Building ice storage system multi-time scale scheduling method based on generalized energy storage model

Abstract

The invention provides a building ice storage system multi-time scale scheduling method based on a generalized energy storage model. The invention discloses an ice storage model based on generalized energy storage. A detailed model for refrigeration of an ice storage unit and double-working-condition operation characteristics of the ice storage unit are comprehensively considered. Firstly, a detailed refrigeration model of an ice storage refrigeration unit is analyzed, and a dynamic ice melting and ice making optimization scheduling method considering time-of-use electricity price is provided. Secondly, aiming at the problem that the ice storage amount is difficult to schedule visually, the generalized energy storage model is introduced to accurately represent the cold storage amount, and the multi-time-scale scheduling method for the ice storage system based on the generalized energy storage model is provided. According to the method, the temperature of the cooling space can be controlled according to the environment temperature and the ice storage level, economic operation of a refrigeration system can be ensured through an optimization strategy, power grid load transfer is effectively assisted, and the purpose of peak load shifting is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of ice storage and cold energy storage scheduling, and particularly provides a multi-time scale scheduling method for a building ice storage and cold storage system based on a generalized energy storage model. Background Technique

[0002] In recent years, the continuous growth of air-conditioning refrigeration demand caused by global warming and the improvement of living standards has led to a sharp increase in refrigeration energy consumption, resulting in a greater gap between peak and valley loads of the power grid in summer. Energy storage devices have become the focus of attention because they can decouple load and supply in time and space. As the core technology of modern cold storage, the ice storage and cold energy storage model plays a crucial role in the energy storage link. However, although traditional ice energy storage has been considered, its storage form is still difficult to intuitively perform reasonable scheduling driven by demand.

[0003] Based on the above background, the present invention proposes a multi-time scale scheduling method for a building ice storage and cold storage system based on a generalized energy storage model, which mainly includes the following two aspects: one is to consider a detailed ice storage and cold refrigeration unit model to optimize the scheduling of the refrigerant flow rate and the production and storage of building cooling capacity; the other is to define a generalized energy storage model of ice storage and cold on the basis of the traditional ice storage and cold model to realize flexible scheduling of ice storage and cold supply according to the cooling load demand and time-of-use electricity price. Summary of the Invention

[0004] Object of the Invention. The present invention aims to overcome the deficiencies of the prior art and provides a multi-time scale scheduling method for a building ice storage and cold storage system based on a generalized energy storage model. This method considers the coordinated scheduling of the power system, the cooling system and the ice storage and cold refrigeration device, and studies the influence of environmental temperature uncertainty on the internal temperature of the refrigeration system. The present invention can not only define the ice storage and cold energy storage through the generalized energy storage model to solve the problem that the stored cold capacity cannot intuitively meet the scheduling requirements, but also meet the cooling load demand by scheduling ice melting and cold release and unit cold release, ensure that the temperature control requirements are met, meet the demand of peak shaving and valley filling of electric energy at the same time, reduce the operation cost, and improve the operation reliability of the system.

[0005] Technical Solution. To solve the above technical problems, the present invention proposes a multi-time scale scheduling method for a building ice storage and cold storage system based on a generalized energy storage model, which includes the following steps:

[0006] Step 1: Obtain the operating parameters of the ice storage and cold refrigeration unit, including the heat exchange efficiency of the evaporator, the work efficiency of the compressor, the heat exchange efficiency of the condenser and the flow rate of the throttle valve;

[0007] Step 2: Obtain the cooling load, the ice storage capacity of the ice storage and cold, the initial temperature of the refrigerant and the enthalpy value information in different states;

[0008] Step 3: Based on the operating parameters of the ice storage refrigeration unit, the cooling load, the initial temperature of the refrigerant, and the enthalpy values in different states, combined with the operating constraints of the refrigeration unit, the operating constraints of ice storage, the electrical energy balance, and the cooling capacity balance, construct the overall operating model of the ice storage building;

[0009] Step 4: Based on the model in Step 3, define the generalized energy storage model, and take the minimization of the expected value of the building operating cost as the objective function, and use the BARON solver to solve the optimal solution to optimize the proportion of ice melting of the ice storage refrigeration unit and the refrigeration of the unit.

