Cooling and electricity joint scheduling method, device, equipment, medium and computer program product

Abstract

The present application relates to a combined cold and electricity scheduling method, device, computer equipment, storage medium and computer program product. The method is applied to a target base station, which includes a phase change cold storage system and a power supply system, and includes: obtaining the non-adjustable prediction parameters of the target base station corresponding to the t-th moment in a preset time period; inputting the non-adjustable prediction parameters into a pre-built base station communication data processing model, a cooling demand model and a combined cold and electricity supply scheduling model, and solving to obtain the prediction control parameters at the t-th moment, the base station communication data processing model is used to characterize the actual operation constraints of the data processing load of the target base station, the cooling demand model is used to characterize the operation constraints of the phase change cold storage system, and the combined cold and electricity supply scheduling model is used to characterize the scheduling target of the target base station within a preset period; and controlling the operation of the phase change cold storage system and the power supply system based on the prediction control parameters. The use of this method can reduce the operating cost of the base station.

Description

Technical Field

[0001] The present application relates to the technical field of base station energy supply, and in particular to a cooling and electricity joint scheduling method, device, computer equipment, storage medium and computer program product. Background Art

[0002] In order to meet the communication needs of remote areas, my country is currently vigorously promoting the construction of base stations. To ensure the operation of base stations in remote areas, energy supply systems will be configured for base stations to meet the power supply and cooling needs of base stations.

[0003] In the prior art, the energy supply system usually includes a power supply system composed of wind turbine power generation, photovoltaic power generation and gas turbine or diesel engine power generation, as well as an air conditioning system configured to meet the working temperature requirements of the communication unit in the base station.

[0004] However, the above method is used to meet the power supply and cooling requirements of the base station, and the operating cost of the base station is relatively high. Summary of the invention

[0005] Based on this, it is necessary to provide a cooling and electricity joint scheduling method, device, computer equipment, computer readable storage medium and computer program product to reduce the operating cost of base stations in response to the above technical problems.

[0006] In a first aspect, the present application provides a cooling and electricity joint scheduling method, which is applied to a target base station, wherein the target base station includes a phase change cooling storage system and a power supply system. The method includes:

[0007] Obtaining a non-adjustable prediction parameter of the target base station corresponding to the t-th moment in the preset time period;

[0008] The non-adjustable prediction parameters are input into the pre-built base station communication data processing model, cooling demand model and combined cooling and power supply scheduling model, and the prediction control parameters at the tth moment are obtained by solving. The base station communication data processing model is used to characterize the actual operation constraints of the data processing load of the target base station, the cooling demand model is used to characterize the operation constraints of the phase change cold storage system, and the combined cooling and power supply scheduling model is used to characterize the scheduling target of the target base station within a preset period;

[0009] The operation of the phase change thermal storage system and the power supply system is controlled based on the predicted control parameters.

[0010] In one embodiment, the non-adjustable prediction parameters include predicted data processing loads corresponding to multiple data processing types, predicted power of renewable energy generation, data processing load heat generation rate, and electric-cooling conversion efficiency of heat pumps in phase change cold storage systems. The non-adjustable prediction parameters are input into a pre-built base station communication data processing model, a cooling demand model, and a combined cooling and power supply scheduling model, including:

[0011] inputting data processing loads corresponding to the various data processing types into a base station communication data processing model;

[0012] Input the data processing load heat generation rate and the electric cooling conversion efficiency into the cooling demand model;

[0013] The data processing load corresponding to various data processing types and the predicted power of renewable energy generation are input into the combined cooling and power supply scheduling model.

[0014] In one embodiment, the predicted data processing loads corresponding to the multiple data processing types include an immediate processing load, an immediate external processing load, and a time-shiftable load. The immediate processing load is used to characterize the predicted data processing load processed by the target base station at the current moment, the immediate external processing load is used to characterize the predicted data processing load transferred from the target base station to other base stations for processing at the current moment, and the time-shiftable load is used to characterize the predicted data processing load transferred from the current moment to other moments for processing by the target base station. The expression of the base station communication data processing model includes:

[0015]

[0016] 0≤α t ≤1,

[0017]

[0018]

[0019]

[0020] Where i≤t, represents the actual data processing load at the tth moment; They represent the immediate processing load and the immediate external processing load corresponding to the tth moment respectively; α t represents the proportion of the load that remains to be processed by the target base station in the instantaneous externally processable load corresponding to the t-th moment; P represents the time-shiftable load actually processed at the tth moment; i EL3 represents the time-shiftable load corresponding to the i-th moment; It represents the time-shiftable load transferred from the i-th moment to the t-th moment, where T is the preset time period.

[0021] In one embodiment, the expression of the refrigeration demand model includes:

[0022]

[0023]

[0024]

[0025]

[0026] in, Indicates the actual cooling power corresponding to the t-th moment; represents the actual data processing load corresponding to the tth moment; β represents the heat generation rate of the data processing load; and They represent the actual heat pump operating power and rated heat pump power corresponding to the tth moment respectively; η PCM Indicates the electric cooling conversion efficiency; and They respectively represent the actual cold storage capacity and the rated cold storage capacity of the phase change cold storage system at the tth moment.

[0027] In one embodiment, the expression of the combined cooling and power supply model includes:

[0028]

[0029]

[0030]

[0031]

[0032]

[0033]

[0034] Among them, p G Indicates the power generation cost per unit power of non-renewable energy; and They represent the power generation and rated power generation of non-renewable energy sources at the tth moment respectively; p E represents the price per unit of power required to transfer the data processing load to other base stations; represents the predicted data processing load transferred to other base stations for processing at the tth time; α t represents the proportion of the load remaining in the target base station in the predicted data processing load transferred to other base stations for processing corresponding to the t-th time; represents the maximum data processing load that other base stations can receive corresponding to the t-th time; represents the power generation of renewable energy corresponding to the tth moment; represents the unabsorbed power of renewable energy corresponding to the t-th moment; Indicates the actual energy storage parameters of the phase change cold storage system corresponding to the start time of the preset time period; Indicates the actual energy storage parameters of the phase change cold storage system corresponding to the end of the preset time period.

[0035] In one embodiment, the predicted control parameters include the actual heat pump operating power of the heat pump, the actual cold storage capacity of the phase change cold storage system, the actual cold release power of the phase change cold storage system, and the power generation power of the non-renewable energy source, and the operation of the phase change cold storage system and the power supply system is controlled based on the predicted control parameters, including:

[0036] Based on the actual heat pump operating power, actual cold storage capacity and actual cold release power, the operation of the phase change cold storage system is controlled;

[0037] Control the operation of the power supply system based on the power generated by non-renewable energy sources.

