Heating ventilation air conditioner generalized energy storage space-time equivalent model construction method
Through the construction method of generalized energy storage space-time equivalent model of HVAC based on AlphaFold, the problem of difficult modeling of multidimensional complexity and dynamic response characteristics in the prior art is solved, and high-precision spatial and temporal parameter identification is achieved, which improves the flexibility and energy-saving performance of HVAC system.
Patent Information
- Application Number
- CN202411973140.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-30
- Publication Date
- 2025-04-25
AI Technical Summary
When building a generalized energy storage space-time equivalent model for HVAC, existing methods have insufficient multidimensional complexity, difficulty in dealing with nonlinearity and coupling, insufficient identification accuracy, insufficient dynamic response characteristics, insufficient long-term series modeling capabilities, and lack of modeling capabilities for complex time correlations.
The generalized energy storage space-time equivalent model construction method of HVAC based on AlphaFold is adopted. By collecting HVAC information, a spatial parameter model and a time parameter model are constructed, and the samples are trained to identify virtual energy storage capacity, equivalent charging and discharging power conversion coefficient, equivalent power storage conversion coefficient, and air conditioner turn-on and off time.
It improves the accuracy of spatial parameter identification, accurately captures dynamic response characteristics, improves the accuracy of model identification, enhances the system's ability to adapt to external disturbances, supports optimization and regulation of HVAC, and reduces energy consumption and carbon emissions.
Smart Images
Figure CN119885881A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of power system regulation and control, and in particular relates to a method for constructing a generalized energy storage spatiotemporal equivalent model for heating, ventilation and air conditioning. Background Art
[0002] Constructing a spatiotemporal equivalent model of HVAC generalized energy storage is an important technical innovation to explore the flexibility of HVAC systems and optimize building energy consumption management. The model accurately quantifies the energy storage capacity and dynamic characteristics of HVAC systems, efficiently matches them with grid demand and energy supply, and comprehensively improves the operating efficiency of the energy system. In the power system, the HVAC generalized energy storage model can achieve balanced regulation of grid loads by shaving peaks and filling valleys and participating in auxiliary services, alleviate the impact of new energy volatility on the grid, and promote the stable operation of the power system. At the same time, the model supports precise power demand side management, dynamically adjusts building loads by optimizing the spatiotemporal control strategy of HVAC, and enhances the system's response to load fluctuations. In terms of energy utilization, the HVAC energy storage model can optimize the path of thermal energy storage and consumption, significantly improve building operation efficiency, reduce ineffective energy consumption and equipment loss, and reduce operating costs. In addition, by guiding the HVAC system to give priority to the use of clean energy, it can effectively improve the new energy absorption capacity, reduce fossil energy dependence, reduce carbon emissions, and provide support for achieving the "dual carbon" goal. The model is also of great significance in the construction of smart grids and energy Internet. It promotes the deep coupling of power and thermal systems, promotes the synergy and complementarity of multiple energies, and provides technical support for the optimal scheduling of distributed energy systems. The HVAC generalized energy storage model is an important foundation for achieving building energy conservation, smart grids and low-carbon energy systems, and provides a strong technical guarantee for green and sustainable development.
[0003] However, the existing methods have the following shortcomings: 1) Insufficient multidimensional complexity. The spatial distribution characteristics of HVAC systems, such as equipment layout, building thermal inertia, and complex energy exchange between regions, make it difficult for existing methods to simultaneously consider multidimensional spatial factors; lack of accurate modeling of the interaction between equipment and environment in the spatial dimension, and unable to reflect the true situation of dynamic distribution of thermal energy. 2) Difficulty in handling nonlinearity and coupling. The spatial thermal dynamics of HVAC systems show highly nonlinear and parameter coupling characteristics, and traditional identification methods have limited ability to model these complexities. 3) Insufficient identification accuracy. Existing spatial parameter identification methods are mostly based on static models, which make it difficult to capture the dynamic interaction relationship in regional heat flow changes, resulting in large deviations in identification results. 4) Insufficient dynamic response characteristics. The time parameters of HVAC systems, such as temperature response time and thermal delay effect, show significant dynamics. Traditional methods fail to fully capture these time series changes; it is difficult to model the external environment, such as weather changes and nonlinear effects of usage patterns on time parameters. 5) Insufficient ability to model long-term series. Time parameter identification requires processing long-term operating data, but existing methods are prone to data loss or low computational efficiency when modeling long-term series characteristics. 6) Lack of modeling capabilities for complex time correlations. The operating behavior of HVAC is subject to multiple influences of historical states and external disturbances. Existing methods are difficult to effectively analyze the above complex correlations. Therefore, it is necessary to develop a new method for constructing a generalized spatiotemporal equivalent model of HVAC energy storage to solve existing problems. Summary of the invention
[0004] The purpose of the present invention is to provide a method for constructing a spatiotemporal equivalent model of generalized energy storage for HVAC to solve the problem of insufficient precision in spatial parameter identification.