[0010] Further, in Step 3, the relevant operating constraints of the overall operating scheduling model of the ice storage building are as follows:

[0011] 1) Refrigeration unit operating constraints

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[0030] In the formula, T represents the number of time sections, the subscript t represents the scheduling period, and the subscript h represents the enthalpy values of the refrigeration working medium at different times. They respectively represent the enthalpy values of the refrigeration working medium corresponding to different temperatures. corresponds to the temperature of 45 °C. corresponds to the temperature range from 60 °C to 80 °C. corresponds to the temperature range from -20 °C to -10 °C; the superscripts ev, com, con, and th respectively represent the evaporator, compressor, condenser, and throttle valve devices. They respectively represent the energies of the refrigeration working medium input into and output from the evaporator at time t. They respectively represent the heat exchange amount with the outside world and the flow rate of the refrigeration working medium at time t. They respectively represent the energies of the refrigeration working medium input into and output from the compressor at time t, Q ev_inmin 、Q ev_inmax They respectively represent the upper and lower limits of the energy of the refrigeration working medium input into the evaporator. W commax They respectively represent the electric energy consumed by the compressor for work and the upper limit of the work done by the compressor at time t, w com represents the electric energy required to compress a unit of refrigeration working medium. represents the energy flowing into and out of the condenser at time t. They respectively represent the energies flowing into and out of the throttle valve at time t. They respectively represent the energy losses of the refrigeration working medium after flowing through the compressor, condenser, and throttle valve at time t, Q commax 、Q conmax 、Q thmax They respectively represent the upper limit values of the energies flowing into the compressor, condenser, and throttle valve per unit time.

[0031] 2) Ice storage operation constraints

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[0042] In the formula, the subscripts t1 and t2 represent the ice storage time and the ice melting time respectively, represent the heat exchange amount during ice making and the heat exchange amount during ice melting respectively, represent the cooling capacity and the ice storage amount at time t1 respectively, represents the ice storage mass of the ice storage tank at time t, represents the ice making and ice melting mass at time t, and Δt represents the minimum time section, which is taken as 1 hour in the formula, represents the electric power consumed for refrigeration at time t, L f_ice represents the latent heat value of ice, represents the ice storage energy in time period t, represent the ice melting heat release and the unit heat release energy at time t2 respectively, represent the ice melting heat release amount and its minimum value in time period t respectively, Q zice_min 、Q zice_max represent the upper and lower limits of ice making and cold storage respectively, represents the ice melting mass in time period t, represents the energy efficiency ratio of the refrigeration unit in time period t;

[0043] 3) Power and cooling capacity balance constraints

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[0047] In the formula, represents the electric energy purchased at time t, represents the cooling load at time t, P cemin 、P cemax represent the upper and lower limits of the power purchase amount respectively.

[0048] Furthermore, in step 4, first, based on the following assumptions:

[0049] Assume that the heat conduction property of the ice block does not change with time, that is, the thermal conductivity k of the ice is a constant;

[0050] Assume that the initial temperature of the ice block is 0 °C, and the temperature at the start of melting is the freezing point;

[0051] Assume that the external environmental temperature T ev is known;

[0052] Assume that the heat convection coefficient h of the environment and the surface area A of the ice remain unchanged during the natural melting process;

[0053] Assume that the ice volume remains constant during natural melting, with the ice layer thickness d unchanged;

[0054] The generalized energy storage model is constrained as follows:

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[0069] H dl = h * v 0.5 (A-46)

[0070] R = d / (k ice * A ice ) (A-47)

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[0074] In the formula, represents the natural melting loss power of ice at time t, represents the energy storage power of the ice storage tank under generalized energy storage, respectively represent the ice making and melting electric power at time t, SOCt Represents the percentage of ice storage, α ice Represents the actual utilization percentage of the ice storage tank, ρ ice Represents the density of ice, V represents the volume of the ice storage tank, Represents the energy storage or release efficiency at time t, ΔT t Represents the temperature change at time t, Represents the heat transferred by heat convection, heat conduction, and heat radiation at time t respectively, M air 、C air Represents the air quality and specific heat capacity in the refrigerated space respectively, Represents the temperature of the refrigerated space at time t, Represents the cold loss at time t, R represents the thermal resistance of the wall, Represents the ambient temperature and the ice layer temperature respectively, H dl 、A ice Represents the heat convection coefficient and the heat convection contact area respectively, θ f 、δ f Represents the influence coefficient of temperature change on radiation power per unit area and the emissivity of the object surface respectively, h is the heat transfer coefficient, v is the air velocity, d is the ice layer thickness, k ice Thermal conductivity, Represents the natural ice melting mass and the corresponding heat loss at time t respectively, Represents the temperature change caused by the loss of stored energy due to natural ice melting at time t.

