Energy recycling combined heating and cooling system

Abstract

The present invention discloses a combined heat and power system for energy recycling, and relates to the technical field of combined heat and power, in order to solve the problems of equipment failure and inaccurate recovery data during renewable energy recovery. The data preprocessing steps of the present invention include data cleaning, processing missing values ​​and deleting duplicate values, which can effectively improve the accuracy and reliability of data, reduce the impact of abnormal values ​​and redundant data on analysis, and data standardization can uniformly process data from different sources and different units to make them comparable, easy to analyze and compare, and by recycling and utilizing waste heat, the demand for new heat sources can be reduced, thereby reducing energy consumption costs. Equipment detection and failure probability assessment of recovery equipment in combined heat and power can improve the operating stability of equipment, ensure energy recovery efficiency, reduce maintenance costs, improve production safety and promote energy recycling.

Description

Technical Field

[0001] The invention relates to the technical field of combined cooling, heating and power generation, and in particular to a combined cooling, heating and power generation system for energy recycling. Background Art

[0002] Combined cooling, heating and power (CHP) is a multi-generation energy system that is based on the concept of cascade utilization of energy and integrates the processes of cooling, heating (heating and hot water) and power generation.

[0003] The Chinese patent with publication number CN209483446U discloses a distributed biomass energy combined heat and power system. It mainly uses a waste heat utilization heating system to fully utilize the excess high-temperature gas generated by the biomass gasification system, save energy, avoid energy waste, and make more full use of energy. At the same time, the distributed biomass energy combined heat and power system has a high energy utilization rate and can achieve energy recycling. It can output electricity, heat and cold at the same time as outputting gas. Although the above patent solves the problem of energy utilization, there are still the following problems in actual operation:

[0004] 1. Failure to further compare the recycled energy data with the preset standard energy data, resulting in reduced complementarity of renewable energy.

[0005] 2. The recycled renewable energy data is not further processed, resulting in reduced accuracy in the subsequent transmission and distribution of the renewable energy data.

[0006] 3. The recycling equipment is not effectively fault-checked, resulting in the recycling equipment being unable to continue recycling after a fault occurs during energy recovery. Summary of the invention

[0007] The purpose of the present invention is to provide a combined heat and power system for energy recycling. The data preprocessing steps include data cleaning, processing missing values ​​and deleting duplicate values, which can effectively improve the accuracy and reliability of data and reduce the impact of abnormal values ​​and redundant data on analysis. Data standardization can unify the data from different sources and different units to make them comparable and easy to analyze and compare. By recycling and utilizing waste heat, the demand for new heat sources can be reduced, thereby reducing energy consumption costs. Equipment detection and failure probability assessment of recovery equipment in the combined heat and power system can improve the operating stability of the equipment, ensure energy recovery efficiency, reduce maintenance costs, improve production safety and promote energy recycling, which can solve the problems in the prior art.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] Energy recycling combined heating and cooling system, including:

[0010] Energy cycle equipment validation unit for:

[0011] Confirm the energy recycling equipment that needs to be recovered in the combined cooling, heating and power generation, and conduct equipment inspection on each energy recycling equipment. After the inspection, each energy recycling equipment will be uniquely coded and numbered;

[0012] Energy cycle data analysis unit for:

[0013] Preprocess the renewable energy data in each uniquely coded energy recycling device, and after the data preprocessing, independently store the renewable energy data to obtain standard renewable energy data;

[0014] Develop a program presentation unit to:

[0015] The standard renewable energy data is formulated in a graphic table, and the graphic table is transmitted to the energy transmission and distribution center. The staff formulates the energy cycle plan according to the preset energy transmission and distribution rules in the energy transmission and distribution center, and presents the formulated energy cycle plan to the display terminal.

[0016] Preferably, the energy cycle equipment confirmation unit includes:

[0017] Recycling equipment confirmation module, used to:

[0018] Recovery equipment in cogeneration includes waste heat boilers of generator sets, absorption chillers, heat exchangers and energy converters;

[0019] Among them, the waste heat boiler of the generator set converts heat energy into steam or hot water; the absorption refrigerator converts heat energy into sublimation heat of the refrigerant; the heat exchanger heats the cold air through the preheater;

[0020] The energy converter converts the energy in the waste heat boiler of the generator set, the absorption chiller and the heat exchanger into heat energy, electrical energy and cold energy respectively.

[0021] Preferably, the energy cycle equipment confirmation unit further includes:

[0022] Recycling equipment detection module, used for:

[0023] Carry out equipment inspection on the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set respectively;

[0024] Acquire the operating data and historical fault data of the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set, wherein the operating data and historical fault data are retrieved from the database;

[0025] The operating data and historical fault data are imported into the fault probability assessment model to conduct fault probability assessment.

[0026] Preferably, the recycling equipment detection module further includes:

[0027] A data extraction module, used to extract historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set;

[0028] A fault assessment parameter acquisition module is used to obtain historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set according to the historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; wherein the historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set are obtained by the following formula:

[0029]

[0030] Where W represents the historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; m represents the number of types of faults corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; p j represents the proportion of the number of failures of the jth type that occur at least twice in a row; n represents the number of historical failures corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; X i represents the operating parameter characterization data corresponding to the i-th failure of the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; i represents the fault type coefficient corresponding to the i-th fault of the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set. When the fault type corresponding to the i-th fault is the same as the fault type corresponding to the i-1-th fault, then λ i =0.1; when the fault type corresponding to the i-th fault is different from the fault type corresponding to the i-1-th fault, then λ i =1.1;

[0031] A comparison module, for comparing the historical fault assessment parameters with preset first assessment thresholds and second assessment thresholds corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set;

[0032] A first fault classification module, configured to determine that the fault level is level one when the historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set are lower than the first assessment thresholds corresponding thereto;

[0033] A second fault classification module is used to determine that the fault level is level 2 when the historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set are not lower than the first assessment threshold corresponding to them, but lower than the second assessment threshold corresponding to them;

[0034] A third fault grading module is used to determine that the fault level is level three when the historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set are not lower than the corresponding second assessment threshold; wherein the higher the fault level, the worse the equipment operation performance;

[0035] The fault data screening module is used to screen the historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set according to the fault level.

