Energy consumption optimization method and system of central air conditioning system

Abstract

The invention discloses an energy consumption optimization method and system of a central air conditioning system. The method comprises the steps that initial energy consumption data of the central air-conditioning system is obtained, preprocessing operation is conducted on the initial energy consumption data to obtain target energy consumption data, and the load of the central air-conditioning system is determined based on the target energy consumption data; the average operation current and the average operation voltage of the central air-conditioning system are obtained, and a system energy consumption index corresponding to the central air-conditioning system is determined based on the central air-conditioning system load, the average operation current, the average operation voltage and a pre-constructed energy consumption index determination model; and under the condition that the system energy consumption index is not smaller than a preset energy consumption threshold value, an energy consumption optimization instruction is generated, and energy consumption optimization is conducted on the central air conditioning system based on the energy consumption optimization instruction. Effective management and optimization of the energy consumption of the central air-conditioning system are realized, and the optimization efficiency of the energy consumption of the central air-conditioning system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of central air-conditioning energy saving, and in particular to an energy consumption optimization method and system for a central air-conditioning system. Background Art

[0002] With the continuous development of the power industry, the scale of the power system continues to expand, and the amount of data generated has also shown explosive growth. These data include power load data, generator data, sensor data, etc., involving all aspects and components of the power system. Central air-conditioning systems are widely used in commercial buildings, office buildings, hospitals, schools and other places. Their energy consumption accounts for a large part of the total energy consumption of buildings. With the increasing global energy consumption and the enhancement of environmental protection awareness, energy conservation and emission reduction have become urgent needs.

[0003] Traditional central air conditioning energy consumption optimization methods have many limitations, such as a single optimization strategy, an inability to respond to energy consumption changes in real time, and a lack of in-depth analysis and prediction capabilities for energy consumption data. These methods usually rely on empirical rules or simple statistical analysis and are difficult to adapt to the complex and changeable power system operating environment. Summary of the invention

[0004] The present invention provides an energy consumption optimization method and system for a central air-conditioning system, so as to solve the problem that the traditional energy consumption optimization method for central air-conditioning has many limitations and is difficult to adapt to the complex and changeable power system operating environment.

[0005] According to one aspect of the present invention, a method for optimizing energy consumption of a central air-conditioning system is provided, the method comprising:

[0006] Acquire initial energy consumption data of the central air-conditioning system, perform preprocessing operations on the initial energy consumption data to obtain target energy consumption data, and determine the load of the central air-conditioning system based on the target energy consumption data;

[0007] Obtaining an average operating current and an average operating voltage of a central air-conditioning system, and determining a system energy consumption index corresponding to the central air-conditioning system based on the central air-conditioning system load, the average operating current, the average operating voltage, and a pre-constructed energy consumption index determination model; wherein the energy consumption index determination model is used to characterize a logical relationship between the system energy consumption index and the central air-conditioning system load, the average operating current, and the average operating voltage;

[0008] When the system energy consumption index is not less than a preset energy consumption threshold, an energy consumption optimization instruction is generated, and energy consumption of the central air-conditioning system is optimized based on the energy consumption optimization instruction.

[0009] According to another aspect of the present invention, there is provided an energy consumption optimization system for a central air conditioning system, the system comprising:

[0010] An energy consumption data acquisition module is used to acquire initial energy consumption data of the central air-conditioning system, perform preprocessing operations on the initial energy consumption data to obtain target energy consumption data, and determine the load of the central air-conditioning system based on the target energy consumption data;

[0011] An energy consumption index determination module, used to obtain the average operating current and average operating voltage of the central air-conditioning system, and determine the system energy consumption index corresponding to the central air-conditioning system based on the central air-conditioning system load, the average operating current, the average operating voltage and a pre-constructed energy consumption index determination model; wherein the energy consumption index determination model is used to characterize the logical relationship between the system energy consumption index and the central air-conditioning system load, the average operating current, and the average operating voltage;

[0012] The system energy consumption optimization module is used to generate an energy consumption optimization instruction when the system energy consumption index is not less than a preset energy consumption threshold, and optimize the energy consumption of the central air-conditioning system based on the energy consumption optimization instruction.

[0013] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising:

[0014] at least one processor; and

[0015] a memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the energy consumption optimization method of the central air-conditioning system described in any embodiment of the present invention.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the energy consumption optimization method of a central air-conditioning system described in any embodiment of the present invention when executed.

