Method for determining optimal phase change temperature of phase change self-insulation building block

Abstract

The application discloses a method for determining optimal phase change temperature of phase change self-insulation blocks, comprising: establishing an office building model and an air conditioning system model; performing heterogeneous outer wall equivalent treatment on the phase change self-insulation blocks; setting inner disturbance and outer disturbance of the office building model; setting enthalpy-temperature curve of the phase change material; setting Genopt optimization tool; starting the Genopt optimization program to call Energyplus simulation software to perform iterative simulation to obtain minimum target value; and determining optimal phase change temperature under each target weighting comprehensive condition. The application determines the optimal phase change temperature of the phase change self-insulation blocks based on simulation and multi-target optimization method, and under the condition of comprehensively considering energy consumption and thermal comfort, solves the optimization design problem of weighting of two targets of thermal comfort and energy saving.

Description

Technical Field

[0001] This invention relates to the field of energy conservation in building envelopes, and more particularly to the determination of phase change materials in phase change envelopes, specifically a method for determining the optimal phase change temperature of a phase change self-insulating block. Background Technology

[0002] Concrete composite self-insulating blocks have attracted much attention in recent years due to their ability to integrate insulation and structural properties, offering advantages such as durability, fire resistance, ease of construction, and a lifespan comparable to that of the building. While the internal insulation material enhances the blocks' thermal insulation performance, it also reduces the wall's heat storage capacity. Further technological breakthroughs are needed to improve the thermal inertia of self-insulating blocks. By incorporating phase change materials into self-insulating blocks, combining self-insulation technology with latent heat storage technology, it is possible to not only improve the wall's thermal insulation performance but also its heat storage capacity, thereby improving the indoor thermal environment and reducing air conditioning energy consumption.

[0003] The thermophysical properties of phase change materials (PCMs) in walls have a significant impact on building air conditioning energy consumption and thermal comfort. According to phase change theory, PCMs can only undergo phase change cycling when the actual temperature of the PCM layer in the wall is within the phase change temperature range, thereby achieving heat storage and release within the wall and improving its thermal inertia. However, the temperature environment of the PCM layer is related to the wall's heat transfer process and is affected by indoor and outdoor air temperatures, wall construction methods, and solar radiation. Therefore, for a given wall structure, obtaining the optimal phase change temperature is a crucial issue.

[0004] Current research on the application of phase change materials (PCMs) in walls mainly focuses on: 1) research on suitable PCMs for different climate zones; and 2) research on the construction methods of PCM walls. Saafi et al. used numerical simulation to study the impact of factors such as PCM temperature, PCM installation location, and wall orientation on annual air conditioning energy saving under Tunisian climate conditions. The study showed that the optimal PCM temperature is near the indoor air conditioning temperature setpoint; the highest energy saving rate for south-facing walls is 13.4%, and installing a 2 cm thick PCM on the roof can reduce the daily surface temperature fluctuation of the roof by 5.35℃. Zhang Weiwei et al. installed two PCMs with different PCM temperatures in hollow concrete blocks, using Nanjing, a hot-summer, cold-winter region, as the research object. They used EnergyPlus simulation to analyze the optimal PCM temperature and optimal installation location in the hollow concrete blocks. The study showed that rooms with walls where the PCM temperature is 18℃ in the inner holes and 26℃ in the middle holes have the highest annual air conditioning energy saving rate, at 19.66%. Frazzica et al. studied the thermal properties of phase change mortar under the climatic conditions of Messina in the Mediterranean region using experimental and simulation methods, and conducted parameter analysis on the phase change material. The study showed that the optimal phase change temperature of the phase change material is 27℃; compared to ordinary cement mortar, incorporating 15% phase change material into cement mortar can improve indoor thermal comfort. Meng et al. encapsulated two phase change materials with different phase change temperatures in aluminum plates and embedded them into the interior surface of a room, studying the effects of the phase change temperature and thickness of the phase change material on the room's thermal environment in different seasons using experimental and simulation methods. The results showed that the phase change material can improve the indoor thermal environment; in summer, it can reduce room air temperature and fluctuation by 4.28–7.7℃ and 28.8–67.8%, respectively; in winter, it can increase room air temperature and fluctuation by 6.93–9.48℃ and decrease by 17.7–25.4%, respectively. Kumar et al. filled hollow bricks with phase change material encapsulated in aluminum foil and established two experimental chambers to study the thermal comfort of the phase change rooms using experimental methods. Studies have shown that the indoor air temperature in a phase change room can be reduced by up to 6°C compared to a normal room.