[0005] To achieve the above object, the present invention provides the following technical solution: a method for constructing a generalized energy storage spatiotemporal equivalent model of HVAC, comprising:
[0006] Collect HVAC information;
[0007] Construct a spatial parameter model of the HVAC generalized energy storage equivalent model, train samples of HVAC operation information, and identify the spatial parameters of the HVAC generalized energy storage equivalent model;
[0008] Construct a time parameter model of HVAC generalized energy storage equivalent model for identifying the air conditioning on-time and off-time in the HVAC indoor temperature dynamic model;
[0009] Among them, the time parameter model of the HVAC generalized energy storage equivalent model includes a HVAC indoor temperature dynamic model that is used to calculate the indoor temperature change according to the heat load, air conditioning power and room heat capacity, control the opening and closing time of the air conditioner, and control the indoor temperature within the set range.
[0010] Preferably, the formula for collecting HVAC information is as follows:
[0011] X C =[T room ,T set ,T out ,Q load ,P HVAC ,RH,C room ,γ store ,α on ,β dis ]Formula (1)
[0012] Where: X C is the collected HVAC information, T room is the current indoor temperature, T set To set the target room temperature, T out is the outdoor temperature, Q load is the indoor heat load, P HVAC is the operating power of the HVAC system, RH is the indoor relative humidity, C room is the indoor heat capacity, γ store is the cold / heat storage efficiency, α on is the device opening rate, β dis is the device discharge efficiency.
[0013] Preferably, the HVAC generalized energy storage equivalent model space parameter model includes: a virtual energy storage capacity identification model, an equivalent charging power conversion coefficient identification model, an equivalent discharge power conversion coefficient identification model and an equivalent storage capacity conversion coefficient identification model.
[0014] Preferably, the virtual energy storage capacity identification model includes:
[0015] E eq =C room ·(T max -T min )Formula (2)
[0016] T max =T set +ΔT allow Formula (3)
[0017] T min =T set -ΔT allow Formula (4)
[0018] The virtual energy storage capacity is calculated by the room temperature fluctuation range and the room heat capacity. The maximum and minimum indoor temperature are calculated according to formula (3) and formula (4) respectively. Formula (2) is the virtual energy storage capacity identification model; where: E eq is the virtual energy storage capacity, C roomis the indoor heat capacity, T max 、T min are the maximum and minimum indoor temperatures, respectively, T set To set the target room temperature, ΔT allow is the permissible room temperature deviation.
[0019] Preferably, the equivalent charging power conversion coefficient identification model includes:
[0020]
[0021] η ch =α on ·φ(T room ,T set ) Formula (6)
[0022]
[0023] Formula (5), Formula (6) and Formula (7) are equivalent charging power conversion coefficient identification models. The equivalent charging power conversion coefficient represents the proportion of actual input power based on the device opening rate and operating status. is the equivalent charging power, is the nominal input power, η ch is the equivalent charging power conversion coefficient, α on is the device opening rate, φ(T room ,T set ) is the influence function of the current temperature difference on efficiency, T room is the current indoor temperature.
[0024] Preferably, the equivalent discharge power conversion coefficient identification model includes:
[0025]
[0026] η dis =β dis ·φ(T room ,T set )Formula (9)
[0027] Formula (8) and Formula (9) are equivalent discharge power conversion coefficient identification models based on equipment operating efficiency and temperature difference state; the equivalent discharge power conversion coefficient reflects the actual discharge efficiency; where, is the equivalent discharge power, is the nominal discharge power, η dis is the equivalent discharge power conversion factor, β dis is the device discharge efficiency.