[0018] The technical solution of the embodiment of the present invention obtains initial energy consumption data of the central air-conditioning system, performs preprocessing operations on the initial energy consumption data to obtain target energy consumption data, and determines the load of the central air-conditioning system based on the target energy consumption data; obtains accurate and reliable target energy consumption data, and accurately determines the load of the central air-conditioning system according to the target energy consumption data; then, obtains the average operating current and average operating voltage of the central air-conditioning system, and determines the system energy consumption index corresponding to the central air-conditioning system based on the central air-conditioning system load, the average operating current, the average operating voltage and a pre-constructed energy consumption index determination model; wherein the energy consumption index determination model is used to characterize the logical relationship between the system energy consumption index and the central air-conditioning system load, the average operating current, and the average operating voltage; accurately evaluates the energy consumption performance of the system and generates an energy consumption optimization instruction when the system energy consumption index is not less than a preset energy consumption threshold, and optimizes the energy consumption of the central air-conditioning system based on the energy consumption optimization instruction. It realizes the intelligence and automation of energy consumption optimization, reduces manual intervention, improves optimization efficiency, solves the many limitations of traditional central air-conditioning energy consumption optimization methods and the problem that they are difficult to adapt to the complex and changeable power system operating environment, and achieves the beneficial effect of improving the central air-conditioning energy consumption optimization efficiency and effectively reducing the energy consumption of the central air-conditioning system.

[0019] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 is a flow chart of an energy consumption optimization method for a central air-conditioning system provided according to Embodiment 1 of the present invention;

[0022] Figure 2 is a flow chart of a method for optimizing energy consumption of a central air-conditioning system provided according to Embodiment 2 of the present invention;

[0023] Figure 3 is a structural schematic diagram of an energy consumption optimization system for a central air-conditioning system provided according to Embodiment 3 of the present invention;

[0024] Figure 4It is a structural schematic diagram of an electronic device for implementing the energy consumption optimization method of a central air-conditioning system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] Embodiment 1

[0028] Figure 1 A flowchart of a method for optimizing energy consumption of a central air-conditioning system is provided for the first embodiment of the present invention. This embodiment is applicable to the case of optimizing energy consumption of a central air-conditioning system. The method can be executed by an energy consumption optimization system of a central air-conditioning system. The energy consumption optimization system of the central air-conditioning system can be implemented in the form of hardware and / or software. The energy consumption optimization system of the central air-conditioning system can be configured in an electronic device. Figure 1 As shown, the method includes:

[0029] S110, acquiring initial energy consumption data of the central air-conditioning system, performing preprocessing operations on the initial energy consumption data to obtain target energy consumption data, and determining the load of the central air-conditioning system based on the target energy consumption data.

[0030] Among them, the initial energy consumption data can be understood as the various energy consumption data generated by the air-conditioning system during daily operation, the target energy consumption data can be understood as the data obtained after a series of preprocessing operations on the initial energy consumption data, and the central air-conditioning system load can be understood as the workload borne by the air-conditioning system during operation.

[0031] Specifically, the energy consumption data of each component of the air conditioning system (such as compressors, fans, water pumps, etc.) is collected and recorded through the power system's energy meter or special energy consumption metering equipment. For example, the energy consumption of the air conditioning system's cooling or heating capacity is reflected through the measurement and calculation of devices such as flow meters, temperature sensors, and energy calculators. Use flow meters to monitor the flow of cooling media to evaluate the cooling efficiency of the system. Record the start-up, operation, and shutdown time of the air conditioning system, as well as any fault or alarm information. Preprocess the initial energy consumption data to obtain more accurate and reliable target energy consumption data.

[0032] Optionally, the initial energy consumption data includes: at least one of: the water flow rate of water flowing into the cooling device, the water temperature of water flowing into the cooling device, the water temperature of water flowing out of the cooling device, the water flow rate of water flowing into the condensing device, the water temperature of water flowing into the condensing device, the water temperature of water flowing out of the condensing device, the operating current of the central air conditioning generator, and the operating voltage of the central air conditioning generator.

[0033] Optionally, the preprocessing operation is performed on the initial energy consumption data to obtain target energy consumption data, including: determining the energy consumption data to be processed based on the initial energy consumption data and a preset length threshold; and determining the target energy consumption data based on the Fourier function and the energy consumption data to be processed.

