An evaluation method, system, device and medium of a cold-heat dual storage system architecture

Abstract

The present application relates to the technical field of energy storage system selection, and discloses a cold-heat dual energy storage system architecture evaluation method, system, device and medium, comprising: determining a plurality of evaluation index factors including space demand, economy, energy efficiency and environmental performance; determining the selection of each unit of a plurality of architecture types and calculating the energy consumption of each unit selection; calculating the evaluation index values of each evaluation index factor based on the energy consumption; constructing a hierarchical structure model; determining the combined weights of all evaluation index factors based on the hierarchical structure model through the analytic hierarchy process and the entropy method, and dynamically optimizing the combined weights to obtain the maximum weight of each evaluation index factor; determining the relative closeness of each architecture type based on the maximum weight of each evaluation index factor and the TOPSIS comprehensive evaluation method, and taking the architecture type corresponding to the highest relative closeness as the optimal architecture type. The present application provides a strong basis for project investment decision-making.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy storage system selection, and particularly relates to an evaluation method, system, device and medium for a cold-heat dual storage system architecture. BACKGROUND

[0002] With a substantial increase in the proportion of renewable energy such as wind and light with power fluctuation, higher requirements are put forward for the flexibility of buildings, and the setting of energy storage systems becomes particularly important.

[0003] Traditional cold and heat source architectures mostly adopt a combination of water chillers and boilers, and only the cold source uses electricity, which is affected by the peak-valley electricity price difference. The heat source uses gas as energy, and the gas price is constant throughout the day without peak-valley price, so the cold storage device is usually only set. However, the trend of full electrification is increasingly obvious, and boilers are gradually being replaced by heat pumps. Heat pumps use electricity as energy, like water chillers, which provides new potential for taking advantage of the peak-valley electricity price difference and peak load shifting.

[0004] In the past, when comparing different energy storage schemes, the economic efficiency of single storage architectures is mostly compared, and only the operation cost of the energy storage system for cold storage in the cooling season or heat storage in the heating season is concerned. The compared schemes and dimensions are relatively single. In the context of fine design, the selection of cold-heat dual storage architecture is particularly critical. How to comprehensively evaluate different cold-heat dual storage architectures from the aspects of space demand, economy, energy efficiency, and environmental performance while taking into account the needs of the owners and technical and economic efficiency, and obtain the best architecture in different application scenarios is a problem that needs to be solved in the HVAC industry. SUMMARY

[0005] In view of the deficiencies and shortcomings of the prior art, the present application provides an evaluation method, system, device and medium for a cold-heat dual storage system architecture, which provides designers with the best cold-heat dual storage architecture scheme that takes into account the needs of the owners and technical and economic efficiency.

[0006] The present application is realized by the following technical solutions:

[0007] An evaluation method for a cold-heat dual storage system architecture, the evaluation method comprising:

[0008] determining a plurality of evaluation index factors based on space demand, economy, energy efficiency, and environmental performance;

[0009] determining the selection of each unit of a plurality of architecture types included in the cold-heat dual storage system, and calculating the energy consumption and initial investment of each unit selection;

[0010] calculating the evaluation index values of each evaluation index factor based on the energy consumption and initial investment of the unit selection corresponding to each architecture type;

[0011] construct a hierarchical model based on the evaluation index factors, the several architecture types and the optimal architecture type;

[0012] determine the combined weight of each evaluation index factor based on the hierarchical model by analytic hierarchy process and entropy method respectively, and dynamically optimize the combined weight to obtain the optimal weight of each evaluation index factor;

[0013] determine the relative closeness of each architecture type based on the optimal weight of each evaluation index factor and the TOPSIS comprehensive evaluation method, and take the architecture type corresponding to the highest relative closeness as the optimal architecture type.

[0014] As an optimization, based on the hierarchical model, the specific process of determining the combined weight of each evaluation index factor in each architecture type by analytic hierarchy process and entropy method respectively is as follows:

[0015] calculate the weight of each evaluation index factor based on the hierarchical model by analytic hierarchy process, and take the weight passed the consistency test as the first weight of the evaluation index factor;

[0016] calculate the weight of each evaluation index factor of each architecture type based on the hierarchical model by entropy method, and obtain the second weight of the evaluation index factor of each architecture type;

[0017] assign the first weight and the second weight of each evaluation index factor to the corresponding linear weighting coefficient, thereby obtaining the combined weight of each evaluation index factor of each architecture type.

[0018] As an optimization, the specific process of calculating the weight of each evaluation index factor based on the hierarchical model by analytic hierarchy process, and taking the weight passed the consistency test as the first weight of the evaluation index factor is as follows:

[0019] value the importance of each evaluation index factor by using "1-9 scale method", and construct index judgment matrix:

[0020] calculate the geometric mean of each column of the index judgment matrix, and normalize the geometric mean to obtain the initial weight of each evaluation index factor;

[0021] calculate the maximum eigenvalue of the index judgment matrix based on the initial weight of each evaluation index factor;

[0022] calculate the actual consistency index based on the maximum eigenvalue CI , and calculate the random consistency index RI based on the maximum eigenvalue CR , ;

[0023] Determine whether the consistency ratio is less than 0.1. If so, it is considered that the indicator judgment matrix passes the consistency test. The initial weight corresponding to the indicator judgment matrix is ​​the first weight, wherein the first j The first weight of the evaluation index factor is expressed as ; Otherwise, return to the first step and readjust the indicator judgment matrix.

[0024] As an optimization, the weight of each evaluation index factor of each architecture type is calculated by the entropy method based on the hierarchical structure model. The specific process of obtaining the second weight of the evaluation index factor of each architecture type is as follows:

[0025] Collect the values ​​of each evaluation indicator for each architecture type to construct the original data matrix X， ,in, For the i The first j The evaluation index value, m is the number of architecture types, n is the number of evaluation index factors;

[0026] The original data matrix is ​​standardized to obtain a standardized index data matrix Y , ,in, For the i The first j The standardized value of the evaluation index factor;

[0027] The second weight of each evaluation index factor is determined by entropy method based on the standardized index data matrix, wherein the j The second weight of the evaluation index factor The calculation formula is:

[0028] ;

[0029] ;

[0030] ;

[0031] ;

[0032] in, For the j Under the evaluation index factor i The proportion of the standard value of each architecture type in the evaluation index factor; For the j The entropy value of the evaluation index factor; the first evaluation index factor j information redundancy of the first evaluation index factor; the first evaluation index factor j entropy value method weight of the first evaluation index factor, i.e., the second weight of the first evaluation index factor. j the first evaluation index factor

[0033] As optimization, the combined weight is represented as W , , , the combined weight of the first evaluation index factor; j linear weighting coefficient, , , the first weight of the first evaluation index factor, j the second weight of the first evaluation index factor, the first evaluation index factor j the second evaluation index factor, n the number of evaluation index factors.

