Process coupling index-based refining wastewater treatment technology screening method and system

Abstract

The invention discloses a refining and chemical wastewater treatment technology screening method and system based on process coupling indexes, and belongs to the technical field of refining and chemical wastewater treatment technology evaluation.The method comprises the steps that an evaluation system used for evaluating the refining and chemical wastewater treatment technology is constructed; forming a data matrix; determining the weight of each evaluation index; according to the data matrix and the weight, a TOPSIS method is adopted, and at least one optimal refining and chemical wastewater treatment technology is screened out from multiple refining and chemical wastewater treatment technologies; the method provided by the invention can accurately quantify the real-time treatment efficiency and stability of different refinery wastewater treatment technologies under complex working conditions, provides a quantitative basis for process optimization, reasonable resource allocation and environmental risk prevention and control, and remarkably improves the systematicness, objectivity and adaptability of refinery wastewater treatment technology selection.

Description

Technical Field

[0001] This invention relates to the field of refining wastewater treatment technology evaluation technology, specifically to a method and system for screening refining wastewater treatment technologies based on process coupling indicators. Background Technology

[0002] With rapid industrialization, water pollution has become increasingly serious, especially wastewater from the refining and chemical industry. This wastewater is complex in composition, highly toxic, and poorly biodegradable, containing large amounts of harmful substances such as oils, phenols, sulfides, and heavy metals, posing a serious threat to the ecological environment and human health. Therefore, scientifically assessing and selecting appropriate refining and chemical wastewater treatment technologies is crucial to solving this pollution problem.

[0003] Currently, there are numerous technologies for managing refining wastewater, ranging from improved biochemical processes to advanced oxidation technologies. However, the industry severely lacks a systematic, quantitative, and universally accepted evaluation framework when selecting the best feasible technology. Existing evaluations often rely on single pollutant removal rates or static investment costs. This approach has fundamental flaws: First, it ignores the stringent requirements of refining wastewater flow and dynamic water quality impacts on the stability of the treatment system, causing many technologies that perform well under ideal conditions to frequently fail in actual operation. Furthermore, traditional evaluations often view technical, economic, and environmental performance in isolation, failing to understand their inherent connections and trade-offs. For example, some technologies, while having high removal rates, may be accompanied by extremely high energy consumption and salt accumulation, leading to pollution transfer. This lack of an evaluation method has resulted in serious consequences, including: blind technology selection, significantly increased project investment risks; low operational efficiency, difficulty in coping with fluctuations in actual production, resulting in excessive emissions; and huge hidden costs, with some technologies having life-cycle costs far exceeding expectations due to stringent pretreatment requirements or the generation of large amounts of hazardous waste.

[0004] Therefore, a comprehensive evaluation method based on holistic consideration, science, system, and objectivity is needed to provide enterprises with an important tool for making scientific decisions and reducing investment risks. Summary of the Invention

[0005] To address the aforementioned problems, this invention provides a method and system for screening refining wastewater treatment technologies based on process coupling indices.

[0006] The screening method for refining and chemical wastewater treatment technologies based on process coupling indicators includes the following steps: An evaluation system is constructed for assessing refining wastewater treatment technologies. The evaluation system includes evaluation indicators for technical dimensions, economic dimensions, and environmental dimensions. The evaluation indicators for technical dimensions include at least one dynamic evaluation indicator for quantitatively characterizing the dynamic response characteristics of physical, chemical, or biological processes within the pollution treatment unit. Dynamic data of each evaluation indicator in the evaluation system corresponding to various refining wastewater treatment technologies are obtained to form a data matrix; Based on the importance of each evaluation indicator in the evaluation system, the weight of each evaluation indicator is determined. Based on the data matrix and weights, the TOPSIS method is used to screen at least one optimal refining wastewater treatment technology from a variety of refining wastewater treatment technologies.

[0007] Explanation: The above method constructs a comprehensive system encompassing multiple dimensions of technology, economy, and environment, including dynamic response characteristic evaluation indicators. This system can accurately quantify the real-time treatment efficiency and stability of different refining wastewater treatment technologies under complex operating conditions. By acquiring dynamic data to form a matrix and combining it with weight allocation, it can effectively capture subtle differences between technologies and avoid the limitations of static evaluation. The TOPSIS method is used for comprehensive comparison, which can not only scientifically select the optimal technical solution, but also clarify the advantages and disadvantages of each technology. This provides a quantitative basis for process optimization, rational resource allocation, and environmental risk prevention and control, significantly improving the systematicness, objectivity, and adaptability of refining wastewater treatment technology selection.

[0008] Furthermore, the dynamic evaluation index is one or more of the following: dynamic response time, process stability index, or adaptability coefficient.