[0034] Specifically, the length of the collected initial energy consumption data is matched based on a preset length threshold. When the length of the initial energy consumption data is within the preset length threshold, the data is retained and the data is determined as the energy consumption data to be processed. When the length of the initial energy consumption data exceeds the preset length threshold, the data is not retained, the initial energy consumption data is recollected and the data is length matched. The energy consumption data to be processed after length matching is sequentially substituted into the Fourier function calculation to obtain the target energy consumption data. Among them, the preset length threshold can be preset based on experience, and this embodiment does not limit it.

[0035] Optionally, the target energy consumption data is determined based on the Fourier function and the energy consumption data to be processed by the following formula:

[0036] f(x)=x(c x cos kx+c x sin kx);

[0037] Where f(x) is the target energy consumption data, k is the preset data processing constant, x is the initial energy consumption data, c x Indicates the data length of the initial energy consumption data.

[0038] S120. Obtain an average operating current and an average operating voltage of a central air-conditioning system, and determine a system energy consumption index corresponding to the central air-conditioning system based on the central air-conditioning system load, the average operating current, the average operating voltage, and a pre-constructed energy consumption index determination model.

[0039] The energy consumption index determination model is used to characterize the logical relationship between the system energy consumption index and the central air-conditioning system load, the average operating current, and the average operating voltage; the average operating current can be understood as the average current value when the central air-conditioning system is operating for a period of time, and the average operating voltage can be understood as the average power supply voltage when the central air-conditioning system is operating. The system energy consumption index can be understood as an indicator reflecting the system energy consumption efficiency.

[0040] Specifically, the central air-conditioning system load, the average operating current, and the average operating voltage are input into an energy consumption index determination model, and the system energy consumption index corresponding to the central air-conditioning system is determined based on the model calculation result.

[0041] Optionally, obtaining the average operating current and the average operating voltage of the central air-conditioning system includes: sampling the operating current and the operating voltage of the central air-conditioning generator to obtain a preset number of sample operating current data and sample operating voltage data; and respectively determining the average operating current corresponding to the sample operating current data and the average operating voltage corresponding to the sample operating voltage data.

[0042] Specifically, the operating current and operating voltage of the central air-conditioning generator are sampled a preset number of times to obtain a preset number of sample operating current data and sample operating voltage data. The average values ​​of multiple groups of sample operating current data are calculated to obtain the average operating current. The average values ​​of multiple groups of sample operating voltage data are calculated to obtain the average operating voltage.

[0043] Exemplarily, the operating current and operating voltage of the central air-conditioning generator are sampled Y times, where y=1, 2, 3, ..., Y; the sample operating current data of the central air-conditioning generator are averaged by the following formula to obtain the average operating current:

[0044]

[0045] in, is the average operating current, I y The sample operating current data of the central air-conditioning generator sampled for the yth time.

[0046] The operating voltage of the central air-conditioning generator is averaged by the following formula to obtain the average operating voltage:

[0047]

[0048] in, is the average operating voltage, V y The sample operating voltage data of the central air-conditioning generator sampled for the yth time.

[0049] Optionally, determining the central air conditioning system load based on the target energy consumption data includes:

[0050] A cooler cooling load and a condenser cooling load corresponding to the central air-conditioning system are determined based on the target energy consumption data; and a load of the central air-conditioning system is determined based on the cooler cooling load and the condenser cooling load.

[0051] The cooler cooling load can be understood as the load of dissipating heat through the cooler, and the condenser cooling load can be understood as the heat that the condenser needs to discharge from the refrigeration system within a certain period of time.

[0052] Specifically, the cooling load of the cooler is calculated based on the water flow rate of the flowing water into the cooling device, the water temperature of the flowing water flowing into the cooling device, and the water temperature of the flowing water flowing out of the cooling device; the cooling load of the condenser is calculated based on the water flow rate of the flowing water into the condensing device, the water temperature of the flowing water flowing into the condensing device, and the water temperature of the flowing water flowing out of the condensing device.

[0053] Exemplarily, the cooling load of the cooler is calculated based on the water flow rate of the flowing water into the cooling device, the water temperature of the flowing water flowing into the cooling device, and the water temperature of the flowing water flowing out of the cooling device by the following formula:

[0054] Q a =η a ×Va ch ×(Ta ch -Ta rh );

[0055] Among them, Q a is the cooling load of the cooler, η a is the cooling coefficient of the cooler, Va ch is the flow rate of water into the cooling device, Ta ch is the water temperature of the flowing water into the cooling device, Ta rh It is the water temperature when the water flows out of the cooling device.