[0075] Furthermore, in step 4, the minimum objective function is:

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[0077] In the formula, the superscript ce represents the purchased electricity quantity, and the superscript e represents the electric energy; Represents the electric energy purchased at time t, Represents the time-of-use electricity price at time t;

[0078] Under the constraints of the refrigeration unit operation, ice storage operation, power and cooling balance, and generalized energy storage, with the minimum expected value of the overall operation cost of the building ice storage system as the objective function, the optimal solution is obtained using the BARON solver, and the ice storage building system is optimized and scheduled.

[0079] Beneficial effects. Compared with the prior art, the technical solution of the present invention has the following beneficial technical effects:

[0080] The present invention takes into account the coordination of the power system, the cooling system, and ice storage energy storage, and studies the impact of the uncertain factors of wind power fluctuations on the system. The present invention can not only control the temperature of the cooling space according to the ambient temperature and the ice storage level, but also ensure the economic operation of the refrigeration system through an optimization strategy, effectively assisting the power grid load transfer and achieving the goal of peak shaving and valley filling. Description of the Drawings

[0081] Figure 1 is the flowchart of the method of the present invention.

[0082] Figure 2 is the comparison chart of the energy consumption of the refrigeration unit under different operating conditions.

[0083] Figure 3 is the column chart of the cold load accumulation when the ice melting of the refrigeration unit is prioritized.

[0084] Figure 4 is the temperature change of the building system under the general energy storage scheduling.

[0085] Figure 5 is the natural leakage power of the general energy storage model. Detailed Embodiment

[0086] The present invention will be further clarified below in conjunction with the drawings and specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and not to limit the scope of the present invention. After reading the present invention, various equivalent modifications of the present invention by those skilled in the art fall within the scope defined by the appended claims of this application.

[0087] As Figure 1 shown, the present invention proposes a multi-time scale scheduling method for a building ice storage cooling system based on a general energy storage model. The method includes the following steps:

[0088] Step 1: Obtain the operating parameters of the ice storage refrigeration unit, including the heat exchange efficiency of the evaporator, the work efficiency of the compressor, the heat exchange efficiency of the condenser, and the flow rate of the throttle valve;

[0089] Step 2: Obtain the cold load, the ice storage capacity of the ice storage, the initial temperature of the refrigerant, and the enthalpy value information in different states;

[0090] Step 3: According to the operating parameters of the ice storage refrigeration unit, the cold load, the initial temperature of the refrigerant, and the enthalpy values in different states, combined with the operating constraints of the refrigeration unit, the operating constraints of the ice storage, the power balance and the cold quantity balance, construct the overall operating model of the ice storage building;

[0091] Step 4: Based on the model in Step 3, define a generalized energy storage model, and take the minimization of the expected value of the building operation cost as the objective function, and use the BARON solver to solve the optimal solution to optimize the proportion of ice melting and refrigeration of the ice storage chiller.

[0092] Further, in Step 3, the relevant operation constraints of the overall operation scheduling model of the ice storage building are as follows:

[0093] 1) Chiller operation constraints

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[0112] In the formula, T represents the number of time sections, the subscript t represents the scheduling period, and the subscript h represents the enthalpy value of the refrigerant at different times. respectively represent the enthalpy values of the refrigerant corresponding to different temperatures. corresponds to the temperature of 45°C. The corresponding temperature is 60°C to 80°C, The corresponding temperature is -20°C to -10°C; the superscripts ev, com, con, and th represent the evaporator, compressor, condenser, and throttle valve device respectively; They respectively represent the energy of the refrigerant flowing into and out of the evaporator at time t, They respectively represent the heat exchange amount with the outside world and the refrigerant flow rate at time t, They respectively represent the energy of the refrigerant flowing into and out of the compressor at time t, Q ev_inmin 、Q ev _inmax They respectively represent the upper and lower limits of the energy of the refrigerant flowing into the evaporator, W commax They respectively represent the electric energy consumed by the compressor doing work and the upper limit of the work done by the compressor at time t, w com It represents the electric energy required to compress a unit of refrigerant, It represents the energy flowing into and out of the condenser at time t, They respectively represent the energy flowing into and out of the throttle valve at time t, They respectively represent the energy losses of the refrigerant after flowing through the compressor, condenser, and throttle valve at time t, Q commax 、Q conmax 、Q thmax They respectively represent the upper limit values of the energy flowing into the compressor, condenser, and throttle valve per unit time;

