Control method and device of cold storage cold source system, and electronic equipment

Abstract

The present application relates to the field of efficient energy application, and more specifically, to a control method for a cold storage cold source system, comprising: obtaining the working hours of a power consumption area; presetting the working mode of the cold storage cold source system; obtaining a cooling influence value and a power consumption influence value of the power consumption area according to the working hours of the power consumption area; obtaining an ambient temperature prediction value, a relative humidity prediction value, and a solar radiation prediction value of the power consumption area; obtaining a cooling load prediction value of the cold storage cold source system according to the cooling influence value and the power consumption influence value and the ambient temperature prediction value, the relative humidity prediction value, and the solar radiation prediction value of the power consumption area; obtaining a power consumption prediction value of the power consumption area according to the power consumption influence value; obtaining a photovoltaic power generation prediction value of a photovoltaic power generation system according to the solar radiation prediction value of the power consumption area; controlling the working mode of the cold storage cold source system according to the working hours of the power consumption area and the cooling load prediction value, the power consumption prediction value, and the photovoltaic power generation prediction value, to achieve efficient joint control.

Description

Technical Field

[0001] The present invention relates to the field of high-efficiency energy applications, and more specifically, to a control method and device, and electronic equipment with a cold storage cold source system. Background Art

[0002] An increasing number of industrial parks are increasing their photovoltaic power generation to achieve low-carbon and cost-effective energy consumption. PV power plants built in industrial parks typically operate on a self-consumption model with surplus power fed to the grid. Because the on-grid tariff for photovoltaic power is lower than the industrial-grade electricity price, maximizing the self-consumption rate of photovoltaic power is economically beneficial for industrial park operators. However, due to the temporal unevenness of photovoltaic power generation and the varying load distribution of consumer equipment at different times, some PV power plants have low self-consumption rates and a long payback period. For industrial parks equipped with photovoltaic, battery storage, and cold storage cooling systems, reasonable scheduling and control can theoretically achieve a high self-consumption rate for photovoltaic power generation, reduce utility power consumption during peak or peak electricity price periods, and ultimately lower electricity costs. However, due to the uncertainty of photovoltaic power generation, the time-varying nature of electricity load, and the diverse operating modes of cold storage cooling systems, manual scheduling based solely on experience is difficult to achieve effective results. Currently, there is a lack of control methods and devices for jointly scheduling these systems in this application scenario. Summary of the Invention

[0003] The present invention aims to overcome at least one defect (shortcoming) of the above-mentioned prior art and provide a control method and device, and electronic equipment for achieving the effect of controlling the system with cold storage cold source.

[0004] According to a first aspect of the present application, a control method for a cold storage cold source system is provided, the method comprising:

[0005] Get the working hours of the electricity consumption area;

[0006] Preset the working mode of the cold storage cold source system;

[0007] Obtaining a cooling impact value and a power consumption impact value of the power consumption area according to the working hours of the power consumption area;

[0008] Obtain the predicted values ​​of ambient temperature, relative humidity, and solar radiation in the power consumption area;

[0009] Obtaining a cooling load prediction value of the cold storage cold source system according to the cooling influence value and the power consumption influence value and the ambient temperature prediction value, relative humidity prediction value, and solar radiation prediction value of the power consumption area;

[0010] Obtaining a power consumption prediction value for the power consumption area according to the power consumption impact value;

[0011] Obtaining a predicted value of photovoltaic power generation of the photovoltaic power generation system according to a predicted value of solar radiation in the power consumption area;

[0012] The operating mode of the cold storage cold source system is controlled according to the operating time of the power consumption area and the cooling load prediction value, the power consumption prediction value, and the photovoltaic power generation prediction value.

[0013] The control method of the cold source system with cold storage can jointly dispatch the systems in actual application scenarios with multiple systems such as photovoltaic power generation system, mains power system, battery, etc., thereby fully reducing production costs and improving production efficiency.

[0014] Optionally, the working mode of the preset cold storage cold source system includes one or more of a cold source cold storage mode, a cold storage tank cooling mode, a cold source direct supply mode, a cold source and cold storage tank joint supply mode, and a cold source storage and supply mode.

[0015] Presetting the working mode of the cold storage cold source system can realize automated management, reduce manual intervention, save time and energy, and facilitate the control system to quickly enter the working state according to the preset mode without the need to reconfigure parameters each time; the preset working mode is usually based on best practices or standard process design, which can reduce errors caused by improper human operation, and ensure that each operation is performed in accordance with the preset rules, avoiding inconsistent results caused by various environmental factors. The preset mode can quickly restore the system to a safe state and reduce the impact of faults on the system. The preset working mode of the cold storage cold source system is a key step in the control strategy and plays an important role.

[0016] Optionally, controlling the operating mode of the cold storage cold source system according to the working hours of the power consumption area and the cooling load prediction value, the power consumption prediction value, and the photovoltaic power generation prediction value includes:

[0017] Obtain the current effective cooling capacity of the cold storage tank in the cold storage cold source system;

[0018] Obtaining a total cooling load prediction value of the cold storage cold source system for the entire day according to the cooling load prediction value;

[0019] Comparing the effective cooling capacity with the total cooling load prediction value to obtain a first comparison result;

[0020] The operating mode of the cold storage cold source system is controlled according to the first size comparison result.

[0021] Optionally, controlling the operating mode of the cold storage cold source system according to the first size comparison result specifically includes:

[0022] If the effective cooling capacity is greater than or equal to the total cooling load prediction value, controlling the cold storage cold source system to execute the cold storage tank cooling mode;

[0023] If the effective cooling capacity is less than the total cooling load prediction value, obtaining a first difference result between the effective cooling capacity and the total cooling load prediction value;

[0024] The operating mode of the cold storage cold source system is controlled according to the first difference result.

[0025] The acquisition of partial real-time data and predicted value data to adjust the control strategy, data-based control can help managers or control systems more accurately evaluate the current situation, identify problems and predict trends, while reducing human subjective judgment and bias, and avoiding the accuracy of control affected by various factors such as the environment. By collecting data through multiple sensors and feeding it back to the automated control system, automatic adjustment and optimization of the production process can be achieved. The real-time nature of data prediction enables the control system to respond to changes quickly and adjust the control strategy in time. In short, data-based control can bring higher efficiency, better decision-making support and stronger adaptability to enterprises, organizations or systems, and improve the efficiency of the entire control strategy.

[0026] Optionally, controlling the operating mode of the cold storage cold source system according to the first difference result includes:

[0027] Preset the cooling capacity proportion of the cold source equipment system when the cold source equipment system and the cold storage tank in the cold storage cold source system jointly provide cooling;

[0028] A preset unit time, wherein the photovoltaic power generation system corresponds to a photovoltaic power generation prediction value in each unit time, and the power consumption area corresponds to a power consumption prediction value in each unit time;

[0029] Performing a difference calculation on the photovoltaic power generation prediction value per unit time and the corresponding power consumption prediction value per unit time to obtain a second difference result;

[0030] The operating mode of the cold storage cold source system is controlled according to the second difference result and the cooling capacity proportion.

[0031] The second difference result is the surplus of photovoltaic power generation. The second difference result is used to start the cold source equipment system, and the surplus of photovoltaic power generation is used to provide cooling to the cold source equipment system, thereby realizing the applicability of the photovoltaic power generation system.

[0032] Optionally, controlling the operating mode of the cold storage cold source system according to the second difference result and the cooling capacity proportion includes:

[0033] Calculate the unit time distribution of the cooling source equipment system for direct cooling or cold storage and the corresponding cooling capacity ratio allowed to be turned on based on the second difference result of each unit time;

[0034] Corresponding the proportion of cooling capacity allowed to be turned on and the working time for each unit time to obtain a corresponding result;

[0035] The cold storage cold source system corresponds to a cooling load prediction value per unit time;

[0036] Calculate the effective cooling capacity for the working interval R of cooling and / or cold storage in the power consumption area according to the cooling load prediction value corresponding to each unit time;

[0037] Determine whether the working interval R belongs to the interval of the corresponding result;

[0038] If the working interval R is not within the interval of the corresponding result, the cold storage cold source system is controlled to execute the cold storage tank cooling mode;

[0039] If the working interval R is within the interval of the corresponding result, then obtaining the total cooling capacity percentage of the cooling source equipment system that is allowed to be turned on within the working interval R;

[0040] Comparing the cooling capacity proportion and the second difference result to obtain a second comparison result;

[0041] The operating mode of the cold storage cold source system is controlled according to the second size comparison result.

