Flow-state ice cold storage circulation energy-saving method and device in refrigeration house and medium

Abstract

The invention belongs to the technical field of refrigeration control of refrigeration houses, and provides an energy-saving method and device for ice slurry storage circulation in a refrigeration house and a medium, and the method comprises the following steps: monitoring operation parameters of the refrigeration house in real time, and obtaining and analyzing data to predict a cold load demand; in a low-ebb electricity price period, refrigerating parameters are automatically adjusted according to cold load prediction and cold storage tank reserves, and ice making is implemented; when the temperature of the refrigeration house is close to a set threshold value, energy-saving regulation and control are performed in combination with a prediction result According to the cold load and reserve conditions, different working condition stages of the refrigeration house are determined, and finally a circulation regulation and control result is generated based on the flow-state ice circulation requirement; according to the method, through cold load prediction and accurate regulation and control according to different working conditions, invalid operation and excessive refrigeration of refrigeration equipment are avoided, energy consumption is effectively reduced, ice making and cold storage are achieved through the low-ebb electricity price, electric energy is reasonably utilized, and the electricity utilization cost is reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of cold storage refrigeration control, and in particular relates to a fluid ice storage cold cycle energy-saving method, equipment and medium in a cold storage. Background Art

[0002] With the rapid development of cold chain logistics and food preservation, the energy consumption of cold storage, a key low-temperature storage facility, is becoming increasingly prominent. Traditional cold storage refrigeration systems mostly use mechanical compression refrigeration, which has many shortcomings during operation.

[0003] Currently, most cold storage refrigeration control technologies use fixed temperature thresholds to control the start and stop of refrigeration equipment. When the cold storage temperature reaches a preset upper limit, the refrigeration equipment starts cooling; when the temperature drops to a preset lower limit, the equipment stops. This simple temperature control method does not take into account the dynamic changes in the cold storage's cooling load and can easily lead to frequent starts and stops of refrigeration equipment. This not only increases equipment wear and tear, but also reduces overall operating efficiency due to high energy consumption at the moment of startup. For example, during periods of frequent inbound and outbound cargo, the cold storage's cooling load fluctuates dramatically, making it difficult for this control method to respond quickly. This can cause excessive temperature fluctuations, affecting the quality of cargo storage. Furthermore, prolonged high-load operation of the refrigeration equipment significantly increases energy consumption.

[0004] Furthermore, most cold storage facilities fail to fully utilize the difference in peak and off-peak electricity prices. They operate their refrigeration equipment in the same mode throughout the day, maintaining high cooling intensity even during peak hours when electricity prices are higher, resulting in high electricity costs. Furthermore, some cold storage facilities lack effective cold storage mechanisms, failing to convert off-peak electricity into stored cold for flexible use during peak hours, resulting in low energy efficiency.

[0005] At the same time, traditional cold storage refrigeration systems have a single-minded approach to determining operating conditions, often determining cooling or shutdown status based solely on temperature conditions, while ignoring key factors such as the cold storage tank's capacity and cooling load forecasts. This one-sided approach to determining operating conditions makes it difficult for the system to accurately adjust based on actual demand. Even when the cold storage tank has sufficient cooling capacity, the refrigeration equipment may still be blindly activated to make ice, resulting in energy waste. When the cooling capacity is insufficient, the refrigeration strategy cannot be adjusted in a timely manner, making it impossible to ensure stable operation of the cold storage.

[0006] To this end, those skilled in the art have proposed an energy-saving method, equipment and medium for the fluid ice storage cycle in a cold storage, aiming to avoid ineffective operation and over-cooling of refrigeration equipment through cooling load prediction and precise regulation according to different working conditions, effectively reduce energy consumption, and make use of low-valley electricity prices to make ice and store cold, rationally utilize electricity and reduce electricity costs. Summary of the Invention

[0007] In order to solve the above technical problems, the present invention provides a fluid ice storage cycle energy-saving method, equipment and medium in a cold storage to solve the problems raised in the background technology.

