Group control optimization method and device for refrigeration units in regional cold source system

Abstract

The present invention provides a group control optimization method and device for a refrigeration unit of a regional cold source system. For each subsystem: based on the chilled water outlet temperature of the subsystem and the first load rate of the refrigeration unit corresponding to the subsystem, a refrigeration unit model is constructed; based on the number of operating units of the refrigeration unit and the chilled water operating flow rate, a chilled water outlet temperature mixed water constraint equation is constructed; based on the constraints on the chilled water outlet temperature and the first load rate, a safe operation constraint equation is determined; with the chilled water outlet temperature mixed water constraint equation of each subsystem and the safe operation constraint equation of the refrigeration unit corresponding to each subsystem as constraints, minimizing the power consumption of the refrigeration unit of the regional cold source system is taken as the optimization goal, based on the refrigeration unit model of each subsystem, the chilled water outlet temperature is optimized to obtain the optimized chilled water outlet temperature; based on the particle swarm optimization algorithm, the number of operating units of the refrigeration unit is optimized to obtain the optimized number of operating units.

Description

Technical Field

[0001] The invention relates to the field of regional cold source systems, and in particular to a group control optimization method and a device for a refrigeration unit of a regional cold source system. Background Art

[0002] In the field of construction, the regional cooling system has attracted extensive attention and application as an efficient way of energy utilization. The system generates cold sources in a centralized manner and transmits cold energy to each user end through a transmission and distribution pipeline network, thus realizing centralized cooling of multiple buildings or regions. Compared with the traditional decentralized cooling method, the regional cooling system has significant advantages such as high energy utilization efficiency, convenient equipment maintenance and management, and low environmental impact.

[0003] However, the operation of regional cold source systems also faces many challenges. For example, traditional refrigeration unit systems often find it difficult to accurately adjust the load rate of the refrigeration units of each cold source subsystem, resulting in excessive energy consumption or unstable operation when the system operates under different load conditions. In addition, the outlet temperature of the chilled water is prone to fluctuations, making it difficult to ensure that the system operates within a safe and efficient temperature range. Summary of the invention

[0004] In view of this, the present invention provides a group control optimization method and device for a refrigeration unit of a regional cold source system.

[0005] One aspect of the present invention provides a group control optimization method for a refrigeration unit of a regional cold source system, wherein the regional cold source system includes a plurality of subsystems, each of which includes a refrigeration unit, and the refrigeration unit is used to deliver chilled water to the end of each building in a target area; the group control optimization method for the refrigeration unit of the regional cold source system includes: for each subsystem: based on the chilled water outlet temperature of the subsystem and the first load rate of the refrigeration unit corresponding to the subsystem, a refrigeration unit model of the subsystem is constructed; based on the number of operating refrigeration units corresponding to the subsystem and the chilled water operating flow rate, a chilled water outlet temperature mixing water constraint equation of the subsystem is constructed; based on the constraint conditions on the chilled water outlet temperature of the subsystem and the first load rate of the refrigeration unit corresponding to the subsystem ... The constraint condition of the first load rate of the refrigeration unit corresponding to the subsystem is used to determine the safe operation constraint equation of the refrigeration unit corresponding to the subsystem; the chilled water outlet temperature mixing constraint equation of each subsystem and the safe operation constraint equation of the refrigeration unit corresponding to each subsystem are used as constraint conditions, and the power consumption of the refrigeration unit of the regional cold source system is minimized as the optimization goal. Based on the refrigeration unit model of each subsystem, the chilled water outlet temperature of each subsystem is optimized to obtain the optimized chilled water outlet temperature of each subsystem; based on the particle swarm optimization algorithm, the operating number of the refrigeration unit corresponding to each subsystem is optimized to obtain the optimized operating number of the refrigeration unit corresponding to each subsystem.

[0006] According to an embodiment of the present invention, taking the chilled water outlet temperature mixing constraint equation of each subsystem and the safe operation constraint equation of the refrigeration unit corresponding to each subsystem as constraint conditions, taking minimizing the power consumption of the refrigeration unit of the regional cold source system as the optimization goal, based on the refrigeration unit model of each subsystem, the chilled water outlet temperature of each subsystem is optimized to obtain the optimized chilled water outlet temperature of each subsystem, including: for each of the subsystems: based on the correlation between the chilled water outlet temperature of the subsystem and the first load rate of the refrigeration unit corresponding to the subsystem, performing simplification operations on the refrigeration unit model of the subsystem to obtain a simplified form of the refrigeration unit model of the subsystem; using the constraint conditions and the optimization goal, using the interior point barrier function method to optimize and solve the simplified form of the refrigeration unit model of each subsystem to obtain the optimized chilled water outlet temperature of each subsystem.