[0113] 2) Ice storage operation constraints

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[0124] In the formula, the subscripts t1 and t2 represent the ice storage time and the ice melting time respectively, respectively represent the heat transfer amount during ice making and the heat transfer amount during ice melting respectively represent the cooling capacity and the ice storage amount at time t1 represents the ice storage mass of the ice storage tank at time t represents the ice making and ice melting mass at time t, and Δt represents the minimum time section, taking 1 hour in the formula represents the electric power consumed for refrigeration at time t, L f_ice represents the latent heat value of ice represents the ice storage energy in time period t respectively represent the ice melting heat release and the chiller heat release energy at time t2 respectively represent the ice melting heat release amount and its minimum value in time period t, Q zice_min 、Q zice_max respectively represent the upper and lower limits of ice making and cold storage represents the ice melting mass in time period t represents the energy efficiency ratio of the refrigeration unit in time period t

[0125] 3) Power and cooling capacity balance constraints

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[0129] In the formula represents the electric energy purchased at time t represents the cooling load at time t, P cemin 、P cemax respectively represent the upper and lower limits of the power purchase amount

[0130] Furthermore, in step 4, first based on the following assumptions

[0131] Assume that the heat conduction property of the ice does not change with time, that is, the thermal conductivity k of the ice is a constant

[0132] Assume that the initial temperature of the ice is 0 °C, and the temperature at the start of melting is the freezing point

[0133] Assume that the external environmental temperature T ev is known

[0134] Assume that the heat convection coefficient h of the environment and the surface area A of the ice remain unchanged during the natural melting process

[0135] Assume that the volume of the ice remains unchanged during the natural melting process and the ice layer thickness d remains unchanged

[0136] The generalized energy storage model is constrained as follows

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[0151] H dl = h * v 0.5 (A - 46)

[0152] R = d / (k ice * A ice ) (A - 47)

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[0156] In the formula, represents the natural melting loss power of ice at time t, represents the energy storage power of the ice storage tank under generalized energy storage, respectively represent the ice-making and ice-melting electric powers at time t, SOC t represents the ice storage percentage, α ice represents the actual utilization percentage of the ice storage tank, ρ ice represents the density of ice, V represents the volume of the ice storage tank, Denote the energy storage or release efficiency at time t, ΔT t Denote the temperature change at time t, Denote the heat transferred by heat convection, heat conduction and heat radiation at time t respectively, M air 、C air Denote the air quality and specific heat capacity in the refrigerated space respectively, Denote the temperature of the refrigerated space at time t, Denote the cold loss at time t, R denotes the thermal resistance of the wall, T ice Denote the ambient temperature and the ice layer temperature respectively, H dl 、A ice Denote the heat convection coefficient and the heat convection contact area respectively, θ f 、δ f Denote the influence coefficient of temperature change on radiation power per unit area and the emissivity of the object surface respectively, h is the heat transfer coefficient, v is the air flow velocity, d is the ice layer thickness, k ice Thermal conductivity, Denote the natural ice melting mass and the corresponding heat loss at time t respectively, Denote the temperature change caused by the loss of stored energy due to natural ice melting at time t.

[0157] Furthermore, in step 4, the minimum objective function is:

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[0159] In the formula, the superscript ce represents the purchased electricity quantity, and the superscript e represents the electrical energy; Denote the electrical energy purchased at time t, Denote the time-of-use electricity price at time t;

[0160] Under the constraints of the refrigeration unit operation, ice storage operation, electrical energy and cooling capacity balance, and generalized energy storage, with the minimum expected value of the overall operation cost of the building ice storage system as the objective function, the optimal solution is obtained using the BARON solver, and the building ice storage system is optimized for scheduling.

[0161] Case study

[0162] The present invention analyzes the energy efficiency optimization and power demand scheduling of a single building ice storage system. The building volume is 40900m 3, with a wall thickness of 20 cm, the system mainly relies on power supply and optimizes management through real-time scheduling of refrigeration demand, air temperature, and time-of-use electricity price, thereby improving the overall energy efficiency of the system and reducing operating costs. The installed capacity of this system is 40.9 MW, where the peak demand for refrigeration load is 2280 KWh, and the total demand of the power system depends on the day-night temperature change and electricity price fluctuation. During the simulation process, the cold load changes in different time periods and different electricity prices are considered, and different electricity price intervals are given according to the peak and valley of electricity consumption, with the electricity price ranging from 0.38 yuan / kWh to 0.6 yuan / kWh. This invention is realized through the GAMS optimization platform, uses the BARON solver to solve the NLP problem, and the optimization goal is to reduce the energy consumption of the refrigeration system and minimize the cost through reasonable scheduling. In a specific example, the system simulates the refrigeration demand in different time periods within 24 hours and schedules the energy usage strategy according to the real-time electricity price.