[0042] Controlling the operating mode of the cold storage cold source system according to the second size comparison result specifically includes:

[0043] If the sum of the cooling capacity proportions is greater than or equal to the sum of all second difference results, the operating mode of the cold storage cold source system is controlled according to the cooling capacity proportions allowed to be turned on, specifically:

[0044] If the cooling load prediction value per unit time is greater than the cooling capacity ratio allowed to be turned on per unit time, the cold storage cold source system is controlled to execute the cold source and cold storage tank joint supply mode;

[0045] If the cooling load prediction value per unit time is less than or equal to the cooling capacity ratio allowed to be opened per unit time, and the effective cooling capacity of the cold storage tank is the maximum cooling capacity, the cold storage cold source system is controlled to execute the cold source direct supply mode;

[0046] If the predicted cooling load value per unit time is less than or equal to the cooling capacity ratio allowed to be opened per unit time, and the effective cooling capacity of the cold storage tank has not reached the maximum cooling capacity, the cold storage cold source system is controlled to execute the cold source storage and supply mode;

[0047] If the sum of the cooling capacity proportions is less than the sum of all second difference results, the cooling capacity proportions and the effective cooling capacity are summed to obtain the total cooling capacity, and the operating mode of the cold storage cold source system is controlled according to the total cooling capacity, specifically:

[0048] The total cooling capacity is obtained as a working interval R1 for cooling and / or storing cooling in the power consumption area;

[0049] If the total cooling capacity is the period after the cooling and / or cold storage in the power consumption area is completed and there is a peak or spike electricity price period, during the electricity price period:

[0050] If a unit time is not within the working interval R1 but within the working time R, the electricity price is at the peak / spike period, the cooling load forecast value of the unit time is greater than the cooling capacity ratio allowed to be turned on in the corresponding unit time, and the effective cooling capacity of the cold storage tank does not reach the maximum cooling capacity, the cold storage cold source system is controlled to execute the cold source and cold storage tank joint supply mode in the corresponding unit time;

[0051] If a unit time is not within the working interval R1 but within the working time R, the cooling load prediction value of the unit time is less than or equal to the cooling capacity ratio allowed to be opened in the corresponding unit time, and the effective cooling capacity of the cold storage tank does not reach the maximum cooling capacity, the cold storage cold source system is controlled to perform the cold source storage and supply mode in the corresponding unit time;

[0052] If a unit time is not within the working interval R1 but within the working time R, the cooling load prediction value of the unit time is less than or equal to the cooling capacity ratio allowed to be opened in the corresponding unit time, the effective cooling capacity of the cold storage tank reaches the maximum cooling capacity, and the cold storage cold source system is controlled to execute the cold source direct supply mode in the corresponding unit time;

[0053] If a certain unit time is not in the working interval R1, the electricity price is in the valley / flat period, and the effective cooling capacity of the cold storage tank does not reach the maximum cooling capacity, the cold storage cold source system is controlled to perform the cold source storage and supply mode in the working interval R;

[0054] If a unit time is not in the working interval R1, the electricity price is in the valley / flat period, and the effective cooling capacity of the cold storage tank reaches the maximum cooling capacity, the cold storage cold source system is controlled to perform the cold source direct supply mode in the working interval R;

[0055] If the total cooling capacity is the time when the cooling and / or cold storage in the power consumption area is completed and there is no peak or spike electricity price period, within the electricity price period:

[0056] If a unit time falls within the working time R, and the cooling load prediction value of the unit time is greater than the cooling capacity ratio allowed to be turned on in the corresponding unit time, the cooling source system is controlled to execute the cooling source and cold storage tank combined supply mode in the corresponding unit time;

[0057] If a unit time falls within the working time R, the cooling load prediction value of the unit time is less than or equal to the cooling capacity ratio allowed to be turned on in the corresponding unit time, and the effective cooling capacity of the cold storage tank does not reach the maximum cooling capacity, the cold source system is controlled to perform the cold source storage and supply mode in the corresponding unit time;

[0058] If a certain unit time is within the working time R, the cooling load prediction value of the unit time is less than or equal to the proportion of cooling capacity allowed to be turned on in the corresponding unit time, the effective cooling capacity of the cold storage tank reaches the maximum cooling capacity, and the cold source system is controlled to execute the cold source direct supply mode in the corresponding unit time.

[0059] After the photovoltaic power generation system meets its own load demand, if there is any surplus, this excess electricity can be used to drive the cold source equipment system, which is the second difference result. During operation, the cold source equipment system selects the appropriate preset working mode based on the real-time monitored cooling demand data and the storage status of the cold storage tank to achieve optimal energy configuration, which helps to reduce electricity costs and improve the operating efficiency of the entire system, thereby improving the efficiency of production operations and providing strong support for the sustainable development of the enterprise.

[0060] Optionally, the control method of the cold storage cold source system further includes:

[0061] If it is non-working hours in the electricity consumption area and the electricity price is at a valley value, the cold storage cold source execution system executes the cold source cold storage mode; and / or,

[0062] The power consumption area also includes a battery, and the preset working mode of the battery includes one or more of charging, discharging, and standby;

[0063] Obtaining the power consumption of the power consumption area and the photovoltaic power generation power of the photovoltaic power generation system per unit time;

[0064] The difference between the power consumption of the power consumption area within the unit time and the photovoltaic power generation power of the photovoltaic power generation system is calculated to obtain a third difference result, and the working mode of the battery is controlled according to the peak, flat and valley time period information of the electricity price and the third difference result.

[0065] Optionally, controlling the operating mode of the battery according to the peak, flat, and valley time period information of the electricity price and the third difference result includes:

[0066] If the electricity price per unit time is at a valley value, the battery is charged until it is fully charged or the valley electricity price period has ended;

[0067] If the electricity price for a certain unit time is at a flat value and the third difference result is a positive value, and there is no sharp or peak electricity price period during the day corresponding to the unit time, the battery is discharged at a value less than or equal to the third difference result and the set maximum discharge power;

[0068] If the electricity price for a certain unit time is at a flat value and the third difference result is a positive value, and there is a sharp or peak electricity price period during the day corresponding to the unit time and the battery power has not reached the maximum storage capacity, charging is commanded according to the set maximum charging power;

[0069] If the electricity price for a certain unit time is at a peak value and the third difference result is a positive value, discharge the battery at a value less than or equal to the third difference result and the set maximum discharge power until the battery is fully discharged;

[0070] If the electricity price per unit time is at a peak value and the third difference result is a positive value, the battery is discharged at a smaller value that is less than or equal to the third difference result and the set maximum discharge power until the battery is fully discharged.

[0071] The control of the battery's operating mode based on the peak, flat, and off-peak electricity price information can rationally arrange the battery's operation during different electricity price periods, storing electricity during off-peak periods (such as at night) and supplying electricity in place of the mains during peak or high-peak periods, thereby reducing unnecessary electricity consumption and significantly reducing electricity bills. The time-of-use electricity price mechanism uses price signals to guide users to adjust their electricity usage behavior, reducing electricity load during peak periods while increasing electricity demand during off-peak periods, thereby balancing load fluctuations in the power grid and improving the operating efficiency of the power system. Using time-of-use electricity price information, devices can flexibly adjust their operating modes based on electricity price periods. Through intelligent control strategies, devices can dynamically adjust their operating modes based on real-time electricity price information, such as peak shaving and off-peak filling, dynamic capacity expansion, etc., thereby enhancing the flexibility and adaptability of the power system. Setting the battery's operation based on the peak, flat, and off-peak electricity price information can achieve economic optimization and improve the overall operating efficiency and sustainability of the power system.

[0072] According to a second aspect of the present application, a control device with a cold storage cold source system is provided, comprising:

[0073] A first acquisition module is used to obtain the working hours of the power consumption area;

[0074] A preset module is used to preset the working mode of the cold storage cold source system;

[0075] A second acquisition module is used to obtain the cooling impact value and the power consumption impact value of the power consumption area according to the working hours of the power consumption area;

[0076] The third acquisition module is used to obtain the predicted value of the ambient temperature, the predicted value of the relative humidity, and the predicted value of the solar radiation in the power consumption area;

[0077] a fourth acquisition module, configured to acquire a cooling load prediction value of the cold storage cold source system according to the cooling influence value and the power consumption influence value and the ambient temperature prediction value, relative humidity prediction value, and solar radiation prediction value of the power consumption area;

[0078] A fifth acquisition module, configured to acquire a power consumption prediction value of the power consumption area according to the power consumption impact value;

[0079] A sixth acquisition module, configured to acquire a predicted value of photovoltaic power generation of the photovoltaic power generation system according to the predicted value of solar radiation of the power consumption area;

[0080] The control module is used to control the working mode of the cold storage cold source system according to the working time of the power consumption area and the cooling load prediction value, the power consumption prediction value, and the photovoltaic power generation prediction value.

[0081] According to a third aspect of the present application, an electronic device is provided, including:

[0082] a memory for storing one or more computer programs;

[0083] The processor implements the control method of the cold storage cold source system according to the first aspect when the one or more computer programs are executed by the processor.

[0084] According to a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement a control method for a cold storage cold source system according to the first aspect when executed.