[0038] In a second aspect, the present application also provides a cooling and electricity joint scheduling device, which is applied to a target base station, and the target base station includes a phase change cold storage system and a power supply system. The device includes:

[0039] An acquisition module, used to acquire the non-adjustable prediction parameters of the target base station corresponding to the t-th moment in a preset time period;

[0040] A solution module is used to input the non-adjustable prediction parameters into the pre-built base station communication data processing model, the cooling demand model and the combined cooling and power supply scheduling model, and solve the prediction control parameters at the tth moment. The base station communication data processing model is used to characterize the actual operation constraints of the data processing load of the target base station, the cooling demand model is used to characterize the operation constraints of the phase change cold storage system, and the combined cooling and power supply scheduling model is used to characterize the scheduling target of the target base station within a preset period;

[0041] The control module is used to control the operation of the phase change thermal storage system and the power supply system based on the predicted control parameters.

[0042] In one embodiment, the non-adjustable prediction parameters include predicted data processing loads corresponding to various data processing types, predicted power of renewable energy generation, heat generation rate of data processing loads, and electric cooling conversion efficiency of heat pumps in phase change cold storage systems. The solution module is specifically used to:

[0043] inputting data processing loads corresponding to the various data processing types into a base station communication data processing model;

[0044] Input the data processing load heat generation rate and the electric cooling conversion efficiency into the cooling demand model;

[0045] The data processing load corresponding to various data processing types and the predicted power of renewable energy generation are input into the combined cooling and power supply scheduling model.

[0046] In one embodiment, the predicted data processing loads corresponding to the multiple data processing types include an immediate processing load, an immediate external processing load, and a time-shiftable load. The immediate processing load is used to characterize the predicted data processing load processed by the target base station at the current moment, the immediate external processing load is used to characterize the predicted data processing load transferred from the target base station to other base stations for processing at the current moment, and the time-shiftable load is used to characterize the predicted data processing load transferred from the current moment to other moments for processing by the target base station. The expression of the base station communication data processing model in the solution module includes:

[0047]

[0048] 0≤α t ≤1,

[0049]

[0050]

[0051]

[0052] Where i≤t, represents the actual data processing load at the tth moment; They represent the immediate processing load and the immediate external processing load corresponding to the tth moment respectively; α t represents the proportion of the load that remains to be processed by the target base station in the instantaneous externally processable load corresponding to the t-th moment; P represents the time-shiftable load actually processed at the tth moment; i EL3 represents the time-shiftable load corresponding to the i-th moment; It represents the time-shiftable load transferred from the i-th moment to the t-th moment, where T is the preset time period.

[0053] In one embodiment, the expression of the refrigeration demand model in the solution module includes:

[0054]

[0055]

[0056]

[0057]

[0058] in, Indicates the actual cooling power corresponding to the t-th moment; represents the actual data processing load corresponding to the tth moment; β represents the heat generation rate of the data processing load; and They represent the actual heat pump operating power and rated heat pump power corresponding to the tth moment respectively; η PCM Indicates the electric cooling conversion efficiency; and They respectively represent the actual cold storage capacity and the rated cold storage capacity of the phase change cold storage system at the tth moment.

[0059] In one embodiment, the expression of the combined cooling and power supply model in the solution module includes:

[0060]

[0061]

[0062]

[0063]

[0064]

[0065]

[0066] Among them, p G Indicates the power generation cost per unit power of non-renewable energy; and They represent the power generation and rated power generation of non-renewable energy sources at the tth moment respectively; p E represents the price per unit of power required to transfer the data processing load to other base stations; represents the predicted data processing load transferred to other base stations for processing at the tth time; α t represents the proportion of the load remaining in the target base station in the predicted data processing load transferred to other base stations for processing corresponding to the t-th time; represents the maximum data processing load that other base stations can receive corresponding to the t-th time; represents the power generation of renewable energy corresponding to the tth moment; represents the unabsorbed power of renewable energy corresponding to the t-th moment; Indicates the actual energy storage parameters of the phase change cold storage system corresponding to the start time of the preset time period; Indicates the actual energy storage parameters of the phase change cold storage system corresponding to the end of the preset time period.

[0067] In one embodiment, the predictive control parameters include the actual heat pump operating power of the heat pump, the actual cold storage capacity of the phase change cold storage system, the actual cold release power of the phase change cold storage system, and the power generation power of the non-renewable energy source. The control module is specifically used to:

[0068] Based on the actual heat pump operating power, actual cold storage capacity and actual cold release power, the operation of the phase change cold storage system is controlled;

[0069] Control the operation of the power supply system based on the power generated by non-renewable energy sources.

[0070] In a third aspect, the present application further provides a computer device, wherein the computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the cooling and electricity joint scheduling method as described in any one of the first aspects above is implemented.

[0071] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the cooling and electricity joint scheduling method as described in any one of the first aspects above is implemented.

[0072] In a fifth aspect, the present application further provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the cooling and electricity joint scheduling method as described in any one of the first aspects above is implemented.

[0073] The above-mentioned cold-electricity combined method, device, computer equipment, storage medium and computer program product obtain the non-adjustable prediction parameters of the target base station corresponding to the t-th moment in the preset time period and input the non-adjustable prediction parameters into the pre-built base station communication data processing model, cooling demand model and combined cooling and power supply scheduling model, and solve the prediction control parameters at the t-th moment to control the operation of the phase change cold storage system and the power supply system. Since the cooling demand of the base station is met by means of the phase change cold storage system, compared with the non-adjustable air-conditioning load, the phase change cold storage system has energy storage capacity and flexible operation characteristics, which improves the flexibility of base station operation scheduling; since the prediction control parameters are obtained based on the three models of the base station communication data processing model, the cooling demand model and the combined cooling and power supply scheduling model, the coordinated scheduling of the data processing load and the phase change cold storage system in the base station is realized, and the operation of the phase change cold storage system and the power supply system can be scheduled in real time, fully optimizing the operation of the base station and reducing the operating cost of the base station. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 A schematic diagram of a cold-electricity combined method according to an embodiment;

[0075] Figure 2is a flow chart of step 102 in one embodiment;

[0076] Figure 3 is a flow chart of step 103 in one embodiment;

[0077] Figure 4 A schematic diagram of a process of a cold-electricity combined method in another embodiment;

[0078] Figure 5 is an experimental result in one embodiment;

