Central air conditioning system operation optimization methods, devices, equipment, media and products

Abstract

The present application discloses a method, device, equipment, medium and product for optimizing the operation of a central air-conditioning system, which relates to the field of air-conditioning energy-saving management technology. The method is to first obtain the static parameters of each device in the central air-conditioning system, and periodically obtain the dynamic parameters of each device, and then optimize the operation plan of the air-conditioning system in the current next cycle based on the optimization algorithm, obtain the operation plan and the optimal search result for minimizing the energy consumption of the air-conditioning system, maximizing the operating efficiency and balancing the equipment loss, and finally execute the optimal search result in the current next cycle, so as to achieve energy saving and consumption reduction of the system, efficient operation and equipment loss balancing. In addition, it can also have a self-protection mechanism in an emergency to ensure the safe operation of the equipment and system, which is convenient for practical application and promotion.

Description

Technical Field

[0001] The present invention belongs to the technical field of air-conditioning energy-saving management, and specifically relates to a method, device, equipment, medium and product for optimizing the operation of a central air-conditioning system. Background Art

[0002] A central air conditioning system centrally manages the air conditioning needs of an entire building or area, using air ducts, water systems, or refrigerants to deliver cooling (heat) and heat to precisely control the indoor environment. A central air conditioning system consists of a heat and cooling subsystem, an air conditioning subsystem, piping, and terminal equipment. It utilizes the principle of liquid vaporization refrigeration to provide the required cooling to the air conditioning subsystem to offset the indoor heat load, while the heat source subsystem provides the required heat to offset the indoor cooling load. Specifically, the heat and cooling subsystem includes the refrigeration unit, cooling tower, chilled water pump, and cooling water pump, responsible for generating the heat and cooling. The air conditioning subsystem includes fan coil units, modular air conditioning units, and fresh air handlers, responsible for delivering the heat and cooling to each room. Piping connects the heat and cooling subsystems to the air conditioning subsystem, enabling heat and cooling transfer. Terminal equipment includes fan coil units and indoor units, providing direct heating and cooling services to the rooms.

[0003] At present, central air-conditioning systems have been widely used in large buildings, and their energy consumption accounts for a high proportion of the total energy consumption of the building. However, the existing central air-conditioning system operation and management solutions have the following main problems: (1) Insufficient dynamic parameter monitoring, that is, there is a lack of real-time monitoring of the dynamic parameters of each device in the system (such as real-time operating power, switch status and fault status, etc.). These parameters will change with the operation of the device and environmental changes. The existing solution cannot obtain these parameters in real time and use them for operation management, resulting in low system operation efficiency and excessive energy consumption; (2) Unbalanced equipment loss, that is, in the existing solution, the operating time of the equipment is not fully utilized to balance the equipment loss. Some equipment may be damaged prematurely due to excessive use, while other equipment is underused, resulting in uneven service life of different equipment; (3) Unclear definition of equipment roles, that is, the responsibilities of different devices in the central air-conditioning system (such as host role, slave role or backup role) are not clearly defined, resulting in a lack of logic in the behavior of the equipment at different operation stages; (4) Untimely response to equipment failure, that is, in the event of equipment failure or emergency, the existing solution lacks a rapid response mechanism. For example, when a device fails, the existing solution cannot automatically switch to the backup device, resulting in system shutdown or unstable operation.

[0004] Based on the above situation, how to optimize the operation of equipment in the central air-conditioning system to achieve energy saving and consumption reduction, efficient operation and equipment loss balancing of the system is a topic that technical personnel in this field urgently need to study. Summary of the Invention

[0005] The purpose of the present invention is to provide a method, device, computer equipment, computer-readable storage medium and computer program product for optimizing the operation of a central air-conditioning system, so as to solve the problems of low system operation efficiency, excessive energy consumption and uneven equipment loss in existing central air-conditioning system operation management solutions.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, a method for optimizing the operation of a central air-conditioning system is provided, comprising:

[0008] Obtaining static parameters of each device in the central air-conditioning system, wherein the static parameters include the rated power of the corresponding device;

[0009] Periodically acquiring dynamic parameters of each device, wherein the dynamic parameters include real-time operating power, switch status, and operating time of the corresponding device;

[0010] Applying the static parameters of each device and the dynamic parameters of each device in the current and most recent consecutive cycles, optimizing the operation plan of the central air-conditioning system in the current and next cycles based on an optimization algorithm, obtaining the operation plan and using it to achieve a multi-objective optimal optimization search result, wherein the operation plan includes the operating status of each device in the current and next cycles, and the multi-objective optimality refers to minimizing energy consumption, maximizing operating efficiency, and balancing equipment losses of the central air-conditioning system in the current and most recent consecutive cycles and the current and next cycles;

[0011] The optimized search result of the operating solution is executed in the current next cycle.

[0012] Based on the above invention content, a new solution is provided for optimizing the operation of equipment in a central air-conditioning system based on the dynamic and static parameters of the equipment and an optimization algorithm. That is, the static parameters of each device in the central air-conditioning system are first obtained, and the dynamic parameters of each device are periodically obtained. Then, based on the optimization algorithm, the operation plan of the air-conditioning system in the current next cycle is optimized to obtain the operation plan and the optimal search result for minimizing the energy consumption of the air-conditioning system, maximizing the operating efficiency, and balancing the equipment loss. Finally, the optimal search result is executed in the current next cycle. In this way, energy saving and consumption reduction, efficient operation, and equipment loss balancing of the system can be achieved, which is convenient for practical application and promotion.