[0163] Based on this example, the method of this invention simulates the electricity consumption cost and power consumption of the dual-condition refrigerating machine under different scheduling operation strategies, and the results are shown in Table 1 and Figure 2 , showing the optimized scheduling results of the cooling capacity supply and consumption under the ice melting priority refrigeration strategy, and the results are shown in Figure 3 , and gives the temperature value of scheduling ice melting for cooling after introducing the generalized energy storage model, and the results are shown in Figure 4 , finally, by introducing the generalized leakage power to characterize the ice melting power in the natural state, the energy loss during the ice storage process is shown, and the results are shown in Figure 5 . This method shows that through reasonable scheduling of ice storage cold energy storage, the electricity consumption cost can be significantly reduced, and at the same time, the cold load and the cooling unit are decoupled in time and space, so as to achieve peak shaving and valley filling and maintain the stability of the system. At the same time, it shows that after introducing the generalized energy storage model, it can better ensure that the temperature of the refrigeration space is maintained within the target range, solves the problem that it is difficult to directly schedule ice storage, and ensures the simplicity of the scheduling process.

[0164] Table 1 Electricity consumption costs of the refrigerating unit under different operating conditions

[0165] Operating condition Ice melting priority refrigeration Unit priority refrigeration Unit full refrigeration Operating cost (￥) 2492.829 2736.320 2935.466 Power consumption (KW) 5448.020 5116.108 5405.414

[0166] This invention is based on a detailed model of ice storage refrigerating unit refrigeration. Through the coordination of the power system, cold network, and energy storage system, and at the same time introducing the generalized energy storage model, the simplified scheduling is realized by analogizing the ice storage of ice storage cold energy storage to electrical energy storage.

[0167] The above is only the specific implementation manner of this invention, but the protection scope of this invention is not limited thereto. Any change or replacement that can be easily thought of by those skilled in the art within the technical scope disclosed by this invention should be covered by the protection scope of this invention.

Claims

1. A multi-time scale scheduling method for a building ice storage cooling system based on a generalized energy storage model, characterized in that, The method comprises the following steps: Step 1: Obtain the operation parameters of the ice storage cooling unit, including the heat exchange efficiency of the evaporator, the work efficiency of the compressor, the heat exchange efficiency of the condenser, and the flow rate of the throttle valve; Step 2: Obtain the cooling load, the ice storage capacity of the ice storage, the initial temperature of the refrigerant, and the enthalpy value information in different states; Step 3: Based on the operation parameters of the ice storage cooling unit, the cooling load, the initial temperature of the refrigerant, and the enthalpy values in different states, and in combination with the operation constraints of the refrigeration unit, the operation constraints of the ice storage, the power balance, and the cooling capacity balance, construct the overall operation model of the ice storage building; Step 4: Based on the model in Step 3, define the generalized energy storage model, and taking the minimum expected value of the building operation cost as the objective function, use the BARON solver to solve the optimal solution and optimize the proportion of ice melting of the ice storage cooling unit and the refrigeration of the unit.