[0036] Preferably, the fault data screening module includes:

[0037] An information retrieval module, used to retrieve historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set;

[0038] The first data limit value acquisition module is used to obtain the first data limit value corresponding to the historical fault data using the first historical data model when the fault level corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set is level one; wherein the structure of the first historical data model is as follows:

[0039]

[0040] Among them, X c01 represents the first data limit value obtained by the first historical data model; W 01 represents the first evaluation threshold; k represents the number of groups of two adjacent historical faults with the same cause in the historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; X j represents the difference between the operating parameter characterization data corresponding to two adjacent faults in the jth group; ω represents the preset initial adjustment coefficient, and the value range is 0.04-0.11;

[0041] The second data limit value acquisition module is used to obtain the second data limit value corresponding to the historical fault data using the second historical data model when the fault level corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set is level 2; wherein the structure of the second historical data model is as follows:

[0042]

[0043]

[0044] Among them, X c02 represents the second data limit value obtained by the second historical data model; e represents a constant; ω 01 and ω 02 Respectively represent the first adjustment coefficient and the second adjustment coefficient; W 02 represents the second evaluation threshold;

[0045] The third data limit value acquisition module is used to obtain the third data limit value corresponding to the historical fault data using the third historical data model when the fault level corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set is level three; wherein the structure of the third historical data model is as follows:

[0046]

[0047]

[0048] Among them, X c03 represents the third data limit value obtained by the third historical data model; ω 03 represents the third adjustment factor;

[0049] A screening module, for screening the historical fault data of the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set according to the first data limit, the second data limit or the third data limit, and taking the fault data whose difference of the operating parameter characterization data corresponding to each two adjacent historical faults in the historical fault data is not less than the first data limit, the second data limit or the third data limit as the target historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set;

[0050] The quality assessment module is used to perform quality assessment on the target historical fault data and obtain the historical fault data ultimately used for fault probability assessment according to the quality assessment result.

[0051] Preferably, the quality assessment module includes:

[0052] The difference parameter acquisition module is used to perform fault data difference evaluation on the target historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set, and obtain the difference parameters corresponding to the target historical fault data of the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; wherein the difference parameters are obtained by the following formula:

[0053]

[0054]

[0055] Where C represents the difference parameter corresponding to the target historical fault data of the generator set waste heat boiler, absorption chiller, heat exchanger and energy converter; r represents the number of fault data contained in the target historical fault data; X ti represents the operating parameter characterization data corresponding to the i-th target historical fault data; R represents the difference factor;

[0056] A difference comparison module, used for comparing the difference parameter with a preset difference parameter threshold;

[0057] A quality determination module, configured to determine whether the target historical fault data meets the quality requirements when the difference parameter exceeds a preset difference threshold;

[0058] The fault data secondary screening module is used to determine that the target historical fault data does not meet the quality requirements when the difference parameter does not exceed the preset difference threshold, and delete the fault data closest to the normal operating data in a group of historical data whose fault data difference values ​​between historical fault data with adjacent fault timestamps in the target historical fault data are lower than the data difference threshold, so as to obtain the historical fault data finally used for fault probability assessment.

[0059] Preferably, the recycling equipment detection module is also used for:

[0060] Based on the failure probability assessment results, determine whether the equipment inspection of the generator set's waste heat boiler, absorption chiller, heat exchanger and energy converter meets the normal working standards;

[0061] Among them, when the failure probability assessment result is not within the preset assessment range, the energy recycling equipment corresponding to the failure probability assessment is in an abnormal state, and the energy recovery work cannot continue;

[0062] At the same time, when the equipment inspections of the generator set's waste heat boiler, absorption chiller, heat exchanger and energy converter are all within the qualified range of the fault probability assessment, each device will be assigned a unique coding number.

[0063] Preferably, the energy cycle data analysis unit comprises:

[0064] Recycled energy statistics module for:

[0065] Confirm the heat, electricity and cold energy data converted in the waste heat boiler, absorption chiller and heat exchanger of the generator set according to the capacity converter;

[0066] Preprocess the thermal energy, electrical energy and cold energy data respectively;

[0067] Among them, data preprocessing is to clean the thermal energy, electrical energy and cold energy data respectively. Data cleaning includes removing outliers, processing missing values ​​and deleting duplicate values.

[0068] The cleaned heat energy, electric energy and cold energy data are standardized, and the standardized heat energy, electric energy and cold energy data are marked as target renewable energy data.

[0069] Preferably, the energy cycle data analysis unit further includes:

[0070] Recycled energy storage modules for:

[0071] Uniquely code and label the target renewable energy data and the recycling equipment corresponding to the data;

[0072] Confirm the data capacity of the target renewable energy data corresponding to the recycling equipment respectively;

[0073] Then confirm the remaining capacity of the memory;

[0074] Among them, the number of target renewable energy data is consistent with the number of memories;

[0075] When the target renewable energy data is stored, the storage attribute of each memory is consistent with the recycling device of the target renewable energy data;

[0076] Among them, the storage properties of the memory are electric energy storage, cold energy storage and thermal energy storage; the target renewable energy data includes renewable electric energy data, renewable cold energy data and renewable thermal energy data.