[0009] Note: Introducing dynamic evaluation indicators such as dynamic response time, process stability index, or adaptability coefficient into the evaluation of refining wastewater treatment technology can accurately capture the real-time adjustment capability and operational stability of the treatment unit in response to actual operating conditions such as water quality fluctuations and load changes, breaking through the limitation of traditional static indicators that only reflect the performance under design conditions.

[0010] Furthermore, the evaluation system for assessing refining wastewater treatment technologies includes: Based on existing monitoring data, a first quantitative parameter is defined for the evaluation indicators used to characterize the technology dimension; the evaluation indicators for the technology dimension include pollutant removal capacity, technological advancement, process energy consumption, technological stability, and dynamic response time. Based on the cost decomposition method, a second quantitative parameter is determined for the evaluation indicators used to characterize the economic dimension; the evaluation indicators for the economic dimension include investment and operation and maintenance costs. Based on existing environmental and social monitoring data, a third quantitative parameter is determined for the evaluation indicators used to characterize the environmental dimension; the evaluation indicators for the environmental dimension include the level of solid waste generation, the level of exhaust gas generation, and the level of noise generation.

[0011] Note: The above method constructs an evaluation system through multi-dimensional quantitative parameters, achieving a comprehensive and accurate assessment of refining wastewater treatment technologies. The synergistic application of the three-dimensional quantitative parameters overcomes the subjectivity of traditional evaluations and can select the optimal solution that is technically feasible, economically reasonable, and has controllable environmental impact for different application scenarios, providing a systematic decision-making tool for the optimization and sustainable development of refining wastewater treatment technologies. The indicators of technological advancement and technological stability are qualitative indicators, and these qualitative indicators need to be converted into quantitative indicators through expert questionnaires in the future.

[0012] Furthermore, the first quantitative parameter includes pollutant removal efficiency, process energy consumption value, and dynamic response time; The second quantitative parameter includes the initial total investment cost, fixed operation and maintenance cost, variable operation and maintenance cost, and operation and maintenance cost sensitivity coefficient; The third quantitative parameter includes solid waste generation rate, exhaust gas emission concentration or exhaust gas emission rate, and noise intensity.

[0013] Note: By using measured data such as pollutant removal efficiency, process energy consumption, and dynamic response time, the technology's treatment efficiency, energy consumption level, and impact resistance can be accurately quantified. From an economic perspective, the technology's economic viability throughout its entire lifecycle is fully revealed by breaking down the initial total investment cost, fixed / variable operation and maintenance costs, and sensitivity coefficients. From an environmental perspective, exhaust gas and noise monitoring data are introduced to effectively assess the technology's potential impact on the surrounding environment.

[0014] Furthermore, dynamic data of each evaluation indicator in the evaluation system corresponding to various refining wastewater treatment technologies are obtained to form a data matrix; including: Based on monitoring data and / or a refining wastewater treatment model, the data of the first quantitative parameter is dynamically calculated; then the data of the second quantitative parameter is calculated in real time; and the data of the third quantitative parameter is acquired in real time. The data of the first quantization parameter, the data of the second quantization parameter, and the data of the third quantization parameter are standardized to obtain dynamic data; Then, a data matrix is ​​constructed using the various refining wastewater treatment technologies as rows and the dynamic data corresponding to each refining wastewater treatment technology as columns.

[0015] Note: The above method significantly improves the accuracy and effectiveness of the evaluation of refining wastewater treatment technology through dynamic data acquisition and matrix processing: standardization eliminates the differences between indicators of different dimensions, making dynamic data comparable; the above processing method not only overcomes the data lag of traditional static evaluation, but also accurately captures the fluctuation patterns in technology operation, providing dynamic optimization basis for highly variable wastewater treatment scenarios, thereby supporting more scientific technology selection and process control decisions.

[0016] Furthermore, based on the importance of each evaluation indicator in the evaluation system, the weight of each evaluation indicator is determined; including: The analytic hierarchy process (AHP) is used to calculate the weights of the evaluation indicators to obtain the subjective weights of each indicator. The objective weights of the evaluation indicators are calculated using the entropy weight method to obtain the objective weights of each indicator. The comprehensive weight of each evaluation indicator is calculated by weighting the subjective and objective weights.

[0017] Note: The above method significantly improves the scientificity and rationality of the weighting of the evaluation indicators for refining wastewater treatment technology by integrating subjective and objective weights; it enables the evaluation results to more accurately reflect the actual contribution of different indicators in complex refining wastewater treatment systems.

[0018] Furthermore, the calculation method for the comprehensive weight is shown in the following formula (1): (1) In the formula, For comprehensive weighting, The resolution coefficient; The subjective weights obtained by the analytic hierarchy process (AHP) The objective weights are obtained using the entropy weight method.