2. The multi-time scale scheduling method for a building ice storage cooling system based on a generalized energy storage model according to claim 1, wherein In Step 3, the relevant operation constraints of the overall operation scheduling model of the ice storage building are as follows: 1) Operation constraints of the refrigeration unit 0 ≤ W t com ≤ W commax (A - 9) In the formula, T represents the number of time sections, the subscript t represents the scheduling period, and the subscript h represents the enthalpy value of the refrigeration working medium at different times. They respectively represent the enthalpy values of the refrigeration working medium corresponding to different temperatures. corresponds to the temperature of 45°C. The corresponding temperature ranges from 60°C to 80°C. The corresponding temperature ranges from -20°C to -10°C; the superscripts ev, com, con, and th respectively represent the evaporator, compressor, condenser, and throttle valve devices. They respectively represent the energy of the refrigeration working medium input into and output from the evaporator at time t. They respectively represent the heat exchange amount with the outside world and the flow rate of the refrigeration working medium at time t. They respectively represent the energy of the refrigeration working medium input into and output from the compressor at time t, Q ev_inmin 、Q ev_inmax They respectively represent the upper and lower limits of the energy of the refrigeration working medium input into the evaporator, W t com 、W commax They respectively represent the electric energy consumed by the compressor for work at time t and the upper limit of the work done by the compressor, w com represents the electric energy required to compress a unit of refrigeration working medium. represents the energy flowing into and out of the condenser at time t. They respectively represent the energy flowing into and out of the throttle valve at time t. They respectively represent the energy losses of the refrigeration working medium after flowing through the compressor, condenser, and throttle valve at time t, Q commax 、Q conmax 、Q thmax They respectively represent the upper limit values of the energy flowing into the compressor, condenser, and throttle valve per unit time. 2) Operation constraints of the ice storage In the formula, the subscripts t1 and t2 represent the ice storage time and the ice melting time respectively. They represent the heat exchange amount during ice making and the heat exchange amount during ice melting respectively. They represent the cooling capacity and the ice storage amount at time t1 respectively. It represents the ice storage mass of the ice storage tank at time t. It represents the ice making and ice melting mass at time t. Δt represents the minimum time section, which is taken as 1 hour in the formula. It represents the electric power consumed for refrigeration at time t, L f_ice It represents the latent heat value of ice. It represents the ice storage energy in time period t. They represent the cold release energy from ice melting and the cold release energy from the unit at time t2 respectively. They represent the cold release amount from ice melting and its minimum value in time period t, Q zice_min Q zice_max They represent the upper and lower limits of ice making and cold storage respectively. It represents the ice melting mass in time period t. It represents the energy efficiency ratio of the refrigeration unit in time period t. 3) Power and cooling capacity balance constraints Where, P t ce represents the electrical energy purchased at time t, represents the cooling load at time t, P cemin and P cemax represent the upper and lower limits of the electricity purchase quantity respectively.

3. A multi-time scale scheduling method for a building ice storage cooling system based on a generalized energy storage model according to claim 1, characterized in that In Step 4, first, based on the following assumptions: Assume that the heat conduction property of the ice does not change with time, that is, the thermal conductivity k of the ice is a constant; Assume that the initial temperature of the ice is 0 °C, and the temperature at the start of melting is the freezing point; Assume that the external environmental temperature T ev is known; Assume that the heat convection coefficient h of the environment and the surface area A of the ice remain unchanged during the natural melting process; Assume that the volume of the ice remains unchanged during the natural melting process and the ice layer thickness d remains unchanged; The constraints of the generalized energy storage model are as follows: H dl = h * v 0.5 (A - 46) R = d / (k ice *A ice )(A - 47) Where, P t loss represents the natural melting loss power of ice at time t, and P t ice represents the energy storage power of the ice storage tank under generalized energy storage, and P t zice , P t rice respectively represent the electro - power of ice making and melting at time t, SOC t represents the percentage of ice storage, α ice represents the actual utilization percentage of the ice storage tank, ρ ice represents the density of ice, V represents the volume of the ice storage tank, represents the energy storage or release efficiency at time t, ΔT t represents the temperature change at time t, respectively represent the heat transferred by heat convection, heat transfer and heat radiation at time t, M air , C air respectively represent the air quality and specific heat capacity in the refrigerated space, T t temp represents the temperature of the refrigerated space at time t, represents the cold loss at time t, R represents the thermal resistance of the wall, T t ev , T ice respectively represent the ambient temperature and the ice layer temperature, H dl , A ice respectively represent the heat convection coefficient and the heat convection contact area, θ f , δ f respectively represent the influence coefficient of temperature change on radiation power per unit area and the emissivity of the object surface, h is the heat transfer coefficient, v is the air flow velocity, d is the ice layer thickness, k ice thermal conductivity, respectively represent the natural melting mass of ice and the corresponding heat loss at time t, T t loss represents the temperature change caused by the loss of stored energy due to natural melting of ice at time t.

4. A multi-time scale scheduling method for a building ice storage cooling system based on a generalized energy storage model according to claim 1, characterized in that In Step 4, the minimum objective function is: In the formula, the superscript ce represents the electricity purchase quantity, and the superscript e represents the electric energy; P t ce represents the electric energy purchased at time t, and C t e represents the time-of-use electricity price at time t; Under the operation constraints of the refrigeration unit, the operation constraints of the ice storage, the power and cooling capacity balance constraints, and the generalized energy storage constraints, taking the minimum expected value of the overall operation cost of the building ice storage system as the objective function, use the BARON solver to obtain the optimal solution and optimize the scheduling of the ice storage building system.

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