[0008] According to a first aspect of the present disclosure, a method for energy saving of a fluidized ice cold storage cycle in a cold storage is proposed, comprising the following steps:

[0009] S1. Obtain real-time monitoring data by monitoring the cold storage operating parameters in real time;

[0010] S2. Analyze and process the real-time monitoring data to obtain an actual temperature sequence, and predict future cooling load demand based on the temperature change trend of the cold storage to obtain a current cooling load forecast result of the cold storage;

[0011] S3. Based on the cooling load prediction result and the storage capacity of the cold storage tank, the refrigeration operation parameters are automatically adjusted during the off-peak electricity price period to generate an ice making implementation result;

[0012] S4. When the temperature of the cold storage approaches a preset temperature threshold according to the real-time monitoring data, the refrigeration operation parameters are adjusted for energy saving in combination with the cooling load prediction result to generate an energy saving adjustment result;

[0013] S5. Determine different operating stages of the cold storage based on the cooling load prediction result and the storage capacity of the cold storage tank, combined with the preset ice-making cooling load threshold range and the cooling release temperature threshold range;

[0014] S6. Based on different operating stages of the cold storage, a circulation control result is generated according to the cooling load prediction result and the slurry ice circulation demand.

[0015] Preferably, analyzing the real-time monitoring data, predicting the future cooling load demand according to the temperature change trend of the cold storage, and obtaining the current cooling load prediction result of the cold storage includes:

[0016] Perform moving average processing on the real-time monitoring data to obtain the actual temperature series

[0017] The polynomial fitting method is used to analyze the temperature change trend of the cold storage using the following formula:

[0018]

[0019] Among them, a0, a1, ..., a m are the polynomial coefficients fitted by the least squares method, so that the fitting curve and the actual temperature series The sum of squared errors is minimized;

[0020] The cooling load prediction model is used to calculate the current cooling load prediction results of the cold storage:

[0021]

[0022] Among them, Q is the cooling load prediction result, t is the time, is the temperature change rate, E is the heat exchange amount of goods entering and leaving the warehouse, T env is the external temperature, β0, β1, β2, β3, β4 are regression coefficients, and ε is the error term.

[0023] Preferably, the method of automatically adjusting refrigeration operation parameters and generating ice making implementation results according to the cooling load prediction result and the storage capacity of the cold storage tank during the off-peak electricity price period includes:

[0024] Based on the cooling load forecast results and the storage capacity of the cold storage tank, use the following formula to calculate the amount of ice required during the off-peak electricity price period:

[0025] Q ice =max(0,Q×HS)

[0026] Among them, Q ice is the ice making capacity, in kW·h; Q×H is the cooling capacity required by the future cooling load during the off-peak electricity price period, H is the duration of the off-peak electricity price period, and S is the current storage capacity of the cold storage tank; when the result is less than 0, it means that the current storage capacity of the cold storage tank has met the future cooling load demand and no ice making is required. At this time, Q ice =0;

[0027] According to the ice production amount Q ice The duration H of the off-peak electricity price period is used to determine the cooling power using the following formula:

[0028]

[0029] Where P is the cooling power and η is the ice making efficiency;

[0030] According to the refrigeration power P, the refrigeration power is adjusted by changing the power supply frequency of the compressor to generate an ice making implementation result.

[0031] Preferably, when the temperature of the cold storage approaches a preset temperature threshold according to the real-time monitoring data, the refrigeration operation parameters are energy-efficiently regulated in combination with the cooling load prediction result to generate an energy-saving regulation result, including:

[0032] Calculate the rate of change of the cold storage temperature based on the real-time monitoring data

[0033]

[0034] Among them, T now is the current real-time temperature of the cold storage, ΔT is the preset temperature threshold range, Tprev The temperature of the cold storage at the last moment;

[0035] When T set -ΔT≤T now ≤T set When , it means that the cold storage temperature is close to the preset temperature threshold, where T set is the preset temperature threshold;

[0036] When the cold storage temperature approaches the preset temperature threshold, the cooling power adjustment amount ΔP is determined according to the temperature change rate and the cooling load prediction result:

[0037]

[0038] Among them, α and β are weight coefficients used to balance the impact of temperature change rate and cooling load prediction results on cooling power adjustment;

[0039] According to the cooling power adjustment amount ΔP, the adjusted ice-making power is calculated:

[0040] P ad =P now -ΔP

[0041] Among them, P now is the current cooling power, P ad is the adjusted ice making power, and P ad The minimum and maximum power limits of refrigeration are met, when the calculated adjusted ice making power P ad If the power limit is exceeded, P ad Limit to boundary values;

[0042] According to the adjusted ice making power P ad By adjusting the compressor frequency and refrigerant flow, and operating according to the new refrigeration power, energy-saving control results are generated.