[0034] As optimization, the dynamic optimization of the combined weight obtains the specific process of the maximum weight of each evaluation index factor in each architecture type as follows:

[0035] Based on the peak-valley electricity price ratio, a peak-valley electricity price ratio correction factor is calculated , and based on the energy storage amount of the energy storage device and the cumulative total load of the design day, an energy storage rate correction factor is calculated ;

[0036] Based on the peak-valley electricity price ratio correction factor , the combined weight of the evaluation index factor for operating cost is adjusted, and based on the energy storage rate correction factor , the combined weight of the evaluation index factor for initial investment is adjusted;

[0037] Based on the adjusted weights of initial investment and operating cost, the weights of all evaluation index factors other than initial investment and operating cost are calculated to obtain the maximum weight, and the calculation formula of the maximum weight is as follows:

[0038] ;

[0039] ;

[0040] ;

[0041] ;

[0042] ;

[0043] wherein, Represents the final weight of the i-th evaluation index factor; 、 are the weights of the adjusted initial investment and operating expenses respectively; 、 are the combined weights of initial investment and operating expenses before adjustment; is the peak-valley electricity price ratio correction factor adjustment coefficient; is the peak electricity price, in yuan / kWh; The off-peak electricity price is in yuan / kWh; is the adjustment coefficient of the energy storage rate correction factor; The energy stored in the energy storage device is in kWh; It is the total cumulative load of the design day, in kWh.

[0044] As an optimization, the specific process of determining the relative closeness of each architecture type based on the final weight of each evaluation index factor and the TOPSIS comprehensive evaluation method is as follows:

[0045] Calculate the indicator weighting matrix based on the final weights Z , Z The calculation formula is:

[0046] ;

[0047] in, is the standardized indicator data matrix; For the j The final weight of the evaluation index factor; m is the number of architecture types; n is the number of evaluation index factors;

[0048] Based on the indicator weighting matrix Z Calculate the positive and negative ideal distances for each of the architecture types using the following formula:

[0049] ;

[0050] ;

[0051] ;

[0052] ;

[0053] in, For the j The evaluation index factor is a positive ideal solution; is a negative ideal solution; Indicates the i The positive ideal distance for each architecture type, represents a negative ideal distance of an i th architecture type, i represents a weight of an i th evaluation index factor in an index weight matrix, i represents a weight of an i th evaluation index factor in an index weight matrix, j represents a product of an evaluation index value of an i th evaluation index factor and a maximum weight;

[0054] The relative closeness of each architecture type is calculated based on the positive and negative ideal distances of each architecture type, and the calculation formula of the relative closeness of an i th architecture type is as follows:

[0055] .

[0056] The application further discloses an evaluation system of a cold-heat dual storage system architecture, which is used for executing the evaluation method of the cold-heat dual storage system architecture, and comprises:

[0057] An evaluation index factor determination module is configured to determine a plurality of evaluation index factors including space demand, economy, energy efficiency and environmental performance;

[0058] A selection module is configured to determine a plurality of architecture types of the cold-heat dual storage system.

[0059] A calculation module is configured to calculate energy consumption and initial investment of each architecture type.

[0060] An evaluation index value calculation module is configured to calculate evaluation index values of the evaluation index factors based on the energy consumption and the initial investment of the corresponding architecture types.

[0061] A hierarchical structure model construction module is configured to construct a hierarchical structure model based on the evaluation index factors, the plurality of architecture types and an optimal architecture type.

[0062] A maximum weight calculation module is configured to determine combined weights of all the evaluation index factors by using the analytic hierarchy process and the entropy method based on the hierarchical structure model, and to obtain the maximum weight of each evaluation index factor by dynamically optimizing the combined weights.

[0063] An evaluation module is configured to determine the relative closeness of each architecture type based on the maximum weight of each evaluation index factor and the TOPSIS comprehensive evaluation method, and to determine the architecture type corresponding to the highest relative closeness as the optimal architecture type.

[0064] ​The application further discloses an electronic device, comprising at least one processor and a memory connected with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the evaluation method of the cold-heat dual-storage system architecture.

[0065] The application further discloses a storage medium storing a computer program, and the computer program is executed by a processor to implement the evaluation method of the cold-heat dual-storage system architecture.

[0066] Compared with the prior art, the application has the following advantages and beneficial effects:

[0067] 1. According to the peak-valley electricity price policy of the project location, the building load characteristics and other conditions, appropriate evaluation indexes are selected from multiple dimensions of spatial demand, economy, energy efficiency and environmental performance, the combination weighting method of the analytic hierarchy process and the entropy method is used to determine the basic weights of different indexes, the combination weights are dynamically optimized by introducing the peak-valley electricity price ratio correction factor and the storage rate correction factor, and finally the comprehensive benefits of each architecture are evaluated by using the TOPSIS multi-attribute comprehensive evaluation method, so that the comprehensive scores of the cold-heat dual-storage air conditioning system architectures in different application scenarios are obtained.

[0068] 2. Based on the evaluation indexes of the multiple dual-storage air conditioning architectures, the key calculation results of the spatial demand, economy, energy efficiency and environmental performance indexes are given, the comprehensive scores of the architectures are given, and the highest ranking is the most suitable cold-heat dual-storage air conditioning system architecture in the application scenario, which provides a strong basis for project investment decision-making and helps decision-makers to comprehensively grasp the economic characteristics of the project and make scientific and reasonable investment choices. BRIEF DESCRIPTION OF DRAWINGS

[0069] The accompanying drawings, which are included to provide a further understanding of the embodiments of the application and constitute a part of this application, illustrate embodiments of the application and are used to explain the principle of the application. In the drawings:

[0070] Figure 1 A flowchart of the evaluation method of the cold-heat dual-storage system architecture according to the application is shown in the drawings;

[0071] Figure 2 A structure diagram of the hierarchical structure model in the application is shown in the drawings;

[0072] Figure 3 A flowchart of the first weight of each evaluation index factor calculated by using the analytic hierarchy process in the application is shown in the drawings;

[0073] Figure 4 A flowchart of the second weight of each evaluation index factor calculated by using the entropy method in the application is shown in the drawings;

[0074] Figure 5 Flow chart for dynamic optimization of combination weight;

[0075] Figure 6 Flow chart for obtaining optimal architecture type by using TOPSIS comprehensive evaluation method in the application. DETAILED DESCRIPTION

[0076] In order to make the objects, technical solutions and advantages of the present application clearer, further detailed description will be given to the present application in combination with embodiments and drawings, the illustrative embodiments of the present application and the description thereof are only used to explain the present application, and do not limit the present application.

[0077] The present application combines the analytic hierarchy process and the entropy method to solve the combination weight, and further integrates with the TOPSIS method, and is applied to the suitability analysis of the cold-heat dual storage air conditioning system architecture. On the one hand, by means of the analytic hierarchy process, subjective importance scoring can be performed according to different project emphases, and subjective judgment targeted to different projects is realized; on the other hand, by means of the entropy method, each evaluation index is standardized, and objective judgment is achieved, finally, the TOPSIS method uses the dynamically optimized weight obtained by combining subjective and objective to perform comprehensive evaluation, so that the optimal architecture screened has higher accuracy.