[0077] Preferably, the plan presentation unit comprises:

[0078] Graphics and text table development module, used for:

[0079] Importing the renewable electric energy data, the renewable cooling energy data and the renewable heat energy data stored in the memory into the graphic table template, wherein the graphic table template is retrieved from the database;

[0080] After the import is completed, the tabular data of renewable electric energy data, renewable cooling energy data and renewable thermal energy data are obtained;

[0081] And send the table data to the energy transmission and distribution center.

[0082] Preferably, the plan presentation unit comprises:

[0083] Energy planning module for:

[0084] Confirm the preset energy transmission and distribution rules in the energy transmission and distribution center;

[0085] Confirm the standard energy values ​​of the electric energy demand data, cooling energy demand data and thermal energy demand data in the preset energy transmission and distribution rules respectively;

[0086] Confirm the actual energy values ​​of the table data in the energy transmission and distribution center;

[0087] Among them, the energy values ​​are the values ​​of electrical energy, cold energy and thermal energy;

[0088] Overlap the standard energy value with the actual energy value to compare the curves;

[0089] According to the comparison result, the size of the non-overlapping area when the standard energy value and the actual energy value overlap is confirmed;

[0090] The size of the non-overlapping area is converted into a numerical value, and after the conversion is completed, the numerical value of the non-overlapping area is obtained;

[0091] Finally, the overlapping data of standard energy values ​​and actual energy values ​​as well as the numerical data of non-overlapping areas are used to formulate a standard plan.

[0092] Compared with the prior art, the present invention has the following beneficial effects:

[0093] 1. The combined heat, cooling and power system with energy recycling provided by the present invention can reduce the demand for new heat sources by recycling and utilizing waste heat, thereby reducing energy consumption costs. Equipment detection and failure probability assessment of the recycling equipment in the combined heat, cooling and power system can improve the operating stability of the equipment, ensure energy recovery efficiency, reduce maintenance costs, improve production safety and promote energy recycling.

[0094] 2. The energy recycling combined heat and power system provided by the present invention has a data preprocessing step including data cleaning, processing of missing values ​​and deletion of duplicate values, which can effectively improve the accuracy and reliability of data and reduce the impact of abnormal values ​​and redundant data on analysis. Data standardization can unify the data from different sources and different units to make them comparable and facilitate analysis and comparison.

[0095] 3. The energy recycling combined heat and power system provided by the present invention can clearly see the distribution, trend and comparison of various energy data through tabular data. By sending the tabular data to the energy transmission and distribution center, information sharing can be realized. By comparing the standard energy value with the actual energy value, the difference between the actual situation of energy transmission and distribution and the preset rules can be clearly understood. Through the formulation of standard plans, scientific and accurate energy transmission and distribution data support can be provided to decision makers. BRIEF DESCRIPTION OF THE DRAWINGS

[0096] Figure 1 This is a schematic diagram of the energy recycling module of the present invention;

[0097] Figure 2 It is a schematic diagram of the working process of the energy recycling system of the present invention. DETAILED DESCRIPTION

[0098] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0099] In order to solve the problem that in the prior art, when the recovery equipment in the combined cooling, heating and power generation is used for energy recovery, there is no effective fault detection of the recovery equipment, which leads to the problem that the recovery equipment cannot continue to recover energy after a fault occurs during energy recovery. Figure 1 and Figure 2 , this embodiment provides the following technical solutions:

[0100] Energy recycling combined heating and cooling system, including:

[0101] Energy cycle equipment validation unit for:

[0102] Confirm the energy recycling equipment that needs to be recovered in the combined cooling, heating and power generation, and conduct equipment inspection on each energy recycling equipment. After the inspection, each energy recycling equipment will be uniquely coded and numbered;

[0103] Energy cycle data analysis unit for:

[0104] Preprocess the renewable energy data in each uniquely coded energy recycling device, and after the data preprocessing, independently store the renewable energy data to obtain standard renewable energy data;

[0105] Develop a program presentation unit to:

[0106] The standard renewable energy data is formulated in a graphic table, and the graphic table is transmitted to the energy transmission and distribution center. The staff formulates the energy cycle plan according to the preset energy transmission and distribution rules in the energy transmission and distribution center, and presents the formulated energy cycle plan to the display terminal.

[0107] Specifically, by using the energy cycle equipment confirmation unit to perform equipment inspection and fault probability assessment on equipment such as the generator set's waste heat boiler, absorption chiller, heat exchanger and energy converter, potential faults and problems in the equipment can be discovered in a timely manner. By using the energy cycle data analysis unit to perform unique coding and labeling, the recovery equipment and storage attributes corresponding to each target renewable energy data can be clearly identified, making it convenient for unified data management and query. By comparing the standard energy values ​​with the actual energy values ​​through the program presentation unit, the difference between the actual situation of energy transmission and distribution and the preset rules can be clearly understood.

[0108] Energy cycle equipment confirmation unit, including:

[0109] Recycling equipment confirmation module, used to:

[0110] Recovery equipment in cogeneration includes waste heat boilers of generator sets, absorption chillers, heat exchangers and energy converters;

[0111] Among them, the waste heat boiler of the generator set converts heat energy into steam or hot water; the absorption refrigerator converts heat energy into sublimation heat of the refrigerant; the heat exchanger heats the cold air through the preheater;

[0112] The energy converter converts the energy in the waste heat boiler of the generator set, the absorption chiller and the heat exchanger into heat energy, electrical energy and cold energy respectively.

[0113] Recycling equipment detection module, used for:

[0114] Carry out equipment inspection on the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set respectively;

[0115] Acquire the operating data and historical fault data of the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set, wherein the operating data and historical fault data are retrieved from the database;

[0116] The operating data and historical fault data are imported into the fault probability assessment model to conduct fault probability assessment.

