Partition regulation and control system for fixed refrigeration house
The cold storage is refrigerated in partitions through the partition control system, which solves the problem that the cold storage temperature control does not meet the temperature requirements of different items, and achieves the effect of extending the shelf life of the items and energy saving.
Patent Information
- Application Number
- CN202510940636.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-09
- Publication Date
- 2025-08-19
AI Technical Summary
The temperature control strategy of existing cold storage cannot adapt to the storage temperature requirements of different items, resulting in cold damage and energy waste.
The partition control system is adopted to collect the historical inlet, outflow, optimal refrigeration conditions and breathing intensity types of items through the information acquisition module. The items are grouped using the item grouping module, and the optimal refrigeration strategy is determined through the partition control module to control the refrigeration unit for partition refrigeration.
It achieves precise refrigeration in different areas, extends the shelf life of items, reduces energy consumption and cold damage, and improves the cooling uniformity and energy utilization efficiency of cold storage.
Smart Images
Figure CN120506761A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of energy-saving refrigeration, and in particular to a partition control system for a fixed cold storage. Background Art
[0002] A cold storage facility is a type of refrigeration equipment. It typically uses a refrigeration mechanism, utilizing a liquid with a very low vaporization temperature as a coolant. This coolant absorbs heat from the storage chamber, thereby achieving cooling. Due to the large size of cold storage, in order to rationally utilize the internal space, it is usually divided into several zones, each used to store different items. Since different items have significantly different refrigeration temperatures, maintaining the appropriate temperature for each item is crucial to extend their shelf life. The storage and preservation temperatures of various items vary greatly. For example, dairy products are generally kept at around -5℃; meat is generally kept at -18℃ to -21℃; seafood is generally kept at around -25℃; poultry and eggs are generally kept at around 0℃; root vegetables (potatoes, sweet potatoes, yams, etc.) are generally kept at around 3℃ to 5℃; leafy vegetables (lettuce, cabbage, celery, spinach, etc.) are generally kept at around 0℃; edible fungi (various mushrooms, etc.) are generally kept at around 0℃; the storage temperature of ordinary flower cold storage is generally around 5℃, tropical flowers generally require 10-12℃, cold-zone flowers generally require around -5℃, and the temperature of tea is generally between 0 and 5℃.
[0003] Existing cold storage temperature control strategies cannot guarantee the storage temperature requirements of all items. Existing technologies also lack temperature control methods suitable for various items, making them prone to cold damage. This leads to premature spoilage and significant economic losses. Furthermore, large cold storage facilities typically have multiple refrigeration units. If a single, unified temperature control strategy is applied to different items without a sound strategy, this can lead to significant waste of resources such as electricity.
[0004] Therefore, it is necessary to provide a zoning control system for fixed cold storage to improve the intelligence level of cold storage zoning storage and reduce energy waste. Summary of the Invention
[0005] The present invention provides a zoning control system for a fixed cold storage, comprising: an information acquisition module for acquiring historical incoming quantities, historical outgoing quantities, optimal refrigeration conditions, and breathing intensity types of a plurality of items to be refrigerated; an item grouping module for grouping a plurality of items to be refrigerated according to the optimal refrigeration conditions and breathing intensity types of the plurality of items to be refrigerated, and determining a plurality of item groups; a zoning control module for determining the items to be refrigerated corresponding to each area of the cold storage according to the plurality of item groups and the historical incoming quantities and historical outgoing quantities of the plurality of items to be refrigerated, and further for determining an optimal refrigeration strategy according to the items to be refrigerated corresponding to each area of the cold storage and the historical incoming quantities, historical outgoing quantities, and optimal refrigeration conditions of the plurality of items to be refrigerated, and controlling a plurality of refrigeration units according to the optimal refrigeration strategy to perform zoned refrigeration of the cold storage.
[0006] Furthermore, the item grouping module groups multiple items to be refrigerated according to the optimal refrigeration conditions and breathing intensity types of the multiple items to be refrigerated, and determines multiple item groups, including: determining the refrigeration cycle of each item to be refrigerated according to the historical inventory and historical outbound quantities of the multiple items to be refrigerated; dividing the multiple items to be refrigerated into multiple item units according to the breathing intensity types of the multiple items to be refrigerated, wherein one item unit corresponds to one breathing intensity type; for each item unit, determining multiple item clusters included in the item unit according to the optimal refrigeration conditions of the multiple items to be refrigerated included in the item unit; for each item cluster, determining multiple initial item groups included in the item cluster according to the refrigeration cycles of the multiple items to be refrigerated included in the item cluster; and merging multiple initial item groups based on the number and space size of the cold storage areas and the historical inventory and historical outbound quantities of the multiple items to be refrigerated to determine multiple item groups.
[0007] Furthermore, determining multiple item clusters included in the item unit based on the optimal refrigeration conditions of the multiple items to be refrigerated included in the item unit includes: calculating the similarity of the optimal refrigeration conditions of any two items to be refrigerated included in the item unit based on the optimal refrigeration conditions of the multiple items to be refrigerated included in the item unit; and determining the multiple item clusters included in the item unit based on the similarity of the optimal refrigeration conditions of any two items to be refrigerated included in the item unit through a first clustering algorithm.
[0008] Furthermore, determining multiple initial item groups included in the item cluster based on the refrigeration cycles of the multiple items to be refrigerated included in the item cluster includes: calculating the refrigeration cycle difference between any two items to be refrigerated included in the item cluster based on the refrigeration cycles of the multiple items to be refrigerated included in the item cluster; and determining the multiple initial item groups included in the item cluster based on the refrigeration cycle difference between any two items to be refrigerated included in the item cluster through a second clustering algorithm.