[0078] Next, the process of the present application will be specifically introduced.

[0079] This embodiment 1 provides an evaluation method for a cold-heat dual storage system architecture, as shown in the following formula (I), the evaluation method comprises the following steps: Figure 1

[0080] S1, determining a plurality of evaluation index factors including space demand, economy, energy efficiency and environmental performance.

[0081] There are many evaluation index factors based on space demand, economy, energy efficiency and environmental performance, for example, initial investment and operating cost based on economy, operating energy efficiency ratio based on energy efficiency, carbon emission based on environment, and land area based on space demand, of course, other evaluation index factors can also be designed, which will not be described here.

[0082] S2, determining the unit selection of a plurality of architecture types included in the cold-heat dual storage system, and calculating the energy consumption and initial investment of each unit selection.

[0083] 1, determining the architecture type and the cold-heat source form:

[0084] ​According to literature research, manufacturer research and engineering case analysis, the characteristics of projects with cold and hot dual storage needs are analyzed, and four kinds of conventional typical cold and heat storage system architectures suitable for civil building use needs are proposed. The four architectures are composed of different energy storage devices. In order to ensure efficient use of energy, stable operation of the system and meet the cold and heat needs in different working conditions, it is necessary to make adaptive adjustments to the cold and heat source form according to the characteristics of the energy storage devices equipped in each architecture. The cold and heat source forms corresponding to the four architectures are shown in Table 1:

[0085] Table 1 Typical cold and heat storage system architecture types and cold and heat source forms

[0086]

[0087] Because the energy efficiency of the chiller in summer is much higher than that of the air source heat pump, the chiller is used for cold storage in summer, and the chiller direct supply cold source scheme is adopted. The air source heat pump has low environmental requirements and flexible installation, and is widely used in residential, commercial, school and other places, and is easy to select, so the air source heat pump is used for low temperature heat storage in winter, and the air source heat pump direct supply heat source scheme (air source heat pump only for heating, not for cooling). Architecture 2 needs high temperature heat storage, so an electric boiler is used for heat storage, and the air source heat pump is only turned on for direct supply during the daytime heating period, and is not used for heat storage during the night low valley period. The electric boiler is only used for heat storage during the night low valley period, and is turned off during the daytime heating period.

[0088] 2. Determine the unit selection:

[0089] a) Water storage main machine model:

[0090] The water storage main machine is a conventional chiller. The actual capacity of the chiller needs to meet the following two conditions: ① fill the water storage pool during the energy storage period; ② the capacity of the water storage pool plus the cumulative amount of the main machine direct supply meets the daily cumulative load, and the calculation formula is as follows:

[0091] ;

[0092] In the formula: is the actual capacity of the conventional chiller, kW; is the summer cold storage capacity, kWh; is the summer design day cumulative cooling load, kWh; is the energy storage time, h; is the building daytime use time, h.

[0093] b) Ice storage main machine model:

[0094] The ice storage host is a double working condition host, including ice making condition and refrigeration condition, and the ice making condition is switched to when storing, and the refrigeration condition is switched to when directly supplying. In order to store the required refrigerating capacity of the double working condition chiller in the ice making condition of the ice storage pool during the energy storage period, the following formula is calculated:

[0095] ;

[0096] In the formula: is the refrigerating capacity of the double working condition chiller in the ice making condition, kW.

[0097] The refrigerating capacity of the double working condition chiller in the ice making condition and the refrigeration condition has a ratio relationship, and the calculation formula is as follows:

[0098] ;

[0099] Similarly, the ice storage pool capacity plus the double working condition host refrigeration condition direct supply cumulative amount meets the design day cumulative load, and the refrigerating capacity calculation formula of the double working condition chiller in the refrigeration condition is as follows:

[0100] ;

[0101] Therefore, the actual capacity of the double working condition chiller needs to meet the above two conditions, that is:

[0102] ;

[0103] In the formula: is the refrigerating capacity of the double working condition chiller in the refrigeration condition, kW; is the ice making coefficient, that is, the ratio of the refrigerating capacity of the double working condition chiller in the ice making condition and the refrigeration condition, generally 0.6-0.75.

[0104] c) Low-temperature water storage and phase change storage host model:

[0105] In the low-temperature water storage and phase change storage air conditioning system, an air source heat pump is used as a heat source. The actual capacity of the air source heat pump needs to consider the heat release amount of the storage device during the energy storage period and the direct heating amount of the air source heat pump during the building daytime use period, so as to ensure sufficient heat supply in winter. At the same time, the air source heat pump needs to consider defrosting correction and temperature correction in winter, and the calculation formula is as follows:

[0106] ;

[0107] In the formula: is the actual capacity of the air source heat pump in the low-temperature water storage and phase change storage system, kW; is the winter storage amount, kWh; is the winter design day cumulative heat load, kWh; The comprehensive correction coefficient considering defrosting correction and temperature correction.

[0108] d) High-temperature water storage host model:

[0109] Since the conventional water outlet temperature of an air source heat pump is usually not more than 60℃, and high-temperature water storage may require a storage temperature of more than 90℃, a conventional air source heat pump is difficult to meet, so high-temperature water storage needs to use an electric boiler for night storage, and the remaining heating capacity during the day is directly supplied by an air source heat pump. The capacity of the electric boiler needs to meet the heat release capacity within the storage hours, and the capacity of the air source heat pump needs to meet the direct heating capacity of the building during the day, and the calculation formula is as follows:

[0110] ;

[0111] ;

[0112] In the formula: is the actual capacity of the air source heat pump in the high-temperature water storage system, kW; is the actual capacity of the electric boiler, kW; is the comprehensive correction coefficient considering defrosting correction and temperature correction.

[0113] e) Host capacity correction:

[0114] Since the fluctuation of the building's daytime load causes the host to not run at full capacity at every moment, the host capacity needs to be corrected. First, according to the host selection formula described in a) ~ d), a trial calculation is performed, and the obtained trial capacity is substituted into the design day. Then, 24-hour energy distribution is performed to obtain the actual cumulative direct supply of the host on the design day. If the storage capacity plus the actual cumulative direct supply of the host on the design day is less than the cumulative load on the design day, then the host capacity is enlarged until the actual cumulative direct supply on the design day is exactly equal to the cumulative load on the design day. At this time, the host capacity correction is complete.

[0115] 3. Calculate energy consumption:

[0116] The energy storage device stores energy during the valley period, fully utilizing the advantage of lower valley electricity price to reduce operating costs. During the building's daytime usage period, it releases energy to meet the building's cooling and heating needs. It prioritizes filling the host's overload gap, then shares the peak and high load, and finally supplements the flat rate period demand. When there is not enough energy, the host directly supplies it, maximizing the use of valley electricity to reduce costs.