[0085] Based on any of the above aspects, the embodiments of the present application provide a control method, device, electronic device and computer storage medium with a cold storage cold source system. For power consumption areas with photovoltaic, cold storage cold source systems and battery storage systems, the charging and discharging modes of the battery energy storage system and the operating mode of the cold source system with cold storage are flexibly scheduled based on the photovoltaic power generation forecast value, the power load forecast value of the power consumption area, and the power consumption forecast value. When there is surplus photovoltaic power generation, the excess power generation is used as much as possible for direct cooling, cold storage and battery storage. When photovoltaic power generation is insufficient, the cold storage tank is used to discharge the cold and the battery is discharged to reduce the mains electricity demand of the park. The cold storage tank discharge and battery discharge must be used first during the peak and peak electricity price periods to achieve the purpose of reducing the electricity cost of the park. The cold storage tank also assumes the role of partial energy storage, thereby reducing the investment in the battery storage system and improving the operating efficiency of the entire system. BRIEF DESCRIPTION OF THE DRAWINGS

[0086] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0087] Figure 1 A schematic application scenario diagram of a control method for a cold storage cold source system provided in this embodiment.

[0088] Figure 2 This is a flow chart of a control method for a cold storage cold source system provided in this embodiment.

[0089] Figure 3 This is a schematic diagram of the functional modules of a control device with a cold storage cold source system provided in this embodiment.

[0090] Figure 4 This is a schematic diagram of the structure of the electronic device provided in this embodiment. DETAILED DESCRIPTION

[0091] The figures in this application are for illustrative purposes only and are not to be construed as limiting the present application. To better illustrate the following embodiments, some components in the figures may be omitted, enlarged, or reduced in size, and do not represent actual product dimensions. Those skilled in the art will appreciate that some well-known structures and their descriptions may be omitted from the figures.

[0092] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0093] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0094] In terms of energy utilization, since the on-grid price of photovoltaic electricity is lower than the industrial level electricity price, for industrial park operators, maximizing the self-consumption rate of photovoltaic power generation is the most economically efficient. However, due to the uneven distribution of photovoltaic power generation and the different load distribution of electrical equipment in different time periods, some photovoltaic power plants have low self-consumption rates and a long payback period. For example, a typical photovoltaic power plant generates a large amount of power between 12:00 and 2:00 p.m. when there is abundant sunshine. However, this is also the time when workers are off work and equipment is shut down, resulting in a low electricity load. Meanwhile, between 3:00 p.m. and 6:00 p.m., factories are still operating, but due to the gradual decrease in sunlight intensity, photovoltaic power generation decreases and cannot meet production electricity needs, necessitating the use of mains electricity. However, this time range often includes peak or even peak electricity prices, resulting in unsatisfactory economic benefits. To solve this problem, using batteries to store excess photovoltaic power generation and then discharging it to supply power loads when sunlight is insufficient is a technically ideal solution. However, battery storage has high costs, a short effective service life, and a long payback period. Therefore, the joint control of photovoltaic power generation systems, cold storage cold source systems, and batteries is an issue that needs to be solved.

[0095] This embodiment provides a technical solution that can solve the above-mentioned problem. The specific implementation methods of this application are described in detail below with reference to the accompanying drawings.

[0096] For example, a schematic diagram of a control application scenario of a cold storage cold source system provided in an embodiment of the present application is provided. Figure 1 As shown, the application scenario at least includes a server 100 and a terminal 200 that can communicate with the server 100. The server 100 has the function of collecting and storing data; the terminal device 200 has the function of processing data.

[0097] It is understandable that the server 100 can be an independent electronic device or a cluster of multiple electronic devices; the terminal 200 can be a smart phone terminal, a personal computer, a tablet computer, a car terminal, etc., but is not limited thereto.

[0098] In one practicable manner, the server 100 and the terminal 200 can respectively execute the control method of the cold storage cold source system provided in the embodiment of the present application, or, optionally, the control method of the cold storage cold source system provided in the embodiment of the present application is partially executed in the server 100 and partially executed in the terminal 200.

[0099] like Figure 2 As shown, this embodiment provides a control method for a cold storage cold source system, which may include the following steps:

[0100] S110, obtaining the working hours of the power consumption area;

[0101] In this embodiment, the power consumption area may include only photovoltaic power generation systems and cold storage cold source systems, or it may include multiple systems such as photovoltaic power generation systems, cold storage cold source systems, etc. The working time refers to the specific time when the equipment needs to run. The specific running time of the equipment can be obtained based on the manual working time, thereby obtaining the relevant data required by the control system.

[0102] In an optional implementation, the control device obtains the manual working hours of the power consumption area, including mainly commuting time, weekdays and rest day information, and determines the equipment operating time of the cold storage cold source system based on the manual working time. The cold storage cold source system needs to store cold at night and release cold during the day. The method of obtaining the equipment operating time includes but is not limited to this.

[0103] S120, presetting the working mode of the cold storage cold source system;

[0104] In this embodiment, the working mode can be set according to the advantages of the device itself, or preset according to the needs of the power consumption area. The working mode of the cold storage cold source system can also be preset based on the advantages of the device itself and the needs of the power consumption area.

[0105] In an optional implementation, the working modes of the cold storage cold source system are preset based on the advantages of the equipment itself and the needs of the electricity consumption area, specifically: cold source cold storage mode, cold storage tank cooling mode, cold source direct supply mode, cold source and cold storage tank joint supply mode, cold source storage and supply mode; the cold source cold storage mode refers to the cold source equipment converting electrical energy into cold energy and storing it in the cold storage tank. This mode is generally used when the electricity price is at a low point, such as 0:00 to 8:00 in some areas (the electricity price low point period varies from region to region); the cold storage tank cooling mode refers to releasing the cold energy stored in the cold storage tank for use by the air conditioning terminal. Based on economic considerations, this mode should be applied preferentially during periods when the electricity price is at a peak or peak value, to avoid turning on high-power cold source equipment for cooling during this period; the cold source direct supply mode refers to turning on the cold source equipment for cooling and directly supplying cold energy to the air conditioning terminal equipment. This mode is generally used in the following scenarios: there is a cooling load demand at the current air-conditioning terminal, the cooling capacity of the cold storage tank has been consumed, or there is still cooling capacity stored in the cold storage tank but it needs to be reserved for use during the period when the electricity price is higher that day; the cold source and cold storage tank joint supply mode refers to the cold source equipment and the cold storage tank jointly providing cooling capacity for the air-conditioning terminal equipment. At this time, the cold source equipment is generally partially put into use, and its electric power is less than the electric power at full load; this mode is generally used in the following scenarios: the current cooling load demand at the air-conditioning terminal is large, but from an economic point of view, it is not suitable to fully use the direct supply of the cold source or the cooling mode of the cold storage tank; the cold source storage and supply mode refers to turning on the cold source equipment for cooling, and part of its cooling capacity is directly supplied to the air-conditioning terminal, and the other part is stored in the cold storage tank. This mode is generally used when the city electricity price is relatively low in the current period or there is surplus photovoltaic power generation, but the subsequent period of cooling demand is the peak or peak value of electricity price;

[0106] It can be understood that the data obtained and recorded by the control device from the cold storage cold source system include power consumption, power consumption, air conditioning terminal cooling load, current cold storage capacity of the cold storage tank and system operation status. The recording period is 5 minutes. The control commands sent by the control device to the cold storage cold source system include working mode selection commands (cold source storage, cold storage tank discharge, direct supply of cold source, joint supply of cold source and cold storage tank, cold source storage and supply at the same time), cold source capacity adjustment commands, and cold source capacity adjustment commands are used to control the capacity input percentage of the cold source equipment, such as 0%, 25%, 50%, 75%, 100%, etc.

[0107] S130, obtaining a cooling impact value and a power consumption impact value of the power consumption area according to the working hours of the power consumption area;

[0108] In this embodiment, the cooling impact value is associated with cooling demand, and the power consumption impact value is associated with power consumption.

[0109] In a preferred implementation, the power consumption area is divided into n units according to the same or similar working and rest time of the personnel. The work and rest of the n units will affect the cooling load and power consumption respectively. Dividing the power consumption area into n units facilitates data statistics and prediction. In order to distinguish and explain, when explaining the impact of these n units on the cooling load, they are marked as Ln, that is, units L1, L2, ..., L n ; When explaining the impact of these n units on power consumption, mark it as D n , that is, units D1, D2, ..., D n .

[0110] In an optional implementation, the method for obtaining the cooling impact value is that the control device automatically obtains or manually inputs the work calendar from the attendance system, mainly the information of working hours, working days and rest days, and runs the corresponding logic to automatically identify each hour L1~L n The cooling impact values ​​for each unit are calculated. For example, if a unit is working at a certain hour, the cooling impact value for that hour is set to: the unit's design cooling load / total design load; if the unit is not working, the value is set to 0. For one unit, for example, its 24-hour cooling impact values ​​are L1_00 to L1_23. Assuming the cooling impact value for a certain hour is set to 0.05, if unit L1 starts at 8:00 and ends at 18:00, then the cooling impact values ​​for L1_08 to L1_17 are 0.05, while the cooling impact values ​​for L1_00 to L1_07 and L1_18 to L1_23 are 0. In a specific embodiment, the cooling impact value is primarily related to cooling demand. For example, if there is a short off-duty period at noon, but cooling is still needed during this period, this period can be set as working hours. The calculation of Ln_0 to Ln_23 for other units is similar. After the above calculation, the cooling impact value of n units corresponding to a certain hour is obtained by accumulation, and the total cooling impact value in that hour is calculated as TL#=L1_#+L2_#+...+L n _#, the symbol # represents the #th hour of the day, which is a value between 0 and 23.