[0028] Preferably, the equivalent storage capacity conversion coefficient identification model includes:
[0029] E eff =η e ·E eq Formula (10)
[0030] η e =γ store ·ψ(T room ) Formula (11)
[0031]
[0032] Formulas (10)-(12) are the identification models of equivalent storage capacity conversion coefficients; where γ store is the cold / heat storage efficiency, η e is the equivalent storage capacity conversion factor, ψ(T room ) is the efficiency change function when the indoor temperature deviates from the set value; the equivalent storage capacity conversion coefficient takes into account the cold / heat storage efficiency and temperature state of the equipment, E eff is the equivalent storage capacity conversion factor.
[0033] Preferably, the training sample of HVAC operation information and identifying the parameters of the HVAC generalized energy storage equivalent model space include:
[0034] For the collected HVAC samples X C Conduct training to identify the virtual energy storage capacity, equivalent charging power conversion factor, equivalent discharge power conversion factor, and equivalent storage capacity conversion factor, as shown in formula (14);
[0035]
[0036] Where: To identify the spatial parameters of the HVAC generalized energy storage equivalent model, It is a spatial parameter identification model of HVAC generalized energy storage equivalent model based on AlphaFold algorithm. For the identified virtual energy storage capacity, is the equivalent charging power conversion factor identified, is the equivalent discharge power conversion factor identified, is the conversion factor of the identified equivalent storage capacity.
[0037] Preferably, the construction of the HVAC indoor temperature dynamic model includes: as shown in formulas (15) and (16), the indoor temperature change is determined by the heat load Q load (t), air conditioning power P HVAC (t), and the room heat capacity C room Decide;
[0038] Formula (17) is the room temperature boundary condition. The time when the air conditioner is turned on and off must keep the indoor temperature within the set range.
[0039] Formula (18) is the air conditioning start time parameter. The air conditioning starts when the indoor temperature reaches the upper limit T max When turned on;
[0040] Formula (19) is the air conditioner off time parameter. The air conditioner is turned off when the indoor temperature reaches the lower limit T min Close when
[0041]
[0042]
[0043] T min ≤T room (t)≤T max Formula (17)
[0044] t on =min{t:T room (t)≥T max}Formula (18)
[0045] t off =min{t:T room (t)≤T min}Formula (19)
[0046] Where: T room is the current indoor temperature, C room is the indoor heat capacity, Q load (t) is the indoor heat load, is the identified equivalent discharge power conversion factor, P HVAC (t) is the operating power of the HVAC system, T max , T min are the maximum and minimum indoor temperature respectively, t on is the air conditioner on time, t off is the air conditioner off time, and d represents the partial derivative of time t.
[0047] Preferably, the HVAC generalized energy storage equivalent model time parameter model includes: C Conduct training to identify the HVAC on and off time, as shown in formula (21);
[0048]
[0049] Where: To identify the HVAC time parameters, It is a time parameter identification model of HVAC generalized energy storage equivalent model based on AlphaFold algorithm. To identify the HVAC opening time, The identified HVAC off time.
[0050] The technical effects and advantages of the present invention are as follows: The method for constructing a spatiotemporal equivalent model of a generalized energy storage for HVAC can model the dynamic distribution of multi-dimensional thermal energy based on the AlphaFold method, and improve the accuracy of spatial parameter identification; through bidirectional time series modeling, it can accurately capture dynamic response characteristics, provide more reliable results for time parameter identification, and improve model identification accuracy; at the same time, it supports HVAC optimization and regulation, and the spatial parameter identification results provide a basis for thermal coupling regulation between building areas; the time parameter identification results provide support for optimizing the dynamic response strategy of the HVAC system; enhance the flexibility of system operation, and through accurate parameter identification, improve the adaptability of the HVAC system to external disturbances, and enhance the flexibility and reliability of system regulation; promote intelligent and energy-saving development, and provide a new tool for intelligent modeling of generalized energy storage for HVAC; accurately identified parameters can support more efficient operation strategies and reduce energy consumption and carbon emissions. BRIEF DESCRIPTION OF THE DRAWINGS
[0051] Figure 1 It is a schematic diagram of an embodiment of the present invention;
[0052] Figure 2 It is a schematic diagram of the process of the present invention;. DETAILED DESCRIPTION
[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0054] The present invention provides Figure 1 , Figure 2 A method for constructing a generalized energy storage spatiotemporal equivalent model for HVAC is shown in , wherein the generalized energy storage spatiotemporal equivalent model includes a generalized energy storage equivalent model space parameter model and a generalized energy storage equivalent model time parameter model;