[0117] The energy consumption of the chiller (conventional / dual working condition) will change with different operating conditions when directly supplying energy and cooperating with the energy storage device. The energy consumption of the chiller (conventional / dual working condition) will change with different operating conditions when directly supplying energy and cooperating with the energy storage device. COP It changes with the change of outdoor environmental parameters and needs to be corrected hour by hour, as shown in the following formula:

[0118] ;

[0119] ;

[0120] ;

[0121] Where: for i The cooling performance coefficient of the chiller when directly supplying water at the time; is the cooling coefficient under standard working conditions when the chiller is directly supplied; for i The cooling performance coefficient of the chiller during cold storage at the time; The cooling coefficient of the chiller under standard operating conditions when storing cold; for i The performance coefficient correction factor of the chiller at the time is, in order to simplify the calculation, only the influence of the cooling water temperature is considered; for i The cooling water supply temperature at the moment, ℃, is taken based on the outdoor hourly wet-bulb temperature and the rated approximation of the cooling tower (4℃) to simplify the calculation; 、 、 、 They are the correction curve coefficients of the chiller respectively. The correction curve is obtained by fitting the sample parameters of products from mainstream equipment manufacturers.

[0122] The hourly energy consumption of the chiller's cold storage is calculated as follows:

[0123] ;

[0124] Where: for i Energy consumption of chiller for cold storage at each moment, kW; for i Cooling capacity of the chiller at any given moment, kW.

[0125] The hourly energy consumption of direct supply chillers is calculated as follows:

[0126] ;

[0127] Where: for i Energy consumption of chiller when directly supplying water, kW; for i Cooling capacity of the chiller directly supplied at any given moment, kW.

[0128] The hourly energy consumption of the cooling tower is calculated as follows:

[0129] ;

[0130] In the formula: is i the cooling tower hourly energy consumption, kW; is the unit refrigeration capacity cooling tower power consumption, kW / kW.

[0131] The heat pump's COP will also change with the outdoor environmental parameters, and needs to be corrected hourly, as shown in the following formula:

[0132] ;

[0133] ;

[0134] ;

[0135] In the formula: is i the air source heat pump direct supply condition at the time of the modified heating performance coefficient; is the rated heating performance coefficient under the air source heat pump direct supply condition; is i the air source heat pump heat storage condition at the time of the modified heating performance coefficient; is the rated heating performance coefficient under the air source heat pump heat storage condition; is i the air source heat pump heating performance coefficient correction coefficient, only the influence of outdoor temperature is considered for simplification of calculation; is i the outdoor dry-bulb temperature at the time, ℃; , , , are respectively the air source heat pump correction curve coefficients, and the correction curve is obtained by fitting the product sample parameters of the main equipment manufacturers.

[0136] The air source heat pump heat storage energy consumption is calculated as follows:

[0137] ;

[0138] In the formula: is i the air source heat pump heat storage energy consumption at the time, kW; is i the air source heat pump heat storage amount at the time, kW.

[0139] The air source heat pump direct supply energy consumption is calculated as follows:

[0140] ;

[0141] In the formula: is iInstantaneous air source heat pump direct supply energy consumption, kW; For i Instantaneous air source heat pump direct supply heat, kW.

[0142] The hourly energy consumption of the electric heating boiler during heat storage is calculated as follows:

[0143] ;

[0144] In the formula: For i Instantaneous electric heating boiler heat storage energy consumption, kW; For i Instantaneous electric heating boiler heat storage, kW; COP is the heating performance coefficient (heating efficiency) of the electric heating boiler.

[0145] The hourly energy consumption of the water pump is calculated as follows:

[0146] ;

[0147] ;

[0148] ;

[0149] ;

[0150] ;

[0151] ;

[0152] ;

[0153] ;

[0154] ;

[0155] ;

[0156] ;

[0157] ;

[0158] The hourly energy consumption of the water pump during the cooling season is calculated as follows:

[0159] Water storage model:

[0160] ;

[0161] Ice storage model:

[0162] ;

[0163] The hourly energy consumption of the water pump in the heating season is calculated as follows:

[0164] ;

[0165] In the formula: is the energy consumption of the circulating cold water pump at the moment, kW; i is the unit refrigeration circulating cold water pump power consumption, kW / kW; is the energy consumption of the cold release water pump at the moment, kW; is the unit refrigeration cold release water pump power consumption, kW / kW; i is the cold quantity released by the energy storage device at the moment, kW; is the energy consumption of the ice storage pump at the moment, kW; is the unit refrigeration ice storage pump power consumption, kW / kW; i is the cold quantity directly supplied by the chiller at the moment, kW; is the energy consumption of the ice melting pump at the moment, kW; i is the unit refrigeration ice melting pump power consumption, kW / kW; is the cold storage quantity of the chiller at the moment, kW; is the hourly energy consumption of the cooling water pump at the moment, kW; i is the unit refrigeration cooling water pump power consumption, kW / kW; is the hourly energy consumption of the chilled water pump at the moment, kW; i is the unit refrigeration chilled water pump power consumption, kW / kW; is the energy consumption of the chiller direct supply chilled water pump at the moment, kW; is the unit refrigeration chilled water pump power consumption, kW / kW; i is the energy consumption of the chiller cold storage chilled water pump at the moment, kW; is the unit refrigeration chilled water pump power consumption, kW / kW; i is the hourly energy consumption of the cooling water pump at the moment, kW; is the unit refrigeration cooling water pump power consumption, kW / kW; is the hourly energy consumption of the chilled water pump at the moment, kW; i is the unit refrigeration chilled water pump power consumption, kW / kW; is the energy consumption of the chiller direct supply chilled water pump at the moment, kW; is the unit refrigeration chilled water pump power consumption, kW / kW; i is the energy consumption of the chiller cold storage chilled water pump at the moment, kW; is the unit refrigeration chilled water pump power consumption, kW / kW; is the energy consumption of the circulating hot water pump at the moment, kW; i is the unit heating circulating hot water pump power consumption, kW / kW; is the heat storage quantity of the main machine (air source heat pump, electric heating boiler) at the moment, kW; i is the energy consumption of the heat release water pump at the moment, kW; is the unit heating heat release water pump power consumption, kW / kW; is the energy consumption of the chiller direct supply chilled water pump at the moment, kW; i is the unit refrigeration chilled water pump power consumption, kW / kW; is the energy consumption of the chiller cold storage chilled water pump at the moment, kW; i is the unit refrigeration chilled water pump power consumption, kW / kW; is the energy consumption of the circulating hot water pump at the moment, kW; is the unit heating circulating hot water pump power consumption, kW / kW; iHeat released by the energy storage device at the moment, kW; For i Air source heat pump direct heating water pump energy consumption at the moment, kW; For unit heating water pump power consumption, kW / kW; For i Heat released by the air source heat pump direct heating at the moment, kW; For i Main machine (air source heat pump, electric boiler) heat storage water pump energy consumption at the moment, kW; For i Water storage cooling water pump energy consumption in cooling season at the moment, kW; For i Ice storage cooling water pump energy consumption in cooling season at the moment, kW; For i Water pump energy consumption in heating season at the moment, kW.