[0013] In one possible design, the multi-objective optimization adopts the following objective function to be minimized: To express:

[0014]

[0015] Where, Indicates the energy consumption of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates the operating efficiency of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates a first indicator value for evaluating equipment loss balance of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates the total number of devices in the central air-conditioning system, Indicates less than or equal to A positive integer, Indicates the first The rated power of the device, Indicates the The running time of each device in the current most recent consecutive cycles and the current next cycle, Indicates the The real-time operating power of each device in the current most recent multiple consecutive cycles and the current next cycle, Indicates the average operating time of all devices in the central air-conditioning system in the most recent consecutive cycles and the next cycle. represents the weight factor corresponding to the energy consumption and is a positive value, represents the weight factor corresponding to the operating efficiency and is a negative value, represents the weight factor corresponding to the first indicator value and is a positive value.

[0016] In a possible design, the dynamic parameters also include the fault status of the corresponding equipment. The multi-objective optimization refers to minimizing the energy consumption of the central air-conditioning system in the current and recent consecutive cycles and the current next cycle, maximizing the operating efficiency, balancing the equipment loss, and timely emergency protection. The objective function Replace it with the following:

[0017]

[0018] Where, Indicates the energy consumption of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates the operating efficiency of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates a first indicator value for evaluating equipment loss balance of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates the second indicator value of the central air-conditioning system in the current next cycle and used to evaluate the timeliness of emergency protection, Indicates the total number of devices in the central air-conditioning system, Indicates less than or equal to A positive integer, Indicates the first The rated power of the device, Indicates the The running time of each device in the current most recent consecutive cycles and the current next cycle, Indicates the The real-time operating power of each device in the current most recent multiple consecutive cycles and the current next cycle, Indicates the The fault continuation flag of each device from the current most recent cycle to the current next cycle is used with a value of zero to indicate that the fault is not continued and a value of 1 to indicate that the fault is continued. Indicates the cycle length, Indicates the average operating time of all devices in the central air-conditioning system in the most recent consecutive cycles and the next cycle. represents the weight factor corresponding to the energy consumption and is a positive value, represents the weight factor corresponding to the operating efficiency and is a negative value, represents the weight factor corresponding to the first index value and is a positive value, represents the weight factor corresponding to the second index value and is a positive value.

[0019] In one possible design, the static parameters further include defined roles of corresponding devices, wherein the defined roles are divided into a master role, a slave role, and / or a backup role. The master role refers to a device role that starts when the central air-conditioning system starts and assumes the main load task. The slave role refers to a device role that starts when the master device is running and assumes the secondary load task and / or takes over the master task when the master device fails. The backup role refers to a device role that automatically starts when the master device fails and ensures uninterrupted operation of the system.

[0020] Applying the static parameters of each device and the dynamic parameters of each device in the most recent consecutive cycles, optimizing the operation plan of the central air-conditioning system in the next cycle based on an optimization algorithm, obtaining the operation plan and using it to achieve the optimal multi-objective optimization search result, including:

[0021] Determine, based on the static parameters of each device and the dynamic parameters of each device in the most recent cycle, whether there is a device in the central air-conditioning system whose role is defined as a master role and whose fault status in the most recent cycle is faulty;

[0022] If it is determined that there is no device in the central air-conditioning system whose role is defined as the host role and whose fault status in the current most recent cycle is faulty, then the static parameters of the various devices and the dynamic parameters of the various devices in the current most recent consecutive cycles are applied to optimize the operation plan of the central air-conditioning system in the current next cycle based on the optimization algorithm, and the operation plan is obtained and used to achieve the optimal optimization search result for multiple objectives, wherein the operation plan includes the operation status of the various devices in the current next cycle, and the multi-objective optimality refers to minimizing the energy consumption of the central air-conditioning system in the current most recent consecutive cycles and the current next cycle, maximizing the operation efficiency, balancing the equipment loss, and timely emergency protection;

[0023] If it is determined that there is any device in the central air-conditioning system whose role is defined as a master role and whose fault status in the most recent cycle is faulty, the following constraint conditions are configured for the operation plan of the central air-conditioning system in the current next cycle according to the static parameters of each device: the operation status of any device in the current next cycle is shutdown, and the operation status of other devices with the same capability as the any device and whose positioning role is a slave role or a standby role is enabled in the current next cycle;

[0024] Applying the static parameters of each device, the dynamic parameters of each device in the most recent multiple consecutive cycles, and the constraints, the operation plan is optimized based on the optimization algorithm to obtain the operation plan and use it to achieve the best optimization search result for multiple objectives.

[0025] In one possible design, the method further includes:

[0026] Determine, according to the static parameters of each device and the dynamic parameters of each device in the most recent current cycle, the number of devices in the central air-conditioning system that are defined as a master role and have a fault status of faulty in the most recent current cycle;

[0027] The weighting factor is adjusted in direct correlation with the quantity .

[0028] In one possible design, the optimization algorithm adopts an improved NSGA-II algorithm, a particle swarm optimization algorithm, a gray wolf optimization algorithm, a bat optimization algorithm, a sky eagle optimization algorithm, a vulture optimization algorithm or a genetic optimization algorithm.