[0009] Furthermore, based on the number of areas and space size of the cold storage and historical incoming and outgoing quantities of various items to be refrigerated, multiple initial item groups are merged to determine multiple item groups, including: determining the number of areas required for each initial item group based on the space size of the cold storage area and historical incoming and outgoing quantities of various items to be refrigerated, and calculating the total number of areas required for multiple initial item groups; judging whether the total number of areas required for multiple initial item groups is greater than the number of areas of the cold storage; if so, merging the multiple initial item groups included in each item cluster based on the difference in refrigeration cycles of any two items to be refrigerated included in the item cluster and the number of areas required for each initial item group.
[0010] Furthermore, the partition control module determines the items to be refrigerated corresponding to each area of the cold storage based on the historical incoming and outgoing quantities of multiple item groups and multiple items to be refrigerated, including: establishing a first set of constraints; generating multiple initial item refrigeration plans based on the first set of constraints, multiple item groups and multiple historical incoming and outgoing quantities of multiple items to be refrigerated, wherein the item refrigeration plans include the item groups corresponding to each area of the cold storage; taking each initial item refrigeration plan as a first individual to generate a first initial population; establishing a first fitness function; determining the fitness value of each first individual of the first initial population according to the first fitness function; performing selection, crossover and mutation operations according to the fitness value of each first individual to generate an optimal item refrigeration plan; and determining the items to be refrigerated corresponding to each area of the cold storage according to the optimal item refrigeration plan.
[0011] Furthermore, according to the fitness function, the fitness value of each first individual of the first initial population is determined, including: for each first individual, determining the refrigeration cycle of the items to be refrigerated corresponding to each area of the cold storage and the minimum transportation distance between each area and the entrance and exit of the cold storage, and calculating the refrigeration condition difference value of any two adjacent areas based on the optimal refrigeration conditions of the items to be refrigerated corresponding to each area of the cold storage, calculating the global refrigeration condition difference value based on the refrigeration condition difference value of any two adjacent areas, and determining the fitness value of the first individual based on the fitness function, based on the refrigeration cycle of the items to be refrigerated corresponding to each area of the cold storage, the minimum transportation distance between each area and the entrance and exit of the cold storage, and the global refrigeration condition difference value.
[0012] Furthermore, according to the historical inbound quantities, historical outbound quantities and optimal refrigeration conditions of the items to be refrigerated and the various items to be refrigerated corresponding to each area of the cold storage, the optimal refrigeration strategy is determined, including: calculating the inbound and outbound correlation coefficients of any two areas according to the historical inbound quantities and historical outbound quantities of the items to be refrigerated and the various items to be refrigerated corresponding to each area of the cold storage; calculating the heat load of each area according to the historical inbound quantities, historical outbound quantities and optimal refrigeration conditions of the items to be refrigerated and the various items to be refrigerated corresponding to each area of the cold storage; establishing a second set of constraint conditions; and based on the second set of constraint conditions, calculating the heat load of each area. and the heat load of each area, generate multiple initial cooling strategies, where the initial cooling strategies include the number of operating refrigeration units and the areas corresponding to each refrigeration unit; take each initial cooling strategy as a second individual to generate a second initial population; establish a second fitness function, where the second fitness function is related to the in-and-out correlation coefficient of any two areas and the heat load of the area corresponding to each refrigeration unit; determine the fitness value of each second individual of the second initial population based on the second fitness function; perform selection, crossover, and mutation operations based on the fitness value of each second individual to generate the optimal cooling strategy.
[0013] Furthermore, based on the historical incoming and outgoing quantities of the items to be refrigerated and the multiple items to be refrigerated corresponding to each area of the cold storage, the incoming and outgoing correlation coefficients of any two areas are calculated: based on the historical incoming quantities and historical outgoing quantities of the multiple items to be refrigerated, the outgoing correlation coefficients and incoming correlation coefficients of any two items to be refrigerated are calculated; based on the outgoing correlation coefficients and incoming correlation coefficients of any two items to be refrigerated, the incoming and outgoing correlation coefficients of any two items to be refrigerated are calculated; for any two areas, based on the incoming and outgoing correlation coefficients of any two items to be refrigerated, the incoming and outgoing correlation coefficients of any one item to be refrigerated corresponding to one area and any one item to be refrigerated corresponding to another area are determined, and the incoming and outgoing correlation coefficients of any two areas are calculated.
[0014] Furthermore, based on the historical incoming and outgoing volumes of items to be refrigerated and the optimal refrigeration conditions of the various items to be refrigerated corresponding to each area of the cold storage, the heat load of each area is calculated, including: for each area, based on the refrigeration temperature of the area and the refrigeration temperature of the adjacent area, the heat transfer load of the enclosure structure of the area is calculated; based on the historical incoming and outgoing volumes and breathing intensity of the items to be refrigerated corresponding to the area, the cargo breathing heat load of the area is calculated; based on the historical incoming and outgoing volumes of the items to be refrigerated corresponding to the area, the door opening heat intrusion load of the area is calculated; and based on the heat transfer load of the enclosure structure of the area, the cargo breathing heat load and the door opening heat intrusion load, the heat load of the area is calculated.