[0019] Note: The above method achieves scientific optimization of the weight allocation of evaluation indicators by introducing a resolution coefficient: the introduction of the resolution coefficient can flexibly adjust the fusion ratio of subjective weight and objective weight, so that the final weight can more accurately match the actual needs of multi-objective decision-making in refining wastewater treatment technology.

[0020] Furthermore, based on the data matrix and weights, the TOPSIS method is used to select the optimal refining wastewater treatment technology among multiple refining wastewater treatment technologies; this includes: Each evaluation indicator in the data matrix is ​​assigned a weight to obtain a standardized matrix; The TOPSIS method was used to calculate the fit of multiple refining wastewater treatment technologies in a standardized matrix. The refining wastewater treatment technology with the highest degree of fit was selected as the optimal refining wastewater treatment technology.

[0021] Note: The above method, through the combined application of weighted standardization matrix and TOPSIS method, significantly improves the objectivity and accuracy of the selection of refining wastewater treatment technologies, effectively avoiding the interference of subjective preferences in traditional screening methods. Ultimately, it selects the technical solution with the highest approximation, ensuring the comprehensive optimization of the selection results in multiple dimensions such as technical efficiency, economic cost, and environmental impact. It is particularly suitable for industrial wastewater treatment scenarios with complex treatment needs and diverse technical options, providing scientific and quantitative technical support for process decision-making.

[0022] The present invention also provides an adaptability evaluation system for refining wastewater treatment technology based on process coupling index, which is used to implement the above-mentioned screening method for refining wastewater treatment technology based on process coupling index, including: evaluation system construction module, data acquisition module, weight calculation module and screening module; The evaluation system construction module is used to construct an evaluation system for assessing refining wastewater treatment technologies. The evaluation system includes evaluation indicators for technical dimensions, economic dimensions, and environmental dimensions. The evaluation indicators for technical dimensions include at least one dynamic evaluation indicator used to quantitatively characterize the dynamic response characteristics of the physical, chemical, or biological processes within the pollution treatment unit. The data acquisition module is used to acquire dynamic data of each evaluation indicator in the evaluation system corresponding to various refining wastewater treatment technologies, forming a data matrix; The weight calculation module is used to determine the weight of each evaluation indicator based on the importance of each evaluation indicator in the evaluation system. The screening module is used to select at least one optimal refining wastewater treatment technology from a variety of refining wastewater treatment technologies based on the data matrix and weights using the TOPSIS method.

[0023] Note: The above system achieves intelligent and scientific evaluation of the entire process of adaptability assessment for refining and chemical wastewater treatment technology through modular design. This system not only overcomes the problems of fragmented indicators, data lag, and subjective bias in traditional screening methods, but also provides customized evaluation for different water quality characteristics and treatment needs, providing strong technical support for the optimization and efficient operation of industrial wastewater treatment processes.

[0024] The beneficial effects of this invention are: This invention constructs a comprehensive system encompassing multiple dimensions, including technology, economics, and environment, and incorporating dynamic response characteristic evaluation indicators. This system can accurately quantify the real-time treatment efficiency and stability of different refining wastewater treatment technologies under complex operating conditions. By acquiring dynamic data to form a matrix and combining it with weight allocation, it can effectively capture subtle differences between technologies and avoid the limitations of static evaluation. By employing the TOPSIS method for comprehensive comparison, it can not only scientifically select the optimal technical solution but also clarify the advantages and disadvantages of each technology. This provides a quantitative basis for process optimization, rational resource allocation, and environmental risk prevention and control, significantly improving the systematicness, objectivity, and adaptability of refining wastewater treatment technology selection. Attached Figure Description

[0025] Figure 1 This is a flowchart illustrating an embodiment of the present invention; Figure 2 These are the objective weights of each indicator in the biological treatment technology for refining wastewater according to embodiments of the present invention; Figure 3 This refers to the combined weights of technical indicators for the biological treatment of refining wastewater in this embodiment of the invention. Figure 4 This is a three-dimensional diagram of the comprehensive technical evaluation of an embodiment of the present invention. Detailed Implementation

[0026] To further illustrate the methods and effects of this invention, the technical solution of this invention will be clearly and completely described below in conjunction with experiments.