[0029] In a second aspect, a central air-conditioning system operation optimization device is provided, comprising a static parameter acquisition unit, a dynamic parameter acquisition unit, an operation plan optimization unit, and an optimal plan execution unit;

[0030] The static parameter acquisition unit is used to acquire the static parameters of each device in the central air-conditioning system, wherein the static parameters include the rated power of the corresponding device;

[0031] The dynamic parameter acquisition unit is used to periodically acquire the dynamic parameters of each device, wherein the dynamic parameters include the real-time operating power, switch status and operating time of the corresponding device;

[0032] The operation plan optimization unit is communicatively connected to the static parameter acquisition unit and the dynamic parameter acquisition unit, respectively, and is used to apply the static parameters of each device and the dynamic parameters of each device in the current and latest consecutive cycles to optimize the operation plan of the central air-conditioning system in the current and next cycles based on the optimization algorithm, so as to obtain the operation plan and achieve a multi-objective optimal optimization search result, wherein the operation plan includes the operation status of each device in the current and next cycles, and the multi-objective optimality refers to minimizing the energy consumption, maximizing the operation efficiency, and balancing the equipment losses of the central air-conditioning system in the current and latest consecutive cycles and the current and next cycles;

[0033] The optimal solution execution unit is communicatively connected to the operation solution optimization unit, and is used to execute the optimized search result of the operation solution in the current next cycle.

[0034] In a third aspect, the present invention provides a computer device comprising a memory, a processor and a transceiver which are communicatively connected in sequence, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the central air-conditioning system operation optimization method as described in the first aspect or any possible design of the first aspect.

[0035] In a fourth aspect, the present invention provides a computer-readable storage medium having instructions stored thereon. When the instructions are executed on a computer, the central air-conditioning system operation optimization method as described in the first aspect or any possible design of the first aspect is executed.

[0036] In a fifth aspect, the present invention provides a computer program product, comprising a computer program or instructions, which, when executed by a computer, implements the central air-conditioning system operation optimization method as described in the first aspect or any possible design of the first aspect.

[0037] Beneficial effects of the above scheme:

[0038] (1) The present invention creatively provides a new solution for optimizing the operation of equipment in a central air-conditioning system based on the dynamic and static parameters of the equipment and an optimization algorithm. That is, the static parameters of each device in the central air-conditioning system are first obtained, and the dynamic parameters of each device are periodically obtained. Then, based on the optimization algorithm, the operation plan of the air-conditioning system in the current next cycle is optimized to obtain the operation plan and the optimal search result for minimizing the energy consumption of the air-conditioning system, maximizing the operation efficiency, and balancing the equipment loss. Finally, the optimal search result is executed in the current next cycle. In this way, energy saving and consumption reduction, efficient operation, and equipment loss balancing of the system can be achieved, which is convenient for practical application and promotion.

[0039] (2) Significant energy-saving effect: that is, the optimized equipment can significantly reduce energy consumption while meeting the system operation requirements;

[0040] (3) Improved operating efficiency: By optimizing the algorithm, the equipment can be ensured to operate in the high-efficiency range, thereby improving the overall operating efficiency of the system;

[0041] (4) Equipment loss balancing: that is, through the optimization algorithm, the equipment with the shortest current operation time can be given priority to achieve loss balancing of different equipment and extend their service life;

[0042] (5) Intelligent optimization: that is, it can dynamically adjust the optimization target weight according to the real-time operating conditions to adapt to the operating requirements under different working conditions;

[0043] (6) It can realize self-protection in emergency situations: that is, when the equipment fails or the system is abnormal, it can automatically switch to the backup equipment and dynamically adjust the operation plan to ensure the stability and security of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 A flow chart of a method for optimizing the operation of a central air-conditioning system provided in an embodiment of the present application.

[0046] Figure 2 A schematic diagram of the structure of the central air-conditioning system operation optimization device provided in an embodiment of the present application.

[0047] Figure 3 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the present invention will be briefly introduced below in conjunction with the drawings and the description of the embodiments or the prior art. Obviously, the following description of the structures of the drawings is only some embodiments of the present invention. For those skilled in the art, other embodiments can be obtained based on these embodiments without creative work. It should be noted that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation of the present invention.

[0049] It should be understood that although the terms first, second, etc. may be used herein to describe various objects, these objects should not be limited by these terms. These terms are merely used to distinguish one object from another. For example, a first object can be referred to as a second object, and similarly, a second object can be referred to as a first object without departing from the scope of the exemplary embodiments of the present invention.

[0050] It should be understood that the term "and / or" that may appear in this document is merely a description of the association relationship between associated objects, indicating that there may be three relationships. For example, A and / or B can indicate three situations: A exists alone, B exists alone, or A and B exist at the same time. For another example, A, B and / or C can indicate the existence of any one of A, B and C or any combination of them. The term " / and" that may appear in this document describes another type of association object relationship, indicating that there may be two relationships. For example, A / and B can indicate two situations: A exists alone or A and B exist at the same time. In addition, the character " / " that may appear in this document generally indicates that the previous and next associated objects are in an "or" relationship.

[0051] Example

[0052] like Figure 1 As shown, the central air-conditioning system operation optimization method provided in the first aspect of this embodiment can be executed by, but is not limited to, a computer device with certain computing resources, such as a central air-conditioning system management server, a cloud server, a personal computer (PC, a multi-purpose computer with a size, price and performance suitable for personal use; desktops, laptops, small laptops, tablets and ultrabooks are all personal computers), a smart phone, a personal digital assistant (PDA) or a wearable device. Figure 1 As shown, the central air-conditioning system operation optimization method may include, but is not limited to, the following steps S1 to S4.