[0015] Compared with the prior art, the partition control system for fixed cold storage provided by the present invention has at least the following beneficial effects:
[0016] Different items have significantly different requirements for refrigeration conditions (such as temperature and humidity), and their respiration intensity types (such as high respiration intensity and low respiration intensity) also affect their storage status in cold storage. The system uses the information acquisition module to collect the optimal refrigeration conditions and respiration intensity types for each item. The item grouping module then groups the items accordingly, ensuring that items within each group have similar storage requirements. This allows for more precise environmental conditions for items within each zone during zoning control, effectively extending the shelf life and freshness of items and reducing item loss due to improper storage. Based on the items corresponding to each zone, historical inflow and outflow volumes, and optimal refrigeration conditions, the zoning control module determines the optimal cooling strategy, enabling the refrigeration unit to cool the cold storage area in a zoned manner. This zoning control approach can better meet the cooling needs of different zones, prevent temperatures from being too high or too low in some areas of the cold storage, and improve cooling uniformity throughout the entire cold storage area. Through zoning control, the refrigeration unit can precisely provide cooling based on the actual needs of each zone, avoiding the energy waste caused by the "one-size-fits-all" cooling approach used in traditional cold storage. For example, for some areas with lower temperature requirements, the refrigeration unit can increase the cooling power; while for areas with relatively high temperature requirements, the cooling power can be appropriately reduced, thereby reducing the energy consumption of the entire cold storage. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] This specification will be further described in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, like numbers represent like structures, wherein:
[0018] Figure 1 This is a module diagram of a partition control system for a fixed cold storage according to some embodiments of this specification;
[0019] Figure 2 is a schematic diagram of a process for determining items to be refrigerated corresponding to each area of a cold storage according to some embodiments of this specification;
[0020] Figure 3 This is a schematic diagram of a process for determining an optimal cooling strategy according to some embodiments of this specification. DETAILED DESCRIPTION
[0021] To more clearly illustrate the technical solutions of the embodiments of this specification, the following briefly describes the drawings required for describing the embodiments. Obviously, the drawings described below are merely examples or embodiments of this specification. Those skilled in the art can apply this specification to other similar scenarios based on these drawings without inventive effort. Unless otherwise apparent from the context or otherwise noted, the same reference numerals in the figures represent the same structure or operation.
[0022] Figure 1 This is a module diagram of a partition control system for a fixed cold storage according to some embodiments of this specification, such as Figure 1 As shown, the partition control system for a fixed cold storage may include an information acquisition module, an item grouping module and a partition control module.
[0023] The information acquisition module is used to obtain the historical inbound quantity, historical outbound quantity, optimal refrigeration conditions and breathing intensity types of various items to be refrigerated.
[0024] Specifically, items to be refrigerated refer to those that are prone to deterioration, rot or lose their original quality at room temperature. They need to be refrigerated to inhibit the growth of microorganisms and slow down the rate of chemical reactions, thereby extending the shelf life and maintaining quality and safety.
[0025] The various items to be refrigerated may be items that need to be refrigerated in the current cold storage, such as fruits and vegetables (e.g., apples, bananas, strawberries, grapes, lettuce, spinach, broccoli, etc.), meat (e.g., pork, beef, mutton, chicken, duck, etc.), aquatic products (e.g., fish, shrimp, crab, shellfish, etc.), dairy products (e.g., milk, yogurt, cheese, etc.), eggs (e.g., chicken eggs, duck eggs, etc.), biological products (e.g., vaccines, blood products, insulin, etc.), antibiotics (e.g., penicillins, cephalosporins), and laboratory samples (e.g., biological tissue samples, blood samples, etc.).
[0026] The historical inbound quantity of items to be refrigerated refers to the number of items to be refrigerated that entered the cold storage during the past period of time. The historical outbound quantity of items to be refrigerated refers to the number of items to be refrigerated that were taken out of the cold storage during the past period of time.
[0027] Optimal refrigeration conditions refer to the temperature, humidity, air circulation rate, etc. that can maintain the best quality and preservation effect when the refrigerated items are stored in a cold storage.
[0028] Refrigerated items respire during storage. Respiration intensity is categorized as high, medium, or low, corresponding to the intensity of the item's respiration. Respiration consumes nutrients, generates heat and moisture, and affects the item's quality and shelf life. Based on long-term cold storage management experience, the respiration intensity of different items can be categorized and summarized. For example, common fruits like apples and bananas typically have a high respiration intensity, while vegetables like potatoes and onions have a relatively low respiration intensity. An item's respiration intensity can also be tested using specialized testing equipment and methods. For example, by measuring an item's oxygen consumption and carbon dioxide release over a specific period of time, its respiration intensity can be calculated. Thresholds can then be set to determine the respiration intensity type.
[0029] The article grouping module is used to group multiple articles to be refrigerated according to the optimal refrigeration conditions and breathing intensity types of the multiple articles to be refrigerated, and determine multiple article groups.
[0030] Specifically include:
[0031] Determine the refrigeration cycle of each item to be refrigerated based on the historical inbound and outbound quantities of the items to be refrigerated;
[0032] Dividing the plurality of items to be refrigerated into a plurality of item units according to their respiration intensity types, wherein one item unit corresponds to one respiration intensity type;
[0033] For each item unit, determining a plurality of item clusters included in the item unit according to optimal refrigeration conditions of a plurality of items to be refrigerated included in the item unit;
[0034] For each item cluster, determining a plurality of initial item groups included in the item cluster according to refrigeration cycles of a plurality of items to be refrigerated included in the item cluster;
[0035] Based on the number of areas and space size of the cold storage and historical inbound and outbound quantities of various items to be refrigerated, multiple initial item groups are merged to determine multiple item groups.
[0036] Specifically, for each item to be refrigerated, the refrigeration time of each batch of items to be refrigerated in the cold storage can be calculated based on the historical inbound and outbound quantities of the items to be refrigerated, and the average of the refrigeration time of each batch of items to be refrigerated in the cold storage can be calculated to obtain the refrigeration cycle of the items to be refrigerated.
[0037] Articles to be refrigerated of the same respiration intensity type may be classified into the same article unit.
[0038] Preferably, determining the multiple item clusters included in the item unit according to the optimal refrigeration conditions of the multiple items to be refrigerated included in the item unit includes:
[0039] Calculating the similarity of the optimal refrigeration conditions of any two items to be refrigerated included in the item unit based on the optimal refrigeration conditions of the multiple items to be refrigerated included in the item unit;
[0040] A plurality of item clusters included in the item unit are determined by using a first clustering algorithm according to similarities between optimal refrigeration conditions of any two items to be refrigerated included in the item unit.
