ammonia-coal co-firing power station boiler according to claim 2 is characterized in that: The pulverized coal burnout rate and the change in furnace outlet flue gas temperature are both combustion indicators; the CO2 reduction and NO emissions are both environmental protection indicators; the fuel cost increase and exergy efficiency are both economic indicators.

4. The energy efficiency evaluation method for ammonia-coal co-firing power station boiler according to claim 1, characterized in that: The specific process of establishing the fuzzy matrix of the ammonia-coal co-firing boiler described in step 2 is as follows: Firstly, the evaluation factor set of ammonia-coal co-firing boiler is established according to the evaluation index system in step 1; Secondly, a comment set is established corresponding to different states of boiler equipment; Again, calculate the relative degradation degree of each indicator; Finally, the membership function is determined and the fuzzy matrix is ​​established.

5. The energy efficiency evaluation method for ammonia-coal co-firing power station boiler according to claim 1, characterized in that: The specific process of using the entropy weight method to determine the weight coefficient of the evaluation index in the energy efficiency evaluation index system described in step 3 is as follows: First, the original data matrix is ​​normalized to construct a normalized matrix; Secondly, calculate the information entropy of the normalized matrix; Finally, the weight value of each indicator is calculated based on the information entropy.

6. The energy efficiency evaluation method for ammonia-coal co-firing power station boiler according to claim 1, characterized in that: The specific process of using the multi-level fuzzy comprehensive evaluation method to evaluate the energy efficiency evaluation index system step by step, calculate the final score and determine the evaluation level as described in step 4 is as follows: Firstly, the fuzzy matrix is ​​transformed into a fuzzy linear form to achieve the weighted synthesis of the weight vector and the fuzzy matrix. Secondly, through the fuzzy operator Calculation is performed to obtain the first-level fuzzy comprehensive evaluation result of the combustion index; Again, through the fuzzy operator Operation, to obtain the first-level fuzzy comprehensive evaluation results of environmental protection indicators; Again, through the fuzzy operator Operation, to obtain the first-level fuzzy comprehensive evaluation results of economic indicators; Finally, the secondary fuzzy comprehensive evaluation results are calculated.

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