[0117] Based on the failure probability assessment results, determine whether the equipment inspection of the generator set's waste heat boiler, absorption chiller, heat exchanger and energy converter meets the normal working standards;

[0118] Among them, when the failure probability assessment result is not within the preset assessment range, the energy recycling equipment corresponding to the failure probability assessment is in an abnormal state, and the energy recovery work cannot continue;

[0119] At the same time, when the equipment inspections of the generator set's waste heat boiler, absorption chiller, heat exchanger and energy converter are all within the qualified range of the fault probability assessment, each device will be assigned a unique coding number.

[0120] Specifically, through the recovery equipment confirmation module, the recovery equipment in the combined heat and cold power generation is converted and utilized to realize the comprehensive utilization of the waste heat of the generator set, the energy in the absorption refrigerator and the heat exchanger. The energy converter converts different types of energy into more useful forms, improves the efficiency of energy utilization, reduces energy waste, and recycles and utilizes waste heat, reduces the heat discharged to the environment, reduces the negative impact on the environment, and contributes to environmental protection. The recovery and utilization of the waste heat of the generator set, the energy in the absorption refrigerator and the heat exchanger can provide a stable supply of heat, electricity and cold energy, which helps to ensure a stable supply of energy. By recycling and utilizing waste heat, the demand for new heat sources can be reduced, thereby reducing Energy consumption costs have been reduced, and economic benefits have been improved. Through the recovery equipment detection module, the recovery equipment in the combined heat and power generation can be inspected and the failure probability assessment can be carried out to improve the operation stability of the equipment, ensure the energy recovery efficiency, reduce maintenance costs, improve production safety and promote energy recycling. Through equipment detection and failure probability assessment of equipment such as the generator set waste heat boiler, absorption chiller, heat exchanger and energy converter, potential failures and problems of the equipment can be discovered in time, and repairs and maintenance can be carried out, thereby improving the operation stability and reliability of the equipment and reducing the impact of equipment failures on production. Equipment failures in the combined heat and power generation system may lead to a decrease in energy recovery efficiency, or even the inability to recover energy normally. By detecting and evaluating the failure probability of the equipment, equipment problems can be discovered and solved in time to ensure energy recovery efficiency.

[0121] In one embodiment of the present invention, the recycling equipment detection module further includes:

[0122] A data extraction module, used to extract historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set;

[0123] A fault assessment parameter acquisition module is used to obtain historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set according to the historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; wherein the historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set are obtained by the following formula:

[0124]

[0125] Where W represents the historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; m represents the number of types of faults corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; p j represents the proportion of the number of failures of the jth type that occur at least twice in a row; n represents the number of historical failures corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; X i represents the operating parameter characterization data corresponding to the i-th failure of the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; i represents the fault type coefficient corresponding to the i-th fault of the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set. When the fault type corresponding to the i-th fault is the same as the fault type corresponding to the i-1-th fault, then λ i =0.1; when the fault type corresponding to the i-th fault is different from the fault type corresponding to the i-1-th fault, then λ i =1.1;

[0126] A comparison module, for comparing the historical fault assessment parameters with preset first assessment thresholds and second assessment thresholds corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set;

[0127] A first fault classification module, configured to determine that the fault level is level one when the historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set are lower than the first assessment thresholds corresponding thereto;

[0128] A second fault classification module is used to determine that the fault level is level 2 when the historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set are not lower than the first assessment threshold corresponding to them, but lower than the second assessment threshold corresponding to them;

[0129] A third fault grading module is used to determine that the fault level is level three when the historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set are not lower than the corresponding second assessment threshold; wherein the higher the fault level, the worse the equipment operation performance;

[0130] The fault data screening module is used to screen the historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set according to the fault level.

[0131] The technical effect of the above technical solution is: through the data extraction module and the fault assessment parameter acquisition module, the system can extract useful information from the historical fault data and evaluate the failure probability of the equipment based on this information. This helps to more accurately identify and locate the fault of the equipment. Through the comparison module, the first fault grading module, the second fault grading module and the third fault grading module, the system can grade the fault of the equipment according to the historical fault assessment parameters. This hierarchical management helps to understand the operating status of the equipment more clearly and provide guidance for subsequent maintenance and repair work.

[0132] By classifying faults, the system can allocate limited maintenance resources to different equipment more reasonably, and can reflect the differences between fault data according to different fault levels, and then carry out targeted fault data screening strategies and methods. At the same time, by real-time monitoring of equipment operation data, the system can promptly detect potential faults and take appropriate measures to prevent or repair them. This helps reduce unexpected equipment downtime and improve the stability of equipment operation.

[0133] Through accurate fault detection and reasonable resource allocation, the system can reduce unnecessary maintenance work and reduce maintenance costs. At the same time, by continuously monitoring the health of the equipment, it can avoid large-scale repairs or replacement of parts due to ignoring certain potential problems, further saving maintenance costs. By improving the operating stability of the equipment and reducing maintenance costs, the system can provide users with a better service experience. This helps to improve user satisfaction with the equipment and system and enhance user loyalty.

[0134] In summary, the above technical solutions achieve more accurate fault detection, more reasonable resource allocation, higher equipment operation stability, lower maintenance costs and better user satisfaction in terms of performance indicators. These technical effects help improve the overall operation efficiency and reliability of the equipment.