[0041] Specifically, the similarity of the optimal refrigeration conditions of any two items to be refrigerated included in the item unit may be calculated using methods such as Euclidean distance and cosine similarity.
[0042] The first clustering algorithm may be a hierarchical clustering algorithm. When the number of item clusters is greater than or equal to the number of cold storage areas, there is no need to perform the next grouping based on the refrigeration cycles of the various items to be refrigerated included in the item clusters. Instead, the multiple item clusters may be directly merged based on the number of cold storage areas. For example, the following steps may be included:
[0043] S11. For each item unit, calculate the Euclidean distance between the mean values of the optimal refrigeration conditions of any two item clusters included in the item unit, where the mean value of the optimal refrigeration conditions of an item cluster may be the mean value of the optimal refrigeration conditions of the items to be refrigerated included in the item cluster;
[0044] S12. Based on the Euclidean distance between the means of the optimal refrigeration conditions of any two item clusters included in each item unit, merge the two item clusters that belong to the same item unit and have the smallest Euclidean distance;
[0045] S13, updating multiple item clusters included in each item unit;
[0046] S14. Determine the number of areas required for each item cluster based on the size of the cold storage area and the historical inbound and outbound volumes of various items to be refrigerated, and calculate the total number of areas required for multiple item clusters.
[0047] S15. Determine whether the sum of the number of areas required for the multiple item clusters is less than or equal to the number of areas in the cold storage. If so, complete the grouping and treat the multiple item clusters as multiple item groups. If not, execute S11.
[0048] When the number of item clusters is less than the number of cold storage areas, multiple initial item groups included in the item cluster are determined based on the refrigeration cycles of the various items to be refrigerated included in the item cluster; based on the number and space size of the cold storage areas and the historical inbound and outbound quantities of the various items to be refrigerated, the multiple initial item groups are merged to determine multiple item groups.
[0049] Preferably, the multiple initial item groups included in the item cluster are determined based on the refrigeration cycles of the multiple items to be refrigerated included in the item cluster, including:
[0050] Calculating a difference in refrigeration cycles between any two items to be refrigerated included in the item cluster based on refrigeration cycles of the multiple items to be refrigerated included in the item cluster, wherein the difference in refrigeration cycles between any two items to be refrigerated may be an absolute value of the difference in refrigeration cycles between the two items to be refrigerated;
[0051] A plurality of initial item groups included in the item cluster are determined by using a second clustering algorithm according to differences in refrigeration cycles between any two items to be refrigerated included in the item cluster.
[0052] The second clustering algorithm may be a hierarchical clustering algorithm.
[0053] Preferably, based on the number and size of cold storage areas and historical inbound and outbound volumes of various items to be refrigerated, multiple initial item groups are merged to determine multiple item groups, including:
[0054] Based on the space size of the cold storage area and the historical inbound and outbound volumes of various items to be refrigerated, determine the number of areas required for each initial item group and calculate the total number of areas required for multiple initial item groups;
[0055] Determine whether the total number of areas required for the multiple initial item groups is greater than the number of areas in the cold storage;
[0056] If so, based on the difference in refrigeration cycles between any two to-be-refrigerated items included in the item cluster and the number of zones required for each initial item group, multiple initial item groups included in each item cluster are merged.
[0057] Specifically, for each item to be refrigerated, the total refrigeration capacity of the items to be refrigerated at multiple historical time points can be determined based on the historical inventory volume and historical outbound volume of the items to be refrigerated, and the average of the total refrigeration capacity at multiple historical time points can be calculated as the total refrigeration capacity required for the items to be refrigerated.
[0058] For each initial item group, the number of zones required for the initial item group can be calculated based on the total refrigeration capacity required for each item to be refrigerated. For example, if the initial item group requires 120 square meters of storage space based on the total refrigeration capacity required for each item to be refrigerated, and each zone has an area of 100 square meters, then the initial item group requires two zones.
[0059] Multiple initial item groups can be merged to determine multiple item groups according to the following process:
[0060] S21. For each item cluster, calculate the difference between the mean refrigeration period values of any two initial item groups included in the item cluster, where the mean refrigeration period value of the initial item group may be the mean refrigeration period value of the items to be refrigerated included in the initial item group;
[0061] S22. Based on the difference in the mean refrigeration period values of any two initial item groups included in each item cluster, merge the two initial item groups that belong to the same item cluster and have the smallest difference in the mean refrigeration period values;
[0062] S23, updating the multiple item groups included in each item cluster;
[0063] S24. Determine the number of areas required for each item group based on the size of the cold storage area and the historical inbound and outbound quantities of the various items to be refrigerated, and calculate the sum of the number of areas required for the multiple item groups.
[0064] S25. Determine whether the sum of the number of areas required for the multiple item groups is less than or equal to the number of areas in the cold storage. If so, complete the grouping, including the remaining multiple item groups. If not, execute S21.
[0065] As you can understand, grouping items by optimal refrigeration conditions and respiration intensity type ensures that items within the same item group have similar refrigeration environment requirements. By calculating the refrigeration cycle and grouping items with similar refrigeration cycles, you can avoid frequent adjustments to the refrigeration environment due to varying refrigeration cycles. For example, storing short-term vegetables and long-term meat separately can reduce the impact of frequent door openings and closings or refrigeration parameter adjustments on other items, maintaining a stable refrigeration environment. Determining the refrigeration strategy based on the optimal refrigeration conditions for each item group ensures a more efficient allocation of refrigeration resources. For item groups with lower temperature requirements, the refrigeration intensity can be appropriately reduced to reduce energy consumption; for item groups with higher temperature requirements, the refrigeration intensity can be increased to ensure product quality. For example, storing frozen and refrigerated foods separately and setting different refrigeration parameters for each can improve refrigeration efficiency and reduce operating costs. Item groups can be merged based on the number of cold storage areas, space size, and historical item in / out volumes to fully utilize cold storage space. The required number of areas is calculated based on the item's refrigeration volume and area, and multiple initial item groups can be merged to avoid wasted space. For example, small-batch items with similar refrigeration cycles can be stored together to improve cold storage space utilization. Appropriate grouping and cooling strategies can reduce frequent starts and stops, overloads, and wear and failure rates of refrigeration equipment. For example, frequent starts and stops of refrigeration units due to frequent adjustments to refrigeration parameters can be avoided, extending equipment life and reducing maintenance and repair costs.