[0055] Among them, the generalized energy storage equivalent model space parameter model includes the virtual energy storage capacity identification model, the equivalent charging power conversion coefficient identification model, the equivalent discharge power conversion coefficient identification model, and the equivalent storage capacity conversion coefficient identification model;
[0056] The time parameter model of the generalized energy storage equivalent model mainly identifies the air conditioning on-time and off-time in the HVAC indoor temperature dynamic model;
[0057] The following steps are involved:
[0058] Step (1): Propose a HVAC information collection technology to collect HVAC operation related information, including current indoor temperature, set target room temperature, HVAC system operating power, indoor relative humidity, indoor heat capacity, cold / heat storage efficiency, equipment opening rate, and equipment discharge efficiency;
[0059] Step (2): Propose a method for identifying the spatial parameters of a generalized energy storage equivalent model of HVAC based on AlphaFold. First, a spatial parameter model of a generalized energy storage equivalent model of HVAC is constructed, including a virtual energy storage capacity identification model, an equivalent charging power conversion coefficient identification model, an equivalent discharge power conversion coefficient identification model, and an equivalent storage capacity conversion coefficient identification model. Since the above-mentioned equivalent parameters will change in actual operation, parameter identification is required. The present invention proposes a HVAC generalized energy storage equivalent spatial parameter identification model based on the AlphaFold algorithm. Based on the AlphaFold algorithm, the HVAC samples collected in step (1) are trained to identify the spatial parameters of the HVAC generalized energy storage equivalent model, including virtual energy storage capacity, equivalent charging power conversion coefficient, equivalent discharge power conversion coefficient, and equivalent storage capacity conversion coefficient.
[0060] Step (3): Propose a method for identifying the time parameters of a generalized energy storage equivalent model of HVAC based on AlphaFold. First, a time parameter model of a generalized energy storage equivalent model of HVAC is constructed, mainly to identify the start-up time and shut-down time parameters of the air conditioner. Construct a dynamic model of indoor temperature of HVAC, mainly to calculate the indoor temperature change based on the heat load, air conditioning power, and room heat capacity of the indoor temperature change. Within the room temperature boundary conditions, the indoor temperature needs to be controlled within a certain range by controlling the start and shut-down time of the air conditioner. Since the above-mentioned equivalent time parameters will change in actual operation, it is necessary to identify the time parameters. The present invention proposes a time parameter identification model of a generalized energy storage equivalent model of HVAC based on the AlphaFold algorithm. Based on the AlphaFold algorithm, the time parameters of the generalized energy storage equivalent model of HVAC are identified, including the start-up time and shut-down time of the HVAC, to provide support for the regulation of the HVAC.
[0061] In step (1), the collected HVAC information is as shown in formula (1), which mainly includes the current indoor temperature, the set target room temperature, the HVAC system operating power, the indoor relative humidity, the indoor heat capacity, the cold / heat storage efficiency, the equipment opening rate, and the equipment discharge efficiency;
[0062] X C =[T room ,T set ,T out ,Q load ,P HVAC ,RH,C room ,γ store ,α on ,β dis ]Formula (1)
[0063] Where: X C is the collected HVAC information, T room is the current indoor temperature, T set To set the target room temperature, T out is the outdoor temperature, Q load is the indoor heat load, P HVAC is the operating power of the HVAC system, RH is the indoor relative humidity, C room is the indoor heat capacity, γ store is the cold / heat storage efficiency, α on is the device opening rate, β dis is the device discharge efficiency.
[0064] In step (2), the proposed AlphaFold-based HVAC generalized energy storage equivalent model spatial parameter identification method is shown in formula (2)-formula (14).
[0065] Firstly, a spatial parameter model of the HVAC generalized energy storage equivalent model is constructed, including the virtual energy storage capacity identification model, the equivalent charging power conversion coefficient identification model, the equivalent discharge power conversion coefficient identification model and the equivalent storage capacity conversion coefficient identification model.
[0066] Formula (2) is the virtual energy storage capacity identification model. The virtual energy storage capacity is calculated by the room temperature fluctuation range and the room heat capacity. The maximum and minimum values of the indoor temperature are calculated according to formula (3) and formula (4) respectively.