[0056] The condenser cooling load is calculated based on the water flow rate into the condensing unit, the water temperature of the water flowing into the condensing unit, and the water temperature of the water flowing out of the condensing unit using the following formula:

[0057] Q b =η b ×Vb ch ×(Tb ch -Tb rh);

[0058] Among them, Q b is the condenser cooling load, η b is the condenser cooling coefficient, Vb ch is the flow rate of water flowing into the condensing device, Tb ch is the water temperature of the flowing water into the condensing device, Tb rh It is the water temperature when the water flows out of the condensing unit.

[0059] Exemplarily, the central air conditioning system load is determined based on the cooler cooling load and the condenser cooling load by the following formula:

[0060]

[0061] Among them, U is the central air conditioning system load, Q a is the cooling load of the chiller, Q b is the condenser cooling load, and λ1 and λ2 are both constants.

[0062] Optionally, the energy consumption index determination model is expressed as:

[0063]

[0064] Where D represents the system energy consumption index, μi represents the current deviation coefficient, and μv represents the voltage deviation coefficient. Indicates the average operating current of the central air-conditioning generator. It represents the average operating voltage of the central air-conditioning generator, and U represents the load of the central air-conditioning system.

[0065] S130. When the system energy consumption index is not less than a preset energy consumption threshold, generate an energy consumption optimization instruction, and optimize the energy consumption of the central air-conditioning system based on the energy consumption optimization instruction.

[0066] Among them, the energy consumption optimization instruction can be understood as a series of control measure instructions formulated based on the difference between the current energy consumption status of the central air-conditioning system and the target energy consumption level.

[0067] Specifically, if the system energy consumption index is less than the preset energy consumption threshold, the energy consumption of the central air-conditioning system is judged to be normal; if the system energy consumption index is not less than the preset energy consumption threshold, the energy consumption of the central air-conditioning system is judged to be abnormal. If the judgment result is that the energy consumption of the central air-conditioning system is normal, no optimization instruction is issued; if the judgment result is that the energy consumption of the central air-conditioning system is abnormal, an optimization instruction is issued.

[0068] The technical solution of the embodiment of the present invention obtains initial energy consumption data of the central air-conditioning system, performs preprocessing operations on the initial energy consumption data to obtain target energy consumption data, and determines the load of the central air-conditioning system based on the target energy consumption data; obtains accurate and reliable target energy consumption data, and accurately determines the load of the central air-conditioning system according to the target energy consumption data; then, obtains the average operating current and average operating voltage of the central air-conditioning system, and determines the system energy consumption index corresponding to the central air-conditioning system based on the central air-conditioning system load, the average operating current, the average operating voltage and a pre-constructed energy consumption index determination model; wherein the energy consumption index determination model is used to characterize the logical relationship between the system energy consumption index and the central air-conditioning system load, the average operating current, and the average operating voltage; accurately evaluates the energy consumption performance of the system and generates an energy consumption optimization instruction when the system energy consumption index is not less than a preset energy consumption threshold, and optimizes the energy consumption of the central air-conditioning system based on the energy consumption optimization instruction. It realizes the intelligence and automation of energy consumption optimization, reduces manual intervention, improves optimization efficiency, solves the many limitations of traditional central air-conditioning energy consumption optimization methods and the problem that they are difficult to adapt to the complex and changeable power system operating environment, and achieves the beneficial effect of improving the central air-conditioning energy consumption optimization efficiency and effectively reducing the energy consumption of the central air-conditioning system.

[0069] Embodiment 2

[0070] Figure 2 A flowchart of a method for optimizing energy consumption of a central air-conditioning system provided in Embodiment 2 of the present invention is provided. This embodiment is a further refinement of how to generate an energy consumption optimization instruction in the above embodiment when the system energy consumption index is not less than a preset energy consumption threshold. Optionally, when the system energy consumption index is not less than a preset energy consumption threshold, generating an energy consumption optimization instruction includes: determining the energy consumption difference between the system energy consumption index and the preset energy consumption threshold, and determining an energy consumption optimization index based on the energy consumption difference and the preset energy consumption threshold; determining an optimization level corresponding to the central air-conditioning system based on the energy consumption optimization index and the preset optimization level threshold, and generating an energy consumption optimization instruction based on the optimization level.