[0053] S1. Obtain static parameters of each device in the central air-conditioning system, wherein the static parameters include but are not limited to the rated power of the corresponding device.

[0054] In step S1, the central air conditioning system is composed of a cold and heat source subsystem, an air conditioning subsystem, a transmission pipeline, and terminal equipment. The cold and heat source subsystem includes, but is not limited to, a refrigeration unit, a cooling tower, a chilled water pump, and a cooling water pump, which are responsible for generating cold and heat sources; the air conditioning subsystem includes, but is not limited to, fan coil units, a combined air conditioning unit, and a fresh air handler, which are responsible for transmitting the cold and heat sources to each room; the transmission pipeline is used to connect the cold and heat source subsystem and the air conditioning subsystem to achieve cold and heat transmission; the terminal equipment includes fan coil units and indoor units, which are used to directly provide cold and heat services to the room; thus, the various devices may include, but are not limited to, a refrigeration unit, a cooling tower, a chilled water pump, a cooling water pump, a combined air conditioning unit, a fresh air handler, and / or an indoor unit. The static parameters may be pre-stored in the equipment file through, but not limited to, manual entry for ready access. In order to address the problem of unclear definition of device roles in the central air-conditioning system, preferably, the static parameters also include but are not limited to the defined roles of the corresponding devices, wherein the defined roles are divided into but not limited to the host role, the slave role and / or the backup role, etc. The host role refers to the device role that starts when the central air-conditioning system starts and takes on the main load task, the slave role refers to the device role that starts when the host device is running and takes on the secondary load task and / or takes over the host task when the host device fails, and the backup role refers to the device role that automatically starts when the host device fails and ensures uninterrupted operation of the system. The defined roles of the aforementioned various devices are determined by the management personnel based on the device configuration and system design requirements, and can be stored in the device file by manual entry, and can also be managed through the system configuration file (that is, the role and responsibilities of each device are clearly defined in the system configuration file, so that the defined roles of different devices can be determined by reading these configuration files during system operation management). In addition, the defined roles of the aforementioned devices can be dynamically adjusted according to the system operating status and operating requirements when the system is running; for example, when the system load increases, the device defined as the slave role can be dynamically adjusted to the master role to share more load; when the device defined as the master role fails, another device defined as the slave role or the backup role can automatically switch to the master role to ensure the normal operation of the system.

[0055] S2. Periodically obtain dynamic parameters of each device, wherein the dynamic parameters include but are not limited to real-time operating power, switch status, and operating time of the corresponding device.

[0056] In step S2, considering that the operating state of the central air-conditioning system is relatively stable at the minute level, and in order to provide sufficient time for the system operation optimization task to complete the calculation and adjust the operation plan, the aforementioned cycle can be specifically designed to be at the minute level, for example, the dynamic parameters of each device in the current last 5 minutes are obtained every 5 minutes (that is, the cycle duration is equal to 5 minutes). The dynamic parameters can be specifically collected and uploaded in real time by existing Internet of Things sensors. For example, the real-time operating power of each device can be obtained by real-time collection through existing power meter products. The operating time can specifically be the actual operating time or the equivalent operating time, wherein the former can be obtained by recording the switch status of the corresponding device in real time and accumulating the duration of the switch status being on, while the latter can be obtained by recording the real-time operating power of the corresponding device in real time and calculating it according to the following formula:

[0057]

[0058] Where, represents a positive integer, Indicates the first The equivalent operating time of a device in a cycle, Indicates the The real-time operating power of each device during the cycle, Indicates the cycle length, Indicates the In addition, the dynamic parameters also include but are not limited to the fault status of the corresponding equipment, wherein the fault status can also be collected and uploaded in real time by existing IoT sensors.

[0059] S3. Apply the static parameters of each device and the dynamic parameters of each device in the current most recent multiple consecutive cycles, optimize the operation plan of the central air-conditioning system in the current next cycle based on the optimization algorithm, obtain the operation plan and use it to achieve the optimal multi-objective search result, wherein the operation plan includes but is not limited to the operation status of each device in the current next cycle, etc. The multi-objective optimization refers to minimizing the energy consumption of the central air-conditioning system in the current most recent multiple consecutive cycles and the current next cycle, maximizing the operation efficiency and balancing the equipment loss.

[0060] In step S3, the operation scheme may be, but is not limited to, the following one-dimensional vector in the optimization algorithm: To express:

[0061]

[0062] Where, Indicates the total number of devices in the central air-conditioning system, Indicates less than or equal to A positive integer, Indicates the first The operating status of each device in the next cycle (i.e., the next cycle after the current most recent consecutive cycles) is represented by a value of zero for shutdown and a value of 1 for activation. Specifically, the multi-objective optimization can be, but is not limited to, the following objective function to be minimized: To express:

[0063]