[0005] In summary, existing research has been conducted on the energy conservation and consumption reduction aspects and the improvement of indoor thermal environment of phase change energy storage technology in buildings, but research on the comprehensive performance of these two aspects is lacking. However, there is a conflict between the two objectives of energy consumption and indoor thermal comfort; an increase in one performance indicator may lead to a decrease in the other. Optimizing a single indicator of energy consumption or thermal comfort makes it difficult to achieve a unified optimal solution for both. Therefore, determining the phase change temperature is an optimization design problem that addresses the trade-off between thermal comfort and energy conservation. Summary of the Invention

[0006] To overcome the shortcomings of the prior art, the present invention provides a method for determining the optimal phase change temperature of a phase change self-insulating block, in order to solve at least one of the above-mentioned technical problems.

[0007] This invention is achieved through the following technical solutions:

[0008] A method for determining the optimal phase transition temperature of a phase change self-insulating block includes:

[0009] Create a model of the office building and its air conditioning system;

[0010] Equivalent treatment of heterogeneous exterior walls for phase change self-insulating blocks;

[0011] Set up the internal and external disturbances of the office building model;

[0012] Set the enthalpy-temperature profile for the phase change material;

[0013] Genopt optimization tool settings;

[0014] The Genopt optimization program is started, and the Energyplus simulation software is used to iteratively simulate and obtain the minimum target value.

[0015] Determine the optimal phase transition temperature under the comprehensive consideration of various objective trade-offs.

[0016] The above technical solution, based on simulation and multi-objective optimization methods, determines the optimal phase change temperature of the phase change self-insulating block while comprehensively considering energy consumption and thermal comfort, thus solving the optimization design problem of balancing the two objectives of thermal comfort and energy saving.

[0017] Furthermore, the Genopt optimization tool settings include objective function creation, optimization variable settings, command file and configuration file settings.

[0018] As a further technical solution, establishing an office building model further includes: setting the building dimensions, the structural form of the building envelope, and thermal parameters.

[0019] Specifically, building dimensions include room area, floor height, room geometric dimensions, window dimensions, and window-to-wall ratio. The structural form and thermal parameters of the building envelope can be determined with reference to the national standard "Energy-Saving Engineering Practices and Data for Building Envelopes" 09J908-3.

[0020] As a further technical solution, the phase change self-insulating block is divided into different material layers in the thickness direction according to the geometric structure distribution of the material, and the resulting heterogeneous material layers are homogenized.

[0021] Considering that EnergyPlus uses a one-dimensional heat transfer algorithm to calculate the heat transfer process of the building envelope, the software requires that the material parameters of each layer of the building envelope, such as walls, be set layer by layer. However, phase change self-insulating blocks are non-homogeneous structures. Therefore, it is necessary to perform a non-homogeneous external wall equivalent treatment on the phase change self-insulating blocks to obtain a homogeneous structural layer, so as to facilitate heat transfer analysis using EnergyPlus.

[0022] As a further technical solution, the internal disturbance settings for the office building model further include: setting settings for office room personnel, lighting, and equipment separately; and setting external disturbance settings based on meteorological data from a typical meteorological year in the city where the office building is located. Furthermore, the internal disturbance settings can refer to the "Standard for Energy-Saving Design of Public Buildings" (GB50189-2015).