[0111] The control device automatically obtains or manually inputs the work calendar from the attendance system, mainly including the information of commuting time, working days and rest days, and runs the corresponding logic to automatically mark each hour D1~D nEach unit's power consumption impact value is calculated. If a unit's working hours are within a certain hour, the power consumption impact value for that hour is set to the unit's design power. If the unit is not working, the power consumption impact value is set to 0. For unit D1, for example, its 24-hour power consumption impact values ​​are D1_00 to D1_23. Assuming unit D1's design power is 36kW, if unit D1's working hours are 8:00 AM and its off-duty hours are 12:00 PM, the power consumption impact values ​​for D1_08 to D1_11 are 36, while the power consumption impact values ​​for D1_00 to L1_07 and L1_12 to L1_23 are 0. Note that these power consumption impact values ​​primarily relate to energy consumption. If key equipment continues to operate during off-duty hours, this period can be set as working hours. The calculations for Dn_00 to Dn_23 for other units are similar. After the above calculations, the power consumption impact value of n units corresponding to a certain hour is accumulated to calculate the power consumption impact value of that hour TD#=D1_#+D2_#+...+Dn_#, where the symbol # represents the #th hour of the day and is a value between 0 and 23. The method of obtaining the cooling impact value and the power consumption impact value includes but is not limited to this.

[0112] S140, obtaining the predicted value of ambient temperature, predicted value of relative humidity, and predicted value of solar radiation in the power consumption area;

[0113] In this embodiment, the predicted value of the ambient temperature, the predicted value of the relative humidity, and the predicted value of the solar radiation in the power consumption area can be obtained by first using historical record data and related data, and then using the corresponding prediction model to obtain the predicted data based on the corresponding prediction model, or by using statistical analysis and time series methods, or based on big data and AI tools, etc.

[0114] In an optional implementation, the control device collects the detection values ​​of the ambient temperature and humidity sensors and the detection values ​​of the solar radiation sensor and records them at intervals of 5 minutes. The control device obtains the predicted values ​​of the temperature, relative humidity, and solar radiation values ​​for each hour in the next 24 hours at the project location from the weather forecast service API on the Internet. The method of obtaining the predicted values ​​of the ambient temperature, relative humidity, and solar radiation in the power consumption area includes but is not limited to this.

[0115] S150, obtaining a cooling load prediction value of the cold storage cold source system according to the cooling influence value and the power consumption influence value and the ambient temperature prediction value, relative humidity prediction value, and solar radiation prediction value of the power consumption area;

[0116] In this embodiment, the method for obtaining the ambient temperature prediction value, the relative humidity prediction value, and the solar radiation prediction value to obtain the cooling load prediction value of the cold storage cold source system can be to use the cooling influence value and the power consumption influence value, or through statistical analysis and time series methods, or based on big data and AI tools and other methods.

[0117] In an optional implementation, the control device uses the cooling impact value to determine the total cooling impact value for the corresponding unit time, the hourly value H (e.g., if it's 8:00, then H = 8), and the weather forecast for the corresponding hour's ambient temperature, relative humidity, and solar radiation value as characteristic variables. These variables are then input into a cooling load prediction neural network algorithm model deployed in the control device CTRL. The model then calculates the cooling load as the target variable, i.e., the cooling load prediction values ​​GL0 to GL23 for each hour of the day, expressed in kWh. For example, the cooling load prediction value for 8:00 is GL8, and the cooling load prediction value for 16:00 is GL16. Subsequently, GLn is used to represent the cooling load prediction value for a particular hour. The neural network algorithm model for cooling load prediction has been trained and deployed in the control device CTRL using historical data, including recorded ambient temperature, relative humidity, solar radiation, the cooling impact value for the corresponding hour, and the actual cooling load. After determining the hourly cooling load prediction value, GL0 to GL23 are accumulated to determine the cooling load prediction value for the entire day, GL_Day. Obtaining the cooling load prediction value for the cold storage cold source system includes, but is not limited to, this method.

[0118] S160: Obtain a power consumption prediction value for the power consumption area according to the power consumption impact value;

[0119] In this embodiment, the power consumption prediction value of the power consumption area may be obtained according to the power consumption impact value, or the power consumption prediction value of the power consumption area may be directly obtained by using other prediction methods.

[0120] In an optional implementation, the control device automatically obtains or manually inputs a work calendar from the attendance system, primarily including information on get off work and off-work hours, weekdays, and rest days. Based on this information, the control device automatically identifies the power consumption impact value for each unit (D1-Dn) for each hour. If a unit is working for a certain hour, the power consumption impact value for that hour is set to the unit's design power; if it is not working, the power consumption impact value is set to 0. For unit D1, for example, its 24-hour power consumption impact values ​​are D1_00-D1_23. Assuming unit D1's design power is 36kW, if unit D1's start time is 8:00 and end time is 12:00, the power consumption impact value for D1_08-D1_11 is 36, while the power consumption impact values ​​for D1_00-L1_07 and L1_12-L1_23 are 0. Note that these power consumption impact values ​​primarily relate to energy consumption. If key equipment remains operational during off-get off work hours, this period can be set as working hours. The calculation of Dn_00 to Dn_23 for other units is similar. After the above calculations, the power consumption impact value for a particular hour is calculated by accumulating the power consumption impact values ​​of n units corresponding to that hour, TD# = D1_# + D2_# + ... + Dn_#, where the symbol # represents the #th hour of the day and is a value between 0 and 23. For example, the total power consumption impact value TD8 at 8 a.m. = D1_08 + D2_08 + ... + Dn_08, and the total power consumption impact values ​​for other hourly periods are similarly calculated. The power consumption impact value TD# of the control device for that hour and the hourly value H (if it is currently 8 a.m., then H = 8) are used as feature variables and input into the power consumption load prediction neural network algorithm model deployed in the control device. The hourly power consumption forecast values ​​for all systems in the power park, excluding the cold storage and cold source systems, are calculated, namely the hourly power consumption forecast values ​​GD0 to GD23, in kWh. For example, the predicted power consumption value at 8 o'clock is GD8, and the predicted power consumption value at 16 o'clock is GD16. Subsequently, GDn is used to represent the predicted power consumption value of EL2 for a particular hour. It is assumed here that the neural network algorithm model used for power consumption prediction has been trained using historical data (power consumption impact value records, hourly values, and actual power consumption recorded for that hour) and has been deployed in the control device. Methods for obtaining the power consumption prediction value include, but are not limited to, this.

[0121] S170, obtaining a predicted value of photovoltaic power generation of the photovoltaic power generation system according to a predicted value of solar radiation in the power consumption area;

[0122] In this embodiment, the predicted value of solar radiation in the power consumption area is used to obtain the predicted value of photovoltaic power generation of the photovoltaic power generation system, which can be obtained through a prediction model or other means of predicting data.

[0123] In an optional implementation, the control device uses the hourly solar radiation value and hourly value H (e.g., at 8 o'clock, H=8) obtained from the weather forecast as feature variables and inputs them into the photovoltaic power generation neural network algorithm model deployed in the control device CTRL to calculate the target variable photovoltaic power generation, i.e., the photovoltaic power generation forecast values ​​PV0 to PV23 for each hour, in kWh. For example, the photovoltaic power generation at 8 o'clock is PV8, and the photovoltaic power generation at 16 o'clock is PV16. Subsequently, PVn is used to represent the photovoltaic power generation forecast value for a particular hour. It is assumed here that the neural network algorithm model for photovoltaic power generation forecasting has been trained using the historically recorded solar radiation sensor measured values ​​and the actual recorded hourly photovoltaic power generation data and has been deployed in the control device. The means for obtaining the photovoltaic power generation forecast value of the photovoltaic power generation system includes, but is not limited to, this.

[0124] S180 , controlling the operating mode of the cold storage cold source system according to the operating hours of the power consumption area and the cooling load prediction value, the power consumption prediction value, and the photovoltaic power generation prediction value.

[0125] In this embodiment, the working mode of the cold storage cold source system is controlled according to the working hours of the power consumption area and the cooling load prediction value, the power consumption prediction value, and the photovoltaic power generation prediction value. The working mode of the cold storage cold source system is preset, and joint scheduling is performed according to relevant data.

[0126] In an optional implementation, the cooling and cooling time of the cold storage cold source system is determined according to the working hours of the human. Specifically, during the off-peak electricity price period when no cooling is provided, the cold storage cold source system performs the cold storage mode until the cold storage tank is fully charged. When cooling starts, the control device detects the effective cooling capacity in the cold storage tank, assuming it is TANK_L, in kWh.