[0135] Specifically, the fault data screening module includes:

[0136] An information retrieval module, used to retrieve historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set;

[0137] The first data limit value acquisition module is used to obtain the first data limit value corresponding to the historical fault data using the first historical data model when the fault level corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set is level one; wherein the structure of the first historical data model is as follows:

[0138]

[0139] Among them, Xc01 represents the first data limit value obtained by the first historical data model; W 01 represents the first evaluation threshold; k represents the number of groups of two adjacent historical faults with the same cause in the historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; X j represents the difference between the operating parameter characterization data corresponding to two adjacent faults in the jth group; ω represents the preset initial adjustment coefficient, and the value range is 0.04-0.11;

[0140] The second data limit value acquisition module is used to obtain the second data limit value corresponding to the historical fault data using the second historical data model when the fault level corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set is level 2; wherein the structure of the second historical data model is as follows:

[0141]

[0142]

[0143] Among them, X c02 represents the second data limit value obtained by the second historical data model; e represents a constant; ω 01 and ω 02 Respectively represent the first adjustment coefficient and the second adjustment coefficient; W 02 represents the second evaluation threshold;

[0144] The third data limit value acquisition module is used to obtain the third data limit value corresponding to the historical fault data using the third historical data model when the fault level corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set is level three; wherein the structure of the third historical data model is as follows:

[0145]

[0146]

[0147] Among them, X c03 represents the third data limit value obtained by the third historical data model; ω 03 represents the third adjustment factor;

[0148] A screening module, for screening the historical fault data of the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set according to the first data limit, the second data limit or the third data limit, and taking the fault data whose difference of the operating parameter characterization data corresponding to each two adjacent historical faults in the historical fault data is not less than the first data limit, the second data limit or the third data limit as the target historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set;

[0149] The quality assessment module is used to perform quality assessment on the target historical fault data and obtain the historical fault data ultimately used for fault probability assessment according to the quality assessment result.

[0150] The technical effect of the above technical solution is: through the information retrieval module, the first data limit acquisition module, the second data limit acquisition module and the third data limit acquisition module, the system can obtain the corresponding data limit according to the fault level of the equipment, and use these limit values ​​to screen the historical fault data. This screening method can more accurately identify the data related to the equipment fault, thereby improving the accuracy of fault data screening. By using the historical data model to obtain the data limit, the system can adaptively adjust the threshold of data screening according to the fault level of the equipment. This method can reduce unnecessary calculations and data processing, thereby improving data processing efficiency. At the same time, through the quality evaluation module, the system can perform quality evaluation on the filtered target historical fault data. This evaluation can further ensure the reliability and accuracy of the selected data, thereby improving the reliability of the fault data quality evaluation. In addition, through the collaborative work of the above modules, the system can obtain historical fault data for fault probability evaluation. These data are strictly screened and quality evaluated, and can more accurately reflect the fault situation of the equipment, thereby promoting the accuracy of fault probability evaluation.

[0151] In addition, by evaluating the quality of the target historical fault data, the system can discover potential failure modes and trends. This helps to more accurately identify the weak links and potential problems of the equipment, and provide more targeted suggestions and guidance for the maintenance and repair of the equipment. By improving the accuracy of fault detection and data screening, the system can reduce unnecessary maintenance work and reduce maintenance costs. At the same time, by continuously monitoring and evaluating the health of the equipment, it can avoid large-scale repairs or replacement of parts due to ignoring certain potential problems, further saving maintenance costs.

[0152] In summary, the above technical solution achieves more accurate fault data screening, more reliable quality assessment, more accurate fault probability assessment, more targeted equipment maintenance, lower maintenance costs and better user satisfaction in terms of performance indicators. These technical effects help improve the overall operating efficiency and reliability of the equipment. At the same time, it can effectively screen out interference data in historical fault data, thereby effectively improving the representation of the screened historical fault data for the equipment's own operating faults.

[0153] Specifically, the quality assessment module includes:

[0154] The difference parameter acquisition module is used to perform fault data difference evaluation on the target historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set, and obtain the difference parameters corresponding to the target historical fault data of the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; wherein the difference parameters are obtained by the following formula:

[0155]

[0156]

[0157] Where C represents the difference parameter corresponding to the target historical fault data of the generator set waste heat boiler, absorption chiller, heat exchanger and energy converter; r represents the number of fault data contained in the target historical fault data; X ti represents the operating parameter characterization data corresponding to the i-th target historical fault data; R represents the difference factor;

[0158] A difference comparison module, used for comparing the difference parameter with a preset difference parameter threshold;

[0159] A quality determination module, configured to determine whether the target historical fault data meets the quality requirements when the difference parameter exceeds a preset difference threshold;

[0160] The fault data secondary screening module is used to determine that the target historical fault data does not meet the quality requirements when the difference parameter does not exceed the preset difference threshold, and delete the fault data closest to the normal operating data in a group of historical data whose fault data difference values ​​between historical fault data with adjacent fault timestamps in the target historical fault data are lower than the data difference threshold, so as to obtain the historical fault data finally used for fault probability assessment.

[0161] The technical effect of the above technical scheme is: since historical fault data often contain two adjacent equipment operation failures caused by the same fault factor not being properly eliminated, the historical fault data generated by the failure of the previous fault problem not being eliminated and resulting in the same problem occurring again within a short period of time cannot fully reflect the occurrence of the equipment's own operation failure because it is not a re-occurrence of the equipment itself after the fault has been eliminated, but a continuation of the original equipment failure caused by improper human operation and maintenance. Therefore, the fault data information corresponding to the secondary fault caused by improper human operation and maintenance is actually interference data for a reasonable fault assessment of the equipment's own fault generation situation. In the traditional fault assessment process, this interference data is often also used for fault probability assessment, resulting in low accuracy of equipment fault assessment and large errors.

[0162] Therefore, the above method can effectively prevent the problem that the same fault will occur again in the future because the fault itself was not properly repaired and the system is still in operation, but the original fault cause is not solved within a certain period of time. By effectively improving the accuracy of screening historical fault data, the accuracy and rationality of equipment failure probability assessment can be effectively improved.