[0067] Formulas (5)-(7) are the identification models of equivalent charging power conversion coefficient. The equivalent charging power conversion coefficient represents the proportion of actual input power and depends on the device startup rate and operating status;
[0068] Formulas (8)-(9) are the identification models of equivalent discharge power conversion coefficient. The equivalent discharge power conversion coefficient reflects the actual discharge efficiency and depends on the equipment operation efficiency and temperature difference state;
[0069] Formulas (10)-(12) are the identification models of equivalent storage capacity conversion coefficient. The equivalent storage capacity conversion coefficient takes into account the cold / hot storage efficiency and temperature state of the equipment;
[0070] Eeq =C room ·(T max -T min ) Formula (2)
[0071] T max =T set +ΔT allow Formula (3)
[0072] T min =T set -ΔT allow Formula (4)
[0073]
[0074] η ch =α on ·φ(T room ,T set ) Formula (6)
[0075]
[0076] η dis =β dis ·φ(T room ,T set ) Formula (9)
[0077] E eff =η e ·E eq Formula (10)
[0078] η e =γ store ·ψ(T room ) Formula (11)
[0079]
[0080] Where: E eq is the virtual energy storage capacity, C room is the indoor heat capacity, T max 、T min are the maximum and minimum indoor temperature, T set To set the target room temperature, ΔT allow is the permissible room temperature deviation. is the equivalent charging power, is the nominal input power, η ch is the equivalent charging power conversion factor. on is the device opening rate, φ(T room ,T set ) is the influence function of the current temperature difference on efficiency, T room is the current indoor temperature. is the equivalent discharge power, is the nominal discharge power, η dis is the equivalent discharge power conversion factor, β dis is the device discharge efficiency. store is the cold / heat storage efficiency, η e is the equivalent storage capacity conversion factor, ψ(T room ) is the efficiency change function when the indoor temperature deviates from the set value, E eff is the equivalent storage capacity conversion factor.
[0081] Since the above equivalent parameters will change in actual operation, it is necessary to identify the parameters. The present invention identifies the spatial parameters of the HVAC generalized energy storage equivalent model based on the AlphaFold algorithm. Formula (13) is a spatial parameter identification model of the HVAC generalized energy storage equivalent model based on the AlphaFold algorithm. The present invention uses the AlphaFold algorithm to identify the spatial parameters of the HVAC generalized energy storage equivalent model. C Through training, the virtual energy storage capacity, equivalent charging power conversion factor, equivalent discharge power conversion factor, and equivalent storage capacity conversion factor are identified, as shown in formula (14).
[0082]
[0083] Where: To identify the spatial parameters of the HVAC generalized energy storage equivalent model, It is a spatial parameter identification model of HVAC generalized energy storage equivalent model based on AlphaFold algorithm. For the identified virtual energy storage capacity, is the equivalent charging power conversion factor identified, is the equivalent discharge power conversion factor identified, is the conversion factor of the identified equivalent storage capacity.
[0084] For step (3), the proposed AlphaFold-based HVAC generalized energy storage equivalent model time parameter identification method is shown in formulas (15) to (21).
[0085] Firstly, a time parameter model of the HVAC generalized energy storage equivalent model is constructed, mainly to identify the start-up time and shut-down time parameters of the air conditioner.
[0086] Construct a dynamic model of indoor temperature of HVAC, as shown in formula (15) and formula (16), the indoor temperature change is determined by the heat load Q load (t), air conditioning power P HVAC (t), and the room heat capacity C room Decide.
[0087] Formula (17) is the room temperature boundary condition. The time when the air conditioner is turned on and off must keep the indoor temperature within a certain range.
[0088] Formula (18) is the air conditioning start time parameter. The air conditioning starts when the indoor temperature reaches the upper limit T max When turned on.
[0089] Formula (19) is the air conditioner off time parameter. The air conditioner is turned off when the indoor temperature reaches the lower limit T min Close when.
[0090]
[0091] T min ≤T room (t)≤T max Formula (17)
[0092] t on =min{t:T room (t)≥T max}Formula (18)
[0093] t off =min{t:T room (t)≤T min}Formula (19)
[0094] Where: T room is the current indoor temperature, C room is the indoor heat capacity, Q load (t) is the indoor heat load, is the identified equivalent discharge power conversion factor, P HVAC (t) is the operating power of the HVAC system, T max , T min are the maximum and minimum indoor temperatures, t on is the air conditioner on time, t off is the air conditioner off time, and d represents the partial derivative of time t.