[0071] like Figure 2 As shown, the method includes:

[0072] S210, acquiring initial energy consumption data of the central air-conditioning system, performing preprocessing operations on the initial energy consumption data to obtain target energy consumption data, and determining the load of the central air-conditioning system based on the target energy consumption data.

[0073] S220. Obtain an average operating current and an average operating voltage of a central air-conditioning system, and determine a system energy consumption index corresponding to the central air-conditioning system based on the central air-conditioning system load, the average operating current, the average operating voltage, and a pre-constructed energy consumption index determination model.

[0074] S230. When the system energy consumption index is not less than a preset energy consumption threshold, determine an energy consumption difference between the system energy consumption index and the preset energy consumption threshold, and determine an energy consumption optimization index based on the energy consumption difference and the preset energy consumption threshold.

[0075] Specifically, whether to issue an optimization instruction is analyzed based on the energy consumption judgment result of the central air-conditioning system. If the judgment result is that the energy consumption of the central air-conditioning system is normal, no optimization instruction is issued. If the judgment result is that the energy consumption of the central air-conditioning system is abnormal, an optimization instruction is issued, and the energy consumption optimization level of the central air-conditioning system is analyzed when the optimization instruction is issued. The energy consumption optimization level of the central air-conditioning system is analyzed as follows: the energy consumption optimization level of the power system is analyzed based on the energy consumption optimization level judgment model of the power system. The energy consumption optimization level judgment model of the power system is expressed as:

[0076]

[0077] Among them, S represents the energy consumption optimization index, D represents the system energy consumption index, and ΔD represents the preset energy consumption threshold.

[0078] S240. Determine an optimization level corresponding to the central air-conditioning system based on the energy consumption optimization index and a preset optimization level threshold, generate an energy consumption optimization instruction based on the optimization level, and optimize energy consumption of the central air-conditioning system based on the energy consumption optimization instruction.

[0079] Specifically, the energy consumption optimization index output by the power system energy consumption optimization level judgment model is compared with a preset optimization level threshold, and the optimization level corresponding to the central air-conditioning system is determined based on the comparison result.

[0080] Optionally, determining the optimization level corresponding to the central air-conditioning system based on the energy consumption optimization index and a preset optimization level threshold includes: when the energy consumption optimization index is less than the preset optimization level threshold, determining the optimization level corresponding to the central air-conditioning system as first-level optimization; and / or, when the energy consumption optimization index is not less than the preset optimization level threshold, determining the optimization level corresponding to the central air-conditioning system as second-level optimization.

[0081] If the energy consumption optimization index of the power system energy consumption optimization level judgment model is less than the preset optimization level threshold, it is judged as first-level optimization. If the energy consumption optimization index of the power system energy consumption optimization level judgment model is not less than the preset optimization level threshold, it is judged as second-level optimization.

[0082] Exemplarily, when it is determined that the optimization level corresponding to the central air-conditioning system is the first-level optimization, a first-level optimization instruction is generated, and the first-level optimization instruction includes adjusting the parameter settings of the operating current and operating voltage of the central air-conditioning generator, and adjusting the load of the cooler and condenser to reduce energy consumption; when it is determined that the optimization level corresponding to the central air-conditioning system is the second-level optimization, a second-level optimization instruction is generated. In addition to all the measures of the first-level optimization instruction, the second-level optimization instruction also includes a more in-depth energy consumption analysis and adjustment of the central air-conditioning system, such as: optimizing the operating mode of the cooling water circulation system and maintaining and upgrading the generator to further reduce energy consumption. Through hierarchical optimization, the energy consumption of the central air-conditioning system can be effectively controlled and reduced, thereby achieving efficient operation of the central air-conditioning system and energy conservation.

[0083] The technical solution of the embodiment of the present invention determines the energy consumption difference between the system energy consumption index and the preset energy consumption threshold, determines the energy consumption optimization index based on the energy consumption difference and the preset energy consumption threshold; determines the optimization level corresponding to the central air-conditioning system based on the energy consumption optimization index and the preset optimization level threshold, and generates an energy consumption optimization instruction based on the optimization level. Accurately determine the optimization level corresponding to the central air-conditioning system, generate energy consumption optimization instructions based on the optimization level, and achieve the beneficial effect of improving the energy consumption optimization efficiency of the central air-conditioning system and effectively reducing the energy consumption of the central air-conditioning system.