[0023] As a further technical solution, setting the enthalpy-temperature curve of the phase change material further includes: obtaining the enthalpy-temperature curve provided by the phase change material manufacturer; keeping the basic shape of the enthalpy-temperature curve unchanged, and translating it to obtain the enthalpy-temperature curve at different phase change temperatures by interpolation to the left and right; using the Energyplus and Genopt optimization tools, setting the phase change temperature variable and performing iterative calculations in a programmed manner to automatically realize the transformation of different enthalpy-temperature curves in Energyplus; and finally obtaining the optimal enthalpy-temperature curve through iterative calculations.

[0024] As a further technical solution, the range, initial value, and step size of the phase transition temperature variable %wendu% are given, and the enthalpy-temperature curves are automatically updated and iterated for different phase transition temperatures. The Genopt software can use function tags to add or subtract variables in Energyplus through variable identifiers, thereby ensuring that the enthalpy-temperature curve changes accordingly to the enthalpy-temperature curve at the phase transition temperature when the phase transition temperature changes.

[0025] As a further technical solution, taking into account both energy consumption and thermal comfort indicators, the objective function is established as follows:

[0026]

[0027] Where, f1(x) ref The reference room's air conditioning energy consumption is g2(x) without the use of phase change materials. ref The average PPD (Power Distribution Count) of the air conditioning season in a reference room without phase change materials; h3(x) refThe reference room without phase change materials represents the average PPD (Predicted Percent Dissatisfied) during the transition season; f1(x) represents the air conditioning energy consumption of the room using phase change materials; g2(x) represents the average PPD (Predicted Percent Dissatisfied) during the transition season for the air conditioning of the room using phase change materials, where PPD represents the percentage of people dissatisfied with the thermal environment; h3(x) represents the average PPD (Predicted Percent Dissatisfied) during the transition season for the room using phase change materials; Q cool Indicates the cooling energy consumption of a room air conditioner using phase change materials; Q heat Indicates the energy consumption of room air conditioning heating using phase change materials; PPD 空调季 This indicates the average PPD (Percentage Per Day) of seasonal operating time for room air conditioning systems using phase change materials; PPD 过渡季 This indicates the average PPD (Power Delivery Time) of the transition season in rooms using phase change materials; (Q) cool +Q heat ) ref This represents the sum of cooling and heating energy consumption of a reference room without phase change materials; PPD 空调季ref This represents the average PPD (Power Distribution Count) of the air conditioning season in a reference room without phase change materials; PPD 过渡季ref This represents the average PPD (Period Working Hours) of a reference room during the transition season when no phase change materials were used.

[0028] As a further technical solution, after starting the Genopt optimization program, the office building model at the initial phase transition temperature is first simulated. A calculated value is obtained by performing mathematical operations on the simulation data through the objective function. Then, the initial variable values ​​are simulated to the left and right and compared with the previous values ​​until the minimum value is found.

[0029] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0030] Based on simulation and multi-objective optimization methods, this invention determines the optimal phase change temperature of the phase change self-insulating block while comprehensively considering energy consumption and thermal comfort, thus solving the optimization design problem of balancing the two objectives of thermal comfort and energy saving. Attached Figure Description

[0031] Figure 1 This is a flowchart illustrating a method for determining the optimal phase change temperature of a phase change self-insulating block according to an embodiment of the present invention.

[0032] Figure 2 This is a schematic diagram illustrating the iterative simulation using Energyplus simulation software called by the Genopt optimization program according to an embodiment of the present invention.

[0033] Figure 3 This is a schematic diagram of a building model according to an embodiment of the present invention.

[0034] Figure 4 This is a schematic diagram illustrating the equivalent processing according to an embodiment of the present invention.

[0035] Figure 5 This diagram illustrates the hourly usage rate of lighting and equipment, the hourly occupancy rate of personnel, and the hourly activation rate of fresh air according to an embodiment of the present invention.

[0036] Figure 6 This is a schematic diagram of PCM temperature search according to an embodiment of the present invention.

[0037] Figure 7 This is a schematic diagram illustrating the processing method of the phase change material module in Genopt and Energyplus according to an embodiment of the present invention.