[0027] Example: The screening method for refining and chemical wastewater treatment technologies based on process coupling indicators includes the following steps: Figure 1 As shown; S1. Construct an evaluation system for assessing refining wastewater treatment technologies; the evaluation system includes evaluation indicators for technical dimensions, economic dimensions, and environmental dimensions; the evaluation indicators for technical dimensions include at least one dynamic evaluation indicator for quantitatively characterizing the dynamic response characteristics of physical, chemical, or biological processes within the pollution treatment unit. The dynamic evaluation index is one or more of the following: dynamic response time, process stability index, or adaptability coefficient; in this embodiment, dynamic response time is used. The evaluation system for assessing refining wastewater treatment technologies includes: Based on existing monitoring data for the technological dimensions, a first quantitative parameter is defined to characterize the evaluation indicators for the technological dimensions. These evaluation indicators include pollutant removal capacity, technological advancement, process energy consumption, technological stability, and dynamic response time. (Technological advancement and technological stability are qualitative indicators; these qualitative indicators will be converted into quantitative indicators through expert questionnaires.) Specifically, this includes identifying parameters from the existing monitoring data for the technological dimensions that can characterize pollutant removal capacity, technological advancement, process energy consumption, technological stability, and dynamic response. These parameters can be the first quantitative parameter, including pollutant removal efficiency, process energy consumption, and dynamic response time, or other parameters that can characterize the above-mentioned aspects. Based on the cost decomposition method, a second quantitative parameter is determined for the evaluation indicators used to characterize the economic dimension; the evaluation indicators for the economic dimension include investment and operation and maintenance costs; specifically, according to the cost decomposition method in the existing technology, all costs are decomposed into the initial total investment cost, fixed operation and maintenance cost, variable operation and maintenance cost, and operation and maintenance cost sensitivity coefficient. Based on existing environmental and social monitoring data, a third quantitative parameter is determined for the evaluation indicators used to characterize the environmental dimension. Specifically, among the parameters in the existing environmental and social monitoring data, the solid waste generation rate, exhaust gas emission concentration or exhaust gas emission rate, and noise intensity are identified as evaluation indicators that can characterize the environmental dimension.

[0028] For example, this embodiment specifically uses a biochemical treatment scheme for wastewater generated in the pretreatment section of a refining and chemical enterprise as an example to comprehensively evaluate three candidate treatment technologies (AO, CASS, and AO-MBR). The AHP-entropy weight method is used for combined weighting, and the TOPSIS method is used for ranking, aiming to verify the feasibility and effectiveness of the screening method of this invention. Based on the actual survey of the current status of water pollution control technology in petrochemical plants, and combined with relevant national standards such as the "Integrated Discharge Standard for Refining and Chemical Wastewater" (GB8978-1996) and the "Emission Standard of Air Pollutants for Refining and Petrochemical Industries" (DB11 447-2015), a comprehensive evaluation system for refining and chemical wastewater treatment technologies is constructed, as shown in Table 1. Table 1. Comprehensive Evaluation Index System for Refining and Chemical Wastewater Treatment Technologies (Evaluation System)

[0029] The categories and meanings of the indicators in the three-level indicator layer in the table are as follows: (1) Effluent COD concentration / removal rate D1: A quantitative indicator, referring to the lowest stable concentration of COD in the effluent or the COD removal efficiency after the implementation of the evaluated technology.

[0030] (2) Effluent ammonia nitrogen concentration / removal rate D2: a quantitative indicator, which refers to the lowest concentration of ammonia nitrogen that can be stably achieved in the effluent after the implementation of the evaluated technology or the ammonia nitrogen removal efficiency.

[0031] (3) Technological advancement D3: Qualitative indicator, which refers to the position of the evaluated technology in terms of its technological level compared with similar technologies at home and abroad (international leader, international runner-up, domestic leader, domestic runner-up, domestic follower). (4) Process energy consumption D4: Qualitative index, referring to the process energy consumption of the technology being evaluated, including pharmaceutical consumption, electricity consumption, etc. (low, relatively low, average, relatively high, high). (5) Technical stability D5: Qualitative indicator, which refers to the ability of the evaluated technology to maintain stable operation under actual water quality and quantity fluctuations (high, relatively high, average, relatively low, low). (6) Investment cost per ton of water (D6): A qualitative indicator, referring to the engineering investment cost during the implementation of the technology being evaluated, including costs for civil engineering, equipment purchase and installation, expressed as investment cost per ton of water (low, relatively low, average, relatively high, high). (7) Operation and maintenance cost per ton of water D7: Qualitative indicator, which refers to the operation and maintenance costs of the technical equipment used to treat wastewater. It mainly includes fuel, power, labor, maintenance, depreciation and other costs, and is expressed as the operation and maintenance cost per ton of water (low, lower, average, higher, high).

[0032] (8) Solid waste generation level D8: Qualitative indicator, which refers to the amount of solid waste such as sludge and slag generated when the technology and equipment are used to treat wastewater (low, lower, average, higher, high).