[0043] Preferably, the determining of different operating stages of the cold storage according to the cooling load prediction result and the storage capacity of the cold storage tank, in combination with a preset ice-making cooling load threshold range and a cooling release temperature threshold range, includes:

[0044] Based on the cooling load prediction result Q satisfying Q≥Q ice,start , and the current storage capacity S of the cold storage tank is less than the maximum storage capacity S max When the cold storage operating stage is ice making stage A, use the following judgment conditions to determine:

[0045]

[0046] Among them, (Q ice,start ,Q ice,stop ) is the preset ice making cooling load threshold range, Qice,start The cooling load threshold for ice making, Q ice,stop The cooling load threshold for ice making stops; when Q ice,stop <Q<Q ice,start If the machine is in the ice-making stage at the previous moment, it will continue to maintain the ice-making stage to avoid frequent switching of working conditions;

[0047] Based on the real-time monitoring data, when the real-time temperature of the cold storage is T now Meet T now ≥T re,start , and when the cold storage tank has sufficient storage capacity, use the following judgment conditions to determine that the cold storage operating stage is the cold release stage B:

[0048]

[0049] Among them, ΔV is the expected release time, S≥Q×ΔV means that the cold storage tank has sufficient reserves, (T re,start ,T re,stop ) is the preset cooling temperature threshold range, T re,start is the cold start temperature threshold, T re,stop is the cooling stop temperature threshold; when T re,stop <T<T re,start If the system is in the cooling release stage at the previous moment, it will continue to maintain the cooling release stage to avoid frequent switching of working conditions;

[0050] Based on the judgment conditions, the different operating stages of the cold storage are determined to be ice making stage A and cold releasing stage B.

[0051] Preferably, the generating of the circulation control result based on the cold storage at different working stages and in accordance with the cooling load prediction result and the slurry ice circulation demand includes:

[0052] Based on the ice making stage A, according to the cooling load demand Q in the ice making stage ice (t), use the following formula to calculate the flow adjustment value of liquid ice in the ice making stage:

[0053]

[0054] Among them, F A (t) is the flow rate of fluid ice in the ice-making stage, Δr is the time interval, λ is the adjustment coefficient of the flow rate of fluid ice in the ice-making stage, 0<λ<1; is the target value of the flow rate of liquid ice in the ice-making stage; C is the refrigeration capacity of slurry ice; k1 is the proportional coefficient between ice making rate and flow ice flow rate;

[0055] Based on the cooling load demand Q in the cooling stage B, re(t), use the following formula to calculate the flow adjustment value of liquid ice in the cooling stage:

[0056]

[0057] Among them, F B (t) is the flow rate of fluid ice in the cooling stage, Δr is the time interval, θ is the adjustment coefficient of the flow rate of fluid ice in the cooling stage, 0<θ<1; is the target value of the flow rate of liquid ice in the cooling stage; C is the refrigeration capacity of slurry ice; Q other (t) The cooling capacity provided to other refrigeration equipment during the cooling stage;

[0058] According to different working stages of the cold storage, the flow adjustment value of the fluidized ice in the ice making stage and the flow adjustment value of the fluidized ice in the cooling stage are obtained as the generated cycle control results.

[0059] According to a second aspect of the present disclosure, a computer device is provided, comprising:

[0060] one or more processors;

[0061] a storage device for storing one or more programs;

[0062] When the one or more programs are executed by the one or more processors, the one or more processors implement the energy-saving method for fluid ice cold storage cycle in a cold storage as described in any of the first aspects.

[0063] According to a third aspect of the present disclosure, a storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the energy-saving method for the fluidized ice cold storage cycle in a cold storage as described in any of the first aspects is implemented.