[0066] The partition control module is used to determine the items to be refrigerated corresponding to each area of the cold storage based on the historical incoming and outgoing quantities of multiple item groups and multiple items to be refrigerated. It is also used to determine the optimal refrigeration strategy based on the historical incoming and outgoing quantities of the items to be refrigerated corresponding to each area of the cold storage and multiple items to be refrigerated, as well as the optimal refrigeration conditions, and control multiple refrigeration units to perform partitioned refrigeration of the cold storage according to the optimal refrigeration strategy.
[0067] Figure 2 This is a flow chart of determining the items to be refrigerated corresponding to each area of the cold storage according to some embodiments of this specification, such as Figure 2 As shown, as an example, the partition control module determines the items to be refrigerated corresponding to each area of the cold storage according to the historical inbound and outbound quantities of multiple item groups and multiple items to be refrigerated, including:
[0068] Establishing a first set of constraints, wherein the first set of constraints may include a maximum regional space constraint, a minimum regional space constraint, and a requirement that refrigerated items included in any two item groups cannot be refrigerated in the same area. The maximum regional space constraint represents the maximum refrigeration capacity of the area in use, and the minimum regional space constraint represents the minimum refrigeration capacity of the area in use.
[0069] Based on the first set of constraints, multiple item groups, and the historical inbound and outbound volumes of various items to be refrigerated, multiple initial item refrigeration plans are generated. Each item refrigeration plan includes an item group corresponding to each cold storage area. The items to be refrigerated included in the item group corresponding to each area are the items to be refrigerated corresponding to that area. Specifically, while satisfying the first set of constraints, the item groups are randomly assigned to each cold storage area. For example, given 15 cold storage areas and 10 item groups, a random assignment plan is generated to assign the 10 item groups to the 15 areas. The number of areas assigned to each item group varies, but the first set of constraints must be satisfied.
[0070] Take each initial item cold storage plan as a first individual to generate a first initial population;
[0071] Establish the first fitness function;
[0072] Determining the fitness value of each first individual of the first initial population according to the first fitness function;
[0073] Perform selection, crossover, and mutation operations based on the fitness value of each first individual to generate the optimal item refrigeration plan;
[0074] According to the optimal item refrigeration plan, determine the items to be refrigerated corresponding to each area of the cold storage.
[0075] Preferably, determining the fitness value of each first individual of the first initial population according to the fitness function includes:
[0076] For each first individual, determine the refrigeration cycle of the items to be refrigerated corresponding to each area of the cold storage and the minimum transportation distance between each area and the entrance and exit of the cold storage, and calculate the refrigeration condition difference value of any two adjacent areas based on the optimal refrigeration conditions of the items to be refrigerated corresponding to each area of the cold storage. Calculate the global refrigeration condition difference value based on the refrigeration condition difference value of any two adjacent areas. According to the fitness function, based on the refrigeration cycle of the items to be refrigerated corresponding to each area of the cold storage and the minimum transportation distance between each area and the entrance and exit of the cold storage and the global refrigeration condition difference value, determine the fitness value of the first individual. The global refrigeration condition difference value is the sum of the refrigeration condition difference values of any two adjacent areas.
[0077] Specifically, the shorter the refrigeration cycle, the shorter the minimum transport distance between the area containing the items to be refrigerated and the cold storage entrance, the greater the value of the first fitness function. The smaller the difference in refrigeration conditions between two adjacent areas, the greater the value of the first fitness function. The refrigeration conditions of a region can be the average of the optimal refrigeration conditions for the items to be refrigerated in that region, and the difference in refrigeration conditions between two regions can be the Euclidean distance between the refrigeration conditions of the two regions.
[0078] For example, the first fitness function can be:
[0079]
[0080] Among them, F1 is the first fitness function, w 11 and w 12 is the weight, w 11 and w 12 Greater than 0, w 11 +w 12 =1, for example, w 11 is 0.5, w 12 is 0.5, T n is the refrigeration period of the nth type of refrigerated goods, T i is the refrigeration cycle of the i-th type of refrigerated items, N is the total number of refrigerated items, D i is the minimum transport distance between the area where the nth type of refrigerated items are located and the entrance and exit of the cold storage, d(m,j) is the difference in refrigeration conditions between the mth area and its jth adjacent area, M is the total number of areas, and J is the total number of adjacent areas of the mth area.
[0081] It can be understood that establishing the first set of constraints, taking into account the maximum and minimum spatial constraints of the region, can ensure that the space in each area is fully utilized. Avoiding regional space waste or overcrowding allows the spatial resources of the cold storage to be optimally allocated. Based on the constraint set, a variety of initial item refrigeration plans are generated, and a genetic algorithm (selection, crossover and mutation operations) is used to generate the optimal plan, providing a standardized process for cold storage management. Managers can operate according to established methods, reducing the uncertainty and arbitrariness of human decision-making and improving the standardization and efficiency of management. The algorithm quickly generates and optimizes item refrigeration plans, which greatly shortens the time for plan determination compared to traditional manual allocation methods. When faced with a large number of item groups and cold storage areas, the optimal allocation plan can be quickly found, which improves the response speed of cold storage operations.