[0038] Figure 8 This is a schematic diagram illustrating the configuration file settings in Genopt according to an embodiment of the present invention.

[0039] Figure 9 This is a schematic diagram of the command file settings in Genopt according to an embodiment of the present invention.

[0040] Figure 10 This is a schematic diagram of the iterative calculation process according to an embodiment of the present invention. Detailed Implementation

[0041] The technical solutions of various embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] Based on simulation and multi-objective optimization methods, this invention proposes a method for determining the optimal phase change temperature of phase change self-insulating blocks for typical public buildings.

[0043] In this embodiment, an office building model was created using Energyplus simulation software, and an air conditioning model was built on this model. Then, by coupling with the optimization tool Genopt, the optimal phase change temperature was determined through a multi-objective optimization method.

[0044] like Figure 1-2 As shown, the method includes the following steps:

[0045] Step 1: Create an office building model. The specific process is as follows:

[0046] Step 101: Create an office building model. This includes setting the building dimensions, the structural form of the building envelope, and the thermal parameters.

[0047] In this embodiment, the building model in step 101 is a typical three-story office building in Xi'an, and the building floor plan is as follows. Figure 3 As shown, the study focuses on office room 202, which has an area of ​​44.85 square meters. 2 The room has a floor height of 3.6m and geometric dimensions of 6.9m × 6.5m × 3.6m (length × width × height). The south wall has two exterior windows, each 1.8m long and 1.8m high. The window-to-wall ratio is 0.26. The structural form and thermal parameters of the building envelope are determined in accordance with the national standard "Construction Practices and Data for Energy-Saving Engineering of Building Envelopes" 09J908-3. Specific structural and thermal parameter settings are shown in Table 1.

[0048] Table 1. Envelope Structure Forms and Their Thermal Parameters

[0049]

[0050] Since EnergyPlus uses a one-dimensional heat transfer algorithm to calculate the heat transfer process of the building envelope, the software requires that the material parameters of each layer of the building envelope, such as walls, be set layer by layer. However, phase change self-insulating blocks are non-homogeneous structures. In order to use EnergyPlus for the heat transfer analysis of this embodiment, it is necessary to perform equivalent treatment on the phase change self-insulating blocks. Introducing formula (1), the equivalent density, equivalent specific heat, equivalent thermal conductivity, and equivalent latent heat of phase change of each layer of the new blocks after homogenization are calculated according to different material proportions. The calculation formula is as follows:

[0051] M = x1·M1 + x2·M2 (1)

[0052] In the formula, M represents the equivalent thermal properties of each material in the new block structure; M1 and M2 represent the thermal properties of two materials in a certain layer of the block structure; x1 and x2 represent the mass percentage, volume percentage, and area percentage in the heat transfer direction (when calculating the equivalent specific heat capacity and latent heat of phase change, x1 and x2 are mass percentages; when calculating the equivalent density, x1 and x2 are volume percentages; when calculating the equivalent thermal conductivity, x1 and x2 are area percentages in the heat transfer direction).

[0053] First, the blocks are divided into different material layers along their thickness direction according to the geometric distribution of the materials. Then, each heterogeneous material layer of the block is simplified into a homogeneous structure layer by equivalent treatment according to formula (1). The blocks are divided into 7 layers according to different material layers, among which L2, L4, and L6 are composed of two materials and need to be equivalently treated. Figure 4As shown, L1, L3, L5, and L7 are lightweight aggregate concrete layers; L2 and L4 are mixed layers of EPS and lightweight aggregate concrete; and L6 is a mixed layer of phase change material and lightweight aggregate concrete. According to formula (1), L2 and L4 are simplified into homogeneous insulation layers (EPS), and L7 is simplified into a homogeneous phase change material layer (PCM). The physical properties of the simplified three layers are shown in Table 2.

[0054] Table 2 Thermophysical parameters of heterogeneous material layer structures and simplified material layers

[0055]

[0056] Step 102: Establish an air conditioning model. Set up a direct expansion heat pump air conditioning system for each room, with rated COPs of 3 for cooling and 2.8 for heating. The COP of the air conditioner under partial load is calculated using equations (2) and (3). The air conditioning setup and air conditioning periods for different climate zones are shown in Tables 3 and 4.