[0064] Compared with the prior art, the present invention has the following beneficial effects:

[0065] 1. This invention avoids inefficient operation and over-cooling of refrigeration equipment by predicting cooling load and accurately adjusting it according to different operating conditions, effectively reducing energy consumption. Furthermore, by utilizing off-peak electricity prices for ice production and cold storage, it rationally utilizes electricity and reduces electricity costs.

[0066] 2. The present invention can maintain the temperature of the cold storage within a relatively stable range through real-time monitoring and regulation according to the temperature threshold, which is beneficial to ensuring the quality of stored goods and extending their shelf life. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 The figure is a flow chart of the energy-saving method for the fluidized ice cold storage cycle in a cold storage of the present invention. DETAILED DESCRIPTION

[0068] The following embodiments of the present invention are described in further detail with reference to the accompanying drawings and examples. The following examples are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0069] As attached Figure 1 As shown:

[0070] Example 1: The present invention provides a method for energy saving of a fluidized ice cold storage cycle in a cold storage, comprising the following steps:

[0071] S1. Obtain real-time monitoring data by real-time monitoring of cold storage operating parameters; through various sensors arranged in the cold storage, collect the operating parameters of the cold storage in real time, such as temperature, humidity, refrigeration equipment operating status and other data, so as to timely understand the current operating status of the cold storage.

[0072] S2. Analyze and process the real-time monitoring data to obtain the actual temperature series, and combine the temperature change trend of the cold storage to predict the future cooling load demand and obtain the current cooling load forecast result of the cold storage;

[0073] Perform moving average processing on real-time monitoring data to obtain the actual temperature series

[0074] The polynomial fitting method is used to analyze the temperature change trend of the cold storage using the following formula:

[0075]

[0076] Among them, a0, a1, ..., a m are the polynomial coefficients fitted by the least squares method, so that the fitting curve and the actual temperature series The sum of squared errors is minimized;

[0077] The cooling load prediction model is used to calculate the current cooling load prediction results of the cold storage:

[0078]

[0079] Among them, Q is the cooling load prediction result, t is the time, is the temperature change rate, E is the heat exchange amount of goods entering and leaving the warehouse, T env is the external temperature, β0, β1, β2, β3, β4 are regression coefficients, and ε is the error term.

[0080] Analyze the real-time monitoring data, extract the actual temperature series, and predict the future cooling load demand by analyzing the temperature change trend and combining historical data. This will enable you to know the future cooling load of the cold storage in advance, provide a basis for subsequent control measures, facilitate the subsequent reasonable arrangement of the operation of the refrigeration equipment, and avoid insufficient or excessive cooling supply.

[0081] S3. Based on the cooling load forecast results and the storage capacity of the cold storage tank, the refrigeration operation parameters are automatically adjusted during the off-peak electricity price period to generate ice making implementation results;

[0082] Based on the cooling load forecast and the cold storage tank capacity, use the following formula to calculate the amount of ice that needs to be produced during the off-peak electricity price period:

[0083] Q ice =max(0,Q×HS)

[0084] Among them, Q ice is the ice making capacity, in kW·h; Q×H is the cooling capacity required by the future cooling load during the off-peak electricity price period, H is the duration of the off-peak electricity price period, and S is the current storage capacity of the cold storage tank; when the result is less than 0, it means that the current storage capacity of the cold storage tank has met the future cooling load demand and no ice making is required. At this time, Q ice =0;

[0085] According to the ice production Q ice The duration H of the off-peak electricity price period is used to determine the cooling power using the following formula:

[0086]

[0087] Where P is the cooling power and η is the ice making efficiency;

[0088] Based on the cooling power (P), the compressor's power supply frequency is varied to adjust the cooling power and generate ice-making results. Based on cooling load forecasts and the cold storage tank's capacity, cooling parameters are automatically adjusted during off-peak electricity price periods, allowing the refrigeration equipment to produce ice when electricity prices are low and storing the cold. By fully utilizing off-peak electricity prices, cooling costs are reduced while storing cold for use during peak electricity price periods or when the cooling load is high, improving energy efficiency and cost-effectiveness.