[0079] Figure 6 Another experimental result in one embodiment;

[0080] Figure 7 is another experimental result in an embodiment;

[0081] Figure 8 is another experimental result in an embodiment;

[0082] Fig. 9 is a structural block diagram of a cold-electricity combined device in one embodiment;

[0083] Fig.10 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0084] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0085] In order to meet the growing communication needs and improve the quality of communication, my country is currently building base stations, which are gradually being promoted from large cities to rural areas and even remote areas. Traditionally, communication base stations in remote areas are mainly powered by gas turbines or diesel engines, and equipped with air conditioning to meet the working temperature requirements of the communication units. However, the power supply method based on the discharge of gas turbines or diesel engines is relatively expensive, and there are problems such as high carbon emissions and air pollution. Usually, renewable energy generation is equipped and can significantly alleviate the power consumption pressure of base stations. However, renewable energy generation is uncontrollable and easily leads to wind and solar power abandonment. The air conditioning load is non-adjustable and cannot be flexibly dispatched.

[0086] Therefore, when the above method is adopted to meet the power supply and cooling requirements of the base station, the operating cost of the base station is relatively high.

[0087] In view of this, an embodiment of the present application provides a cooling and electricity joint scheduling method, which can reduce the operating costs of base stations.

[0088] It should be noted that the cooling and electricity joint scheduling method provided in the embodiment of the present application may be executed by a cooling and electricity joint scheduling device, which may be implemented as part or all of a terminal through software, hardware, or a combination of software and hardware.

[0089] In view of this, an embodiment of the present application provides a cooling and electricity joint scheduling method, which can achieve an optimization effect of improving the operating cost of a base station.

[0090] In the following method embodiments, the execution subject is taken as an example to illustrate, wherein the terminal can be a personal computer, a laptop computer, a media player, a smart TV, a smart phone, a tablet computer, and a portable wearable device, etc. It can be understood that the method can also be applied to a server, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server.

[0091] Please refer to Figure 1 , which shows a flow chart of a cold-electricity joint scheduling method provided in an embodiment of the present application. The method is applied to a target base station, which includes a phase change cold storage system and a power supply system. Optionally, the type of the target base station is a 5G communication base station or a 4G communication base station, etc. In an embodiment of the present application, a phase change cold storage system is used to meet the refrigeration needs of the base station operation. The core component of the phase change cold storage system is the phase change material, which can absorb or release a large amount of heat near the phase change point while the temperature remains basically unchanged. The heat pump is responsible for cooling the power side of the phase change cold storage system, and the fan accelerates the release of cold on the thermal side. The unbalanced cold energy is stored or released by the phase change material. Compared with air conditioning, the phase change cold storage system has energy storage capacity and can flexibly adjust its operating load. As Figure 1 As shown, the cooling and electricity joint scheduling method may include the following steps:

[0092] Step 101: Obtain a non-adjustable prediction parameter of a target base station corresponding to the t-th moment in a preset time period.

[0093] Among them, the non-adjustable prediction parameters include wind speed, sunshine intensity, predicted data processing load, predicted power of renewable energy generation, heat generation rate of data processing load, and electric cooling conversion efficiency of heat pump in phase change cold storage system, etc. The predicted power of renewable energy generation includes at least one of wind turbine power generation and photovoltaic power generation.

[0094] Optionally, the length of the preset time period is 1 day or 1 week. The preset time period is divided according to the preset time length to obtain multiple time points, wherein the preset time length can be 1 hour, several hours, several minutes or tens of minutes, etc. For example, when the length of the preset time period is 1 day, the preset time period is divided with 1 hour as the preset time length to obtain 24 time points.

[0095] Optionally, if the non-adjustable prediction parameters include wind speed and sunshine intensity, the wind turbine power generation power of the corresponding time period is obtained according to the wind speed by using the prediction algorithm corresponding to the wind turbine power generation power prediction, wherein the prediction algorithm includes one of the long short-term memory network (LSTM), the time convolution network (TCN), and the time sequence graph network (TGNs). Similarly, the wind turbine power generation power of the corresponding time period is obtained according to the sunshine intensity by using the prediction algorithm corresponding to the photovoltaic power generation power prediction, wherein the prediction algorithm includes one of the long short-term memory network (LSTM), the time convolution network (TCN), and the time sequence graph network (TGNs).

[0096] Step 102, input the non-adjustable prediction parameters into the pre-built base station communication data processing model, cooling demand model and combined cooling and power supply scheduling model, and solve to obtain the prediction control parameters at the tth moment.

[0097] Among them, the base station communication data processing model is used to characterize the actual operation constraints of the data processing load of the target base station, the refrigeration demand model is used to characterize the operation constraints of the phase change cold storage system, and the combined cooling and power supply scheduling model is used to characterize the scheduling target of the target base station within a preset period. The predictive control parameters include at least one or more of the actual heat pump operating power of the heat pump and the power generation power of non-renewable energy. Non-renewable energy includes at least one of diesel engine power generation and gas engine power generation.

[0098] Optionally, the refrigeration demand model includes at least actual cold storage capacity constraints of the phase change cold storage system, operation constraints of a heat pump of the phase change cold storage system, and the like.

[0099] Optionally, the scheduling target of the combined cooling and power supply scheduling model is to minimize the duration of power generation using non-renewable energy within a preset time period. The scheduling model includes an objective function and constraints corresponding to the objective function. Correspondingly, the objective function is a function corresponding to the shortest duration of power generation using non-renewable energy within a preset time period.

[0100] Optionally, the Gurobi solver is called to solve a joint model consisting of a base station communication data processing model, a refrigeration demand model, and a combined cooling and power supply scheduling model to obtain the prediction control parameters at the tth moment.

[0101] Step 103: Control the operation of the phase change cold storage system and the power supply system based on the predicted control parameters.

[0102] The power supply system includes a power generation system using renewable energy and a power generation system using non-renewable energy.

[0103] Optionally, when the predicted control parameter is the actual heat pump operating power of the heat pump, the operation of the phase change cold storage system is controlled according to the predicted control parameter. When the predicted parameter is the power generation power of non-renewable energy, the operation of the power supply system is controlled according to the power generation power of non-renewable energy.