[0166] The energy consumption of each moment is summed up as:

[0167] ;

[0168] In the formula: The system i Energy consumption at the moment, kW; Here means that only one kind of energy consumption can exist at the same moment, that is, or. When it is a water storage system, the cooling season water pump energy consumption is When it is an ice storage system, the cooling season water pump energy consumption is .

[0169] In summary, the annual operation energy consumption of each architecture can be calculated through the energy consumption model.

[0170] S3, calculate the evaluation index value of each evaluation index factor based on the energy consumption and / or initial investment of the unit selection corresponding to each architecture type.

[0171] Taking the above-mentioned five evaluation index factors (initial investment, operation cost, floor area, operation energy efficiency ratio and carbon emission) as an example, the evaluation index values of the five evaluation index factors are calculated according to the energy consumption generated by the units corresponding to different architecture types, that is, assuming that there are five evaluation index factors, then each architecture type has five evaluation index values.

[0172] Core index calculation model:

[0173] a) Calculate the initial investment and floor area:

[0174] In terms of initial investment, its composition covers multiple equipment and site-related costs. Mainly includes the cost of main engine, energy storage device, cooling tower, plate heat exchanger, machine room, water pump, commercial land cost and power capacity expansion cost, the calculation formula is as follows:

[0175]

[0176] In the formula: Total initial investment, ten thousand yuan; , The unit price of main engine (conventional / dual working condition water chiller unit, air source heat pump, electric boiler, and including supporting water pump), yuan / kW; , , The economic value unit price of energy storage device, plate heat exchanger, and equipment occupied space, yuan / m 2 ; The unit price of machine room power capacity expansion cost, yuan / KVA; The capacity of main engine (conventional / dual working condition water chiller unit, air source heat pump, electric boiler), kW; The capacity of water chiller unit (conventional / dual working condition water chiller unit), kW; , The occupied area of energy storage device and the entire system, m 2 ; The heat exchange area of plate heat exchanger, m 2 ; The maximum power of main engine, KVA.

[0177] In terms of space requirements, the building space size required for the layout of components of different architecture systems needs to be measured, as well as the adaptability to different building structures, to avoid affecting system installation and use due to space limitations. The occupied area required for each architecture system is calculated, and the formula is as follows:

[0178]

[0179] In the formula: The total occupied area of the system, m 2 ; , The outdoor commercial land area coefficient and indoor machine room land area coefficient of main engine (conventional / dual working condition water chiller unit, air source heat pump, electric boiler, and including supporting water pump), m 2 / kW; , The machine room land area coefficient of energy storage device and the machine room land area coefficient of plate heat exchanger, m 2 / kW; The energy storage capacity of energy storage device, kW.​​

[0180] The energy storage device herein refers to a device for storing cold and heat in a cold and heat dual storage system.

[0181] b) Calculate the annual operating cost, operating energy efficiency ratio, carbon emission:

[0182] According to the hourly electricity price and hourly energy consumption, the hourly electricity fee can be obtained, and the annual 8760-hour electricity fee is summed up to obtain the annual operating electricity fee, as shown in the following formula:

[0183] ;

[0184] In the formula: The annual operating electricity fee is ten thousand yuan; The hourly electricity price is yuan / kWh. i The operating energy efficiency ratio reflects the energy-saving performance of the system in the actual operation process, and the indexes for investigation include the summer operating energy efficiency ratio, the winter operating energy efficiency ratio, and the annual operating energy efficiency ratio, and the calculation formula is as follows:

[0185]

[0186] ;

[0187] ;

[0188] ; In the formula:

[0189] The summer operating energy efficiency ratio is; The system summer refrigeration capacity is kWh; The system summer power consumption is kWh; The winter operating energy efficiency ratio is; The system winter heating capacity is kWh; The system winter power consumption is kWh; The system annual operating energy efficiency ratio is. Based on the comprehensive electrification background, the device does not directly burn fossil fuels, so only the indirect carbon emission generated by the device consuming power grid power is calculated, and the calculation formula is as follows:

[0190]

[0191] ; In the formula:

[0192] The annual indirect carbon emission is tCO2; The power carbon emission coefficient is.

[0193] ​The above multiple core indexes involve four dimensions of economy, energy efficiency, environment, and space requirement, so that the optimal cold and heat dual storage air conditioning system architecture is evaluated from multiple dimensions, and the finally given architecture ranking has scientificity and rationality.

[0194] After obtaining the evaluation index values, next, the evaluation method of the present application is specifically introduced.

[0195] The evaluation method of the present application adopts a subjective and objective combined evaluation method, combines the analytic hierarchy process and the entropy method to determine the combined weight of each evaluation factor (space requirement, system operation energy efficiency, operation cost, initial investment, carbon emission, etc.), introduces a "peak-valley electricity price ratio correction factor" and an "energy storage rate correction factor" to dynamically optimize the combined weight, and finally performs comprehensive evaluation on each architecture by the TOPSIS method to analyze the suitability of each architecture in different application scenarios. The specific process is as follows:

[0196] S4, based on the evaluation index factor, a plurality of architecture types and the optimal architecture type, a hierarchical structure model is constructed.

[0197] In the hierarchical structure model of the present application, the target layer is the optimal cold and heat dual storage air conditioning system architecture, the scheme layer is each architecture model, and the criterion layer is various indexes for evaluating air conditioning energy storage projects. Common core indexes include operation cost, initial investment, annual operation energy efficiency ratio, carbon emission, and floor area. These indexes involve economy, environment, energy efficiency, and space requirement. Designers can also supplement according to project requirements, such as Figure 2 as shown.

[0198] S5, based on the hierarchical structure model, the combined weight of all the evaluation index factors is determined by the analytic hierarchy process and the entropy method respectively, and the combined weight is dynamically optimized to obtain the optimal weight of each evaluation index factor.

[0199] The specific process of step S5 is as follows:

[0200] S5.1, based on the hierarchical structure model, the weight of each evaluation index factor is calculated by the analytic hierarchy process, and the weight that passes the consistency test is taken as the first weight of the evaluation index factor.

[0201] As Figure 3 shown, the specific process of step S5.1 is as follows:

[0202] S5.1.1, the importance of each evaluation index factor is valued by using the "1-9 scale method", and an index judgment matrix is constructed.

[0203] The analytic hierarchy process can reflect the needs of the owners to some extent, but the index weight is easily disturbed by the subjective intention of the personnel. First, the indicators at the same level need to be compared with each other, and the importance is valued according to the importance. The 1-9 scale method is usually used to judge the importance of elements, and the specific content is shown in Table 2:

[0204] Table 2 meaning of judgment matrix scale

[0205]

[0206] The importance of each index is valued by using the 1-9 scale method to construct the judgment matrix A , as follows:

[0207]

[0208] Among them, represents the importance of the ith evaluation index factor relative to the jth evaluation index factor, and n is the number of evaluation index factors.