[0089] S4. Based on real-time monitoring data, when the cold storage temperature approaches the preset temperature threshold, combined with the cooling load prediction results, the refrigeration operation parameters are adjusted to save energy and generate energy-saving control results;

[0090] Calculate the rate of change of cold storage temperature based on real-time monitoring data

[0091]

[0092] Among them, T now is the current real-time temperature of the cold storage, ΔT is the preset temperature threshold range, T prev The temperature of the cold storage at the last moment;

[0093] When T set -ΔT≤T now ≤T set When , it means that the cold storage temperature is close to the preset temperature threshold, where T set is the preset temperature threshold;

[0094] When the cold storage temperature approaches the preset temperature threshold, the cooling power adjustment ΔP is determined based on the temperature change rate and cooling load prediction results:

[0095]

[0096] Among them, α and β are weight coefficients used to balance the impact of temperature change rate and cooling load prediction results on cooling power adjustment;

[0097] According to the cooling power adjustment ΔP, calculate the adjusted ice-making power:

[0098] P ad =P now -ΔP

[0099] Among them, P now is the current cooling power, P ad is the adjusted ice making power, and P ad To meet the minimum and maximum power limits of refrigeration, when the calculated adjusted ice making power P ad If the power limit is exceeded, P ad Limit to boundary values;

[0100] According to the adjusted ice making power P ad By adjusting the compressor frequency and refrigerant flow, and operating according to the new refrigeration power, energy-saving control results are generated.

[0101] When the cold storage temperature approaches the preset temperature threshold, the refrigeration operation parameters are adjusted for energy saving in combination with the cooling load forecast results to avoid over-cooling of the refrigeration equipment when not necessary and to prevent energy waste caused by excessively low temperatures. At the same time, the cold storage temperature is ensured to fluctuate within a reasonable range to ensure the storage quality of the goods.

[0102] S5. Determine the different operating stages of the cold storage based on the cooling load prediction results and the storage capacity of the cold storage tank, combined with the preset ice-making cooling load threshold range and the cooling release temperature threshold range;

[0103] Based on the cooling load prediction result Q satisfies Q≥Q ice,start, and the current storage capacity S of the cold storage tank is less than the maximum storage capacity S max When the cold storage operating stage is ice making stage A, use the following judgment conditions to determine:

[0104]

[0105] Among them, (Q ice,start ,Q ice,stop ) is the preset ice making cooling load threshold range, Q ice,start The cooling load threshold for ice making, Q ice,stop It is the cooling load threshold for ice making to stop; when Q ice,stop <Q<Q ice,start If the machine is in the ice-making stage at the previous moment, it will continue to maintain the ice-making stage to avoid frequent switching of working conditions;

[0106] Based on real-time monitoring data, when the real-time temperature of the cold storage is T now Meet T now ≥T re,start , and when the cold storage tank has sufficient storage capacity, use the following judgment conditions to determine that the cold storage operating stage is the cold release stage B:

[0107]

[0108] Among them, ΔV is the expected release time, S≥Q×ΔV means that the cold storage tank has sufficient reserves, (T re,start ,T re,stop ) is the preset cooling temperature threshold range, T re,start is the cold start temperature threshold, T re,stop is the cooling stop temperature threshold; when T re,stop <T<T re,start If the system is in the cooling release stage at the previous moment, it will continue to maintain the cooling release stage to avoid frequent switching of working conditions;

[0109] Based on the judgment conditions, the different operating stages of the cold storage are determined to be ice making stage A and cold releasing stage B.

[0110] Based on the cooling load prediction results, the storage capacity of the cold storage tank, and the preset ice-making cooling load threshold range and cooling release temperature threshold range, determine whether the cold storage is currently in the ice-making stage or the cooling release stage; by clarifying the operating status of the cold storage, provide the prerequisite for subsequent targeted circulation control, so that the system can take corresponding optimization measures according to different working conditions.