[0033] (9) Waste gas generation level D9: Qualitative index, which refers to the amount of waste gas generated when the technical equipment is used to treat wastewater (low, lower, average, higher, high).

[0034] (10) Noise impact level D 10 Qualitative indicators refer to the degree of impact (low, relatively low, moderate, relatively high, high) of noise generated by the evaluated technical facility during operation on the surrounding environment. Among these, D1, D2, D3, and D5 are positive indicators, while D4, D6, D7, D8, D9, and D5 are negative indicators. 10 It is a negative indicator; To facilitate the evaluation and value calculation, the qualitative indicators in the above evaluation system can be quantified according to the standards listed in Table 2 below. Table 2. Qualitative Indicator Quantification Conversion Standards

[0035] S2. Obtain dynamic data of each evaluation indicator in the evaluation system corresponding to various refining wastewater treatment technologies, and form a data matrix; Dynamic data for each evaluation indicator in the evaluation system corresponding to various refining wastewater treatment technologies are acquired to form a data matrix; including: Based on monitoring data and a refining wastewater treatment model (the existing ASM2 / ASM2d model), the data of the first quantification parameter is dynamically calculated; then the data of the second quantification parameter is calculated in real time; and the data of the third quantification parameter is acquired in real time. The data of the first quantization parameter, the data of the second quantization parameter, and the data of the third quantization parameter are standardized to obtain dynamic data; Then, a data matrix is ​​constructed using the various refining wastewater treatment technologies as rows and the dynamic data corresponding to each refining wastewater treatment technology as columns.

[0036] ① For quantitative parameters such as pollutant removal capacity, influent and effluent water quality indicators are obtained based on real-time monitoring data from enterprises or by building models using BioWin software; ② For D3 (technological advancement), D5 (technological stability), D4 (process energy consumption), D6 (investment cost per ton of water), D7 (operating cost per ton of water), D8 (solid waste generation level), D9 (waste gas generation level), D... 10 Indicators such as (degree of noise impact) can be quantitatively evaluated using an expert scoring method (1-9 points). S3. Based on the importance of each evaluation indicator in the evaluation system, determine the weight of each evaluation indicator; including: The analytic hierarchy process (AHP) is used to calculate the weights of the evaluation indicators to obtain the subjective weights of each indicator. The comprehensive weight of each evaluation indicator is calculated by weighting the subjective and objective weights.

[0037] The calculation method for the comprehensive weight is shown in the following formula (1): (1) In the formula, For comprehensive weighting, The resolution coefficient; The subjective weights obtained by the analytic hierarchy process (AHP) The objective weights are obtained using the entropy weight method.

[0038] For example, the results of performing S2 and S3 in this embodiment are as follows: The Analytic Hierarchy Process (AHP) was developed by experts or company personnel specializing in the treatment of refining and chemical wastewater. The weights of the evaluation system were determined, resulting in a judgment matrix, weights, and specific results, as shown in Tables 3.1 to 3.8 below. Table 3.1 Calculation results of the criterion layer data matrix

[0039] Table 3.2 Criterion Level Consistency Test

[0040] Table 3.3 Calculation Results of the Data Matrix for Technical B1—Secondary Indicator Layer

[0041] Table 3.4 Technical B1 Consistency Check

[0042] Table 3.5 Calculation Results of the Economic B2—Secondary Indicator Layer Matrix

[0043] Table 3.6 Calculation Results of Environmental B3—Secondary Indicator Layer Data Matrix

[0044] Table 3.7 Environmental B3 Consistency Test

[0045] Table 3.8 Calculation Results of Pollutant Removal Capacity C1—Secondary Index Layer Data Matrix

[0046] Table 3.8 Comprehensive Evaluation Index System for Biological Treatment Technology of Refining and Chemical Wastewater: Overall Weights

[0047] As can be seen from the data in the table above, the weights of each indicator have passed the consistency test.

[0048] As shown in Table 3.8, the comprehensive evaluation system for biological treatment technology of refining and chemical wastewater includes three primary indicators: technology (B1), economy (B2), and environment (B3). The environmental indicator has the highest weight (0.536), followed by the economic indicator (0.295), and the technology indicator has the lowest weight (0.169), indicating that environmental impact is the core element of the evaluation. Among the secondary indicators, the technology layer is mainly influenced by process stability (C4, 0.063) and energy consumption (C3, 0.047); in the economic layer, operation and maintenance costs (C6, 0.218) are significantly higher than investment costs (C5, 0.074), reflecting the greater importance of long-term operational economics; in the environmental layer, noise impact (C9, 0.327) has the highest weight, followed by waste gas (C8, 0.123) and solid waste generation level (C7, 0.075). Overall, the comprehensive evaluation of biological treatment technology for refining and chemical wastewater is primarily driven by environmental friendliness, while also considering economic feasibility and technological reliability.