[0084] As an optional example of the first embodiment of the present invention, the energy consumption optimization method of the central air-conditioning system of this embodiment specifically includes the following steps:

[0085] Step 1: Collect the on-site energy consumption data of the central air-conditioning system through the power energy consumption metering tool, and transmit the collected on-site energy consumption data of the central air-conditioning system to the database through the network controller for storage.

[0086] Step 2: Extract the on-site energy consumption data of the central air-conditioning system from the database, perform preprocessing operations on the on-site energy consumption data of the central air-conditioning system, establish an energy consumption index determination model for the central air-conditioning system, and complete the modeling processing of the energy consumption data of the central air-conditioning system.

[0087] Step 3: Analyze the energy consumption of the central air-conditioning system to determine whether the energy consumption of the central air-conditioning system is abnormal.

[0088] Step 4: The network control end analyzes whether to issue an optimization instruction based on the judgment result, and calculates the power system energy consumption optimization level when issuing the optimization instruction.

[0089] The technical solution of the embodiment of the present invention collects the on-site energy consumption data of the central air-conditioning system through an electric power energy consumption metering tool, transmits the collected on-site energy consumption data of the central air-conditioning system to a database for storage, establishes an energy consumption index determination model based on the on-site energy consumption data of the central air-conditioning system to complete the modeling processing of the energy consumption data of the central air-conditioning system, performs energy consumption analysis on the central air-conditioning system, and the network control end analyzes whether to issue an optimization instruction based on the judgment result, and calculates the energy consumption optimization level of the central air-conditioning system when issuing the optimization instruction. By real-time monitoring of the energy consumption of the central air-conditioning system, energy consumption anomalies are discovered in time and the operating parameters are automatically adjusted to achieve the purpose of reducing energy consumption and improving energy efficiency.

[0090] Embodiment 3

[0091] Figure 3 This is a schematic diagram of the structure of an energy consumption optimization system for a central air conditioning system provided by Embodiment 3 of the present invention. Figure 3 As shown, the device includes: an energy consumption data acquisition module 310, an energy consumption index determination module 320 and a system energy consumption optimization module 330.

[0092] Among them, the energy consumption data acquisition module 310 is used to obtain the initial energy consumption data of the central air-conditioning system, pre-process the initial energy consumption data to obtain the target energy consumption data, and determine the load of the central air-conditioning system based on the target energy consumption data; the energy consumption index determination module 320 is used to obtain the average operating current and average operating voltage of the central air-conditioning system, and determine the system energy consumption index corresponding to the central air-conditioning system based on the central air-conditioning system load, the average operating current, the average operating voltage and a pre-constructed energy consumption index determination model; wherein the energy consumption index determination model is used to characterize the logical relationship between the system energy consumption index and the central air-conditioning system load, the average operating current, and the average operating voltage; the system energy consumption optimization module 330 is used to generate an energy consumption optimization instruction when the system energy consumption index is not less than a preset energy consumption threshold, and optimize the energy consumption of the central air-conditioning system based on the energy consumption optimization instruction.

[0093] The technical solution of the embodiment of the present invention obtains initial energy consumption data of the central air-conditioning system, performs preprocessing operations on the initial energy consumption data to obtain target energy consumption data, and determines the load of the central air-conditioning system based on the target energy consumption data; obtains accurate and reliable target energy consumption data, and accurately determines the load of the central air-conditioning system according to the target energy consumption data; then, obtains the average operating current and average operating voltage of the central air-conditioning system, and determines the system energy consumption index corresponding to the central air-conditioning system based on the central air-conditioning system load, the average operating current, the average operating voltage and a pre-constructed energy consumption index determination model; wherein the energy consumption index determination model is used to characterize the logical relationship between the system energy consumption index and the central air-conditioning system load, the average operating current, and the average operating voltage; accurately evaluates the energy consumption performance of the system and generates an energy consumption optimization instruction when the system energy consumption index is not less than a preset energy consumption threshold, and optimizes the energy consumption of the central air-conditioning system based on the energy consumption optimization instruction. It realizes the intelligence and automation of energy consumption optimization, reduces manual intervention, improves optimization efficiency, solves the many limitations of traditional central air-conditioning energy consumption optimization methods and the problem that they are difficult to adapt to the complex and changeable power system operating environment, and achieves the beneficial effect of improving the central air-conditioning energy consumption optimization efficiency and effectively reducing the energy consumption of the central air-conditioning system.