[0111] S6. Based on the different working conditions of the cold storage, the circulation control results are generated according to the cooling load prediction results and the liquid ice circulation demand;

[0112] Based on the ice making stage A, according to the cooling load demand Q in the ice making stage ice(t), use the following formula to calculate the flow adjustment value of liquid ice in the ice making stage:

[0113]

[0114] Among them, F A (t) is the flow rate of fluid ice in the ice-making stage, Δr is the time interval, λ is the adjustment coefficient of the flow rate of fluid ice in the ice-making stage, 0<λ<1; is the target value of the flow rate of liquid ice in the ice-making stage; C is the refrigeration capacity of slurry ice; k1 is the proportional coefficient between ice making rate and flow ice flow rate;

[0115] Based on the cooling load demand Q in the cooling stage B, re (t), use the following formula to calculate the flow adjustment value of liquid ice in the cooling stage:

[0116]

[0117] Among them, F B (t) is the flow rate of fluid ice in the cooling stage, Δr is the time interval, θ is the adjustment coefficient of the flow rate of fluid ice in the cooling stage, 0<θ<1; is the target value of the flow rate of liquid ice in the cooling stage; C is the refrigeration capacity of slurry ice; Q other (t) The cooling capacity provided to other refrigeration equipment during the cooling stage;

[0118] According to different working stages of the cold storage, the flow adjustment value of the fluidized ice in the ice making stage and the flow adjustment value of the fluidized ice in the cooling stage are obtained as the generated cycle control results.

[0119] Based on the different operating stages of the cold storage, combined with the cooling load prediction results and the slurry ice circulation demand, the slurry ice circulation system is regulated, such as adjusting the flow rate of slurry ice and the operating frequency of the refrigeration equipment, to achieve the optimal operation of the slurry ice circulation system, improve the refrigeration efficiency, meet the cooling load demand of the cold storage under different operating conditions, and further reduce energy consumption.

[0120] As can be seen from the above, this method combines real-time monitoring data and temperature change trends to predict cooling load, and accurately adjusts refrigeration operating parameters and the fluidized ice circulation system based on the prediction results and different operating stages. Compared with traditional fixed refrigeration modes or simple temperature control methods, it is more intelligent and precise, and can better adapt to the dynamic changes in cold storage load. It also fully considers the off-peak electricity price period, combines electricity price factors with the operation of the refrigeration system, and actively utilizes off-peak electricity price periods for ice making and cold storage, effectively reducing electricity costs. At the same time, by comprehensively considering multiple parameters such as the cooling load prediction results, the storage capacity of the cold storage tank, and the preset ice making cooling load threshold range and the cooling release temperature threshold range to determine the cold storage operating stage, it is more comprehensive and accurate than a single parameter judgment, and can provide a more reliable basis for subsequent regulation, thereby achieving more optimized operation control.

[0121] Embodiment 2: A computer device comprising:

[0122] one or more processors;

[0123] a storage device for storing one or more programs;

[0124] When one or more programs are executed by one or more processors, the one or more processors implement the energy-saving method for fluid ice cold storage cycle in a cold storage as proposed in the first embodiment.

[0125] Embodiment 3: A storage medium stores a computer program thereon, which, when executed by a processor, implements the energy-saving method for the fluidized ice cold storage cycle in a cold storage as proposed in embodiment 1.

[0126] The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. Computer-readable storage media include, but are not limited to: electrical, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or components, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROMD), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device.

[0127] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0128] Program code embodied on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0129] The computer program code for performing the operations of the present invention may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages such as Java, Smalltalk, C++, and conventional procedural programming languages such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0130] It is important to note that the construction and arrangement of the present application shown in a plurality of different exemplary embodiments are merely illustrative. Although only a few embodiments are described in detail in this disclosure, it will be readily understood by those who consult this disclosure that many modifications are possible without departing substantially from the novel teachings and advantages of the subject matter described in this application. Other replacements, modifications, changes, and omissions may be made in the design, operating conditions, and arrangement of the exemplary embodiments without departing from the scope of the present invention. Therefore, the present invention is not limited to specific embodiments, but extends to a variety of modifications still falling within the scope of the appended claims.

[0131] It will be understood that in the development of any actual embodiment, as in any engineering or design project, numerous implementation-specific decisions may be made. Such a development effort may be complex and time-consuming, but for those of ordinary skill having the benefit of this disclosure, the development effort will be a routine task of design, fabrication, and production without undue experimentation.