[0049] In other embodiments, the subjective weights of the evaluation indicators are calculated using the fuzzy hierarchical analysis method to obtain the subjective weights of each indicator; the objective weights of the evaluation indicators are calculated using the fuzzy entropy weight method to obtain the objective weights of each indicator. S4. Based on the data matrix and weights, the TOPSIS method is used to select at least one optimal refining wastewater treatment technology from among multiple refining wastewater treatment technologies.

[0050] The process involves using the TOPSIS method, based on a data matrix and weights, to select the optimal refining wastewater treatment technology from among multiple refining wastewater treatment technologies; including: Each evaluation indicator in the data matrix is ​​assigned a weight to obtain a standardized matrix; The TOPSIS method was used to calculate the fit of multiple refining wastewater treatment technologies in a standardized matrix. The refining wastewater treatment technology with the highest degree of fit was selected as the optimal refining wastewater treatment technology.

[0051] Specifically, it includes (1) to (4): (1) Determine the positive ideal solution and the negative ideal solution. The positive ideal solution consists of the maximum value of each column element in the weighted normalized matrix, and the negative ideal solution consists of the minimum value of each column element; (2) Use Euclidean distance to calculate the distance between the object (refining wastewater treatment technology) and the positive and negative ideal solutions. (2) (3) in, Let be the Euclidean distance from the i-th refining wastewater treatment technology to the positive ideal solution. Let be the Euclidean distance from the i-th refining wastewater treatment technology to the negative ideal solution. Let j be the value of the positive ideal solution at the j-th index. Let the value of the negative ideal solution be the j-th index. The calculation method for the value of the i-th scheme (the i-th refining wastewater treatment technology) on the j-th index follows the conventional calculation method in the existing technology, and will not be elaborated here.

[0052] (3) Calculate the relative proximity using the distance to the negative ideal solution and sort them. The relative proximity is between 0 and 1. The larger the value, the farther away from the negative ideal solution, and the better.

[0053] (4) (4) For different stages of refining wastewater treatment technology, the relative distance Si between each evaluation object and the optimal solution is ranked according to the degree of fit. The higher the degree of fit, the better the refining wastewater treatment technology corresponding to the evaluation object. The highest degree of fit is selected as the optimal refining wastewater treatment technology for different treatment stages.

[0054] After calculating the weights of each indicator layer, in order to better compare the importance of each indicator layer, it is necessary to calculate its global weight. The method is to multiply each indicator layer by the weight of its corresponding superior indicator layer, as shown in the following formula: (5) In equation (5), Let i be the global weight of the i-th refining wastewater treatment technology. The index weights for the i-th refining wastewater treatment technology are: , where represents the weight of the upper-level index corresponding to the i-th refining wastewater treatment technology.

[0055] In summary, based on the actual operational data from the above steps, relevant literature, and standardized data obtained from expert scoring, the global weight of each indicator was calculated using the entropy weight method. The objective weights of each indicator in the biological treatment technology for refining wastewater are as follows: Figure 2 As shown, through the aforementioned steps, the subjective weights of each evaluation indicator were determined using the Analytic Hierarchy Process (AHP) method, and the objective weights were determined using the entropy weight method. The AHP weights reflect experts' empirical judgments on technical, economic, and environmental factors, while the entropy weights reflect the differences in actual evaluation data and objective information. Considering the characteristics of refining wastewater, such as high concentration, high salinity, and complex pollutant types, the selection and evaluation results of its treatment technology largely depend on the applicability of the process, operational stability, and the accumulation of engineering experience. Therefore, relying solely on objective data may not fully reflect the applicability of the technology and the reliability of the engineering. Therefore, this embodiment uses the coefficients of the subjective weights... The weighting is set to 0.6 to emphasize the importance of expert experience and engineering practice; at the same time, an objective weighting of 0.4 is retained to balance the objectivity and scientific nature of the data and achieve an organic unity of subjective and objective factors.

[0056] The comprehensive weights of each evaluation indicator are obtained through calculation, as follows: Figure 3 As shown. This comprehensive weight reflects both expert experience and objective information from the evaluation data, enabling a more comprehensive and reasonable assessment of the merits of technical solutions. Subsequently, based on this comprehensive weight, a TOPSIS comprehensive evaluation and ranking of each candidate technical solution will be conducted. After determining the comprehensive weight of each evaluation indicator, a TOPSIS comprehensive evaluation of the three candidate processing technologies will be further performed. This invention employs the TOPSIS method, constructing ideal and negative ideal solutions, and calculating the relative closeness of each solution to the ideal solution, thereby achieving a comprehensive ranking and optimization of the technical solutions.