[0104] In the above-mentioned combined cooling and electricity supply method, by obtaining the non-adjustable prediction parameters of the target base station corresponding to the t-th moment in the preset time period and inputting the non-adjustable prediction parameters into the pre-built base station communication data processing model, cooling demand model and combined cooling and electricity supply scheduling model, the prediction control parameters at the t-th moment are solved to control the operation of the phase change cold storage system and the power supply system. Since the cooling demand of the base station is met by means of the phase change cold storage system, compared with air conditioning, the phase change cold storage system has energy storage capacity and flexible operation characteristics, which improves the flexibility of base station operation scheduling; since the prediction control parameters are obtained based on the three models of the base station communication data processing model, the cooling demand model and the combined cooling and electricity supply scheduling model, the coordinated scheduling of the data processing load in the base station and the phase change cold storage system is realized, and the operation of the phase change cold storage system and the power supply system can be scheduled in real time, fully optimizing the operation of the base station and reducing the operating cost of the base station.

[0105] In one embodiment, the non-adjustable prediction parameters include the predicted data processing load corresponding to various data processing types, the predicted power of renewable energy generation, the heat generation rate of the data processing load, and the electric-cooling conversion efficiency of the heat pump in the phase change cold storage system. Figure 1 The embodiment shown, see Figure 2 This embodiment involves the implementation process of inputting the non-adjustable prediction parameters into the pre-built base station communication data processing model, cooling demand model and combined cooling and power supply scheduling model in step 102. Figure 2 As shown, the implementation process includes step 201, step 202 and step 203:

[0106] Step 201, inputting data processing loads corresponding to a plurality of data processing types into a base station communication data processing model.

[0107] Optionally, the predicted data processing load is divided into immediate processing load, immediate external processing load and time-shiftable load according to the urgency of the communication data. Among them, the immediate processing load is used to characterize the predicted data processing load processed by the target base station at the current moment, the immediate external processing load is used to characterize the predicted data processing load transferred from the target base station to other base stations for processing at the current moment, and the time-shiftable load is used to characterize the predicted data processing load transferred from the current moment to other moments and processed by the target base station.

[0108] Optionally, based on a trained data processing load forecasting model, the instant processing load, externally processable load and time-shiftable load corresponding to each historical moment in the historical time period are obtained to obtain the instant processing load, externally processable load and time-shiftable load corresponding to multiple time periods in the preset time period.

[0109] Optionally, the base station communication data processing model includes the following constraints: actual data processing load constraint corresponding to the t-th moment (see the following formula (1)); the proportion constraint of the immediate externally processable load actually remaining in the target base station for processing (see the following formula (2)); the composition constraint of the actual processed time-shiftable load corresponding to the t-th moment (i.e., the immediate externally processable actual load) (see the following formula (3)); the power constraint of the actual processed time-shiftable load corresponding to the t-th moment (see the following formulas (4)-(5)), i.e., the power value of the time-shiftable load transferred from the i-th moment (i≤t) to the t-th moment cannot be greater than the power value of the time-shiftable load corresponding to the i-th moment; the cumulative sum of the power values ​​of the time-shiftable load transferred from the i-th moment (i≤t) to the moment t must be equal to the power value of the time-shiftable load corresponding to the i-th moment. The expression of the base station communication data processing model includes:

[0110]

[0111] 0≤α t ≤1; (2)

[0112]

[0113]

[0114]

[0115] Where i≤t, represents the actual data processing load at the tth moment; They represent the immediate processing load and the immediate external processing load corresponding to the tth moment respectively; α t represents the proportion of the load that remains to be processed by the target base station in the instantaneous externally processable load corresponding to the t-th moment; represents the time-shiftable load actually processed corresponding to the t-th moment; represents the time-shiftable load corresponding to the i-th moment; It represents the time-shiftable load transferred from the i-th moment to the t-th moment, where T is the preset time period.

[0116] At this time, the actual external processing load corresponding to the tth moment is

[0117] The base station communication data processing model takes into account the elasticity of adjusting the data processing load by setting the load proportion of the immediate external processing load that is retained for processing at the target base station, making the base station communication data processing model closer to the actual operation of the base station and improving the accuracy of the calculation results.

[0118] Step 202: input the data processing load heat generation rate and the electric cooling conversion efficiency into a cooling demand model.

[0119] Optionally, the cooling demand model includes the following constraints: an association constraint between the data processing load of the target base station and the cooling demand; a cooling energy supply and demand balance constraint; a heat pump operating power constraint; a cooling power storage power and actual cooling power release constraint; and a phase change cooling system energy storage capacity constraint.

[0120] Correspondingly, the expression of the cooling demand model includes:

[0121]

[0122]

[0123]

[0124]

[0125] in, Indicates the actual cooling power corresponding to the t-th moment; represents the actual data processing load corresponding to the tth moment; β represents the heat generation rate of the data processing load; and They represent the actual heat pump operating power and rated heat pump power corresponding to the tth moment respectively; η PCM Indicates the electric cooling conversion efficiency; and They respectively represent the actual cold storage capacity and the rated cold storage capacity of the phase change cold storage system at the tth moment.

[0126] Step 203: input the data processing loads corresponding to the various data processing types and the predicted power of renewable energy generation into the combined cooling and power supply scheduling model.

[0127] Optionally, the scheduling target of the combined cooling and power supply model is to minimize the sum of the power generation cost of non-renewable energy and the payment for transferring data from the target base station to other base stations for processing. The model also includes the following constraints: power generation constraints of non-renewable energy; the power of the actual load that can be processed externally cannot be greater than the power that other base stations can receive; the power balance constraint of the target base station; the unabsorbed power of renewable energy cannot be less than 0; the energy storage of the phase change cold storage system must return to the initial value at the end of scheduling. Among them, when the renewable energy includes wind turbine power generation and photovoltaic power generation, the unabsorbed power is the abandoned wind and photovoltaic power. The combined cooling and power supply model gives full play to the peak-shaving and valley-filling effect of the controllable data processing load and the energy storage capacity and flexible operation characteristics of the phase change energy storage system. It adjusts the power of the phase change energy storage system and the controllable data processing load in real time according to the power generation of renewable energy, significantly improves the absorption rate of renewable energy, and greatly reduces the operating cost of the combined cooling and power supply system.

[0128] Correspondingly, the expression of the combined cooling and power supply model includes:

[0129]

[0130]

[0131]

[0132]

[0133]

[0134]

[0135] Among them, p G Indicates the power generation cost per unit power of non-renewable energy; and They represent the power generation and rated power generation of non-renewable energy sources at the tth moment respectively; p E represents the price per unit of power required to transfer the data processing load to other base stations; represents the predicted data processing load transferred to other base stations for processing at the tth time; α t represents the proportion of the load remaining in the target base station in the predicted data processing load transferred to other base stations for processing corresponding to the t-th time; represents the maximum data processing load that other base stations can receive corresponding to the t-th time; represents the power generation of renewable energy corresponding to the tth moment; represents the unabsorbed power of renewable energy corresponding to the t-th moment; Indicates the actual energy storage parameters of the phase change cold storage system corresponding to the start time of the preset time period; Indicates the actual energy storage parameters of the phase change cold storage system corresponding to the end of the preset time period.