[0209] S5.1.2, calculate the geometric mean of each column of the index judgment matrix, and normalize the geometric mean to obtain the initial weight of each evaluation index factor.

[0210] The geometric mean of each column of the judgment matrix is calculated as follows:

[0211]

[0212] In the formula, is the geometric mean of each column;

[0213] is normalized to obtain the index weight vector, and the calculation formula is as follows:

[0214]

[0215] In the formula, is the weight of the jth evaluation index factor, that is, the initial weight of the jth evaluation index factor. j S5.1.3, calculate the maximum eigenvalue of the index judgment matrix based on the initial weight of each evaluation index factor.

[0216] The obtained index judgment matrix is subjected to consistency check, and the maximum eigenvalue of the index judgment matrix is calculated, and the calculation formula is as follows:

[0217]

[0218]

[0219] ​​​​​​represents the maximum eigenvalue of the indicator judgment matrix, and A is the indicator judgment matrix.

[0220] S5.1.4. Calculate the actual consistency index based on the maximum characteristic root CI , and based on the random consistency index RI Calculate the consistency ratio CR , ;

[0221] ;

[0222] Look up the table to get the random consistency index RI As shown in Table 3;

[0223] Table 3

[0224]

[0225] S5.1.5. Determine whether the consistency ratio is less than 0.1. If so, the indicator judgment matrix is ​​considered to have passed the consistency test. The initial weight corresponding to the indicator judgment matrix is ​​the first weight, where the first weight of the j-th evaluation index factor is expressed as Otherwise, return to the first step and readjust the indicator judgment matrix to make it have satisfactory consistency.

[0226] S5.2. Calculate the weight of each evaluation index factor of each architecture type using an entropy method based on the hierarchical structure model to obtain a second weight of the evaluation index factor of each architecture type.

[0227] The entropy method is an objective weighting method based on information theory. It is primarily used to determine the weight of each indicator in a multi-indicator comprehensive evaluation. It analyzes the degree of dispersion of the indicator data distribution to determine the weight of each indicator in the comprehensive evaluation. Its core concept is that the greater the dispersion of the indicator data, the more information it contains, and therefore a higher weight should be assigned. Information entropy is a measure of the degree of disorder in a system. A higher entropy value indicates a more uniform data distribution and a lower information utility value.

[0228] Next, the application of the entropy method in the present invention is specifically introduced. Figure 4 shown.

[0229] S5.2.1. Collect the values ​​of each evaluation indicator for each architecture type to construct the original data matrix X， ,in, For the i The first architecture type j The evaluation index value, m is the number of architecture types, n is the number of evaluation index factors.

[0230] S5.2.2, standardizing the original data matrix to obtain a standardized index data matrix Y , , is the standardized value of the jth evaluation index factor of the ith architecture type. i j

[0231] That is, in order to eliminate the influence of different index dimensions and orders of magnitude, the original data matrix needs to be standardized. For positive indicators, the larger the indicator value, the better, and the calculation is as follows:

[0232] ;

[0233] For negative indicators, the smaller the indicator value, the better, and the calculation is as follows:

[0234] ;

[0235] After standardization, the standardized index data matrix is obtained, and the calculation is as follows:

[0236] ;

[0237] In the formula: is the standardized index data matrix; is the standardized value of the jth index of the ith architecture. i j

[0238] S5.2.3, determining the second weight of each evaluation index factor based on the standardized index data matrix by entropy method, wherein the second weight of the jth evaluation index factor The calculation formula is:

[0239] ;

[0240] ;

[0241] ;

[0242] ;

[0243] Wherein, is the proportion of the standardized value of the jth evaluation index factor of the ith architecture type to the evaluation index factor; note that if j i , it needs to be corrected to a very small value (such as 10 -6 ) to avoid calculation errors. ​​​​​​​

[0244] is the entropy value of the jth evaluation index factor; j , when , .

[0245] is the information redundancy (also known as the difference coefficient, reflecting the importance of the index) of the jth evaluation index factor; j

[0246] is the entropy weight of the jth evaluation index factor, i.e., the second weight of the jth evaluation index factor. j j

[0247] S5.3, assigning the first weight and the second weight of each of the evaluation index factors to a corresponding linear weighting coefficient, thereby obtaining the combined weight of each of the evaluation index factors of each architecture type.

[0248] The combined weight of each index determined by combining the analytic hierarchy process and the entropy method can comprehensively consider subjective and objective factors, and the set of combined weights of each evaluation index factor is represented as: W

[0249] , , is the combined weight of the jth evaluation index factor; j is a linear weighting coefficient, , is the first weight of the jth evaluation index factor, is the second weight of the jth evaluation index factor, j is the number of evaluation index factors. j n

[0250] reflects the degree of emphasis on subjective and objective weights. The value can be determined according to specific circumstances and needs, for example, when the subjective information is reliable and important, a larger value can be taken; when the data is more abundant and the objective factor is more important, a smaller value can be taken. The optimal value can also be determined by some optimization method, so that the combined weight can better reflect the actual situation.

[0251] S5.4, dynamically optimizing the combined weight to obtain the optimal weight of each evaluation index factor.

[0252] As shown in Figure 5 , the specific process is:

[0253] ​​​​​​​​S5.4.1, calculating a peak-valley electricity price ratio correction factor based on the peak segment electricity price and the peak-valley electricity price , and calculating an energy storage rate correction factor based on the energy storage amount of the energy storage device and the cumulative total load on the design day ;

[0254] S5.4.2, adjusting the combined weight of the evaluation index factor for the operation cost based on the peak-valley electricity price ratio correction factor adjusting the combined weight of the evaluation index factor for the initial investment based on the energy storage rate correction factor adjusting the combined weight of the evaluation index factor for the initial investment based on the energy storage rate correction factor

[0255] In the engineering practice of air conditioning energy storage systems, electricity price policy plays a decisive role in its economy. Different engineering projects have significant differences in the adapted electricity price policy due to different geographical locations, electricity categories, and electricity time periods. The traditional system evaluation method often ignores the sensitive influence of electricity price fluctuations on the economy of the system, resulting in a large deviation between the economic evaluation results and the actual operation. In order to accurately quantify the specific effect of electricity price policy on the architecture of double storage systems, this patent introduces a peak-valley electricity price ratio correction factor coefficient.

[0256] ;

[0257] ;

[0258] In the formula: is the peak-valley electricity price ratio correction factor; is the peak-valley electricity price ratio correction factor adjustment coefficient, which is determined according to expert experience or based on historical project data regression analysis; is the peak segment electricity price, yuan / kWh; is the valley segment electricity price, yuan / kWh; is the adjusted weight of the operation cost; is the uncorrected weight of the operation cost.