[0057] (1) Based on the standardized evaluation matrix and the determined comprehensive weights, a weighted standardized decision matrix is ​​constructed to ensure that each indicator is compared under the same scale. Next, the positive ideal solution (i.e., the set of optimal values ​​among each indicator) and the negative ideal solution (i.e., the set of worst values ​​among each indicator) are determined. Then, the Euclidean distance between each candidate solution and the positive and negative ideal solutions is calculated to measure the overall superiority or inferiority of each solution in each evaluation indicator. (2) Calculate and rank the relative proximity using the distance to the negative ideal solution. The relative proximity is between 0 and 1; a higher value indicates a greater distance from the negative ideal solution, and thus a better result. The TOPSIS comprehensive screening method is used to calculate the proximity values ​​of the three candidate biochemical treatment technologies for refining wastewater. Based on the weighted standardized decision matrix, the distances between each scheme and the positive and negative ideal solutions are obtained, and the corresponding proximity is calculated, such as... Figure 4 As shown.

[0058] The comprehensive evaluation of three candidate refining wastewater treatment technologies shows that the AO-MBR technology has the highest similarity score, indicating that this technology performs best overall across all evaluation indicators. The AO technology is second, while the CASS technology is relatively weaker. Further analysis of the scores for each technology across different evaluation dimensions reveals: ①Technical Dimension: AO-MBR technology has significant advantages in terms of effluent quality compliance rate, pollutant removal efficiency, and process stability. The introduction of its membrane modules effectively improves solid-liquid separation efficiency, resulting in less fluctuation in effluent quality, making it suitable for treating high-concentration, complex-composition refining wastewater. AO technology is at a moderate level in terms of treatment effect and operational stability, while CASS technology is slightly lacking in operational stability and process flexibility.

[0059] ② Economic dimension: AO technology has relatively low investment and operating costs, making it economical; AO-MBR technology has slightly higher investment and operating costs, but it has high processing efficiency and small footprint, giving it a good advantage in terms of total life cycle cost; CASS technology is relatively less economical, with higher operating costs and higher energy consumption.

[0060] ③ Environmental Dimension: AO-MBR technology produces less secondary pollution and sludge, resulting in less impact on the surrounding environment; AO technology performs moderately well in terms of environmental friendliness; CASS technology, due to its high aeration intensity, has higher energy consumption and secondary emissions. In summary, AO-MBR technology demonstrates superior performance in terms of technological advancement, economic applicability, and environmental friendliness. Therefore, it was selected as the optimal technical solution in this case, capable of meeting the engineering requirements for efficient and stable treatment of refining wastewater.

[0061] This invention also provides an evaluation system for the adaptability of refining and chemical wastewater treatment technology based on process coupling indicators, used to implement the above method, including: an evaluation system construction module, a data acquisition module, a weight calculation module, and a screening module; The evaluation system construction module is used to construct an evaluation system for assessing refining wastewater treatment technologies. The evaluation system includes evaluation indicators for technical dimensions, economic dimensions, and environmental dimensions. The evaluation indicators for technical dimensions include at least one dynamic evaluation indicator used to quantitatively characterize the dynamic response characteristics of the physical, chemical, or biological processes within the pollution treatment unit. The data acquisition module is used to acquire dynamic data of each evaluation indicator in the evaluation system corresponding to various refining wastewater treatment technologies, forming a data matrix; The weight calculation module is used to determine the weight of each evaluation indicator based on the importance of each evaluation indicator in the evaluation system. The screening module is used to select at least one optimal refining wastewater treatment technology from a variety of refining wastewater treatment technologies based on the data matrix and weights using the TOPSIS method.

Claims

1. A method for screening refining and chemical wastewater treatment technologies based on process coupling indices, characterized in that, Includes the following steps: An evaluation system is constructed for assessing refining wastewater treatment technologies. The evaluation system includes evaluation indicators for technical dimensions, economic dimensions, and environmental dimensions. The evaluation indicators for technical dimensions include at least one dynamic evaluation indicator for quantitatively characterizing the dynamic response characteristics of physical, chemical, or biological processes within the pollution treatment unit. Dynamic data of each evaluation indicator in the evaluation system corresponding to various refining wastewater treatment technologies are obtained to form a data matrix; Based on the importance of each evaluation indicator in the evaluation system, the weight of each evaluation indicator is determined. Based on the data matrix and weights, the TOPSIS method is used to screen at least one optimal refining wastewater treatment technology from a variety of refining wastewater treatment technologies.

2. The method for screening refining wastewater treatment technologies based on process coupling indicators as described in claim 1, characterized in that, The dynamic evaluation index is one or more of the following: dynamic response time, process stability index, or adaptability coefficient.