[0082] Figure 3 is a flow chart of determining the optimal cooling strategy according to some embodiments of this specification, such as Figure 3 As shown, preferably, according to the items to be refrigerated corresponding to each area of the cold storage and the historical inbound and outbound quantities of the various items to be refrigerated and the optimal refrigeration conditions, the optimal refrigeration strategy is determined, including:
[0083] Calculate the correlation coefficient between the inflow and outflow of any two areas based on the historical inflow and outflow of items to be refrigerated and the historical outflow of multiple items to be refrigerated corresponding to each area of the cold storage;
[0084] Calculate the heat load of each area of the cold storage based on the items to be refrigerated, the historical inbound and outbound volumes of various items to be refrigerated, and the optimal refrigeration conditions.
[0085] Establish a second set of constraints, which may include the maximum and minimum heat loads of the refrigeration units in operation. If the total heat load assigned to a refrigeration unit exceeds its maximum heat load, the refrigeration unit may be overloaded, affecting the cooling effect and equipment life. If the refrigeration unit operates below a certain heat load, it may not work stably and its efficiency will also be reduced. Therefore, it is necessary to set a minimum heat load constraint to ensure that the refrigeration unit operates within a reasonable load range.
[0086] Based on the second set of constraints and the heat load of each zone, multiple initial cooling strategies are generated, where the initial cooling strategies include the number of operating refrigeration units and the zones corresponding to each refrigeration unit. Specifically, under the premise of satisfying the second set of constraints and taking into account the heat load of each zone, the multiple initial cooling strategies are generated using a random or heuristic method;
[0087] Take each initial cooling strategy as a second individual to generate a second initial population;
[0088] A second fitness function is established, wherein the second fitness function is related to the in-and-out correlation coefficient of any two areas and the heat load of the area corresponding to each refrigeration unit. Specifically, the larger the mean of the in-and-out correlation coefficients of any two areas corresponding to each operating refrigeration unit, the smaller the absolute value of the difference between the sum of the heat loads of the area corresponding to each operating refrigeration unit and the optimal heat load, and the larger the second fitness value. The optimal heat load refers to the ideal heat load value that needs to be borne when the refrigeration unit reaches the optimal operating state (such as the highest energy efficiency, the lowest operating cost, the best cooling effect, and other comprehensive goals). The optimal heat load can be determined through experimental data. The larger the mean of the in-and-out correlation coefficients of any two areas corresponding to each operating refrigeration unit in the second fitness function, the larger the fitness value. This setting guides the refrigeration strategy to try to allocate areas with high in-and-out correlation to the same refrigeration unit or adjacent areas during the generation process. This can reduce the impact of temperature fluctuations caused by frequent opening and closing of the cold storage door on items in other areas, improve the temperature stability in the cold storage, and ensure the quality of items.
[0089] determining a fitness value of each second individual of the second initial population according to a second fitness function;
[0090] Selection, crossover and mutation operations are performed according to the fitness value of each second individual to generate the optimal cooling strategy.
[0091] Preferably, the heat load of each area of the cold storage is calculated based on the items to be refrigerated corresponding to each area of the cold storage and the historical inbound and outbound quantities of the various items to be refrigerated, as well as the optimal refrigeration conditions, including:
[0092] For each area, the heat transfer load of the area's enclosure structure is calculated based on the area's refrigeration temperature and the refrigeration temperature of the adjacent area. The cargo breathing heat load of the area is calculated based on the historical incoming and outgoing volumes of the items to be refrigerated in the area, as well as the breathing intensity. The door opening heat intrusion load of the area is calculated based on the historical incoming and outgoing volumes of the items to be refrigerated in the area. The heat load of the area is calculated based on the heat transfer load of the area's enclosure structure, the cargo breathing heat load, and the door opening heat intrusion load.
[0093] Specifically, the heat transfer load of the enclosure structure refers to the load caused by heat transfer due to the temperature difference between the regional enclosure structure (such as walls, ceilings, floors, etc.) and the external environment or adjacent areas. Accurately calculating this load helps to understand the heat lost or absorbed by the regional enclosure structure. First, it is necessary to determine the regional refrigeration temperature T reg and the refrigeration temperature T of the adjacent area adj (If it is adjacent to the outside environment, use the outside environment temperature T ext ). Calculate the temperature difference ΔT = |Treg -T adj ∣(When adjacent to the external environment, ΔT = ∣T reg -T ext ∣). Obtain the area A and heat transfer coefficient K of the enclosure structure. The heat transfer coefficient K reflects the ability of the enclosure structure to prevent heat transfer. Its value is related to factors such as the material, thickness, and thermal insulation performance of the enclosure structure. The heat transfer load Q of the enclosure structure wall = K × A × ΔT × t, where t is time, typically expressed in hours. This formula represents the amount of heat transferred through the building envelope during that time. If considering building envelopes with different orientations (such as walls facing different directions), the heat transfer load in each direction must be calculated separately and then summed to obtain the total building envelope heat transfer load.
[0094] Many items to be refrigerated (such as fruits and vegetables) will respire during storage, releasing heat. The cargo respiration heat load reflects the heat generated by this biological activity and has a significant impact on the total heat load of the area. Assuming that the total refrigeration capacity at multiple historical time points is averaged over a period of time, and the total refrigeration capacity required for the items to be refrigerated is calculated as W, then the cargo respiration heat load Q is resp =q×W×t, where t is time and q is breathing intensity, that is, the amount of heat released by an item of unit weight per unit time, which can be determined based on experimental data.
[0095] The historical inbound and outbound volumes of refrigerated items in the corresponding area can be counted to estimate the number of door openings n and the average time t for each door opening in a period (for example, daily or weekly) in the area. open , get the external environment temperature T ext , Regional refrigeration temperature T reg 、The area of the gate A door And the heat transfer coefficient h of the air, each time the door is opened, the heat entering the area Q open,single It can be calculated by approximate formula, such as Q open,single =h×A door ×(T ext -T reg )×t open The door opening heat intrusion load Q in one cycle is open =n×Q open,single .