[0095] Since the above-mentioned equivalent time parameters will change in actual operation, it is necessary to identify the time parameters. Based on the AlphaFold algorithm, the present invention identifies the time parameters of the HVAC generalized energy storage equivalent model. Formula (20) is a HVAC generalized energy storage equivalent model time parameter identification model based on the AlphaFold algorithm. Based on the AlphaFold algorithm, the present invention identifies the HVAC sample X C Train to identify the HVAC on and off time, as shown in formula (21).
[0096]
[0097] Where: To identify the HVAC time parameters, It is a time parameter identification model of HVAC generalized energy storage equivalent model based on AlphaFold algorithm. To identify the HVAC opening time, The identified HVAC off time.
[0098] After the above steps, the parameters of the HVAC generalized energy storage equivalent model can be effectively identified, and the control efficiency of HVAC can be improved, which is of great significance to improving the benefits of virtual power plants and promoting the dual carbon goals.
[0099] This method for constructing a spatiotemporal equivalent model of generalized energy storage for HVAC can model the dynamic distribution of multi-dimensional thermal energy based on the AlphaFold method and improve the accuracy of spatial parameter identification. It can accurately capture dynamic response characteristics through bidirectional time series modeling, provide more reliable results for time parameter identification, and improve model identification accuracy. It also supports HVAC optimization and regulation, and the spatial parameter identification results provide a basis for thermal coupling regulation between building areas. The time parameter identification results provide support for optimizing the dynamic response strategy of the HVAC system. It enhances the flexibility of system operation, and through accurate parameter identification, improves the adaptability of the HVAC system to external disturbances, and enhances the flexibility and reliability of system regulation. It promotes the development of intelligence and energy conservation, and provides a new tool for intelligent modeling of generalized energy storage for HVAC. Accurately identified parameters can support more efficient operation strategies and reduce energy consumption and carbon emissions.
[0100] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.
Claims
1. A method for constructing a spatiotemporal equivalent model of generalized energy storage for HVAC, characterized by: include: Collect HVAC information; Construct a spatial parameter model of the HVAC generalized energy storage equivalent model, train samples of HVAC operation information, and identify the spatial parameters of the HVAC generalized energy storage equivalent model; Construct a time parameter model of HVAC generalized energy storage equivalent model for identifying the air conditioning on-time and off-time in the HVAC indoor temperature dynamic model; Among them, the time parameter model of the HVAC generalized energy storage equivalent model includes: a HVAC indoor temperature dynamic model used to calculate indoor temperature changes based on heat load, air conditioning power and room heat capacity, control the opening and closing time of the air conditioner, and control the indoor temperature within a set range.
2. A method for constructing a spatiotemporal equivalent model of HVAC generalized energy storage according to claim 1, characterized in that: The formula for collecting HVAC information is as follows: X C = [T room , T set , T out , Q load , P HVAC , RH, C room , γ store , α on , β dis Formula (1) Where: X C is the collected HVAC information, T room is the current indoor temperature, T set To set the target room temperature, T out is the outdoor temperature, Q load is the indoor heat load, P HVAC is the operating power of the HVAC system, RH is the indoor relative humidity, C room is the indoor heat capacity, γ store is the cold / heat storage efficiency, α on is the device opening rate, β dis is the device discharge efficiency.
3. A method for constructing a generalized energy storage spatiotemporal equivalent model for HVAC according to claim 1, characterized in that: The HVAC generalized energy storage equivalent model spatial parameter model includes: a virtual energy storage capacity identification model, an equivalent charging power conversion coefficient identification model, an equivalent discharge power conversion coefficient identification model and an equivalent storage capacity conversion coefficient identification model.
4. A method for constructing a spatiotemporal equivalent model of HVAC generalized energy storage according to claim 3, characterized in that: The virtual energy storage capacity identification model includes: E eq =C room ·(T max -T min ) Formula (2) T max =T set +ΔT allow Formula (3) T min =T set -ΔT allow Formula (4) The virtual energy storage capacity is calculated by the room temperature fluctuation range and the room heat capacity. The maximum and minimum indoor temperature are calculated according to formula (3) and formula (4) respectively. Formula (2) is the virtual energy storage capacity identification model; where: E eq is the virtual energy storage capacity, C room is the indoor heat capacity, T max , T min are the maximum and minimum indoor temperatures, respectively, T set To set the target room temperature, ΔT allow is the permissible room temperature deviation.