[0064] Where, Indicates the energy consumption of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates the operating efficiency of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates a first indicator value for evaluating equipment loss balance of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates the total number of devices in the central air-conditioning system, Indicates less than or equal to A positive integer, Indicates the first The rated power of the device, Indicates the The running time of each device in the current most recent multiple consecutive cycles and the current next cycle, Indicates the The real-time operating power of each device in the current most recent multiple consecutive cycles and the current next cycle, Indicates the average operating time of all devices in the central air-conditioning system in the most recent consecutive cycles and the next cycle. represents the weight factor corresponding to the energy consumption and is a positive value, represents the weight factor corresponding to the operating efficiency and is a negative value, represents the weight factor corresponding to the first index value and is a positive value. The operation time and real-time operation power of the device in the current most recent multiple consecutive cycles can be directly based on the first The dynamic parameters of the device are obtained by regular statistics of the most recent multiple consecutive cycles. Although the operation time and real-time operation power of each device in the next cycle cannot be collected in advance, they can be estimated in the following ways, but not limited to: (1) If the first The running state of the device in the next cycle is shutdown (i.e. ), then it is estimated that the The running time and real-time running power of the device in the next cycle are both zero; (2) if the The operating state of the device in the next cycle is enabled (i.e. ), then it is estimated that the The running time of the device in the next cycle is The first device extracts the dynamic parameters of the most recent multiple consecutive cycles The running time of the device in the most recent cycle when the switch state is on (or estimated as the the average running time of each device in all cycles when the switch state is on), and estimate the The real-time operating power of the device in the next cycle is from the The first device extracts the dynamic parameters of the most recent multiple consecutive cycles The real-time operating power of the device in the most recent cycle (or estimated to be the The average real-time operating power of each device in all cycles when the switch state is on). In addition, the average operating time It can be obtained based on the conventional statistics of the running time of all the devices in the current multiple consecutive cycles and the current next cycle, as well as the aforementioned weight factor 、 and Default values ​​preset based on the optimization strategy may be specifically adopted, and the sum of their absolute values ​​may be equal to 1 or may not be equal to 1.

[0065] In step S3, the optimization algorithm may be, but is not limited to, a modified NSGA-II algorithm, a particle swarm optimization algorithm, a gray wolf optimization algorithm, a bat optimization algorithm, a sky eagle optimization algorithm, a vulture optimization algorithm, or a genetic optimization algorithm. These algorithms are all existing algorithms, and the specific optimization process can be derived from conventional methods of existing algorithms. Taking the modified NSGA-II algorithm as an example, the optimization process specifically includes, but is not limited to, the following operations (A) to (E).

[0066] (A) Initialize the population: The population size is designed to be , each population individual represents an operation scheme to be selected, and randomly generates the initialized The operating plan described above.

[0067] (B) Fitness calculation: For each individual in the population, the corresponding fitness is calculated based on the objective function according to the corresponding operation plan.

[0068] (C) Genetic operation: When performing a selection operation, a roulette wheel selection method is used to select excellent individuals to enter the next generation based on their fitness values; when performing a crossover operation, a single-point crossover method is used to combine the chromosomes of two parent individuals (i.e., the operation scheme) to generate new offspring individuals.

[0069] (D) Mutation operation: Randomly change certain gene positions in the chromosome at a certain mutation rate to increase the diversity of the population.

[0070] (E) Iterative optimization: The operation plan is gradually optimized through iterative selection, crossover and mutation operations until a stopping condition is met (such as reaching a maximum number of iterations or a fitness threshold).

[0071] In step S3, in order to achieve the following optimization goal: in an emergency (such as equipment failure or system abnormality), a self-protection mechanism is provided to ensure the safety of the system and equipment. Preferably, when the dynamic parameters also include the failure status of the corresponding equipment, the multi-objective optimization refers to minimizing the energy consumption of the central air-conditioning system in the current and recent consecutive cycles and the current next cycle, maximizing the operating efficiency, balancing the equipment loss, and timely emergency protection. The objective function Replace it with the following:

[0072]

[0073] Where, Indicates the energy consumption of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates the operating efficiency of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates a first indicator value for evaluating equipment loss balance of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates the second indicator value of the central air-conditioning system in the current next cycle and used to evaluate the timeliness of emergency protection, Indicates the total number of devices in the central air-conditioning system, Indicates less than or equal to A positive integer, Indicates the first The rated power of the device, Indicates the The running time of each device in the current most recent multiple consecutive cycles and the current next cycle, Indicates the The real-time operating power of each device in the current most recent multiple consecutive cycles and the current next cycle, Indicates the The fault continuation flag of each device from the current most recent cycle to the current next cycle is used with a value of zero to indicate that the fault is not continued and a value of 1 to indicate that the fault is continued. Indicates the cycle length, Indicates the average operating time of all devices in the central air-conditioning system in the most recent consecutive cycles and the next cycle. represents the weight factor corresponding to the energy consumption and is a positive value, represents the weight factor corresponding to the operating efficiency and is a negative value, represents the weight factor corresponding to the first index value and is a positive value, represents the weight factor corresponding to the second index value and is a positive value. The fault continuation flag of a device from the current most recent cycle to the current next cycle can be specifically based on the The dynamic parameters of the device in the current most recent multiple consecutive cycles and the The operating status of a device in the next cycle is determined as follows: The fault status of the device in the current most recent cycle is that there is a fault, and the If the running state of the device in the next cycle is still enabled, the fault continuation flag is determined. is 1, otherwise the fault continuation flag is determined In addition, the aforementioned weight factor 、 、 and Similarly, default values ​​preset based on the optimization strategy may be specifically adopted, and the sum of their absolute values ​​may be equal to 1 or may not be equal to 1.