[0259] Electricity price policy is very important for energy storage systems, but the traditional evaluation method may not consider the influence of electricity price difference on economy. The invention creates a "peak-valley electricity price ratio correction factor" to adjust the weight of the operation cost according to the electricity price difference of the project location, which is used to quantify the influence of electricity price policy on the economy of cold and heat double storage systems, to amplify the influence of operation cost in high peak-valley ratio scenarios, and to solve the problem of architecture selection deviation caused by the inability of static weight to distinguish electricity price sensitivity.

[0260] The energy storage rate also has a great influence on the investment of an energy storage project, the higher the energy storage rate, the lower the operation cost, but the larger the initial investment. Some projects pay more attention to the operation cost saving rate and adopt a higher energy storage rate. In order to weaken the initial investment weight of the high energy storage rate project and better consider the influence of the energy storage rate, the application introduces an energy storage rate correction factor coefficient, and the calculation formula is as follows:

[0261] ;

[0262] ;

[0263] In the formula, is the energy storage rate correction factor; is an energy storage rate correction factor adjustment coefficient, which is determined according to expert experience or based on historical project data regression analysis; is the energy storage amount of the energy storage device, kWh; is the cumulative total load of the design day, kWh; is the initial investment weight after correction; is the initial investment weight without correction.

[0264] The energy storage rate also has a great influence on the investment of an energy storage project, the higher the energy storage rate, the lower the operation cost, but the larger the initial investment. Some projects pay more attention to the operation cost saving rate and adopt a higher energy storage rate. In order to weaken the initial investment weight of the high energy storage rate project and better consider the influence of the energy storage rate, the application introduces an energy storage rate correction factor coefficient, which avoids the ranking of some architectures being reduced due to high initial investment of high energy storage projects, so as to balance the long and short economic efficiency.

[0265] S5.4.3, the weight of all evaluation index factors except the initial investment and operation cost is calculated based on the adjusted initial investment and operation cost, to obtain the final weight, and the calculation formula of the final weight is:

[0266] ;

[0267] In the formula, is the final weight of the first j index; is the combined weight value of each index except the initial investment and operation cost, wherein the adjusted operation cost weight is equal to , and the adjusted initial investment weight is equal to . , respectively represent and .

[0268] ; is a set of final weights of each evaluation index factor.

[0269] S6. Determine the relative closeness of each architecture type based on the maximum weight of each evaluation index factor and the TOPSIS comprehensive evaluation method, and take the architecture type corresponding to the highest relative closeness as the optimal architecture type.

[0270] The TOPSIS comprehensive evaluation method is a commonly used multi-attribute decision analysis method. First, the index weighted matrix is calculated according to the obtained maximum weight , and the specific process is shown in Figure 6 .

[0271] S6.1. Calculate the index weighted matrix based on the maximum weight Z , Z The calculation formula is:

[0272] ;

[0273] Wherein, is the standardized index data matrix; is the maximum weight of the j th evaluation index factor; m is the number of architecture types; n is the number of evaluation index factors;

[0274] S6.2. Calculate the positive and negative ideal distance of each architecture type based on the index weighted matrix Z The calculation formula is:

[0275] ;

[0276] ;

[0277] ;

[0278] ;

[0279] Wherein, is the positive ideal solution of the j th evaluation index factor; is the negative ideal solution; denotes the positive ideal distance of the i th architecture type, denotes the negative ideal distance of the i th architecture type, denotes the product of the evaluation index value of the i th architecture type in the index weighted matrix and the maximum weight of the j th evaluation index factor;

[0280] , means that, for positive indicators, , ; for negative indicators, , .

[0281] S6.3, calculate the relative closeness of each architecture type based on the positive and negative ideal distances of each architecture type, and the calculation formula of the relative closeness of the i-th architecture type is:

[0282] .

[0283] The value is between 0 and 1, closer to 1, indicating that the architecture is closer to the positive ideal solution, and the comprehensive evaluation effect is better; closer to 0, indicating that the architecture is closer to the negative ideal solution, and the comprehensive evaluation effect is worse.

[0284] In summary, according to The value of the four architecture types (the above example has four architecture types, of course, other architecture types can also be set according to actual conditions) is ranked, The greater the value, the higher the ranking of the architecture type, and thus the most suitable optimal cold and heat dual storage air conditioning system architecture form under the scene of the owner is screened out.

[0285] Embodiment 2 discloses an evaluation system of a cold and heat dual storage system architecture, which is used to execute the evaluation method of the cold and heat dual storage system architecture described in Embodiment 1, and comprises:

[0286] An evaluation index factor determination module is used to determine a plurality of evaluation index factors including space demand, economy, energy efficiency, and environmental nature;

[0287] A selection module is used to determine the selection of each unit of a plurality of architecture types included in the cold and heat dual storage system;

[0288] A calculation module is used to calculate the energy consumption and initial investment of each unit selection;

[0289] An evaluation index value calculation module is used to calculate the evaluation index values of each evaluation index factor based on the energy consumption and initial investment of the unit selection corresponding to each architecture type;

[0290] A hierarchical structure model construction module is used to construct a hierarchical structure model based on the evaluation index factors, a plurality of architecture types, and an optimal architecture type;

[0291] The most weight calculation module is configured to determine the combined weights of all the evaluation index factors by analytic hierarchy process and entropy method respectively based on the hierarchical structure model, and dynamically optimize the combined weights to obtain the most weight of each evaluation index factor.

[0292] The evaluation module is configured to determine the relative closeness of each architecture type based on the most weight of each evaluation index factor and the TOPSIS comprehensive evaluation method, and take the architecture type corresponding to the highest relative closeness as the optimal architecture type.

[0293] Embodiment 3 discloses an electronic device, comprising at least one processor, and a memory connected with the at least one processor in communication; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the evaluation method of the cold-heat dual storage system architecture as described in Embodiment 1.

[0294] Embodiment 4 discloses a storage medium storing a computer program, and the computer program is executed by a processor to implement the evaluation method of the cold-heat dual storage system architecture as described in Embodiment 1.