[0127] The capacity of the cold source equipment system that can work in conjunction with the cold storage tank is preset. Specifically, the rated cooling capacity RC of the cold source system per hour is input into the control device, in kWh; in addition, the rated hourly power consumption RD of the cold source system when fully loaded is input, in kWh. The cold source equipment system can have five capacity input plans between 0 and 100%, namely RC0 (0), RC1 (0.25RC), RC2 (0.5RC), RC3 (0.75RC), and RC4 (RC). The corresponding hourly power demands are RD0, RD1, RD2, RD3, and RD4, in kWh, and RD0 < RD1 < RD2 < RD3 < RD4.

[0128] The control device compares the effective cooling capacity TANK_L in the cold storage tank with the total cooling load forecast value GL_Day. If TANK_L ≥ GL_Day, the cold storage tank cooling mode is directly implemented during cooling. If TANK_L < GL_Day, the difference between GL_Day and TANK_L is calculated to obtain the cooling capacity gap GTD (in kWh) that needs to be supplemented by the cold source equipment, and the strategy described below is implemented:

[0129] The control device compares the hourly photovoltaic power generation prediction values ​​PV0~PV23 with the hourly power consumption prediction values ​​GD0~GD23 of other systems in the power park except the cold storage source and cold source system, and subtracts the hourly power consumption prediction values ​​GD0~GD23 from the photovoltaic power generation prediction value of each hour, such as PG0=PV0-GD0, PG1=PV1-GD1, ..., PG23=PV23-GD23. After calculation, find the hour that meets PG#≥RD1 and is in the cooling period (# represents 0~23 Assuming that the hour values ​​that meet the above requirements are t1, t2, ..., tn in the order of early to late time, the corresponding cooling source equipment capacities allowed to be put into use are RCt1, RCt2, ..., RCtn. RCtn refers to the cooling source capacity with an electric power less than but closest to PGtn during the period of tn. For example, PGt1 in period t1 has the relationship RD3>PGt1>RD2, then the cooling source capacity RC2 corresponding to the power load of RD2 is turned on in period t1, and the same applies to the other periods.

[0130] Taking into account the case where the cold storage tank is full, if RCtn>GLn, the excess cold capacity of the cold source equipment cannot be stored in the cold storage tank, and the system will automatically unload and operate according to the GLn load. Therefore, in this case, RCtn is corrected to the value of GLn.

[0131] Through the above calculation and correction, the time distribution {t1, t2, ..., tn} and the corresponding cold source capacity allowed to be turned on {RCt1, RCt2, ..., RCtn} when there is surplus photovoltaic power generation that can be used to turn on the cold source equipment for direct cooling or cold storage are obtained. At this time, the hourly power consumption corresponding to the cold source system with cold storage is marked as RDXn (RDX is one of the described RD1 to RD4, and n corresponds to the hourly value).

[0132] Based on the predicted hourly cooling load demand distribution, calculate the estimated time that the cooling capacity of the cold storage tank TANK_L can be maintained from the current start in the cold storage tank cooling mode. It is assumed that it can be maintained for R hours.

[0133] If there are elements distributed in {t1, t2, ..., tn} hours within a time range of R hours, these elements are distributed as ta1, ta2..., tak, so there is a set The corresponding cold source capacity allowed to be turned on in the set {ta1, ta2..., tak} is also marked as {RCta1, RCta2,..., RCtak}.

[0134] If (RCta1+RCta2+...+RCtak)≥GTD (cooling capacity gap), then the capacity RCtak of the corresponding cooling source equipment is opened in the time periods ta1, ta2, ..., tak. In the set {ta1, ta2..., tak} time period, the cooling source system executes according to the following command mode:

[0135] A. If the predicted cooling load GLn for this period is greater than RCtak, the control device CTRL will issue a command for the combined supply mode of the cooling source and the cold storage tank, and the cooling source capacity will be based on RCtak;

[0136] B. If the predicted cooling load GLn for this period is less than or equal to RCtak, and the cold storage tank is full, the control device CTRL issues a cold source direct supply mode command, and the cold source capacity is issued according to RCtak, and then the cold source equipment automatically matches the cooling load;

[0137] C. If the predicted cooling load GLn for this period is less than or equal to RCtak, and the cold storage tank is not full, the control device CTRL issues a cold source storage and supply mode command, and the cold source capacity is based on RCtak;

[0138] If (RCta1+RCta2+...+RCtak) (PV power generation) < GTD (cooling capacity gap), then calculate the duration of cooling capacity (TANK_L+RCta1+RCta2+...+RCtak) from the current time. This is assumed to be R1 hours. If there is a peak or spike electricity price period from R1 hours to the end of cooling, then from the start of cooling to the first peak or spike electricity price period after R1 hours, the cooling system will operate as follows:

[0139] A1. During a time period belonging to the set {t1, t2, ..., tn}, and during a peak or spike electricity price period, if the predicted cooling load GLn is greater than RCtn, and the cooling capacity of the cold storage tank is not zero, the control device CTRL issues a command for the cold source and cold storage tank combined supply mode, and the cold source system capacity is issued according to RCtn;

[0140] B1. During the time period belonging to the set {t1, t2, ..., tn}, if the predicted cooling load GLn for that period is less than or equal to RCtan, and the cooling capacity of the cold storage tank is not 100%, the control device CTRL issues a cold source simultaneous storage and supply command, and the cooling source system capacity is issued according to RCtn. If the cooling capacity of the cold storage tank is 100%, a cold source direct supply command is issued, and the cooling source system capacity is issued according to RCtn.

[0141] C1. From the start of cooling until the first peak or peak electricity price period after R1 hours, as long as there is a valley electricity price or flat electricity price period, as long as the cold storage tank cooling capacity is not 100%, the simultaneous storage and supply mode will be activated, and the cooling source system capacity will operate at 100%. When the cold storage tank cooling capacity is 100%, the direct supply mode will be used.

[0142] If there is no peak or spike electricity price period between R1 hour and the end of cooling, the cooling system will operate as follows:

[0143] A2. During the period of {t1, t2, ..., tn}, the predicted cooling load GLn is greater than RCtn. The control device CTRL issues a command for the combined supply mode of the cooling source and the cold storage tank. The cooling source system issues a command based on the capacity of RCt.

[0144] B2. During the time period {t1, t2, ..., tn}, if the predicted cooling load GLn is less than or equal to RCtan and the cold storage tank capacity is not 100%, the control device issues a simultaneous storage and supply command, and the cold source system follows RCtn. If the cold storage tank capacity is 100%, the control device issues a direct cold supply command, and the cold source system automatically follows the air conditioner terminal load.

[0145] C2. If (RCta1+RCta2+...+RCtak)≥GTD (cooling capacity gap) and (RCta1+RCta2+...+RCtak)<GTD (cooling capacity gap), the cooling mode command is issued as follows:

[0146] a1. When the cold storage tank has cold capacity, the cold storage tank cooling mode is issued;

[0147] a2. When there is no cold capacity in the cold storage tank, the cold source direct supply mode is activated and the cold source output capacity is adjusted by the cold source system itself;

[0148] In a preferred implementation, the operating mode of the battery is controlled according to the peak, flat, and valley time period information of the electricity price and the third difference result, specifically as follows:

[0149] A3. During the off-peak electricity price period, the control device issues a preset maximum charging power command to charge the battery until it is fully charged or the off-peak electricity price period has ended.

[0150] B3. During the period of flat electricity price and when the value of (electricity power consumption - photovoltaic power generation) is positive, if there is no sharp or peak electricity price period in the following time of the day, the control device will issue a discharge command to the battery to discharge at a power not greater than (electricity power consumption - photovoltaic power generation) and the preset maximum discharge power; if there is a sharp or peak electricity price period in the following time of the day and the battery power is not 100%, the preset maximum charging power command will be used for charging.

[0151] C3. During the peak electricity price period and when the value of (electricity consumption - photovoltaic power generation) is positive, if any of the following four conditions is met, a command is issued to discharge the battery at a power not exceeding (electricity consumption - photovoltaic power generation) and the preset maximum discharge power until it is fully discharged.

[0152] 1. If there is no peak electricity price period in the rest of the day;

[0153] 2. Subsequently, when there is a peak period, the photovoltaic power generation PVtsn predicted during the peak period is greater than the predicted load power consumption GDtsn of the park;

[0154] 3. There is a valley or flat electricity price period before the peak electricity price period arrives;

[0155] 4. Before the peak electricity price period arrives, there is a period of time that satisfies (PVn-GDn-RDXn-maximum battery charge capacity in hours) and is positive;

[0156] Note: PVn is the predicted value of photovoltaic power generation during the period, GDn is the power load value of EL2 during the period, RDXn is the load of EL1 expected to be put into operation during the period, and EL1 and EL2 constitute the distribution system in the power consumption area.