[0074] In step S3, in order to achieve automatic switching to the slave device and / or backup device through the operation plan when a device failure is detected, it is further preferred that when the static parameters also include the defined role of the corresponding device, the static parameters of each device and the dynamic parameters of each device in the current recent multiple consecutive cycles are applied, and the operation plan of the central air-conditioning system in the current next cycle is optimized based on the optimization algorithm to obtain the operation plan and to achieve the best multi-objective optimization search result, including but not limited to the following steps S31 to S34.

[0075] S31. Based on the static parameters of each device and the dynamic parameters of each device in the most recent cycle, determine whether there is a device in the central air-conditioning system whose role is defined as a host role and whose fault status in the most recent cycle is faulty.

[0076] In step S31 , since the static parameters also include the defined role of the corresponding device and the dynamic parameters also include the fault status of the corresponding device, the above-mentioned judgment can be directly implemented.

[0077] S32. If it is determined that there is no device in the central air-conditioning system whose role is defined as the host role and whose fault status in the current most recent cycle is faulty, then the static parameters of each device and the dynamic parameters of each device in the current most recent consecutive cycles are applied, and the operation plan of the central air-conditioning system in the current next cycle is optimized based on the optimization algorithm to obtain the operation plan and to achieve the optimal multi-objective search result, wherein the operation plan includes the operation status of each device in the current next cycle, and the multi-objective optimal refers to minimizing the energy consumption of the central air-conditioning system in the current most recent consecutive cycles and the current next cycle, maximizing the operation efficiency, balancing the equipment loss, and timely emergency protection.

[0078] S33. If it is determined that there is any device in the central air-conditioning system whose role is defined as the host role and whose fault status in the current most recent cycle is faulty, the following constraints are configured for the operation plan of the central air-conditioning system in the current next cycle based on the static parameters of each device: the operation status of any device in the current next cycle is shutdown, and other devices with the same capabilities as any device and whose positioning roles are slave roles or standby roles are enabled in the operation status of the current next cycle.

[0079] In step S33, for example, if any of the devices is a chiller, the other device may be a backup chiller. In addition, if there are multiple faulty devices, the constraint conditions need to be configured for each of these faulty devices.

[0080] S34. Apply the static parameters of each device, the dynamic parameters of each device in the current multiple consecutive cycles and the constraints, optimize the operation plan based on the optimization algorithm, and obtain the operation plan and use it to achieve the best optimization search result for multiple objectives.

[0081] In step S34, the constraint conditions are used as a basis for judging whether the generated operation plan is qualified during the optimization process: if the constraint conditions are met, it is qualified; otherwise, it is unqualified and a new operation plan needs to be regenerated. In addition, in order to achieve optimal processing of fault responses when equipment fails or the system is abnormal, it is further preferred that the method also includes but is not limited to: first, based on the static parameters of each device and the dynamic parameters of each device in the most recent current cycle, determine the number of devices in the central air-conditioning system that are defined as host roles and have a faulty fault status in the most recent current cycle, and then adjust the weight factor in positive correlation according to the number (i.e. the larger the number, the greater the weight factor The larger the number, the smaller the weight factor the smaller).

[0082] S4. Execute the optimized search result of the operation plan in the current next cycle.

[0083] Based on the central air-conditioning system operation optimization method described in the aforementioned steps S1 to S4, a new solution for optimizing the operation of equipment in the central air-conditioning system based on the dynamic and static parameters of the equipment and the optimization algorithm is provided. That is, the static parameters of each device in the central air-conditioning system are first obtained, and the dynamic parameters of each device are periodically obtained. Then, based on the optimization algorithm, the operation plan of the air-conditioning system in the current next cycle is optimized to obtain the optimal search result for the operation plan and to minimize the energy consumption of the air-conditioning system, maximize the operating efficiency, and balance the equipment losses. Finally, the optimal search result is executed in the current next cycle. In this way, energy saving and consumption reduction, efficient operation, and equipment loss balancing of the system can be achieved. In addition, it can also have a self-protection mechanism in emergency situations to ensure the safe operation of the equipment and system, which is convenient for practical application and promotion.

[0084] like Figure 2As shown, the second aspect of this embodiment provides a virtual device for implementing the central air-conditioning system operation optimization method described in the first aspect, comprising a static parameter acquisition unit, a dynamic parameter acquisition unit, an operation plan optimization unit, and an optimal plan execution unit;

[0085] The static parameter acquisition unit is used to acquire the static parameters of each device in the central air-conditioning system, wherein the static parameters include the rated power of the corresponding device;

[0086] The dynamic parameter acquisition unit is used to periodically acquire the dynamic parameters of each device, wherein the dynamic parameters include the real-time operating power, switch status and operating time of the corresponding device;

[0087] The operation plan optimization unit is communicatively connected to the static parameter acquisition unit and the dynamic parameter acquisition unit, respectively, and is used to apply the static parameters of each device and the dynamic parameters of each device in the current and latest consecutive cycles to optimize the operation plan of the central air-conditioning system in the current and next cycles based on the optimization algorithm, so as to obtain the operation plan and achieve a multi-objective optimal optimization search result, wherein the operation plan includes the operation status of each device in the current and next cycles, and the multi-objective optimality refers to minimizing the energy consumption, maximizing the operation efficiency, and balancing the equipment losses of the central air-conditioning system in the current and latest consecutive cycles and the current and next cycles;

[0088] The optimal solution execution unit is communicatively connected to the operation solution optimization unit, and is used to execute the optimized search result of the operation solution in the current next cycle.