[0295] The above specific embodiments further illustrate the purpose, technical solutions and beneficial effects of the present application. It should be understood that the above description is only a specific embodiment of the present application and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for evaluating a cold and hot dual storage system architecture, characterized in that: The evaluation method includes: Determine several evaluation index factors based on space demand, economy, energy efficiency and environment; Determine the type of units for each of several architecture types included in the dual-storage cooling and heating system, and calculate the energy consumption and initial investment for each type of unit; Calculating the evaluation index value of each evaluation index factor based on the energy consumption and initial investment of the unit selection corresponding to each architecture type; Constructing a hierarchical structure model based on the evaluation index factor, the plurality of architecture types and the optimal architecture type; Based on the hierarchical structure model, determining the combined weights of all the evaluation index factors by using the hierarchical analysis method and the entropy method respectively, and dynamically optimizing the combined weights to obtain the final weight of each evaluation index factor; The combined weight is expressed as W , , , For the j The combined weight of the evaluation index factors; is the linear weighting coefficient, , For the j The first weight of the evaluation index factor, For the j The second weight of the evaluation index factor, n is the number of evaluation index factors; The specific process of dynamically optimizing the combined weights to obtain the final weight of each evaluation index factor in each architecture type is as follows: Calculate the peak-valley electricity price ratio correction factor based on peak electricity price and peak-valley electricity price , and calculate the energy storage rate correction factor based on the energy storage device storage capacity and the total cumulative load on the design day ; Based on the peak-valley electricity price ratio correction factor The combined weight of the evaluation index factor for operating costs is adjusted, and at the same time, based on the energy storage rate correction factor Adjust the weight of the portfolio of initial investment for the evaluation index factor; Based on the adjusted weights of initial investment and operating costs, the weights of all evaluation index factors other than the initial investment and operating costs are calculated to obtain the final weight. The calculation formula of the final weight is: ； ； ； ； ； in, Represents the final weight of the i-th evaluation index factor; 、 are the weights of the adjusted initial investment and operating expenses respectively; 、 are the combined weights of initial investment and operating expenses before adjustment; is the peak-valley electricity price ratio correction factor adjustment coefficient; is the peak electricity price, in yuan / kWh; The off-peak electricity price is in yuan / kWh; is the adjustment coefficient of the energy storage rate correction factor; The energy stored in the energy storage device is in kWh; is the total cumulative load of the design day, in kWh; The relative closeness of each of the architecture types is determined based on the final weight of each of the evaluation index factors and the TOPSIS comprehensive evaluation method, and the architecture type corresponding to the highest relative closeness is taken as the optimal architecture type.

2. The evaluation method for a cold and hot dual storage system architecture according to claim 1 is characterized in that: Based on the hierarchical structure model, the specific process of determining the combined weights of all the evaluation index factors in each of the architecture types by using the hierarchical analysis method and the entropy method is as follows: Calculating the weight of each evaluation index factor by using the hierarchical analysis method based on the hierarchical structure model, and using the weight that passes the consistency test as the first weight of the evaluation index factor; Calculating the weight of each evaluation index factor of each architecture type by an entropy method based on the hierarchical structure model to obtain a second weight of the evaluation index factor of each architecture type; The first weight and the second weight of each evaluation index factor are assigned corresponding linear weighting coefficients, thereby obtaining a combined weight of each evaluation index factor of each architecture type.

3. The evaluation method for a cold and hot dual storage system architecture according to claim 2, characterized in that: The specific process of calculating the weight of each evaluation index factor by the hierarchical structure model through the hierarchical analysis method and taking the weight that passes the consistency test as the first weight of the evaluation index factor is as follows: The "1-9 scale method" is used to assign values ​​to the importance of each evaluation index factor and construct an index judgment matrix: Calculating the geometric mean of each column of the indicator judgment matrix, and normalizing the geometric mean to obtain the initial weight of each evaluation indicator factor; Calculating the maximum eigenvalue of the index judgment matrix based on the initial weight of each evaluation index factor; Calculate the actual consistency index based on the maximum characteristic root CI , and based on the random consistency index RI Calculate the consistency ratio CR, ; Determine whether the consistency ratio is less than 0.

1. If so, it is considered that the indicator judgment matrix passes the consistency test. The initial weight corresponding to the indicator judgment matrix is ​​the first weight, wherein the first j The first weight of the evaluation index factor is expressed as ; Otherwise, return to the first step and readjust the indicator judgment matrix.

4. The evaluation method for a cold and hot dual storage system architecture according to claim 2, characterized in that: The specific process of calculating the weight of each evaluation index factor of each architecture type by the entropy method based on the hierarchical structure model to obtain the second weight of the evaluation index factor of each architecture type is as follows: Collect the values ​​of each evaluation indicator for each architecture type to construct the original data matrix X , ,in, For the i The first j The evaluation index value, m is the number of architecture types, n is the number of evaluation index factors; The original data matrix is ​​standardized to obtain a standardized index data matrix Y , ,in, For the i The first j The standardized value of the evaluation index factor; The second weight of each evaluation index factor is determined by entropy method based on the standardized index data matrix, wherein the j The second weight of the evaluation index factor The calculation formula is: ； ； ； ； in, For the j Under the evaluation index factor i The proportion of the standard value of each architecture type in the evaluation index factor; For the j The entropy value of the evaluation index factor; For the j Information redundancy of the evaluation index factors; No. j The entropy weight of the evaluation index factor, that is, j The second weight of the evaluation index factor.

5. The evaluation method for a cold and hot dual storage system architecture according to claim 1 is characterized in that: The specific process of determining the relative closeness of each architecture type based on the final weight of each evaluation index factor and the TOPSIS comprehensive evaluation method is as follows: Calculate the indicator weighting matrix based on the final weights Z , Z The calculation formula is: ； Among them, Y is the standardized indicator data matrix; For the j The final weight of the evaluation index factor; m is the number of architecture types; n is the number of evaluation index factors; Based on the indicator weighting matrix Z Calculate the positive and negative ideal distances for each of the architecture types using the following formula: ； ； ； ； in, For the j The evaluation index factor is a positive ideal solution; is a negative ideal solution; Indicates the i The positive ideal distance for each architecture type, Indicates the i Negative ideal distance for each architecture type, Indicates the first i The first structural type j The product of the evaluation index value of each evaluation index factor and the final weight; The relative closeness of each architecture type is calculated based on the positive and negative ideal distances of each architecture type. The calculation formula for the relative closeness of the i-th architecture type is: 。 6. An evaluation system for a dual-storage cold storage system architecture, used to execute the evaluation method for a dual-storage cold storage system architecture according to any one of claims 1 to 5, characterized in that: include: Evaluation index factor determination module, used to determine several evaluation index factors based on space demand, economy, energy efficiency, and environment; The selection module is used to determine the selection of various units of several architecture types included in the dual-storage cooling and heating system; A calculation module, used to calculate the energy consumption and initial investment of each type of unit selected; An evaluation index value calculation module, configured to calculate the evaluation index value of each evaluation index factor based on the energy consumption and initial investment of the unit selection corresponding to each of the architecture types; A hierarchical structure model construction module, configured to construct a hierarchical structure model based on the evaluation index factors, the plurality of architecture types, and the optimal architecture type; A final weight calculation module is used to determine the combined weights of all the evaluation index factors based on the hierarchical structure model by using the hierarchical analysis method and the entropy method, and dynamically optimize the combined weights to obtain the final weight of each evaluation index factor; An evaluation module is used to determine the relative closeness of each of the architecture types based on the final weight of each of the evaluation index factors and the TOPSIS comprehensive evaluation method, and to take the architecture type corresponding to the highest relative closeness as the optimal architecture type.

7. An electronic device, characterized in that: The system comprises at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a method for evaluating a cold and hot dual storage system architecture according to any one of claims 1 to 5.

8. A storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the evaluation method of a cold and hot dual storage system architecture according to any one of claims 1 to 5 is implemented.

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