[0096] The heat load of the area can be calculated by summing the heat transfer load of the area's enclosure structure, the cargo breathing heat load, and the door opening heat intrusion load.
[0097] Preferably, the in-and-out correlation coefficient between any two areas is calculated based on the historical in-and-out quantities of the items to be refrigerated and the historical out-and-in quantities of the items to be refrigerated corresponding to each area of the cold storage:
[0098] Calculate the outbound correlation coefficient and inbound correlation coefficient of any two items to be refrigerated based on historical inbound quantities and historical outbound quantities of a plurality of items to be refrigerated. Specifically, for any two items to be refrigerated, the historical inbound quantities of the two items to be refrigerated may be substituted into a correlation coefficient calculation formula (e.g., a Pearson correlation coefficient, a Spearman rank correlation coefficient, etc.) to obtain the outbound correlation coefficient of the two items to be refrigerated. The historical outbound quantities of the two items to be refrigerated may be substituted into the correlation coefficient calculation formula to obtain the outbound correlation coefficient of the two items to be refrigerated.
[0099] Calculate the outbound and inbound correlation coefficients of any two items to be refrigerated based on the outbound correlation coefficients and inbound correlation coefficients of any two items to be refrigerated. Specifically, the outbound and inbound correlation coefficients of the two items to be refrigerated may be weighted and summed to obtain the outbound and inbound correlation coefficients of the two items to be refrigerated.
[0100] For any two areas, based on the in-and-out correlation coefficients of any two items to be refrigerated, determine the in-and-out correlation coefficient of any one type of item to be refrigerated corresponding to one area and any one type of item to be refrigerated corresponding to another area, and calculate the in-and-out correlation coefficients of any two areas. Specifically, the average of the in-and-out correlation coefficients of each type of item to be refrigerated corresponding to one area and each type of item to be refrigerated corresponding to another area can be calculated as the in-and-out correlation coefficient of the two areas.
[0101] As you can understand, the heat load of each zone is calculated and an initial cooling strategy is generated based on the heat load to ensure that the heat load assigned to the refrigeration units matches the actual demand. This prevents refrigeration units from overloading due to excessive heat load, which affects cooling performance and equipment lifespan. It also prevents refrigeration units from operating stably and reducing efficiency due to insufficient heat load. Through precise matching, refrigeration units consistently operate within a reasonable load range, improving cooling efficiency and ensuring stable temperatures in all areas of the cold storage, thereby meeting the refrigeration needs of goods. Multiple initial cooling strategies are generated and continuously optimized using a genetic algorithm (selection, crossover, and mutation operations) to ultimately determine the optimal cooling strategy. This strategy appropriately determines the number of operating refrigeration units and the zones assigned to each refrigeration unit, avoiding unnecessary refrigeration unit operation, improving the overall operating efficiency of the refrigeration system, and ensuring appropriate cooling performance for all areas of the cold storage. The optimal cooling strategy takes into account the heat load matching of the refrigeration units, avoiding energy waste caused by refrigeration units operating at excessive or insufficient loads. By rationally distributing the heat load and optimizing refrigeration unit operation, energy consumption is reduced, thereby lowering cold storage operating costs.
[0102] Finally, it should be understood that the embodiments described in this specification are intended only to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, by way of example and not limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly described and illustrated in this specification.
Claims
1. A partition control system for fixed cold storage, characterized in that: include: An information acquisition module is used to obtain the historical inbound and outbound quantities, optimal refrigeration conditions, and respiratory intensity types of various items to be refrigerated; An item grouping module is used to group a plurality of items to be refrigerated according to the optimal refrigeration conditions and respiration intensity types of the plurality of items to be refrigerated, and determine a plurality of item groups; The partition control module is used to determine the items to be refrigerated corresponding to each area of the cold storage based on the historical incoming and outgoing quantities of multiple item groups and multiple items to be refrigerated. It is also used to determine the optimal refrigeration strategy based on the historical incoming and outgoing quantities of the items to be refrigerated corresponding to each area of the cold storage and multiple items to be refrigerated, as well as the optimal refrigeration conditions, and control multiple refrigeration units to perform partitioned refrigeration of the cold storage according to the optimal refrigeration strategy.
2. The partition control system for fixed cold storage according to claim 1 is characterized in that: The item grouping module groups a plurality of items to be refrigerated according to the optimal refrigeration conditions and the respiratory intensity types of the plurality of items to be refrigerated, and determines a plurality of item groups, including: Determine the refrigeration cycle of each item to be refrigerated based on the historical inbound and outbound quantities of the items to be refrigerated; Dividing the plurality of items to be refrigerated into a plurality of item units according to their respiration intensity types, wherein one item unit corresponds to one respiration intensity type; For each item unit, determining a plurality of item clusters included in the item unit according to optimal refrigeration conditions of a plurality of items to be refrigerated included in the item unit; For each item cluster, determining a plurality of initial item groups included in the item cluster according to refrigeration cycles of a plurality of items to be refrigerated included in the item cluster; Based on the number of areas and space size of the cold storage and historical inbound and outbound quantities of various items to be refrigerated, multiple initial item groups are merged to determine multiple item groups.
3. The partition control system for fixed cold storage according to claim 2 is characterized in that: According to the optimal refrigeration conditions of the multiple items to be refrigerated included in the item unit, a plurality of item clusters included in the item unit are determined, including: Calculating the similarity of the optimal refrigeration conditions of any two items to be refrigerated included in the item unit based on the optimal refrigeration conditions of the multiple items to be refrigerated included in the item unit; A plurality of item clusters included in the item unit are determined by using a first clustering algorithm according to similarities between optimal refrigeration conditions of any two items to be refrigerated included in the item unit.