[0094] Optionally, the energy consumption index determination module includes:

[0095] A data sampling unit is used to sample the operating current and operating voltage of the central air-conditioning generator to obtain a preset number of sample operating current data and sample operating voltage data;

[0096] The average data determining unit is used to respectively determine an average operating current corresponding to the sample operating current data and an average operating voltage corresponding to the sample operating voltage data.

[0097] Optionally, the energy consumption data acquisition module includes:

[0098] a first load determination unit, configured to determine a cooler cooling load and a condenser cooling load corresponding to the central air conditioning system based on the target energy consumption data;

[0099] The second load determination unit is used to determine the central air conditioning system load based on the cooler cooling load and the condenser cooling load.

[0100] Optionally, the energy consumption index determination model is expressed as:

[0101]

[0102] Where D represents the system energy consumption index, μi represents the current deviation coefficient, and μv represents the voltage deviation coefficient. Indicates the average operating current of the central air-conditioning generator. It represents the average operating voltage of the central air-conditioning generator, and U represents the load of the central air-conditioning system.

[0103] Optionally, the system energy consumption optimization module includes:

[0104] An optimization index determination unit, used to determine an energy consumption difference between a system energy consumption index and a preset energy consumption threshold, and determine an energy consumption optimization index based on the energy consumption difference and the preset energy consumption threshold;

[0105] The optimization instruction generating unit is used to determine the optimization level corresponding to the central air-conditioning system based on the energy consumption optimization index and a preset optimization level threshold, and to generate an energy consumption optimization instruction based on the optimization level.

[0106] Optionally, the optimization instruction generating unit includes:

[0107] A first-level optimization subunit, configured to determine that the optimization level corresponding to the central air-conditioning system is first-level optimization when the energy consumption optimization index is less than a preset optimization level threshold; and / or,

[0108] The secondary optimization subunit is used to determine that the optimization level corresponding to the central air-conditioning system is secondary optimization when the energy consumption optimization index is not less than a preset optimization level threshold.

[0109] Optionally, the energy consumption data acquisition module includes:

[0110] a to-be-processed energy consumption data determining unit, configured to determine the to-be-processed energy consumption data based on the initial energy consumption data and a preset length threshold;

[0111] The target energy consumption data determining unit is used to determine the target energy consumption data based on the Fourier function and the energy consumption data to be processed.

[0112] Optionally, the target energy consumption data determination unit is specifically used to:

[0113] The target energy consumption data is determined based on the Fourier function and the energy consumption data to be processed by the following formula:

[0114] f(x)=x(c x cos kx+c x sin kx);

[0115] Where f(x) is the target energy consumption data, k is the preset data processing constant, x is the initial energy consumption data, c x Indicates the data length of the initial energy consumption data.

[0116] Optionally, the initial energy consumption data includes: at least one of: the water flow rate of water flowing into the cooling device, the water temperature of water flowing into the cooling device, the water temperature of water flowing out of the cooling device, the water flow rate of water flowing into the condensing device, the water temperature of water flowing into the condensing device, the water temperature of water flowing out of the condensing device, the operating current of the central air conditioning generator, and the operating voltage of the central air conditioning generator.

[0117] The energy consumption optimization system of the central air-conditioning system provided in the embodiment of the present invention can execute the energy consumption optimization method of the central air-conditioning system provided in any embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method.

[0118] Embodiment 4

[0119] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0120] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0121] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0122] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 11 executes the various methods and processes described above, such as the method for optimizing the energy consumption of a central air conditioning system.

[0123] In some embodiments, the method for optimizing the energy consumption of a central air conditioning system may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for optimizing the energy consumption of a central air conditioning system described above may be executed. Alternatively, in other embodiments, the processor 11 may be configured to execute the method for optimizing the energy consumption of a central air conditioning system in any other appropriate manner (e.g., by means of firmware).

[0124] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0125] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0126] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0127] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0128] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0129] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0130] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0131] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for optimizing energy consumption of a central air conditioning system, characterized in that: include: Acquire initial energy consumption data of the central air-conditioning system, perform preprocessing operations on the initial energy consumption data to obtain target energy consumption data, and determine the load of the central air-conditioning system based on the target energy consumption data; Obtaining an average operating current and an average operating voltage of a central air-conditioning system, and determining a system energy consumption index corresponding to the central air-conditioning system based on the central air-conditioning system load, the average operating current, the average operating voltage, and a pre-constructed energy consumption index determination model; wherein the energy consumption index determination model is used to characterize a logical relationship between the system energy consumption index and the central air-conditioning system load, the average operating current, and the average operating voltage; When the system energy consumption index is not less than a preset energy consumption threshold, an energy consumption optimization instruction is generated, and energy consumption of the central air-conditioning system is optimized based on the energy consumption optimization instruction.