[0089] The working process, working details and technical effects of the aforementioned device provided in the second aspect of this embodiment can be found in the central air-conditioning system operation optimization method described in the first aspect, and will not be repeated here.

[0090] like Figure 3As shown, a third aspect of this embodiment provides a computer device for executing the central air conditioning system operation optimization method described in the first aspect, comprising a memory, a processor, and a transceiver communicatively connected in sequence, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the central air conditioning system operation optimization method described in the first aspect. Specifically, the memory may include, but is not limited to, random-access memory (RAM), read-only memory (ROM), flash memory, first-input first-output (FIFO), and / or first-input last-output (FILO) memory, etc.; the processor may include, but is not limited to, a microprocessor from the STM32F105 series. Furthermore, the computer device may include, but is not limited to, a power module, a display screen, and other necessary components.

[0091] The working process, working details and technical effects of the aforementioned computer equipment provided in the third aspect of this embodiment can be found in the central air-conditioning system operation optimization method described in the first aspect, and will not be repeated here.

[0092] A fourth aspect of this embodiment provides a computer-readable storage medium storing instructions containing the central air conditioning system operation optimization method described in the first aspect, that is, the computer-readable storage medium stores instructions that, when executed on a computer, execute the central air conditioning system operation optimization method described in the first aspect. The computer-readable storage medium refers to a data storage medium and may include, but is not limited to, computer-readable storage media such as a floppy disk, an optical disk, a hard disk, a flash memory, a USB flash drive, and / or a memory stick. The computer may be a general-purpose computer, a dedicated computer, a computer network, or other programmable device.

[0093] The working process, working details and technical effects of the aforementioned computer-readable storage medium provided in the fourth aspect of this embodiment can be found in the central air-conditioning system operation optimization method described in the first aspect, and will not be repeated here.

[0094] A fifth aspect of this embodiment provides a computer program product, including a computer program or instructions, which, when executed by a computer, implements the central air conditioning system operation optimization method described in the first aspect. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0095] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention.

Claims

1. A method for optimizing the operation of a central air-conditioning system, characterized in that: include: Obtaining static parameters of each device in the central air-conditioning system, wherein the static parameters include the rated power of the corresponding device; Periodically acquiring dynamic parameters of each device, wherein the dynamic parameters include real-time operating power, switch status, and operating time of the corresponding device; Apply the static parameters of each device and the dynamic parameters of each device in the current and recent consecutive cycles, optimize the operation plan of the central air-conditioning system in the current and next cycle based on the optimization algorithm, obtain the operation plan and use it to achieve the optimal search result of multiple objectives, wherein the operation plan includes the operating status of each device in the current and next cycle, and the multi-objective optimization refers to minimizing the energy consumption of the central air-conditioning system in the current and recent consecutive cycles and the current and next cycle, maximizing the operating efficiency, and balancing the equipment loss, and adopting the following objective function to be minimized To express: Where, Indicates the energy consumption of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates the operating efficiency of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates a first indicator value for evaluating equipment loss balance of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates the total number of devices in the central air-conditioning system, Indicates less than or equal to A positive integer, Indicates the first The rated power of the device, Indicates the The running time of each device in the current most recent consecutive cycles and the current next cycle, Indicates the The real-time operating power of each device in the current most recent multiple consecutive cycles and the current next cycle, Indicates the average operating time of all devices in the central air-conditioning system in the most recent consecutive cycles and the next cycle. represents the weight factor corresponding to the energy consumption and is a positive value, represents the weight factor corresponding to the operating efficiency and is a negative value, represents a weight factor corresponding to the first indicator value and is a positive value; The optimized search result of the operating solution is executed in the current next cycle.

2. The method for optimizing the operation of a central air-conditioning system according to claim 1, characterized in that: The dynamic parameters also include the fault status of the corresponding equipment. The multi-objective optimization refers to minimizing the energy consumption of the central air-conditioning system in the current and recent consecutive cycles and the current next cycle, maximizing the operating efficiency, balancing the equipment loss and timely emergency protection. The objective function Replace it with the following: Where, Indicates the energy consumption of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates the operating efficiency of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates a first indicator value for evaluating equipment loss balance of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates the second indicator value of the central air-conditioning system in the current next cycle and used to evaluate the timeliness of emergency protection, Indicates the total number of devices in the central air-conditioning system, Indicates less than or equal to A positive integer, Indicates the first The rated power of the device, Indicates the The running time of each device in the current most recent consecutive cycles and the current next cycle, Indicates the The real-time operating power of each device in the current most recent multiple consecutive cycles and the current next cycle, Indicates the The fault continuation flag of each device from the current most recent cycle to the current next cycle is used with a value of zero to indicate that the fault is not continued and a value of 1 to indicate that the fault is continued. Indicates the cycle length, Indicates the average operating time of all devices in the central air-conditioning system in the most recent consecutive cycles and the next cycle. represents the weight factor corresponding to the energy consumption and is a positive value, represents the weight factor corresponding to the operating efficiency and is a negative value, represents the weight factor corresponding to the first index value and is a positive value, represents the weight factor corresponding to the second index value and is a positive value.