[0163] At the same time, through the difference parameter acquisition module, the system can perform fault data difference evaluation on the target historical fault data and obtain the corresponding difference parameters. This difference evaluation can more accurately reflect the characteristics and changes of the fault data, thereby improving the accuracy of the fault data quality evaluation. Through the difference comparison module and the fault data secondary screening module, the system can screen the target historical fault data according to the preset difference threshold and data difference threshold. This screening method can further optimize the selection of fault data and improve the quality of fault data. In addition, through the quality judgment module, the system can determine whether the target historical fault data meets the quality requirements. Only historical fault data that meets the quality requirements will be used for fault probability evaluation. This quality evaluation can further improve the reliability and accuracy of fault probability evaluation. At the same time, by using difference parameters for screening and quality evaluation, the system can reduce unnecessary calculations and data processing and reduce calculation complexity. This optimization can improve the processing efficiency of the system and reduce resource consumption.

[0164] On the other hand, by conducting quality assessment and screening of target historical fault data, the system can discover potential failure modes and trends. This helps to more accurately identify the weak links and potential problems of the equipment, and provide more targeted suggestions and guidance for the maintenance and repair of the equipment. By improving the accuracy of fault detection, data screening, and quality assessment, the system can reduce unnecessary maintenance work and reduce maintenance costs. At the same time, by continuously monitoring and evaluating the health status of the equipment, large-scale repairs or replacement of parts caused by ignoring certain potential problems can be avoided, further saving maintenance costs. By improving the operating stability of the equipment and reducing maintenance costs, the system can provide users with a better service experience. This helps to improve user satisfaction with the equipment and system and enhance user loyalty.

[0165] In summary, the above technical solutions have achieved more accurate fault data quality assessment, more optimized fault data screening process, more reliable fault probability assessment, lower calculation complexity, more targeted equipment maintenance, lower maintenance costs and better user satisfaction in terms of technical effects. These technical effects help improve the overall operating efficiency and reliability of the equipment.

[0166] In order to solve the problem in the prior art that the recycled renewable energy data is not further processed, which leads to the reduction of the accuracy of the renewable energy data in the later transmission and distribution, please refer to Figure 1 and Figure 2 , this embodiment provides the following technical solutions:

[0167] Energy cycle data analysis unit, including:

[0168] Recycled energy statistics module for:

[0169] Confirm the heat, electricity and cold energy data converted in the waste heat boiler, absorption chiller and heat exchanger of the generator set according to the capacity converter;

[0170] Preprocess the thermal energy, electrical energy and cold energy data respectively;

[0171] Among them, data preprocessing is to clean the thermal energy, electrical energy and cold energy data respectively. Data cleaning includes removing outliers, processing missing values ​​and deleting duplicate values.

[0172] The cleaned heat energy, electric energy and cold energy data are standardized, and the standardized heat energy, electric energy and cold energy data are marked as target renewable energy data.

[0173] Recycled energy storage modules for:

[0174] Uniquely code and label the target renewable energy data and the recycling equipment corresponding to the data;

[0175] Confirm the data capacity of the target renewable energy data corresponding to the recycling equipment respectively;

[0176] Then confirm the remaining capacity of the memory;

[0177] Among them, the number of target renewable energy data is consistent with the number of memories;

[0178] When the target renewable energy data is stored, the storage attribute of each memory is consistent with the recycling device of the target renewable energy data;

[0179] Among them, the storage properties of the memory are electric energy storage, cold energy storage and thermal energy storage; the target renewable energy data includes renewable electric energy data, renewable cold energy data and renewable thermal energy data.

[0180] Specifically, by processing and standardizing the thermal energy, electrical energy and cold energy data through the energy recovery statistics module, the capacity converter can improve data quality, enhance data comparability, provide decision support, optimize energy management and promote energy recycling. The data preprocessing steps include data cleaning, processing missing values ​​and deleting duplicate values, which can effectively improve the accuracy and reliability of data and reduce the impact of abnormal values ​​and redundant data on analysis. Data standardization can unify the data from different sources and units to make them comparable and easy to analyze and compare. Standardized data is easier to analyze and visualize, and can more intuitively reflect the distribution and trend of thermal energy, electrical energy and cold energy data. Through the unique coding and labeling of the energy recovery storage module, the recycling equipment and storage attributes corresponding to each target renewable energy data can be clearly identified, which is convenient for unified management and query of data. At the same time, data capacity confirmation and memory remaining capacity confirmation can ensure that there is sufficient storage space for data and avoid data overflow and loss. By real-time monitoring and recording of target renewable energy data, it is possible to timely understand energy recovery, storage and use, and improve the level of intelligent energy management. Through unique coding numbers and data management optimization, the security of target renewable energy data can be enhanced, avoiding illegal acquisition and use of data, and ensuring the security and stability of the energy system.

[0181] In order to solve the problem in the prior art that after the energy recovery scheme in the combined cooling, heating and power generation is completed, the recovered energy data is not further compared with the preset standard energy data, which leads to the reduction of the complementarity of renewable energy, please refer to Figure 1 and Figure 2 , this embodiment provides the following technical solutions:

[0182] Develop a program presentation unit, including:

[0183] Graphics and text table development module, used for:

[0184] Importing the renewable electric energy data, the renewable cooling energy data and the renewable heat energy data stored in the memory into the graphic table template, wherein the graphic table template is retrieved from the database;

[0185] After the import is completed, the tabular data of renewable electric energy data, renewable cooling energy data and renewable thermal energy data are obtained;

[0186] And send the table data to the energy transmission and distribution center.