[0136] In this embodiment, the association constraint between the data processing load and the cooling demand is realized by inputting the heat production rate of the data processing load and the electric cooling conversion efficiency into the cooling demand model; the data processing loads corresponding to multiple data processing types are input into the base station communication data processing model, the heat production rate of the data processing load and the electric cooling conversion efficiency are input into the cooling demand model, and the data processing loads corresponding to multiple data processing types and the predicted power of renewable energy generation are input into the combined cooling and power supply scheduling model for calculating the predicted control parameters, thereby improving the absorption rate of renewable energy and reducing the operating cost of the combined cooling and power system.

[0137] In the embodiment of the present application, the predictive control parameters include the actual heat pump operating power of the heat pump, the actual cold storage capacity of the phase change cold storage system, the actual cold release power of the phase change cold storage system, and the power generation power of non-renewable energy. Figure 1 or Figure 2 The embodiment shown, see Figure 3 This embodiment involves the implementation process of controlling the operation of the phase change cold storage system and the power supply system based on the predicted control parameters in step 103. Figure 3 As shown, the implementation process includes step 301 and step 302:

[0138] Step 301, based on the actual heat pump operating power, the actual cold storage capacity and the actual cold release power, control the operation of the phase change cold storage system.

[0139] Optionally, for the time interval from moment t-1 to moment t, the phase change cold storage system is controlled to operate according to the actual heat pump operating power, actual cold storage capacity, actual cold release power and actual cold release power corresponding to the calculated moment t.

[0140] Step 302: Control the operation of the power supply system based on the power generated by the non-renewable energy source.

[0141] Optionally, for the time interval from moment t-1 to moment t, the non-renewable energy in the power supply system is controlled to generate electricity according to the calculated power generation power corresponding to the non-renewable energy at moment t.

[0142] This embodiment controls the operation of the phase change cold storage system based on the actual heat pump operating power, the actual cold storage capacity and the actual cold release power, and controls the operation of the power supply system based on the power generation power of non-renewable energy, thereby realizing the scheduling planning of base station operation and reducing the operating cost of the communication base station.

[0143] In the embodiments of the present application, Figure 4 As shown, a cooling and electricity joint scheduling method is provided, the method comprising the following steps:

[0144] Step 401: Obtain a non-adjustable prediction parameter of a target base station corresponding to the t-th moment in a preset time period.

[0145] Among them, the non-adjustable prediction parameters include instant processing load, instant external processing load, time-shiftable load, predicted power of renewable energy generation, heat production rate of data processing load, and electric-to-cooling conversion efficiency of heat pump in phase change cold storage system.

[0146] Step 402, inputting data processing loads corresponding to a plurality of data processing types into a base station communication data processing model.

[0147] The expression of the base station communication data processing model includes:

[0148]

[0149] 0≤α t ≤1,

[0150]

[0151]

[0152]

[0153] Where i≤t, represents the actual data processing load at the tth moment; They represent the immediate processing load and the immediate external processing load corresponding to the tth moment respectively; α t represents the proportion of the load that remains to be processed by the target base station in the instantaneous externally processable load corresponding to the t-th moment; P represents the time-shiftable load actually processed at the tth moment; i EL3 represents the time-shiftable load corresponding to the i-th moment; Represents the time-shiftable load transferred from the i-th moment to the t-th moment; T is the preset time period.

[0154] Step 403: input the data processing load heat generation rate and the electric cooling conversion efficiency into the cooling demand model.

[0155] The expression of the cooling demand model includes:

[0156]

[0157]

[0158]

[0159]

[0160] in, Indicates the actual cooling power corresponding to the t-th moment; represents the actual data processing load corresponding to the tth moment; β represents the heat generation rate of the data processing load; and They represent the actual heat pump operating power and rated heat pump power corresponding to the tth moment respectively; η PCM Indicates the electric cooling conversion efficiency; and They respectively represent the actual cold storage capacity and the rated cold storage capacity of the phase change cold storage system at the tth moment.

[0161] Step 404: input the data processing loads corresponding to the various data processing types and the predicted power of renewable energy generation into the combined cooling and power supply scheduling model.

[0162] The expression of the combined cooling and power supply model includes:

[0163]

[0164]

[0165]

[0166]

[0167]

[0168]

[0169] Among them, p G Indicates the power generation cost per unit power of non-renewable energy; and They represent the power generation and rated power generation of non-renewable energy sources at the tth moment respectively; p E represents the price per unit of power required to transfer the data processing load to other base stations; represents the predicted data processing load transferred to other base stations for processing at the tth time; α t represents the proportion of the load remaining in the target base station in the predicted data processing load transferred to other base stations for processing corresponding to the t-th time; represents the maximum data processing load that other base stations can receive corresponding to the t-th time; represents the power generation of renewable energy corresponding to the tth moment; represents the unabsorbed power of renewable energy corresponding to the t-th moment; Indicates the actual energy storage parameters of the phase change cold storage system corresponding to the start time of the preset time period; Indicates the actual energy storage parameters of the phase change cold storage system corresponding to the end of the preset time period.

[0170] Step 405: Call the Gurobi solver to solve and obtain the predictive control parameters at the tth moment.

[0171] Among them, the prediction control parameters include the actual heat pump operating power of the heat pump, the actual cold storage capacity of the phase change cold storage system, the actual cold release power of the phase change cold storage system and the power generation power of non-renewable energy.

[0172] Step 406, based on the actual heat pump operating power, the actual cold storage capacity and the actual cold release power, control the operation of the phase change cold storage system.

[0173] Step 407: Control the operation of the power supply system based on the power generated by the non-renewable energy source.

[0174] This embodiment fully considers the adjustment elasticity of the data processing load of the target base station and the cooling and electricity association constraints of the target base station, realizes the coordinated scheduling of the data processing load and the phase change cold storage system in the base station, gives full play to the peak shaving and valley filling effect of the controllable data processing load and the energy storage capacity and flexible operation characteristics of the phase change energy storage system, and adjusts the power of the phase change energy storage system and the controllable data processing load in real time according to the power generation power of renewable energy, significantly improves the absorption rate of renewable energy power generation, and greatly reduces the operating cost of the combined cooling and power system.