[0157] D3. During the peak electricity price period and when the value of (electricity consumption - photovoltaic power generation) is positive, if none of the above four conditions are met and there is a peak electricity price period in the subsequent period, if the estimated power gap ∑(GDn+RDxn-PVn) during the peak period is positive and greater than the current storage capacity of the battery system, a standby command is issued to the battery, that is, neither charging nor discharging; if ∑(GDn+RDxn-PVn) is positive and less than the current storage capacity of the battery system, a discharge command is issued to the battery until ∑(GDn+RDxn-PVn) is equal to the current storage capacity of the battery system, and then the battery enters the standby state.

[0158] Note: GDn is the electricity load value of EL2 load in this period, RDXn is the load of EL1 expected to be put into use in this period, and the expected power gap in the peak period ∑(GDn+RDxn-PVn) represents the cumulative value of the power gap in the peak period of not less than 1 hour.

[0159] E3. During the peak electricity price period and when the value of (electricity consumption - photovoltaic power generation) is positive, a command is issued to discharge the battery at a power not exceeding (electricity consumption - photovoltaic power generation) and the preset maximum discharge power until the battery is fully discharged.

[0160] F3. When none of the above conditions are met, the control device sends a standby command to the battery system, that is, neither charging nor discharging.

[0161] In a more preferred implementation, the control device calculates all data once before the start of each hour, and the time that has passed on the day is no longer included in the calculation. Before the start of each hour, the strategy for the subsequent hours of the day is output again based on the new hourly weather forecast value and the current state of the system, and the next hour is executed according to the updated strategy.

[0162] like Figure 3 As shown, the embodiment of the present application further provides a control device 210 with a cold storage cold source system. Optionally, the control device 210 with a cold storage cold source system may include:

[0163] The first acquisition module 211 is used to obtain the working hours of the power consumption area;

[0164] In this embodiment, the first acquisition module 211 can be used to perform Figure 2 As shown in step S110, for a detailed description of the first acquisition module 211, reference may be made to the description of step S110.

[0165] A preset module 212 is used to preset the working mode of the cold storage cold source system;

[0166] In this embodiment, the preset module 212 can be used to execute Figure 2 As shown in step S120, for a detailed description of the preset module 212, reference may be made to the description of step S120.

[0167] The second acquisition module 213 is configured to acquire a cooling impact value and a power consumption impact value of the power consumption area according to the working hours of the power consumption area;

[0168] In this embodiment, the second acquisition module 213 can be used to perform Figure 2 As shown in step S130, for a detailed description of the second obtaining module 213, reference may be made to the description of step S130.

[0169] The third acquisition module 214 is used to obtain the predicted value of the ambient temperature, the predicted value of the relative humidity, and the predicted value of the solar radiation in the power consumption area;

[0170] In this embodiment, the third acquisition module 214 can be used to perform Figure 2 As shown in step S140 , for a detailed description of the third acquisition module 214 , reference may be made to the description of step S140 .

[0171] A fourth acquisition module 215 is configured to acquire a cooling load prediction value of the cold storage cold source system based on the cooling impact value and the power consumption impact value and the ambient temperature prediction value, relative humidity prediction value, and solar radiation prediction value of the power consumption area;

[0172] In this embodiment, the third acquisition module 215 can be used to perform Figure 2 As shown in step S150, for a detailed description of the third acquisition module 215, reference may be made to the description of step S150.

[0173] A fifth acquisition module 216 is configured to acquire a power consumption prediction value of the power consumption area according to the power consumption impact value;

[0174] In this embodiment, the fifth acquisition module 216 can be used to perform Figure 2 As shown in step S160 , for a detailed description of the fifth obtaining module 216 , reference may be made to the description of step S160 .

[0175] A sixth acquisition module 217 is configured to acquire a predicted value of photovoltaic power generation of the photovoltaic power generation system according to the predicted value of solar radiation of the power consumption area;

[0176] In this embodiment, the sixth acquisition module 217 can be used to perform Figure 2 As shown in step S170 , for a detailed description of the sixth obtaining module 217 , reference may be made to the description of step S170 .

[0177] The control module 218 is configured to control the operating mode of the cold storage cold source system according to the operating hours of the power consumption area and the cooling load prediction value, the power consumption prediction value, and the photovoltaic power generation prediction value.

[0178] In this embodiment, the control module 218 can be used to execute Figure 2 For the detailed description of the control module 218 in step S180 , please refer to the description of step S180 .

[0179] It can be understood that the above-mentioned device embodiments and the above-mentioned method embodiments can correspond to each other, and similar descriptions of the device embodiments can refer to the method embodiments. To avoid repetition, no further description is given here. A control device with a cold storage cold source system provided in an embodiment of the present application can execute a control method for a cold storage cold source system provided in any embodiment of the present application, and has functional modules and beneficial effects corresponding to the execution method. The functional modules of the control device with a cold storage cold source system can be implemented in the form of hardware, can be implemented by instructions in the form of software, and can also be implemented by a combination of hardware and software modules.

[0180] Specifically, each step of the method embodiment of the present application can be completed by the hardware integrated logic circuit and / or software instructions in the processor. The steps of the control method of the cold storage cold source system in combination with the embodiment of the present application can be directly embodied as a hardware coding processor for execution, or can be completed by a combination of hardware and software modules in the coding processor. Optionally, the software module can be located in a random access memory, a read-only memory, a programmable read-only memory, a flash memory, an electrically erasable programmable memory, a register, or other storage media. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps in the above method embodiment in combination with its hardware.

[0181] The embodiment of the present application provides an electronic device 410, whose structure is as follows Figure 4 The electronic device 410 may be Figure 1 The server 100 or the terminal 200 is shown.

[0182] like Figure 4 As shown, the electronic device 410 includes a memory 411, a processor 412, a communication module 413 and an input / output interface 414, etc. Optionally, the memory 411, the processor 412, the communication module 413 and the input / output interface 414 can be connected and communicated through a bus 415.

[0183] The memory 411 is used to store one or more computer programs and transmit the code of the computer program to the processor 412; when the one or more computer programs are executed by the processor 412, a control method for a cold storage cold source system in an embodiment of the present application is implemented.

[0184] Optionally, the electronic device 410 can be connected to a network via a communication module 413 to communicate with other devices, such as a terminal or a server, via the network to achieve data interaction. The electronic device 410 can be various forms of digital computers, such as desktop computers, servers, workstations, mainframe computers, or other types of computers. The electronic device 410 can also be various forms of mobile terminals, such as smartphones, tablet computers, wearable devices (such as helmets, glasses, watches, etc.), and other similar mobile terminals.

[0185] Optionally, the electronic device 410 can be connected to the required input / output devices, such as a keyboard, a display device, etc., through the input / output interface 414. The electronic device 410 itself can have a display device, and can also be connected to other display devices through the input / output interface 414. Optionally, a storage device, such as a hard disk, can also be connected through the input / output interface 414, so that data in the electronic device 410 can be stored in the storage device, or data in the storage device can be read, and data in the storage device can also be stored in the memory 411. It can be understood that the input / output interface 414 can be a wired interface or a wireless interface. Depending on the actual application scenario, the device connected to the input / output interface 414 can be a component of the electronic device 410, or it can be an external device connected to the electronic device 410 when needed.

[0186] Optionally, the memory 411 may be a volatile memory and / or a non-volatile memory, the volatile memory may be a random access memory, etc., and the non-volatile memory may be a read-only memory, a programmable read-only memory, an erasable programmable read-only memory, an electrically erasable programmable read-only memory or a flash memory, etc.

[0187] Optionally, the computer program stored in the processor 412 may be divided into one or more modules, which are stored in the memory 411 and executed by the processor 412 to implement the method provided in the embodiment. The one or more modules may be a series of computer program instruction segments capable of implementing specific functions, and the computer program instruction segments are used to describe the execution process of the computer program in the electronic device 410.

[0188] Optionally, processor 412 may be any general-purpose and / or specialized processing component with processing and computing capabilities. Examples of processor 412 include, but are not limited to, a central processing unit, a graphics processing unit, a digital signal processor, various specialized artificial intelligence computing chips, various processors for running machine learning model algorithms, and may also be any appropriate controller, microcontroller, processor, etc. Processor 412 executes the various methods and processes of this embodiment, illustratively, such as a control method for a cold storage cold source system according to an embodiment of the present application.

[0189] Optionally, the bus 415 may include a path for transmitting information. The bus 415 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. Depending on their functions, the bus 415 may be classified as an address bus, a data bus, a control bus, or the like.

[0190] In an optional implementation, the present embodiment further provides a computer storage medium having a computer program stored thereon. When the computer program is executed by a computer, the computer is enabled to perform the method of the above-described method embodiment. Part or all of the computer program can be loaded and / or installed into the memory 411 of the electronic device 410. When the computer program is executed by the processor 412, one or more steps of the control method of a cold storage cold source system of the present embodiment can be performed.

[0191] Optionally, the computer-readable storage medium may be a random access memory, a read-only memory, a programmable read-only memory, an erasable programmable read-only memory, an electrically erasable programmable read-only memory, or the like.