[0132] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for energy saving by using fluidized ice to store cold in a cold storage, characterized in that: The following steps are involved: S1. Obtain real-time monitoring data by real-time monitoring of cold storage operating parameters; S2. Analyze and process the real-time monitoring data to obtain an actual temperature sequence, and predict future cooling load demand based on the temperature change trend of the cold storage to obtain a current cooling load forecast result of the cold storage; S3. Based on the cooling load prediction result and the storage capacity of the cold storage tank, the refrigeration operation parameters are automatically adjusted during the off-peak electricity price period to generate an ice making implementation result; S4. When the temperature of the cold storage approaches a preset temperature threshold according to the real-time monitoring data, the refrigeration operation parameters are adjusted for energy saving in combination with the cooling load prediction result to generate an energy saving adjustment result; S5. Determine different operating stages of the cold storage based on the cooling load prediction result and the storage capacity of the cold storage tank, combined with the preset ice-making cooling load threshold range and the cooling release temperature threshold range; S6. Based on different operating stages of the cold storage, a circulation control result is generated according to the cooling load prediction result and the slurry ice circulation demand.

2. The method for energy saving of fluidized ice cold storage cycle in a cold storage as claimed in claim 1, characterized in that: The real-time monitoring data is analyzed, and future cooling load demand is predicted based on the temperature change trend of the cold storage to obtain the current cooling load prediction result of the cold storage, including: Perform moving average processing on the real-time monitoring data to obtain the actual temperature series The polynomial fitting method is used to analyze the temperature change trend of the cold storage using the following formula: Among them, a0, a1, ..., a m are the polynomial coefficients fitted by the least squares method, so that the fitting curve and the actual temperature series The sum of squared errors is minimized; The cooling load prediction model is used to calculate the current cooling load prediction results of the cold storage: Among them, Q is the cooling load prediction result, t is the time, is the temperature change rate, E is the heat exchange amount of goods entering and leaving the warehouse, T env is the external temperature, β0, β1, β2, β3, β4 are regression coefficients, and ε is the error term.

3. The energy-saving method for fluidized ice cold storage cycle in a cold storage according to claim 1, characterized in that: According to the cooling load prediction result and in combination with the storage capacity of the cold storage tank, the refrigeration operation parameters are automatically adjusted during the off-peak electricity price period to generate the ice making implementation result, including: Based on the cooling load forecast results and the storage capacity of the cold storage tank, use the following formula to calculate the amount of ice required during the off-peak electricity price period: Q ice =max(0,Q×H-S) Among them, Q ice is the ice making capacity, in kW·h; Q×H is the cooling capacity required by the future cooling load during the off-peak electricity price period, H is the duration of the off-peak electricity price period, and S is the current storage capacity of the cold storage tank; when the result is less than 0, it means that the current storage capacity of the cold storage tank has met the future cooling load demand and no ice making is required. At this time, Q ice =0; According to the ice production amount Q ice The duration H of the off-peak electricity price period is used to determine the cooling power using the following formula: Where P is the cooling power and η is the ice making efficiency; According to the refrigeration power P, the refrigeration power is adjusted by changing the power supply frequency of the compressor to generate an ice making implementation result.

4. The method for energy saving of fluidized ice cold storage cycle in a cold storage as claimed in claim 1, characterized in that: According to the real-time monitoring data, when the temperature of the cold storage approaches a preset temperature threshold, combined with the cooling load prediction result, the refrigeration operation parameters are energy-efficiently regulated to generate an energy-saving regulation result, including: Calculate the rate of change of the cold storage temperature based on the real-time monitoring data Among them, T now is the current real-time temperature of the cold storage, ΔT is the preset temperature threshold range, T prev The temperature of the cold storage at the last moment; When T set -ΔT≤T now ≤T set When , it means that the cold storage temperature is close to the preset temperature threshold, where T set is the preset temperature threshold; When the cold storage temperature approaches the preset temperature threshold, the cooling power adjustment amount ΔP is determined according to the temperature change rate and the cooling load prediction result: Among them, α and β are weight coefficients used to balance the impact of temperature change rate and cooling load prediction results on cooling power adjustment; According to the cooling power adjustment amount ΔP, the adjusted ice-making power is calculated: P ad =P now -ΔP Among them, P now is the current cooling power, P ad is the adjusted ice making power, and P ad The minimum and maximum power limits of refrigeration are met, when the calculated adjusted ice making power P ad If the power limit is exceeded, P ad Restricted to boundary values; According to the adjusted ice making power P ad By adjusting the compressor frequency and refrigerant flow, and operating according to the new refrigeration power, energy-saving control results are generated.