[0175] The following is an experimental result of verifying the scheduling method of the mobile energy storage system of the embodiment of the present application.

[0176] Here, the preset time period is 24 hours. The preset time period is divided into 1 hour units to obtain multiple time points, namely the 1st hour, the 2nd hour, ..., the 24th hour. The predicted power of renewable energy generation includes wind turbine power generation and photovoltaic power generation. Non-renewable energy generation is diesel engine power generation.

[0177] The distribution of predicted data processing load, wind turbine power generation and photovoltaic power generation is as follows: Figure 5 The Gurobi solver is called to solve the calling model, and the daily operating cost of the target base station is 2219 yuan. Figure 6 The optimized target base station forecast data processing load includes hourly time-shiftable load and immediate processing load. Figure 7The actual heat pump operating power, diesel engine power generation power and wind and solar power curtailment power of the phase change cold storage system are shown. Figure 8 The actual cold storage capacity of the phase change cold storage system and the cooling demand power of the target base station, that is, the actual cold release power of the phase change cold storage system, are demonstrated.

[0178] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0179] Based on the same inventive concept, the embodiment of the present application also provides a cooling and electricity joint scheduling device for implementing the cooling and electricity joint scheduling method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more cooling and electricity joint scheduling device embodiments provided below can refer to the limitations of the cooling and electricity joint scheduling method above, and will not be repeated here.

[0180] In one embodiment, Fig. 9 As shown, a cooling and electricity joint scheduling device is provided, including: an acquisition module, a solution module and a control module, wherein:

[0181] An acquisition module, used to acquire the non-adjustable prediction parameters of the target base station corresponding to the t-th moment in a preset time period;

[0182] A solution module is used to input the non-adjustable prediction parameters into the pre-built base station communication data processing model, the cooling demand model and the combined cooling and power supply scheduling model, and solve the prediction control parameters at the tth moment. The base station communication data processing model is used to characterize the actual operation constraints of the data processing load of the target base station, the cooling demand model is used to characterize the operation constraints of the phase change cold storage system, and the combined cooling and power supply scheduling model is used to characterize the scheduling target of the target base station within a preset period;

[0183] The control module is used to control the operation of the phase change thermal storage system and the power supply system based on the predicted control parameters.

[0184] In one embodiment, the non-adjustable prediction parameters include predicted data processing loads corresponding to various data processing types, predicted power of renewable energy generation, heat generation rate of data processing load, and electric-cooling conversion efficiency of heat pumps in phase change cold storage systems. The solution module is specifically used to:

[0185] inputting data processing loads corresponding to the various data processing types into a base station communication data processing model;

[0186] Input the data processing load heat generation rate and the electric cooling conversion efficiency into the cooling demand model;

[0187] The data processing load corresponding to various data processing types and the predicted power of renewable energy generation are input into the combined cooling and power supply scheduling model.

[0188] In one embodiment, the predicted data processing loads corresponding to the multiple data processing types include an immediate processing load, an immediate external processing load, and a time-shiftable load. The immediate processing load is used to characterize the predicted data processing load processed by the target base station at the current moment, the immediate external processing load is used to characterize the predicted data processing load transferred from the target base station to other base stations for processing at the current moment, and the time-shiftable load is used to characterize the predicted data processing load transferred from the current moment to other moments for processing by the target base station. The expression of the base station communication data processing model in the solution module includes:

[0189]

[0190] 0≤α t ≤1,

[0191]

[0192]

[0193]

[0194] Where i≤t, represents the actual data processing load at the tth moment; They represent the immediate processing load and the immediate external processing load corresponding to the tth moment respectively; α t represents the proportion of the load that remains to be processed by the target base station in the instantaneous externally processable load corresponding to the t-th moment; represents the time-shiftable load actually processed corresponding to the t-th moment; represents the time-shiftable load corresponding to the i-th moment; It represents the time-shiftable load transferred from the i-th moment to the t-th moment, where T is the preset time period.

[0195] In one embodiment, the expression of the refrigeration demand model in the solution module includes:

[0196]

[0197]

[0198]

[0199]

[0200] in, Indicates the actual cooling power corresponding to the t-th moment; represents the actual data processing load corresponding to the tth moment; β represents the heat generation rate of the data processing load; and They represent the actual heat pump operating power and rated heat pump power corresponding to the tth moment respectively; η PCM Indicates the electric cooling conversion efficiency; and They respectively represent the actual cold storage capacity and the rated cold storage capacity of the phase change cold storage system at the tth moment.

[0201] In one embodiment, the expression of the combined cooling and power supply model in the solution module includes:

[0202]

[0203]

[0204]

[0205]

[0206]

[0207]

[0208] Among them, p G Indicates the power generation cost per unit power of non-renewable energy; and They represent the power generation and rated power generation of non-renewable energy sources at the tth moment respectively; p E represents the price per unit of power required to transfer the data processing load to other base stations; represents the predicted data processing load transferred to other base stations for processing at the tth time; α t represents the proportion of the load remaining in the target base station in the predicted data processing load transferred to other base stations for processing corresponding to the t-th time; represents the maximum data processing load that other base stations can receive corresponding to the t-th time; represents the power generation of renewable energy corresponding to the tth moment; represents the unabsorbed power of renewable energy corresponding to the t-th moment; Indicates the actual energy storage parameters of the phase change cold storage system corresponding to the start time of the preset time period; Indicates the actual energy storage parameters of the phase change cold storage system corresponding to the end of the preset time period.

[0209] In one embodiment, the predictive control parameters include the actual heat pump operating power of the heat pump, the actual cold storage capacity of the phase change cold storage system, the actual cold release power of the phase change cold storage system, and the power generation power of non-renewable energy. The control module is specifically used to:

[0210] Based on the actual heat pump operating power, actual cold storage capacity and actual cold release power, the operation of the phase change cold storage system is controlled;

[0211] Control the operation of the power supply system based on the power generated by non-renewable energy sources.

[0212] Each module in the above-mentioned cooling and power combined device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module.