[0192] Obviously, the above embodiments of the present application are merely examples for clearly illustrating the technical solution of the present application, and are not intended to limit the specific implementation methods of the present application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the claims of the present application shall be included in the scope of protection of the claims of the present application.

Claims

1. A control method for a cold storage cold source system, characterized in that: The control method is applied to a power consumption area with at least a photovoltaic power generation system and a cold storage cold source system, and includes: Get the working hours of the electricity consumption area; Preset the working mode of the cold storage cold source system; Obtaining a cooling impact value and a power consumption impact value of the power consumption area according to the working hours of the power consumption area; Obtain the predicted values ​​of ambient temperature, relative humidity, and solar radiation in the power consumption area; Obtaining a cooling load prediction value of the cold storage cold source system according to the cooling influence value and the power consumption influence value and the ambient temperature prediction value, relative humidity prediction value, and solar radiation prediction value of the power consumption area; Obtaining a power consumption prediction value for the power consumption area according to the power consumption impact value; Obtaining a predicted value of photovoltaic power generation of the photovoltaic power generation system according to a predicted value of solar radiation in the power consumption area; Controlling the operating mode of the cold storage cold source system according to the working hours of the power consumption area and the cooling load prediction value, the power consumption prediction value, and the photovoltaic power generation prediction value; The controlling of the working mode of the cold storage cold source system according to the working hours of the power consumption area and the cooling load prediction value, the power consumption prediction value, and the photovoltaic power generation prediction value includes: Obtain the current effective cooling capacity of the cold storage tank in the cold storage cold source system; Obtaining a total cooling load prediction value of the cold storage cold source system for the entire day according to the cooling load prediction value; Comparing the effective cooling capacity with the total cooling load prediction value to obtain a first comparison result; controlling the operating mode of the cold storage cold source system according to the first size comparison result; The controlling the operating mode of the cold storage cold source system according to the first size comparison result specifically includes: If the effective cooling capacity is greater than or equal to the total cooling load prediction value, controlling the cold storage cold source system to execute the cold storage tank cooling mode; If the effective cooling capacity is less than the total cooling load prediction value, obtaining a first difference result between the effective cooling capacity and the total cooling load prediction value; controlling the operating mode of the cold storage cold source system according to the first difference result; The controlling the operating mode of the cold storage cold source system according to the first difference result includes: Preset the cooling capacity proportion of the cold source equipment system when the cold source equipment system and the cold storage tank in the cold storage cold source system jointly provide cooling; A preset unit time, wherein the photovoltaic power generation system corresponds to a photovoltaic power generation prediction value in each unit time, and the power consumption area corresponds to a power consumption prediction value in each unit time; Performing a difference calculation on the photovoltaic power generation prediction value per unit time and the corresponding power consumption prediction value per unit time to obtain a second difference result; controlling the operating mode of the cold storage cold source system according to the second difference result and the cooling capacity proportion; The controlling the working mode of the cold storage cold source system according to the second difference result and the cooling capacity proportion includes: Calculate the unit time distribution of the cooling source equipment system for direct cooling or cold storage and the corresponding cooling capacity ratio allowed to be turned on based on the second difference result of each unit time; Corresponding the proportion of cooling capacity allowed to be turned on and the working time for each unit time to obtain a corresponding result; The cold storage cold source system corresponds to a cooling load prediction value per unit time; Calculate the effective cooling capacity for the working interval R of the power consumption area according to the cooling load prediction value corresponding to each unit time; Determine whether the working interval R belongs to the interval of the corresponding result; If the working interval R is not within the interval of the corresponding result, the cold storage cold source system is controlled to execute the cold storage tank cooling mode; If the working interval R is within the interval of the corresponding result, then obtaining the total cooling capacity percentage of the cooling source equipment system that is allowed to be turned on within the working interval R; Comparing the cooling capacity proportion and the second difference result to obtain a second comparison result; controlling the operating mode of the cold storage cold source system according to the second size comparison result; The controlling the operating mode of the cold storage cold source system according to the second size comparison result specifically includes: If the sum of the cooling capacity proportions is greater than or equal to the sum of all second difference results, the operating mode of the cold storage cold source system is controlled according to the cooling capacity proportions allowed to be turned on, specifically: If the cooling load prediction value per unit time is greater than the cooling capacity ratio allowed to be turned on per unit time, the cold storage cold source system is controlled to execute the cold source and cold storage tank joint supply mode; If the cooling load prediction value per unit time is less than or equal to the cooling capacity ratio allowed to be opened per unit time, and the effective cooling capacity of the cold storage tank is the maximum cooling capacity, the cold storage cold source system is controlled to execute the cold source direct supply mode; If the predicted cooling load value per unit time is less than or equal to the cooling capacity ratio allowed to be opened per unit time, and the effective cooling capacity of the cold storage tank has not reached the maximum cooling capacity, the cold storage cold source system is controlled to execute the cold source storage and supply mode; If the sum of the cooling capacity proportions is less than the sum of all second difference results, the cooling capacity proportions and the effective cooling capacity are summed to obtain the total cooling capacity, and the operating mode of the cold storage cold source system is controlled according to the total cooling capacity, specifically: The total cooling capacity is obtained as a working interval R1 for cooling and / or storing cooling in the power consumption area; If the total cooling capacity is the period after the cooling and / or cold storage in the power consumption area is completed and there is a peak or spike electricity price period, during the electricity price period: If a unit time is not within the working interval R1 but within the working interval R, the electricity price is at the peak / spike period, the cooling load forecast value of the unit time is greater than the cooling capacity ratio allowed to be turned on in the corresponding unit time, and the effective cooling capacity of the cold storage tank does not reach the maximum cooling capacity, the cold storage cold source system is controlled to execute the cold source and cold storage tank joint supply mode in the corresponding unit time; If a unit time is not in the working interval R1 but in the working interval R, the cooling load prediction value of the unit time is less than or equal to the cooling capacity ratio allowed to be opened in the corresponding unit time, and the effective cooling capacity of the cold storage tank does not reach the maximum cooling capacity, the cold storage cold source system is controlled to perform the cold source storage and supply mode in the corresponding unit time; If a unit time is not in the working range R1 but in the working range R, the cooling load prediction value of the unit time is less than or equal to the cooling capacity ratio allowed to be opened in the corresponding unit time, the effective cooling capacity of the cold storage tank reaches the maximum cooling capacity, and the cold storage cold source system is controlled to perform the cold source direct supply mode in the corresponding unit time; If a certain unit time is not in the working interval R1, the electricity price is in the valley / flat period, and the effective cooling capacity of the cold storage tank does not reach the maximum cooling capacity, the cold storage cold source system is controlled to perform the cold source storage and supply mode in the working interval R; If a unit time is not in the working interval R1, the electricity price is in the valley / flat period, and the effective cooling capacity of the cold storage tank reaches the maximum cooling capacity, the cold storage cold source system is controlled to perform the cold source direct supply mode in the working interval R; If the total cooling capacity is the time when the cooling and / or cold storage in the power consumption area is completed and there is no peak or spike electricity price period, within the electricity price period: If a unit time is within the working range R, and the cooling load prediction value of the unit time is greater than the cooling capacity ratio allowed to be turned on in the corresponding unit time, the cooling source system is controlled to execute the cooling source and cold storage tank combined supply mode in the corresponding unit time; If a unit time is within the working interval R, the cooling load prediction value of the unit time is less than or equal to the cooling capacity ratio allowed to be opened in the corresponding unit time, and the effective cooling capacity of the cold storage tank has not reached the maximum cooling capacity, the cold source system is controlled to perform the cold source storage and supply mode in the corresponding unit time; If a unit time is in the working range R, the cooling load prediction value of the unit time is less than or equal to the proportion of cooling capacity allowed to be turned on in the corresponding unit time, the effective cooling capacity of the cold storage tank reaches the maximum cooling capacity, and the cold source system is controlled to execute the cold source direct supply mode in the corresponding unit time.

2. The control method of a cold storage cold source system according to claim 1, characterized in that: The working modes of the preset cold storage cold source system include one or more of a cold source cold storage mode, a cold storage tank cold release mode, a cold source direct supply mode, a cold source and cold storage tank joint supply mode, and a cold source storage and supply mode.

3. The control method of a cold storage cold source system according to claim 1, further comprising: If it is non-working hours in the electricity consumption area and the electricity price is at a valley value, the cold storage cold source system executes the cold source cold storage mode; and / or, The power consumption area also includes a battery, and the preset working mode of the battery includes one or more of charging, discharging, and standby; Obtaining the power consumption of the power consumption area and the photovoltaic power generation power of the photovoltaic power generation system per unit time; The difference between the power consumption of the power consumption area within the unit time and the photovoltaic power generation power of the photovoltaic power generation system is calculated to obtain a third difference result, and the working mode of the battery is controlled according to the peak, flat and valley time period information of the electricity price and the third difference result.