[0187] Energy planning module for:

[0188] Confirm the preset energy transmission and distribution rules in the energy transmission and distribution center;

[0189] Confirm the standard energy values ​​of the electric energy demand data, cooling energy demand data and thermal energy demand data in the preset energy transmission and distribution rules respectively;

[0190] Confirm the actual energy values ​​of the table data in the energy transmission and distribution center;

[0191] Among them, the energy values ​​are the values ​​of electrical energy, cold energy and thermal energy;

[0192] Overlap the standard energy value with the actual energy value to compare the curves;

[0193] According to the comparison result, the size of the non-overlapping area when the standard energy value and the actual energy value overlap is confirmed;

[0194] The size of the non-overlapping area is converted into a numerical value, and after the conversion is completed, the numerical value of the non-overlapping area is obtained;

[0195] Finally, the overlapping data of standard energy values ​​and actual energy values ​​as well as the numerical data of non-overlapping areas are used to formulate a standard plan.

[0196] Specifically, the data is displayed in an intuitive way through the graphic table formulation module, which is convenient for decision makers to quickly understand the recovery, storage and use of energy. Through the tabular data, the distribution, trend and comparison of various energy data can be clearly seen. Sending the tabular data to the energy transmission and distribution center can realize information sharing, so that relevant departments and personnel can understand the energy data in a timely manner and work together. This helps to improve work efficiency and strengthen communication and collaboration between departments. By comparing the standard energy values ​​with the actual energy values ​​through the energy plan formulation module, the difference between the actual situation of energy transmission and distribution and the preset rules can be clearly understood. This helps to discover bottlenecks and problems in the energy transmission and distribution process, optimize the configuration and use of energy, and improve the efficiency and stability of energy transmission and distribution. Through the formulation of standard solutions, scientific and accurate energy transmission and distribution data support can be provided to decision makers. This helps to make more reasonable and scientific energy management decisions and promote the sustainable development of the energy industry.

[0197] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0198] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A combined cooling, heating and power system for energy recycling, characterized in that: include: Energy cycle equipment validation unit for: Confirm the energy recycling equipment that needs to be recovered in the combined cooling, heating and power generation, and conduct equipment inspection on each energy recycling equipment. After the inspection, each energy recycling equipment will be uniquely coded and numbered; Energy cycle data analysis unit for: Preprocess the renewable energy data in each uniquely coded energy recycling device, and after the data preprocessing, independently store the renewable energy data to obtain standard renewable energy data; Develop a program presentation unit to: The standard renewable energy data is formulated in a graphic form, and the standard renewable energy data formulated in the graphic form is transmitted to the energy transmission and distribution center. The staff formulates an energy cycle plan according to the preset energy transmission and distribution rules in the energy transmission and distribution center, and presents the formulated energy cycle plan to the display terminal; The energy cycle equipment confirmation unit comprises: Recycling equipment confirmation module, used to: Recovery equipment in cogeneration includes waste heat boilers of generator sets, absorption chillers, heat exchangers and energy converters; Among them, the waste heat boiler of the generator set converts heat energy into steam or hot water; the absorption refrigerator converts heat energy into sublimation heat of the refrigerant; the heat exchanger heats the cold air through the preheater; The energy converter converts the energy in the waste heat boiler of the generator set, the absorption chiller and the heat exchanger into heat energy, electrical energy and cold energy respectively; Recycling equipment detection module, used for: Carry out equipment inspection on the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set respectively; Acquire the operating data and historical fault data of the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set, wherein the operating data and historical fault data are retrieved from the database; Importing operation data and historical fault data into the fault probability assessment model to conduct fault probability assessment; The recycling equipment detection module also includes: A data extraction module, used to extract historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; A fault assessment parameter acquisition module is used to obtain historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set according to the historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; wherein the historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set are obtained by the following formula: ； Wherein, W represents the historical fault assessment parameter corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; m represents the number of types of faults corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; pj represents the proportion of the number of faults of the jth type that occur at least twice in a row; n represents the number of historical faults corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; Xi represents the operating parameter characterization data corresponding to the i-th fault of the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; λi represents the fault type coefficient corresponding to the i-th fault of the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set. When the fault type corresponding to the i-th fault is the same as the fault type corresponding to the i-1-th fault, λi=0.1; when the fault type corresponding to the i-th fault is different from the fault type corresponding to the i-1-th fault, λi=1.1; A comparison module, for comparing the historical fault assessment parameters with preset first assessment thresholds and second assessment thresholds corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; A first fault classification module, configured to determine that the fault level is level one when the historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set are lower than the first assessment thresholds corresponding thereto; A second fault classification module is used to determine that the fault level is level 2 when the historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set are not lower than the first assessment threshold corresponding to them, but lower than the second assessment threshold corresponding to them; A third fault grading module is used to determine that the fault level is level three when the historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set are not lower than the corresponding second assessment threshold; wherein the higher the fault level, the worse the equipment operation performance; A fault data screening module is used to screen the historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set according to the fault level; The fault data screening module includes: An information retrieval module, used to retrieve historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; The first data limit value acquisition module is used to obtain the first data limit value corresponding to the historical fault data using the first historical data model when the fault level corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set is level one; wherein the structure of the first historical data model is as follows: ； Among them, X c01 represents the first data limit value obtained by the first historical data model; W 01 represents the first evaluation threshold; k represents the number of groups of two adjacent historical faults with the same cause in the historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; X j represents the difference between the operating parameter characterization data corresponding to two adjacent faults in the jth group; ω represents the preset initial adjustment coefficient, which ranges from 0.04 to 0.11; W represents the historical fault assessment parameters corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; The second data limit value acquisition module is used to obtain the second data limit value corresponding to the historical fault data using the second historical data model when the fault level corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set is level 2; wherein the structure of the second historical data model is as follows: ； Among them, X c02 represents the second data limit value obtained by the second historical data model; e represents a constant; ω 01 and ω 02 Respectively represent the first adjustment coefficient and the second adjustment coefficient; W 02 represents the second evaluation threshold; The third data limit value acquisition module is used to obtain the third data limit value corresponding to the historical fault data using the third historical data model when the fault level corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set is level three; wherein the structure of the third historical data model is as follows: ； Among them, X c03 represents the third data limit value obtained by the third historical data model; ω 03 represents the third adjustment factor; A screening module, for screening the historical fault data of the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set according to the first data limit, the second data limit or the third data limit, and taking the fault data whose difference of the operating parameter characterization data corresponding to each two adjacent historical faults in the historical fault data is not less than the first data limit, the second data limit or the third data limit as the target historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; A quality assessment module, used to perform quality assessment on the target historical fault data, and obtain the historical fault data ultimately used for fault probability assessment according to the quality assessment result; Quality assessment modules, including: The difference parameter acquisition module is used to perform fault data difference evaluation on the target historical fault data corresponding to the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set, and obtain the difference parameters corresponding to the target historical fault data of the waste heat boiler, absorption chiller, heat exchanger and energy converter of the generator set; wherein the difference parameters are obtained by the following formula: ； Wherein, C represents the difference parameter corresponding to the target historical fault data of the generator set waste heat boiler, absorption chiller, heat exchanger and energy converter; r represents the number of fault data contained in the target historical fault data; Xti represents the operating parameter characterization data corresponding to the i-th target historical fault data; R represents the difference factor; A difference comparison module, used for comparing the difference parameter with a preset difference parameter threshold; A quality determination module, configured to determine whether the target historical fault data meets the quality requirements when the difference parameter exceeds a preset difference threshold; The fault data secondary screening module is used to determine that the target historical fault data does not meet the quality requirements when the difference parameter does not exceed the preset difference threshold, and delete the fault data closest to the normal operating data in a group of historical data whose fault data difference values ​​between historical fault data with adjacent fault timestamps in the target historical fault data are lower than the data difference threshold, so as to obtain the historical fault data finally used for fault probability assessment.