3. The method for screening refining wastewater treatment technologies based on process coupling indicators as described in claim 1, characterized in that, The evaluation system for assessing refining wastewater treatment technologies includes: Based on existing monitoring data for the technical dimensions, a first quantitative parameter is determined for the evaluation indicators used to characterize the technical dimensions; the evaluation indicators for the technical dimensions include pollutant removal capacity, process energy consumption, and dynamic response. Based on the cost decomposition method, a second quantitative parameter is determined for the evaluation indicators used to characterize the economic dimension; the evaluation indicators for the economic dimension include investment and operation and maintenance costs. Based on existing environmental and social monitoring data, a third quantitative parameter is determined for the evaluation indicators used to characterize the environmental dimension; the evaluation indicators for the environmental dimension include the level of solid waste generation, the level of exhaust gas generation, and the level of noise generation.

4. The method for screening refining wastewater treatment technologies based on process coupling indicators as described in claim 3, characterized in that, The first quantitative parameter includes pollutant removal efficiency, process energy consumption, and dynamic response time; The second quantitative parameter includes the initial total investment cost, fixed operation and maintenance cost, variable operation and maintenance cost, and operation and maintenance cost sensitivity coefficient; The third quantitative parameter includes solid waste generation rate, exhaust gas emission concentration or exhaust gas emission rate, and noise intensity.

5. The method for screening refining wastewater treatment technologies based on process coupling indicators as described in claim 4, characterized in that, The process of acquiring dynamic data for each evaluation indicator in the evaluation system corresponding to various refining wastewater treatment technologies, forming a data matrix, includes: Based on monitoring data and / or a refining wastewater treatment model, dynamically calculate the data of the first quantitative parameter, calculate the data of the second quantitative parameter in real time, and acquire the data of the third quantitative parameter in real time; The data of the first quantization parameter, the data of the second quantization parameter, and the data of the third quantization parameter are standardized to obtain dynamic data; Then, a data matrix is ​​constructed using the various refining wastewater treatment technologies as rows and the dynamic data corresponding to each refining wastewater treatment technology as columns.

6. The method for screening refining wastewater treatment technologies based on process coupling indicators as described in claim 1, characterized in that, Based on the importance of each evaluation indicator in the aforementioned evaluation system, the weight of each evaluation indicator is determined; including: The analytic hierarchy process (AHP) is used to calculate the weights of the evaluation indicators to obtain the subjective weights of each indicator. The objective weights of the evaluation indicators are calculated using the entropy weight method to obtain the objective weights of each indicator. The comprehensive weight of each evaluation indicator is calculated by weighting the subjective and objective weights.

7. The method for screening refining wastewater treatment technologies based on process coupling indicators as described in claim 6, characterized in that, The calculation method for the comprehensive weight is shown in the following formula (1): （1） In the formula, For comprehensive weighting, The resolution coefficient; The subjective weights obtained by the analytic hierarchy process (AHP) The objective weights are obtained using the entropy weight method.

8. The method for screening refining wastewater treatment technologies based on process coupling indicators as described in claim 6, characterized in that, The process involves using the TOPSIS method, based on a data matrix and weights, to screen for at least one optimal refining wastewater treatment technology from a variety of refining wastewater treatment technologies; including: Each evaluation indicator in the data matrix is ​​assigned a weight to obtain a standardized matrix; The TOPSIS method was used to calculate the fit of multiple refining wastewater treatment technologies in a standardized matrix. The refining wastewater treatment technology with the highest degree of fit was selected as the optimal refining wastewater treatment technology.

9. A technology screening system for refining wastewater treatment based on process coupling indices, used to implement the technology screening method for refining wastewater treatment based on process coupling indices as described in any one of claims 1 to 8, characterized in that, include: The evaluation system includes modules for construction, data acquisition, weight calculation, and screening. The evaluation system construction module is used to construct an evaluation system for assessing refining wastewater treatment technologies. The evaluation system includes evaluation indicators for technical dimensions, economic dimensions, and environmental dimensions. The evaluation indicators for technical dimensions include at least one dynamic evaluation indicator used to quantitatively characterize the dynamic response characteristics of the physical, chemical, or biological processes within the pollution treatment unit. The data acquisition module is used to acquire dynamic data of each evaluation indicator in the evaluation system corresponding to various refining wastewater treatment technologies, forming a data matrix; The weight calculation module is used to determine the weight of each evaluation indicator based on the importance of each evaluation indicator in the evaluation system. The screening module is used to select at least one optimal refining wastewater treatment technology from a variety of refining wastewater treatment technologies based on the data matrix and weights using the TOPSIS method.

Images