[0057] Refrigeration COP = (0.85 + 0.15 × x) × COP 额 (2)

[0058] Heating COP = (0.75 + 0.15 × x) × COP 额 (3)

[0059] In the formula, x is the partial load factor.

[0060] Table 3 Air Conditioning Settings

[0061]

[0062] Table 4 Air Conditioning Periods in Different Climate Zones

[0063]

[0064] Step 103: Setting Internal and External Disturbances. This involves setting parameters for office occupants, lighting, and equipment, including occupant work and rest schedules, heat dissipation, and clothing thermal resistance. External disturbances are set using meteorological data from typical meteorological years for each city.

[0065] In this embodiment, the internal disturbance in step 103 is set with reference to the "Energy Conservation Design Standard for Public Buildings" (GB50189-2015). The average office space per person is 10 people / m². 2 The heat dissipation of personnel per unit time is 108W / m 2 The fresh air volume for personnel is 30m³. 3 / h, indoor lighting power density and equipment power density are 9W / m² 2 and 15W / m 2Hourly usage rate of lighting and equipment, hourly occupancy rate of personnel, and hourly activation rate of fresh air systems, such as... Figure 5 As shown. The thermal resistance of clothing is set to 0.5clo in the cooling season, 1clo in the heating season, and 0.7clo in the transition season. The air velocity is set to 0.2 m / s, and the metabolic rate of personnel is set to 132 W. In step 103, the external disturbance is simulated based on meteorological data from typical meteorological years of representative cities in different climate zones.

[0066] Step 104: Setting Output Variables. Output the annual air conditioning energy consumption data for office buildings and the predicted percentage of dissatisfaction (PPD) data.

[0067] Step 2: Setting the enthalpy-temperature profile of the phase change material

[0068] Currently, when using Energyplus to simulate heat transfer in phase change materials (PCMs), different enthalpy-temperature curves need to be created in the software for each simulation to optimize the PCM temperature. However, this method is slow in simulation and optimization and cannot accurately find the optimal PCM temperature. This invention uses an iterative update method to calculate the enthalpy-temperature curves of different PCMs. First, the enthalpy-temperature curves provided by the PCM manufacturer are used. Then, keeping the basic shape of the curves unchanged, the enthalpy-temperature curves at different phase change temperatures are obtained by left and right interpolation. In the Energyplus and Genopt optimization tools, the phase change temperature variable is set, and iterative calculations are performed programmatically. This automatically transforms the enthalpy-temperature curves in Energyplus, and finally, the optimal enthalpy-temperature curve is obtained through iterative calculation, thus yielding the optimal phase change temperature. Figure 6 As shown.

[0069] This example first obtains the enthalpy-temperature curve at a phase transition temperature of 20℃. Using mathematical methods, the curve can be shifted to obtain enthalpy-temperature curves for different phase transition temperatures. The processing method is shown in Table 5. As shown in Table 5, by assigning any phase transition temperature to %wendu%, the enthalpy value at other temperatures also changes accordingly, thus achieving the shifting of the enthalpy-temperature curve.

[0070] The Genopt software allows you to add or subtract variables in Energyplus using Functions based on variable identifiers. This enables the enthalpy-temperature curve to change accordingly with each phase transition temperature. Providing the phase transition temperature variable (%wendu%), its range, initial value, and step size allows for automatic iteration of different enthalpy-temperature curves. The processing methods in Genopt and Energyplus are as follows: Figure 7 As shown.

[0071] Table 5. Enthalpy-temperature curves with a phase transition temperature of 20℃.

[0072]

[0073] Step 3: Setting up the Genopt optimization tool

[0074] Step 301 involves setting up the configuration file. Genopt connects with Energyplus through the .ini format configuration file. Code 1-26 means that Genopt starts the simulation of the office building model (office_pcm_template.idf file) by launching the Energyplus simulation program in the cfg folder. This file contains optimization variables, which can be changed through the Genopt command file. Code 27-66 sets the objective function. The objective function used in this example considers energy consumption and thermal comfort indicators to be equally important, comprehensively considering both to achieve the optimal value for all objectives. Figure 8 As shown.