5. The energy-saving method for fluidized ice cold storage cycle in a cold storage as claimed in claim 1, characterized in that: The method of determining different operating stages of the cold storage based on the cooling load prediction result and the storage capacity of the cold storage tank, combined with the preset ice making cooling load threshold range and the cooling release temperature threshold range, includes: Based on the cooling load prediction result Q satisfying Q≥Q ice,start , and the current storage capacity S of the cold storage tank is less than the maximum storage capacity S max When the cold storage operating stage is ice making stage A, use the following judgment conditions to determine: Among them, (Q ice,start ,Q ice,stop ) is the preset ice making cooling load threshold range, Q ice,start The cooling load threshold for ice making, Q ice,stop It is the cooling load threshold for ice making to stop; when Q ice,stop <Q<Q ice,start If the machine is in the ice-making stage at the previous moment, it will continue to maintain the ice-making stage to avoid frequent switching of working conditions; Based on the real-time monitoring data, when the real-time temperature of the cold storage is T now Meet T now ≥T re,start , and when the cold storage tank has sufficient storage capacity, use the following judgment conditions to determine that the cold storage operating stage is the cold release stage B: Among them, ΔV is the expected release time, S≥Q×ΔV means that the cold storage tank has sufficient reserves, (T re,start ,T re,stop ) is the preset cooling temperature threshold range, T re,start is the cold start temperature threshold, T re,stop is the cooling stop temperature threshold; when T re,stop <T<T re,start If the system is in the cooling release stage at the previous moment, it will continue to maintain the cooling release stage to avoid frequent switching of working conditions; Based on the judgment conditions, the different operating stages of the cold storage are determined to be ice making stage A and cold releasing stage B.

6. The method for energy saving of fluidized ice cold storage cycle in a cold storage as claimed in claim 1, characterized in that: The generation of circulation control results based on the different operating stages of the cold storage and the cooling load prediction results combined with the slurry ice circulation demand includes: Based on the ice making stage A, according to the cooling load demand Q in the ice making stage ice (t), use the following formula to calculate the flow adjustment value of liquid ice in the ice making stage: Among them, F A (t) is the flow rate of fluid ice in the ice-making stage, Δr is the time interval, λ is the adjustment coefficient of the flow rate of fluid ice in the ice-making stage, 0<λ<1; is the target value of the flow rate of liquid ice in the ice-making stage; C is the refrigeration capacity of slurry ice; k1 is the proportional coefficient between ice making rate and flow ice flow rate; Based on the cooling load demand Q in the cooling stage B, re (t), use the following formula to calculate the flow adjustment value of liquid ice in the cooling stage: Among them, F B (t) is the flow rate of fluid ice in the cooling stage, Δr is the time interval, θ is the adjustment coefficient of the flow rate of fluid ice in the cooling stage, 0<θ<1; is the target value of the flow rate of liquid ice in the cooling stage; C is the refrigeration capacity of slurry ice; Q other (t) The cooling capacity provided to other refrigeration equipment during the cooling stage; According to different working stages of the cold storage, the flow adjustment value of the fluidized ice in the ice making stage and the flow adjustment value of the fluidized ice in the cooling stage are obtained as the generated cycle control results.

7. A computer device, characterized in that: The device comprises: one or more processors; a storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the energy-saving method for fluid ice cold storage cycle in a cold storage as described in any one of claims 1 to 6.

8. A storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the energy-saving method for fluid ice storage cycle in a cold storage as described in any one of claims 1 to 6 is implemented.

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