4. The partition control system for a fixed cold storage according to claim 3 is characterized in that: According to the refrigeration cycles of the multiple items to be refrigerated included in the item cluster, a plurality of initial item groups included in the item cluster are determined, including: Calculating a difference in refrigeration cycles between any two items to be refrigerated included in the item cluster based on refrigeration cycles of the multiple items to be refrigerated included in the item cluster; A plurality of initial item groups included in the item cluster are determined by using a second clustering algorithm according to differences in refrigeration cycles between any two items to be refrigerated included in the item cluster.
5. The partition control system for fixed cold storage according to claim 4 is characterized in that: Based on the number and size of cold storage areas and the historical inbound and outbound volumes of various items to be refrigerated, multiple initial item groups are merged to determine multiple item groups, including: Based on the space size of the cold storage area and the historical inbound and outbound volumes of various items to be refrigerated, determine the number of areas required for each initial item group and calculate the total number of areas required for multiple initial item groups; Determine whether the total number of areas required for the multiple initial item groups is greater than the number of areas in the cold storage; If so, based on the difference in refrigeration cycles between any two to-be-refrigerated items included in the item cluster and the number of zones required for each initial item group, multiple initial item groups included in each item cluster are merged.
6. The partition control system for a fixed cold storage according to any one of claims 1 to 5, characterized in that: The partition control module determines the items to be refrigerated corresponding to each area of the cold storage according to the historical inbound and outbound quantities of multiple item groups and multiple items to be refrigerated, including: Establishing a first set of constraints; generating a plurality of initial item refrigeration plans based on the first set of constraints, a plurality of item groups, and historical inbound and outbound quantities of a plurality of items to be refrigerated, wherein the item refrigeration plans include an item group corresponding to each area of the cold storage; Take each initial item cold storage plan as a first individual to generate a first initial population; Establish the first fitness function; Determining the fitness value of each first individual of the first initial population according to the first fitness function; Perform selection, crossover, and mutation operations based on the fitness value of each first individual to generate the optimal item refrigeration plan; According to the optimal item refrigeration plan, determine the items to be refrigerated corresponding to each area of the cold storage.
7. The partition control system for a fixed cold storage according to claim 5, characterized in that: Determining the fitness value of each first individual of the first initial population according to the fitness function includes: For each first individual, determine the refrigeration cycle of the items to be refrigerated corresponding to each area of the cold storage and the minimum transportation distance between each area and the entrance and exit of the cold storage, and calculate the refrigeration condition difference value of any two adjacent areas based on the optimal refrigeration conditions of the items to be refrigerated corresponding to each area of the cold storage. Calculate the global refrigeration condition difference value based on the refrigeration condition difference value of any two adjacent areas. According to the fitness function, determine the fitness value of the first individual based on the refrigeration cycle of the items to be refrigerated corresponding to each area of the cold storage, the minimum transportation distance between each area and the entrance and exit of the cold storage, and the global refrigeration condition difference value.
8. The partition control system for a fixed cold storage according to any one of claims 1 to 5, characterized in that: Determine the optimal refrigeration strategy based on the items to be refrigerated in each cold storage area, the historical inbound and outbound volumes of various items to be refrigerated, and the optimal refrigeration conditions, including: Calculate the correlation coefficient between the inflow and outflow of any two areas based on the historical inflow and outflow of items to be refrigerated and the historical outflow of multiple items to be refrigerated corresponding to each area of the cold storage; Calculate the heat load of each area of the cold storage based on the items to be refrigerated, the historical inbound and outbound volumes of various items to be refrigerated, and the optimal refrigeration conditions. Establishing a second set of constraints; generating a plurality of initial cooling strategies based on the second set of constraints and the heat load of each zone, wherein the initial cooling strategies include the number of operating refrigeration units and the zones corresponding to each refrigeration unit; Take each initial cooling strategy as a second individual to generate a second initial population; Establishing a second fitness function, wherein the second fitness function is related to the in-and-out correlation coefficient of any two areas and the heat load of the area corresponding to each refrigeration unit; determining a fitness value of each second individual of the second initial population according to a second fitness function; Selection, crossover and mutation operations are performed according to the fitness value of each second individual to generate the optimal cooling strategy.
9. The partition control system for a fixed cold storage according to claim 8, characterized in that: Based on the historical inbound and outbound quantities of items to be refrigerated and various items to be refrigerated corresponding to each area of the cold storage, the inbound and outbound correlation coefficients of any two areas are calculated: Calculate the outbound correlation coefficient and inbound correlation coefficient of any two items to be refrigerated based on the historical inbound and outbound quantities of multiple items to be refrigerated; Calculate the outbound and inbound correlation coefficients of any two items to be refrigerated based on the outbound correlation coefficients and inbound correlation coefficients of any two items to be refrigerated; For any two areas, based on the in-and-out correlation coefficients of any two items to be refrigerated, the in-and-out correlation coefficients of any one type of item to be refrigerated corresponding to one area and any one type of item to be refrigerated corresponding to another area are determined, and the in-and-out correlation coefficients of any two areas are calculated.
10. The partition control system for a fixed cold storage according to claim 9, characterized in that: Based on the items to be refrigerated in each cold storage area, the historical inbound and outbound volumes of various items to be refrigerated, and the optimal refrigeration conditions, the heat load of each area is calculated, including: For each area, the heat transfer load of the area's enclosure structure is calculated based on the area's refrigeration temperature and the refrigeration temperature of the adjacent area. The cargo breathing heat load of the area is calculated based on the historical incoming and outgoing volumes of the items to be refrigerated in the area, as well as the breathing intensity. The door opening heat intrusion load of the area is calculated based on the historical incoming and outgoing volumes of the items to be refrigerated in the area. The heat load of the area is calculated based on the heat transfer load of the area's enclosure structure, the cargo breathing heat load, and the door opening heat intrusion load.