2. The combined cooling, heating and power system for energy recycling according to claim 1 is characterized by: The recycling equipment detection module is also used for: Based on the failure probability assessment results, determine whether the equipment inspection of the generator set's waste heat boiler, absorption chiller, heat exchanger and energy converter meets the normal working standards; Among them, when the failure probability assessment result is not within the preset assessment range, the energy recycling equipment corresponding to the failure probability assessment is in an abnormal state, and the energy recovery work cannot continue; At the same time, when the equipment inspections of the generator set's waste heat boiler, absorption chiller, heat exchanger and energy converter are all within the qualified range of the fault probability assessment, each device will be assigned a unique coding number.

3. The combined cooling, heating and power system for energy recycling according to claim 2 is characterized by: The energy cycle data analysis unit comprises: Recycled energy statistics module for: Confirm the heat, electricity and cold energy data converted in the waste heat boiler, absorption chiller and heat exchanger of the generator set according to the capacity converter; Preprocess the thermal energy, electrical energy and cold energy data respectively; Among them, data preprocessing is to clean the thermal energy, electrical energy and cold energy data respectively. Data cleaning includes removing outliers, processing missing values ​​and deleting duplicate values. The cleaned heat energy, electric energy and cold energy data are standardized, and the standardized heat energy, electric energy and cold energy data are marked as target renewable energy data.

4. The combined cooling, heating and power system for energy recycling according to claim 3 is characterized by: The energy cycle data analysis unit further includes: Recycled energy storage modules for: Uniquely code and label the target renewable energy data and the recycling equipment corresponding to the data; Confirm the data capacity of the target renewable energy data corresponding to the recycling equipment respectively; Then confirm the remaining capacity of the memory; Among them, the number of target renewable energy data is consistent with the number of memories; When the target renewable energy data is stored, the storage attribute of each memory is consistent with the recycling device of the target renewable energy data; Among them, the storage properties of the memory are electric energy storage, cold energy storage and thermal energy storage; the target renewable energy data includes renewable electric energy data, renewable cold energy data and renewable thermal energy data.

5. The combined cooling, heating and power system for energy recycling according to claim 4 is characterized by: The formulation scheme presentation unit comprises: Graphics and text table development module, used for: Importing the renewable electric energy data, the renewable cooling energy data and the renewable heat energy data stored in the memory into the graphic table template, wherein the graphic table template is retrieved from the database; After the import is completed, the tabular data of renewable electric energy data, renewable cooling energy data and renewable thermal energy data are obtained; And send the table data to the energy transmission and distribution center.

6. The combined cooling, heating and power system for energy recycling according to claim 5 is characterized by: The formulation scheme presentation unit comprises: Energy planning module for: Confirm the preset energy transmission and distribution rules in the energy transmission and distribution center; Confirm the standard energy values ​​of the electric energy demand data, cooling energy demand data and thermal energy demand data in the preset energy transmission and distribution rules respectively; Confirm the actual energy values ​​of the table data in the energy transmission and distribution center; Among them, the energy values ​​are the values ​​of electrical energy, cold energy and thermal energy; Overlap the standard energy value with the actual energy value to compare the curves; According to the comparison result, the size of the non-overlapping area when the standard energy value and the actual energy value overlap is confirmed; The size of the non-overlapping area is converted into a numerical value, and after the conversion is completed, the numerical value of the non-overlapping area is obtained; Finally, the overlapping data of standard energy values ​​and actual energy values ​​as well as the numerical data of non-overlapping areas are used to formulate a standard plan.

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