3. The method for optimizing the operation of a central air-conditioning system according to claim 2, characterized in that: The static parameters also include defined roles of the corresponding devices, wherein the defined roles are divided into a master role and a slave role and / or a standby role. The master role refers to a device role that starts when the central air-conditioning system starts and assumes the main load task. The slave role refers to a device role that starts when the master device is running and assumes the secondary load task and / or takes over the master task when the master device fails. The standby role refers to a device role that automatically starts when the master device fails and ensures uninterrupted operation of the system. Applying the static parameters of each device and the dynamic parameters of each device in the most recent consecutive cycles, optimizing the operation plan of the central air-conditioning system in the next cycle based on an optimization algorithm, obtaining the operation plan and using it to achieve the optimal multi-objective optimization search result, including: Determine, based on the static parameters of each device and the dynamic parameters of each device in the most recent cycle, whether there is a device in the central air-conditioning system whose role is defined as a master role and whose fault status in the most recent cycle is faulty; If it is determined that there is no device in the central air-conditioning system whose role is defined as the host role and whose fault status in the current most recent cycle is faulty, then the static parameters of the various devices and the dynamic parameters of the various devices in the current most recent consecutive cycles are applied to optimize the operation plan of the central air-conditioning system in the current next cycle based on the optimization algorithm, and the operation plan is obtained and used to achieve the optimal optimization search result for multiple objectives, wherein the operation plan includes the operation status of the various devices in the current next cycle, and the multi-objective optimality refers to minimizing the energy consumption of the central air-conditioning system in the current most recent consecutive cycles and the current next cycle, maximizing the operation efficiency, balancing the equipment loss, and timely emergency protection; If it is determined that there is any device in the central air-conditioning system whose role is defined as a master role and whose fault status in the most recent cycle is faulty, the following constraint conditions are configured for the operation plan of the central air-conditioning system in the current next cycle according to the static parameters of each device: the operation status of any device in the current next cycle is shutdown, and the operation status of other devices with the same capability as the any device and whose positioning role is a slave role or a standby role is enabled in the current next cycle; Applying the static parameters of each device, the dynamic parameters of each device in the most recent multiple consecutive cycles, and the constraints, the operation plan is optimized based on the optimization algorithm to obtain the operation plan and use it to achieve the best optimization search result for multiple objectives.

4. The method for optimizing the operation of a central air-conditioning system according to claim 3, characterized in that: The method further comprises: Determine, according to the static parameters of each device and the dynamic parameters of each device in the most recent current cycle, the number of devices in the central air-conditioning system that are defined as a master role and have a fault status of faulty in the most recent current cycle; The weighting factor is adjusted in direct correlation with the quantity .

5. The method for optimizing the operation of a central air-conditioning system according to claim 1, characterized in that: The optimization algorithm adopts improved NSGA-II algorithm, particle swarm optimization algorithm, gray wolf optimization algorithm, bat optimization algorithm, sky eagle optimization algorithm, vulture optimization algorithm or genetic optimization algorithm.

6. A central air conditioning system operation optimization device, characterized in that: It includes a static parameter acquisition unit, a dynamic parameter acquisition unit, an operation plan optimization unit and an optimal plan execution unit; The static parameter acquisition unit is used to acquire the static parameters of each device in the central air-conditioning system, wherein the static parameters include the rated power of the corresponding device; The dynamic parameter acquisition unit is used to periodically acquire the dynamic parameters of each device, wherein the dynamic parameters include the real-time operating power, switch status and operating time of the corresponding device; The operation scheme optimization unit is respectively communicatively connected to the static parameter acquisition unit and the dynamic parameter acquisition unit, and is used to apply the static parameters of each device and the dynamic parameters of each device in the current and most recent consecutive cycles, and optimize the operation scheme of the central air-conditioning system in the current and next cycle based on the optimization algorithm, so as to obtain the operation scheme and achieve the optimal search result for multiple objectives, wherein the operation scheme includes the operation status of each device in the current and next cycle, and the multi-objective optimization refers to minimizing the energy consumption of the central air-conditioning system in the current and most recent consecutive cycles and the current and next cycle, maximizing the operation efficiency, and balancing the equipment loss, and adopting the following objective function to be minimized To express: Where, Indicates the energy consumption of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates the operating efficiency of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates a first indicator value for evaluating equipment loss balance of the central air-conditioning system in the most recent consecutive cycles and the next cycle. Indicates the total number of devices in the central air-conditioning system, Indicates less than or equal to A positive integer, Indicates the first The rated power of the device, Indicates the The running time of each device in the current most recent consecutive cycles and the current next cycle, Indicates the The real-time operating power of each device in the current most recent multiple consecutive cycles and the current next cycle, Indicates the average operating time of all devices in the central air-conditioning system in the most recent consecutive cycles and the next cycle. represents the weight factor corresponding to the energy consumption and is a positive value, represents the weight factor corresponding to the operating efficiency and is a negative value, represents a weight factor corresponding to the first indicator value and is a positive value; The optimal solution execution unit is communicatively connected to the operation solution optimization unit, and is used to execute the optimized search result of the operation solution in the current next cycle.

7. A computer device, characterized in that: The method comprises a memory, a processor and a transceiver which are communicatively connected in sequence, wherein the memory is used to store a computer program, the transceiver is used to send and receive messages, and the processor is used to read the computer program and execute the central air-conditioning system operation optimization method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions. When the instructions are executed on a computer, the central air-conditioning system operation optimization method according to any one of claims 1 to 5 is executed.

9. A computer program product comprising a computer program or instructions, characterized in that When the computer program or the instruction is executed by a computer, the central air-conditioning system operation optimization method according to any one of claims 1 to 5 is implemented.

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