[0213] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Fig.10 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a cold-electricity joint scheduling method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0214] Those skilled in the art will understand that Fig.10 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0215] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0216] Obtaining a non-adjustable prediction parameter of the target base station corresponding to the t-th moment in the preset time period;

[0217] The non-adjustable prediction parameters are input into the pre-built base station communication data processing model, cooling demand model and combined cooling and power supply scheduling model, and the prediction control parameters at the tth moment are obtained by solving. The base station communication data processing model is used to characterize the actual operation constraints of the data processing load of the target base station, the cooling demand model is used to characterize the operation constraints of the phase change cold storage system, and the combined cooling and power supply scheduling model is used to characterize the scheduling target of the target base station within a preset period;

[0218] The operation of the phase change thermal storage system and the power supply system is controlled based on the predicted control parameters.

[0219] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0220] The data processing loads corresponding to various data processing types are input into the base station communication data processing model; the data processing load heat generation rate and the electric cooling conversion efficiency are input into the refrigeration demand model; the data processing loads corresponding to various data processing types and the predicted power of renewable energy generation are input into the combined cooling and power supply scheduling model.

[0221] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0222] A base station communication data processing model is constructed according to an expression of the base station communication data processing model. The predicted data processing loads corresponding to the various data processing types include an immediate processing load, an immediate externally-processable load, and a time-shiftable load. The immediate processing load is used to characterize the predicted data processing load processed by the target base station at the current moment. The immediate externally-processable load is used to characterize the predicted data processing load transferred from the target base station to other base stations for processing at the current moment. The time-shiftable load is used to characterize the predicted data processing load transferred from the current moment to other moments for processing by the target base station.

[0223] The expression of the base station communication data processing model includes:

[0224]

[0225] 0≤α t ≤1,

[0226]

[0227]

[0228]

[0229] Where i≤t, represents the actual data processing load at the tth moment; They represent the immediate processing load and the immediate external processing load corresponding to the tth moment respectively; α t represents the proportion of the load that remains to be processed by the target base station in the instantaneous externally processable load corresponding to the t-th moment; represents the time-shiftable load actually processed corresponding to the t-th moment; represents the time-shiftable load corresponding to the i-th moment; It represents the time-shiftable load transferred from the i-th moment to the t-th moment, where T is the preset time period.

[0230] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0231] A refrigeration demand model is constructed according to an expression of the refrigeration demand model, wherein the expression of the refrigeration demand model includes:

[0232]

[0233]

[0234]

[0235]

[0236] in, Indicates the actual cooling power corresponding to the t-th moment; represents the actual data processing load corresponding to the tth moment; β represents the heat generation rate of the data processing load; and They represent the actual heat pump operating power and rated heat pump power corresponding to the tth moment respectively; η PCM Indicates the electric cooling conversion efficiency; and They respectively represent the actual cold storage capacity and the rated cold storage capacity of the phase change cold storage system at the tth moment.

[0237] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0238] According to the expression of the combined cooling and power supply model, a combined cooling and power supply model is constructed. The expression of the combined cooling and power supply model includes:

[0239]

[0240]

[0241]

[0242]

[0243]

[0244]

[0245] Among them, p G Indicates the power generation cost per unit power of non-renewable energy; and They represent the power generation and rated power generation of non-renewable energy sources at the tth moment respectively; p E represents the price per unit of power required to transfer the data processing load to other base stations; represents the predicted data processing load transferred to other base stations for processing at the tth time; α t represents the proportion of the load remaining in the target base station in the predicted data processing load transferred to other base stations for processing corresponding to the t-th time; represents the maximum data processing load that other base stations can receive at the t-th time; represents the power generation of renewable energy corresponding to the tth moment; represents the unabsorbed power of renewable energy corresponding to the t-th moment; Indicates the actual energy storage parameters of the phase change cold storage system corresponding to the start time of the preset time period; Indicates the actual energy storage parameters of the phase change cold storage system corresponding to the end of the preset time period.

[0246] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0247] Based on the actual heat pump operating power, actual cold storage capacity and actual cold release power, the operation of the phase change cold storage system is controlled; based on the power generation power of non-renewable energy, the operation of the power supply system is controlled.

[0248] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0249] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0250] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0251] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0252] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A cooling and electricity joint scheduling method, characterized in that: Applied in a target base station, the target base station includes a phase change cold storage system and a power supply system, and the method includes: Obtaining a non-adjustable prediction parameter of the target base station corresponding to the t-th moment in a preset time period; The non-adjustable prediction parameters are input into a pre-built base station communication data processing model, a refrigeration demand model, and a combined cooling and power supply scheduling model, and the prediction control parameters at the t-th moment are obtained by solving the model. The base station communication data processing model is used to characterize the actual operation constraints of the data processing load of the target base station. The refrigeration demand model is used to characterize the operation constraints of the phase change cold storage system. The combined cooling and power supply scheduling model is used to characterize the scheduling target of the target base station within the preset period. Controlling the operation of the phase change thermal storage system and the power supply system based on the predicted control parameters; The non-adjustable prediction parameters include predicted data processing loads corresponding to various data processing types, predicted power of renewable energy generation, data processing load heat production rate, and electric-cooling conversion efficiency of the heat pump in the phase-change cold storage system; the non-adjustable prediction parameters are input into a pre-built base station communication data processing model, a refrigeration demand model, and a combined cooling and power supply scheduling model, including: inputting data processing loads corresponding to the plurality of data processing types into the base station communication data processing model; Inputting the data processing load heat generation rate and the electric cooling conversion efficiency into the refrigeration demand model; Inputting the data processing loads corresponding to the multiple data processing types and the predicted power generation of renewable energy into the combined cooling and power supply scheduling model; Among them, the predicted data processing loads corresponding to the multiple data processing types include immediate processing load, immediate external processing load and time-shiftable load, the immediate processing load is used to characterize the predicted data processing load processed by the target base station at the current moment, the immediate external processing load is used to characterize the predicted data processing load transferred from the target base station to other base stations for processing at the current moment, the time-shiftable load is used to characterize the predicted data processing load transferred from the current moment to other moments processed by the target base station, and the expression of the base station communication data processing model includes: ， ， ， ， ， Where i≤t, represents the actual data processing load at the tth moment; , They represent the immediate processing load and the immediate external processing load corresponding to the t-th moment respectively; represents the proportion of the load that remains to be processed by the target base station in the instantaneous externally processable load corresponding to the t-th moment; represents the time-shiftable load actually processed corresponding to the t-th moment; represents the time-shiftable load corresponding to the i-th moment; represents the time-shiftable load transferred from the i-th moment to the t-th moment; T is the preset time period; The expression of the refrigeration demand model includes: ， ， ， ， in, Indicates the actual cooling power corresponding to the t-th moment; represents the actual data processing load corresponding to the t-th moment; represents the heat generation rate of data processing load; and They represent the actual heat pump operating power and the rated heat pump power corresponding to the t-th moment respectively; Indicates the electric cooling conversion efficiency; and They represent the actual cold storage capacity and rated cold storage capacity of the phase change cold storage system at the tth moment respectively; The expression of the combined cooling and power supply model includes: ； ； ； ； ； ； in, Indicates the power generation cost per unit power of non-renewable energy; and They represent the power generation and rated power generation of non-renewable energy sources corresponding to the t-th moment respectively; represents the price per unit of power required to transfer the data processing load to other base stations; represents the predicted data processing load transferred to other base stations for processing corresponding to the t-th time; represents the proportion of the load remaining in the target base station in the predicted data processing load transferred to other base stations for processing corresponding to the t-th time; represents the maximum data processing load that other base stations can receive at the t-th time; represents the power generation of renewable energy corresponding to the tth moment; represents the unabsorbed power of renewable energy corresponding to the t-th moment; Indicates the actual energy storage parameters of the phase change cold storage system corresponding to the start time of the preset time period; Indicates the actual energy storage parameters of the phase change cold storage system corresponding to the end of the preset time period.