5. A method for constructing a generalized energy storage spatiotemporal equivalent model for HVAC according to claim 3, characterized in that: The equivalent charging power conversion coefficient identification model includes: η ch = α on · φ(T room , T set ) Equation (6) Formula (5), Formula (6) and Formula (7) are equivalent charging power conversion coefficient identification models. The equivalent charging power conversion coefficient represents the proportion of actual input power based on the device opening rate and operating status. is the equivalent charging power, is the nominal input power, η ch is the equivalent charging power conversion coefficient, α on is the device opening rate, φ(T room ,T set ) is the influence function of the current temperature difference on efficiency, T room is the current indoor temperature.
6. A method for constructing a spatiotemporal equivalent model of HVAC generalized energy storage according to claim 3, characterized in that: The equivalent discharge power conversion coefficient identification model includes: η dis = β dis · φ(T room , T set ) Equation (9) Formula (8) and Formula (9) are equivalent discharge power conversion coefficient identification models based on equipment operating efficiency and temperature difference state; the equivalent discharge power conversion coefficient reflects the actual discharge efficiency; where, is the equivalent discharge power, is the nominal discharge power, η dis is the equivalent discharge power conversion factor, β dis is the device discharge efficiency.
7. A method for constructing a spatiotemporal equivalent model of HVAC generalized energy storage according to claim 3, characterized in that: The equivalent storage capacity conversion coefficient identification model includes: E eff = η e ·E eq Equation (10) η e = γ store · ψ(T room ) Equation (11) Formulas (10)-(12) are the identification models of equivalent storage capacity conversion coefficients; where γ store is the cold / heat storage efficiency, η e is the equivalent storage capacity conversion factor, ψ(T room ) is the efficiency change function when the indoor temperature deviates from the set value; the equivalent storage capacity conversion coefficient takes into account the cold / heat storage efficiency and temperature state of the equipment, E eff is the equivalent storage capacity conversion factor.
8. A method for constructing a spatiotemporal equivalent model of a generalized energy storage system for heating, ventilation and air conditioning according to any one of claims 1 to 7, characterized in that: The training sample of HVAC operation information and the identification of parameters of the HVAC generalized energy storage equivalent model space include: For the collected HVAC samples X C Conduct training to identify the virtual energy storage capacity, equivalent charging power conversion factor, equivalent discharge power conversion factor, and equivalent storage capacity conversion factor, as shown in formula (14); Where: To identify the spatial parameters of the HVAC generalized energy storage equivalent model, It is a spatial parameter identification model of HVAC generalized energy storage equivalent model based on AlphaFold algorithm. For the identified virtual energy storage capacity, is the equivalent charging power conversion factor identified, is the equivalent discharge power conversion factor identified, is the conversion factor of the identified equivalent storage capacity.
9. A method for constructing a spatiotemporal equivalent model of a generalized energy storage system for heating, ventilation and air conditioning according to any one of claims 1 to 7, characterized in that: The construction of the HVAC indoor temperature dynamic model includes: As shown in formulas (15) and (16), the indoor temperature change is determined by the heat load Q load (t), air conditioning power P HVAC (t), and the room heat capacity C room Decide; Formula (17) is the room temperature boundary condition. The time when the air conditioner is turned on and off must keep the indoor temperature within the set range. Formula (18) is the air conditioning start time parameter. The air conditioning starts when the indoor temperature reaches the upper limit T max When turned on; Formula (19) is the air conditioner off time parameter. The air conditioner is turned off when the indoor temperature reaches the lower limit T min Close when T min ≤T room (t)≤T max Formula (17) t on =min{t:T room (t)≥T max } Formula (18) t off =min{t:T room (t)≤T min } Formula (19) Where: T room is the current indoor temperature, C room is the indoor heat capacity, Q load (t) is the indoor heat load, is the identified equivalent discharge power conversion factor, P HVAC (t) is the operating power of the HVAC system, T max , T min are the maximum and minimum indoor temperature respectively, t on is the air conditioner on time, t off is the air conditioner off time, and d represents the partial derivative of time t.
10. A method for constructing a spatiotemporal equivalent model of a generalized energy storage system for heating, ventilation and air conditioning according to any one of claims 1 to 7, characterized in that: The HVAC generalized energy storage equivalent model time parameter model includes: C Conduct training to identify the HVAC on and off time, as shown in formula (21); Where: To identify the HVAC time parameters, It is a time parameter identification model of HVAC generalized energy storage equivalent model based on AlphaFold algorithm. To identify the HVAC opening time, The identified HVAC off time.