2. The method according to claim 1, characterized in that The obtaining of the average operating current and the average operating voltage of the central air conditioning system includes: Sampling the operating current and operating voltage of the central air-conditioning generator to obtain a preset number of sample operating current data and sample operating voltage data; An average operating current corresponding to the sample operating current data and an average operating voltage corresponding to the sample operating voltage data are determined respectively.

3. The method according to claim 1, characterized in that Determining the central air conditioning system load based on the target energy consumption data includes: Determining a cooler cooling load and a condenser cooling load corresponding to the central air conditioning system based on the target energy consumption data; The central air conditioning system load is determined based on the chiller cooling load and the condenser cooling load.

4. The method according to claim 1, characterized in that: The energy consumption index determination model is expressed as: Where D represents the system energy consumption index, μi represents the current deviation coefficient, and μv represents the voltage deviation coefficient. Indicates the average operating current of the central air-conditioning generator. It represents the average operating voltage of the central air-conditioning generator, and U represents the load of the central air-conditioning system.

5. The method according to claim 1, characterized in that When the system energy consumption index is not less than a preset energy consumption threshold, generating an energy consumption optimization instruction includes: Determine an energy consumption difference between the system energy consumption index and a preset energy consumption threshold, and determine an energy consumption optimization index based on the energy consumption difference and the preset energy consumption threshold; An optimization level corresponding to the central air-conditioning system is determined based on the energy consumption optimization index and a preset optimization level threshold, and an energy consumption optimization instruction is generated based on the optimization level.

6. The method according to claim 5, characterized in that The step of determining the optimization level corresponding to the central air-conditioning system based on the energy consumption optimization index and the preset optimization level threshold comprises: When the energy consumption optimization index is less than a preset optimization level threshold, determining the optimization level corresponding to the central air-conditioning system as first-level optimization; and / or, When the energy consumption optimization index is not less than a preset optimization level threshold, the optimization level corresponding to the central air-conditioning system is determined to be secondary optimization.

7. The method according to claim 1, characterized in that The preprocessing operation on the initial energy consumption data to obtain target energy consumption data includes: Determining energy consumption data to be processed based on the initial energy consumption data and a preset length threshold; The target energy consumption data is determined based on the Fourier function and the energy consumption data to be processed.

8. The method according to claim 7, characterized in that The target energy consumption data is determined based on the Fourier function and the energy consumption data to be processed by the following formula: f(x)=x(c x cos kx+c x sin kx); Among them, f(x) is the target energy consumption data, k is the preset data processing constant, x is the initial energy consumption data, c x Indicates the data length of the initial energy consumption data.

9. The method according to claim 1, characterized in that: The initial energy consumption data includes: at least one of the water flow rate of water flowing into the cooling device, the water temperature of water flowing into the cooling device, the water temperature of water flowing out of the cooling device, the water flow rate of water flowing into the condensing device, the water temperature of water flowing into the condensing device, the water temperature of water flowing out of the condensing device, the operating current of the central air conditioning generator, and the operating voltage of the central air conditioning generator.

10. An energy consumption optimization system for a central air conditioning system, characterized in that: include: An energy consumption data acquisition module is used to acquire initial energy consumption data of the central air-conditioning system, perform preprocessing operations on the initial energy consumption data to obtain target energy consumption data, and determine the load of the central air-conditioning system based on the target energy consumption data; An energy consumption index determination module, used to obtain the average operating current and average operating voltage of the central air-conditioning system, and determine the system energy consumption index corresponding to the central air-conditioning system based on the central air-conditioning system load, the average operating current, the average operating voltage and a pre-constructed energy consumption index determination model; wherein the energy consumption index determination model is used to characterize the logical relationship between the system energy consumption index and the central air-conditioning system load, the average operating current, and the average operating voltage; The system energy consumption optimization module is used to generate an energy consumption optimization instruction when the system energy consumption index is not less than a preset energy consumption threshold, and optimize the energy consumption of the central air-conditioning system based on the energy consumption optimization instruction.

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