2. The method according to claim 1, characterized in that The predicted control parameters include the actual heat pump operating power of the heat pump, the actual cold storage capacity of the phase change cold storage system, the actual cold release power of the phase change cold storage system, and the power generation power of the non-renewable energy source. The operation of the phase change cold storage system and the power supply system is controlled based on the predicted control parameters, including: Based on the actual heat pump operating power, the actual cold storage capacity and the actual cold release power, controlling the operation of the phase change cold storage system; Based on the power generation power of the non-renewable energy source, the operation of the power supply system is controlled.

3. The method according to claim 2, characterized in that The controlling the operation of the phase change cold storage system based on the actual heat pump operating power, the actual cold storage capacity and the actual cold release power includes: For the time interval from the t-1th moment to the tth moment, the phase change cold storage system is controlled to operate according to the actual heat pump operating power, the actual cold storage capacity, and the actual cold release power corresponding to the tth moment obtained by calculation; The controlling the operation of the power supply system based on the power generation power of the non-renewable energy source comprises: For the time interval from the t-1th moment to the tth moment, the non-renewable energy in the power supply system is controlled to generate electricity according to the calculated power generation power corresponding to the non-renewable energy at the tth moment.

4. The method according to any one of claims 1 to 3, characterized in that: The length of the preset time period is 1 day or 1 week.

5. The method according to any one of claims 1 to 3, characterized in that: The tth moment is one of multiple moments; the multiple moments are obtained by dividing the preset time period with a preset time length.

6. The method according to any one of claims 1 to 3, characterized in that: The instant processing load, the instant external processing load and the time-shiftable load are obtained by dividing the predicted data processing load according to the urgency of communication data.

7. A cooling and electricity joint dispatching device, characterized in that: Applied in a target base station, the target base station includes a phase change cold storage system and a power supply system, and the device includes: An acquisition module, used to acquire the non-adjustable prediction parameter of the target base station corresponding to the t-th moment in a preset time period; A solution module, used for inputting the non-adjustable prediction parameters into a pre-built base station communication data processing model, a refrigeration demand model, and a combined cooling and power supply scheduling model, and solving to obtain the prediction control parameters at the t-th moment, wherein the base station communication data processing model is used to characterize the actual operation constraints of the data processing load of the target base station, the refrigeration demand model is used to characterize the operation constraints of the phase change cold storage system, and the combined cooling and power supply scheduling model is used to characterize the scheduling target of the target base station within the preset period; A control module, used for controlling the operation of the phase change cold storage system and the power supply system based on the predicted control parameters; The non-adjustable prediction parameters include the predicted data processing load corresponding to various data processing types, the predicted power of renewable energy generation, the heat generation rate of the data processing load, and the electric-cooling conversion efficiency of the heat pump in the phase change cold storage system; the solution module is also used for: inputting data processing loads corresponding to the plurality of data processing types into the base station communication data processing model; Inputting the data processing load heat generation rate and the electric cooling conversion efficiency into the refrigeration demand model; Inputting the data processing loads corresponding to the multiple data processing types and the predicted power generation of renewable energy into the combined cooling and power supply scheduling model; Among them, the predicted data processing loads corresponding to the multiple data processing types include immediate processing load, immediate external processing load and time-shiftable load, the immediate processing load is used to characterize the predicted data processing load processed by the target base station at the current moment, the immediate external processing load is used to characterize the predicted data processing load transferred from the target base station to other base stations for processing at the current moment, the time-shiftable load is used to characterize the predicted data processing load transferred from the current moment to other moments processed by the target base station, and the expression of the base station communication data processing model includes: ， ， ， ， ， Where i≤t, represents the actual data processing load at the tth moment; , They represent the immediate processing load and the immediate external processing load corresponding to the t-th moment respectively; represents the proportion of the load that remains to be processed by the target base station in the instantaneous externally processable load corresponding to the t-th moment; represents the time-shiftable load actually processed corresponding to the t-th moment; represents the time-shiftable load corresponding to the i-th moment; represents the time-shiftable load transferred from the i-th moment to the t-th moment; T is the preset time period; The expression of the refrigeration demand model includes: ， ， ， ， in, Indicates the actual cooling power corresponding to the t-th moment; represents the actual data processing load corresponding to the t-th moment; represents the heat generation rate of data processing load; and They represent the actual heat pump operating power and the rated heat pump power corresponding to the t-th moment respectively; Indicates the electric cooling conversion efficiency; and They represent the actual cold storage capacity and rated cold storage capacity of the phase change cold storage system at the tth moment respectively; The expression of the combined cooling and power supply model includes: ； ； ； ； ； ； in, Indicates the power generation cost per unit power of non-renewable energy; and They represent the power generation and rated power generation of non-renewable energy sources corresponding to the t-th moment respectively; represents the price per unit of power required to transfer the data processing load to other base stations; represents the predicted data processing load transferred to other base stations for processing corresponding to the t-th time; represents the proportion of the load remaining in the target base station in the predicted data processing load transferred to other base stations for processing corresponding to the t-th time; represents the maximum data processing load that other base stations can receive at the t-th time; represents the power generation of renewable energy corresponding to the tth moment; represents the unabsorbed power of renewable energy corresponding to the t-th moment; Indicates the actual energy storage parameters of the phase change cold storage system corresponding to the start time of the preset time period; Indicates the actual energy storage parameters of the phase change cold storage system corresponding to the end of the preset time period.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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