[0075]

[0076] In the formula, f1(x) re f represents the reference room air conditioning energy consumption without phase change materials; g2(x) re f represents the average PPD (Power Distribution Count) of the air conditioning system during the seasonal operating time in a reference room without phase change materials; h3(x) ref The reference room without phase change materials represents the average PPD (Predicted Percent Dissatisfied) during the transition season; f1(x) represents the air conditioning energy consumption of the room using phase change materials; g2(x) represents the average PPD (Predicted Percent Dissatisfied) during the transition season for the air conditioning of the room using phase change materials, where PPD represents the percentage of people dissatisfied with the thermal environment; h3(x) represents the average PPD (Predicted Percent Dissatisfied) during the transition season for the room using phase change materials; Q cool Indicates the cooling energy consumption of a room air conditioner using phase change materials; Q heat Indicates the energy consumption of room air conditioning heating using phase change materials; PPD 空调季 This indicates the average PPD (Percentage Per Day) of seasonal operating time for room air conditioning systems using phase change materials; PPD 过渡季 This indicates the average PPD (Power Delivery Time) of the transition season in rooms using phase change materials; (Q) cool +Q heat ) ref This represents the sum of cooling and heating energy consumption of a reference room without phase change materials; PPD 空调季ref This represents the average PPD (Power Distribution Count) of the air conditioning season in a reference room without phase change materials; PPD 过渡季refThis represents the average PPD (Period Working Hours) of a reference room during the transition season when no phase change materials were used.

[0077] The specific implementation steps are as follows: First, Energyplus software is used to simulate the reference room building model without phase change materials to obtain the sum of the air conditioning energy consumption during the heating season and the air conditioning energy consumption during the cooling season, which is 5620792992 J; the average PPD data for the air conditioning season is 10.1228; and the average PPD data for the transition season is 46.5186. Then, the codes of the output variables are obtained from the eso file in code 17. The codes of each output variable are shown in codes 50-64. The code for the air conditioning energy consumption data during the heating season is 1335, the code for the air conditioning energy consumption data during the cooling season is 1334, the code for the average PPD data during the air conditioning season is 1022, and the code for the average PPD data during the transition season is 1023. Then, codes 29-48 mean the implementation of the objective function through programming. Finally, codes 67-74 mean the execution of the command file operations. The code of the command file is as follows. Figure 9 As shown: Code 1-46 means the setting of optimization variables, including the optimization range, starting value and step size; Code 47-53 means the setting of optimization parameters, including the maximum number of calculation iterations; Code 55-64 means the setting of optimization algorithm. In this example, the Hooke-Jeeves algorithm is selected for optimization calculation.

[0078] Step 4: Start the Genopt optimization program

[0079] After starting the optimization program, it first simulates an office building model with an initial phase transition temperature of 20℃. A calculated value is obtained by performing mathematical operations on the simulated data using the objective function. Then, the optimization algorithm simulates the initial variable values ​​to the left and right, comparing them with previous values ​​until it finds the minimum value. The calculation process is as follows: Figure 10 As shown.

[0080] The calculation results show that the objective function value is minimized when the phase change temperature is 20.625℃. Therefore, the optimal phase change temperature for the entire year in Xi'an is 20.625℃, and the annual air conditioning energy consumption per room at this temperature is 34.56 kWh / m². 2 The average PPD value during the air-conditioning season was 10.35, and the average PPD value during the transitional season was 33.63. Compared with the reference room, the air-conditioning energy saving rate was 7.62%, the PPD reduction rate during the air-conditioning season was 0.77%, and the PPD reduction rate during the transitional season was 12.19%, demonstrating good energy saving rate and indoor thermal comfort. The optimization process for other climate zones was similar, and the optimization results are shown in Table 6.