4. The control method of a cold storage cold source system according to claim 3, wherein the controlling the operating mode of the battery according to the peak, flat, and valley time period information of the electricity price and the third difference result comprises: If the electricity price per unit time is at a valley value, the battery is charged until it is fully charged or the valley electricity price period has ended; If the electricity price for a certain unit time is at a flat value and the third difference result is a positive value, and there is no sharp or peak electricity price period during the day corresponding to the unit time, the battery is discharged at a value less than or equal to the third difference result and the set maximum discharge power; If the electricity price for a certain unit time is at a flat value and the third difference result is a positive value, and there is a sharp or peak electricity price period during the day corresponding to the unit time and the battery power has not reached the maximum storage capacity, charging is commanded according to the set maximum charging power; If the electricity price for a certain unit time is at a peak value and the third difference result is a positive value, discharge the battery at a value less than or equal to the third difference result and the set maximum discharge power until the battery is fully discharged; If the electricity price per unit time is at a peak value and the third difference result is a positive value, the battery is discharged at a smaller value that is less than or equal to the third difference result and the set maximum discharge power until the battery is fully discharged.

5. A control device with a cold storage cold source system, characterized in that: The control device comprises: A first acquisition module is used to obtain the working hours of the power consumption area; A preset module is used to preset the working mode of the cold storage cold source system; A second acquisition module is used to obtain the cooling impact value and the power consumption impact value of the power consumption area according to the working hours of the power consumption area; The third acquisition module is used to obtain the predicted value of the ambient temperature, the predicted value of the relative humidity, and the predicted value of the solar radiation in the power consumption area; a fourth acquisition module, configured to acquire a cooling load prediction value of the cold storage cold source system according to the cooling influence value and the power consumption influence value and the ambient temperature prediction value, relative humidity prediction value, and solar radiation prediction value of the power consumption area; A fifth acquisition module, configured to acquire a power consumption prediction value of the power consumption area according to the power consumption impact value; A sixth acquisition module, configured to acquire a predicted value of photovoltaic power generation of the photovoltaic power generation system according to the predicted value of solar radiation in the power consumption area; a control module, configured to control an operating mode of the cold storage cold source system according to the operating hours of the power consumption area and the cooling load prediction value, the power consumption prediction value, and the photovoltaic power generation prediction value; The controlling of the working mode of the cold storage cold source system according to the working hours of the power consumption area and the cooling load prediction value, the power consumption prediction value, and the photovoltaic power generation prediction value includes: Obtain the current effective cooling capacity of the cold storage tank in the cold storage cold source system; Obtaining a total cooling load prediction value of the cold storage cold source system for the entire day according to the cooling load prediction value; Comparing the effective cooling capacity with the total cooling load prediction value to obtain a first comparison result; controlling the operating mode of the cold storage cold source system according to the first size comparison result; The controlling the operating mode of the cold storage cold source system according to the first size comparison result specifically includes: If the effective cooling capacity is greater than or equal to the total cooling load prediction value, controlling the cold storage cold source system to execute the cold storage tank cooling mode; If the effective cooling capacity is less than the total cooling load prediction value, obtaining a first difference result between the effective cooling capacity and the total cooling load prediction value; controlling the operating mode of the cold storage cold source system according to the first difference result; The controlling the operating mode of the cold storage cold source system according to the first difference result includes: Preset the cooling capacity proportion of the cold source equipment system when the cold source equipment system and the cold storage tank in the cold storage cold source system jointly provide cooling; A preset unit time, wherein the photovoltaic power generation system corresponds to a photovoltaic power generation prediction value in each unit time, and the power consumption area corresponds to a power consumption prediction value in each unit time; Performing a difference calculation on the photovoltaic power generation prediction value per unit time and the corresponding power consumption prediction value per unit time to obtain a second difference result; controlling the operating mode of the cold storage cold source system according to the second difference result and the cooling capacity proportion; The controlling the working mode of the cold storage cold source system according to the second difference result and the cooling capacity proportion includes: Calculate the unit time distribution of the cooling source equipment system for direct cooling or cold storage and the corresponding cooling capacity ratio allowed to be turned on based on the second difference result of each unit time; Corresponding the proportion of cooling capacity allowed to be turned on and the working time for each unit time to obtain a corresponding result; The cold storage cold source system corresponds to a cooling load prediction value per unit time; Calculate the effective cooling capacity for the working interval R of the power consumption area according to the cooling load prediction value corresponding to each unit time; Determine whether the working interval R belongs to the interval of the corresponding result; If the working interval R is not within the interval of the corresponding result, the cold storage cold source system is controlled to execute the cold storage tank cooling mode; If the working interval R is within the interval of the corresponding result, then obtaining the total cooling capacity percentage of the cooling source equipment system that is allowed to be turned on within the working interval R; Comparing the cooling capacity proportion and the second difference result to obtain a second comparison result; controlling the operating mode of the cold storage cold source system according to the second size comparison result; The controlling the operating mode of the cold storage cold source system according to the second size comparison result specifically includes: If the sum of the cooling capacity proportions is greater than or equal to the sum of all second difference results, the operating mode of the cold storage cold source system is controlled according to the cooling capacity proportions allowed to be turned on, specifically: If the cooling load prediction value per unit time is greater than the cooling capacity ratio allowed to be turned on per unit time, the cold storage cold source system is controlled to execute the cold source and cold storage tank joint supply mode; If the cooling load prediction value per unit time is less than or equal to the cooling capacity ratio allowed to be opened per unit time, and the effective cooling capacity of the cold storage tank is the maximum cooling capacity, the cold storage cold source system is controlled to execute the cold source direct supply mode; If the predicted cooling load value per unit time is less than or equal to the cooling capacity ratio allowed to be opened per unit time, and the effective cooling capacity of the cold storage tank has not reached the maximum cooling capacity, the cold storage cold source system is controlled to execute the cold source storage and supply mode; If the sum of the cooling capacity proportions is less than the sum of all second difference results, the cooling capacity proportions and the effective cooling capacity are summed to obtain the total cooling capacity, and the operating mode of the cold storage cold source system is controlled according to the total cooling capacity, specifically: The total cooling capacity is obtained as a working interval R1 for cooling and / or storing cooling in the power consumption area; If the total cooling capacity is the period after the cooling and / or cold storage in the power consumption area is completed and there is a peak or spike electricity price period, during the electricity price period: If a unit time is not within the working interval R1 but within the working interval R, the electricity price is at the peak / spike period, the cooling load forecast value of the unit time is greater than the cooling capacity ratio allowed to be turned on in the corresponding unit time, and the effective cooling capacity of the cold storage tank does not reach the maximum cooling capacity, the cold storage cold source system is controlled to execute the cold source and cold storage tank joint supply mode in the corresponding unit time; If a unit time is not in the working interval R1 but in the working interval R, the cooling load prediction value of the unit time is less than or equal to the cooling capacity ratio allowed to be opened in the corresponding unit time, and the effective cooling capacity of the cold storage tank does not reach the maximum cooling capacity, the cold storage cold source system is controlled to perform the cold source storage and supply mode in the corresponding unit time; If a unit time is not in the working range R1 but in the working range R, the cooling load prediction value of the unit time is less than or equal to the cooling capacity ratio allowed to be opened in the corresponding unit time, the effective cooling capacity of the cold storage tank reaches the maximum cooling capacity, and the cold storage cold source system is controlled to perform the cold source direct supply mode in the corresponding unit time; If a certain unit time is not in the working interval R1, the electricity price is in the valley / flat period, and the effective cooling capacity of the cold storage tank does not reach the maximum cooling capacity, the cold storage cold source system is controlled to perform the cold source storage and supply mode in the working interval R; If a unit time is not in the working interval R1, the electricity price is in the valley / flat period, and the effective cooling capacity of the cold storage tank reaches the maximum cooling capacity, the cold storage cold source system is controlled to perform the cold source direct supply mode in the working interval R; If the total cooling capacity is the time when the cooling and / or cold storage in the power consumption area is completed and there is no peak or spike electricity price period, within the electricity price period: If a unit time is within the working range R, and the cooling load prediction value of the unit time is greater than the cooling capacity ratio allowed to be turned on in the corresponding unit time, the cooling source system is controlled to execute the cooling source and cold storage tank combined supply mode in the corresponding unit time; If a unit time is within the working interval R, the cooling load prediction value of the unit time is less than or equal to the cooling capacity ratio allowed to be opened in the corresponding unit time, and the effective cooling capacity of the cold storage tank has not reached the maximum cooling capacity, the cold source system is controlled to perform the cold source storage and supply mode in the corresponding unit time; If a unit time is in the working range R, the cooling load prediction value of the unit time is less than or equal to the proportion of cooling capacity allowed to be turned on in the corresponding unit time, the effective cooling capacity of the cold storage tank reaches the maximum cooling capacity, and the cold source system is controlled to execute the cold source direct supply mode in the corresponding unit time.

6. An electronic device, characterized in that: include: a memory for storing one or more computer programs; The processor implements the control method of the cold storage cold source system according to any one of claims 1 to 4 when the one or more computer programs are executed by the processor.

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