[0081] Table 6. Room air conditioning power consumption and PPD at the optimal phase change temperature throughout the year in different climate zones.

[0082]

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining the optimal phase change temperature of a phase change self-insulating block, characterized in that, include: Create a model of the office building and its air conditioning system; Equivalent treatment of heterogeneous exterior walls for phase change self-insulating blocks; Set up the internal and external disturbances of the office building model; Set the enthalpy-temperature profile for the phase change material; Genopt optimization tool settings; The Genopt optimization program is launched, and the Energyplus simulation software is used to iteratively simulate and obtain the minimum target value. Determine the optimal phase transition temperature under the comprehensive consideration of various objective trade-offs, including: Taking into account both energy consumption and thermal comfort indices, the following objective function is established. Solving for this objective function yields the optimal value under the combined condition of all objectives: ， in, The reference room's air conditioning energy consumption is used without phase change materials. The average PPD of the air conditioning season in the reference room without phase change materials is the predicted percentage of dissatisfaction, which represents the percentage of people who are dissatisfied with the thermal environment. The average PPD of the transition season working time for the reference room that does not use phase change materials; This indicates the energy consumption of air conditioning in a room using phase change materials; This represents the average PPD (Power Delivery Time) of air conditioning units operating during the season in rooms using phase change materials. This indicates the average PPD (Power Delivery Time) of the transition season in rooms using phase change materials. This indicates the cooling energy consumption of air conditioning in a room using phase change materials; This indicates the energy consumption for air conditioning heating in rooms using phase change materials; This represents the average PPD (Power Delivery Time) of air conditioning units operating during the season in rooms using phase change materials. This indicates the average PPD (Power Delivery Time) of the transition season in rooms using phase change materials. This represents the sum of cooling and heating energy consumption of a reference room without phase change materials. This represents the average PPD (Power Distribution Count) of the air conditioning season in a reference room that does not use phase change materials. This represents the average PPD (Period Working Hours) of a reference room during the transition season when no phase change materials were used.

2. The method for determining the optimal phase change temperature of a phase change self-insulating block according to claim 1, characterized in that, Establishing an office building model further includes setting the building dimensions, the structural form of the building envelope, and thermal parameters.

3. The method for determining the optimal phase change temperature of a phase change self-insulating block according to claim 1, characterized in that, Based on the geometric structure distribution of the material, the phase change self-insulating block is divided into different material layers in the thickness direction, and the resulting heterogeneous material layers are homogenized.

4. The method for determining the optimal phase transition temperature of a phase change self-insulating block according to claim 1, characterized in that, The internal disturbance settings for the office building model further include: setting the personnel, lighting, and equipment in the office rooms separately; the external disturbance settings are set based on the meteorological data of a typical meteorological year in the city where the office building is located.

5. The method for determining the optimal phase change temperature of a phase change self-insulating block according to claim 1, characterized in that, Setting the enthalpy-temperature profile of the phase change material further includes: obtaining the enthalpy-temperature profile provided by the phase change material manufacturer; keeping the basic shape of the enthalpy-temperature profile unchanged, shifting it left and right to obtain the enthalpy-temperature profile at different phase change temperatures; using Energyplus and Genopt optimization tools, setting the phase change temperature variable and performing iterative calculations in a programmed manner to automatically transform different enthalpy-temperature profiles in Energyplus; and finally obtaining the optimal enthalpy-temperature profile through iterative calculations.

6. The method for determining the optimal phase transition temperature of a phase change self-insulating block according to claim 5, characterized in that, Given the phase transition temperature variable %wendu% range, initial value, and step size, it automatically updates and iterates different enthalpy-temperature curves.

7. The method for determining the optimal phase transition temperature of a phase change self-insulating block according to claim 1, characterized in that, After starting the Genopt optimization program, the office building model at the initial phase transition temperature is first simulated. A calculated value is obtained by performing mathematical operations on the simulation data through the objective function. Then, the initial variable values ​​are simulated to the left and right and compared with the previous values ​​until the minimum value is found.

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