[0007] According to an embodiment of the present invention, the group control optimization method of the refrigeration unit of the regional cold source system also includes: for each building terminal in the target area: based on the parameters of the fan coil at the building terminal, determining the heat capacity ratio and the number of heat transfer units of the fan coil; based on the heat capacity ratio and the number of heat transfer units of the fan coil, determining the heat exchange efficiency of the fan coil; based on the heat exchange efficiency of the fan coil, the indoor design temperature at the building terminal, the physical properties of the chilled water and the cooling load at the building terminal, determining the chilled water supply temperature at the building terminal; based on the number of building terminals in the target area and the chilled water supply temperature at each building terminal, determining the total chilled water supply temperature in the target area; according to the cold source load parameters of the regional cold source system, determining the load rate of the regional cold source system; based on the second load rate of the regional cold source system, the total chilled water supply temperature and the cold water temperature sensitivity characteristics of the refrigeration unit, determining the expected chilled water return temperature of the regional cold source system; based on the expected chilled water return temperature, the rated cooling capacity of the refrigeration unit corresponding to the subsystem and the chilled water operating flow rate of the refrigeration unit corresponding to the subsystem, determining the correlation.

[0008] According to an embodiment of the present invention, the refrigeration unit model of the subsystem is used to determine the refrigeration power of the refrigeration unit corresponding to the subsystem; The refrigeration unit model of each subsystem includes the following formula (1):

[0009] (1)

[0010] in, Indicates The cooling power of the refrigeration unit corresponding to each subsystem is: Indicates The rated cooling power of the refrigeration unit corresponding to each subsystem, , …, Sequentially indicates The first to tenth model coefficients in the refrigeration unit model of the subsystem, Indicates The chilled water outlet temperature of each subsystem is Indicates The cooling water outlet temperature of each subsystem is Indicates The first load rate of the refrigeration unit corresponding to the subsystem.

[0011] According to an embodiment of the present invention, based on the correlation between the chilled water outlet temperature of the subsystem and the first load rate of the refrigeration unit corresponding to the subsystem, a simplification operation is performed on the refrigeration unit model of the subsystem to obtain a simplified form of the refrigeration unit model of the subsystem, including: determining an equation for the first load rate of the refrigeration unit corresponding to the subsystem according to the correlation; replacing the equation with the first load rate of the refrigeration unit corresponding to the subsystem; The refrigeration unit model of the subsystem The first load rate of the refrigeration unit corresponding to the subsystem is obtained to obtain the replaced refrigeration unit model; and the known items in the replaced refrigeration unit model are simplified to obtain the simplified form of the refrigeration unit model of the subsystem.

[0012] According to an embodiment of the present invention, subsystems, the relevant relationships are shown in equations (2) and (3):

[0013] (2)

[0014] (3)

[0015] in, Indicates The first load rate of the refrigeration unit corresponding to the subsystem is about The first-order coefficient of the chilled water outlet temperature of each subsystem is: represents the density of frozen water, represents the specific heat capacity of chilled water, Indicates The chilled water flow rate of the refrigeration unit corresponding to each subsystem is Indicates The rated cooling capacity of the refrigeration unit corresponding to each subsystem is: Indicates The first load rate of the refrigeration unit corresponding to the subsystem is about The constant coefficient of the chilled water outlet temperature of each subsystem is: Indicates the expected return temperature of chilled water in the district cooling system.

[0016] According to an embodiment of the present invention, the simplified form of the refrigeration unit model of each subsystem is optimized and solved using the interior point barrier function method with constraints and optimization objectives to obtain the optimized chilled water outlet temperature of each subsystem, including: determining the nonlinear optimization problem based on the refrigeration unit model and optimization objectives of the subsystem; constructing a barrier function for the nonlinear optimization problem; combining the optimization objective with the barrier function to obtain an objective function with a penalty term; based on Newton's method and constraints, performing constrained optimization solution on the objective function until iterative convergence to obtain the optimized chilled water outlet temperature of each subsystem.

[0017] According to an embodiment of the present invention, based on a particle swarm optimization algorithm, the number of operating refrigeration units corresponding to each subsystem is optimized to obtain the optimized number of operating refrigeration units corresponding to each subsystem, including: based on a particle swarm optimization algorithm, the chilled water operating flow rate of the refrigeration unit corresponding to each subsystem is optimized to obtain the optimized chilled water operating flow rate of the refrigeration unit corresponding to each subsystem; according to the ratio of the optimized chilled water operating flow rate of the refrigeration unit corresponding to each subsystem and the rated operating condition chilled water operating flow rate of the refrigeration unit corresponding to each subsystem, the optimized number of operating refrigeration units corresponding to each subsystem is obtained.

[0018] According to an embodiment of the present invention, based on a particle swarm optimization algorithm, the chilled water running flow of the refrigeration unit corresponding to each subsystem is optimized to obtain the optimized chilled water running flow of the refrigeration unit corresponding to each subsystem, including: randomly initializing position information and speed information of multiple particles, wherein the particles are used to indicate the refrigeration unit corresponding to each subsystem, the position information is used to indicate the chilled water running flow of the refrigeration unit corresponding to each subsystem, and the speed information is used to indicate the speed of the particles; the position information and the speed information are input into a fitness function, and the fitness of each particle is output, wherein the fitness function is determined based on the optimization objective and the equality constraint penalty term, and the equality constraint penalty term is determined by the equality constraint penalty coefficient and the chilled water running flow of the refrigeration unit; based on the fitness of each particle, the chilled water running flow of the refrigeration unit corresponding to each subsystem is iteratively optimized until the number of iterations reaches a preset number of iterations, to obtain the optimized chilled water running flow of the refrigeration unit corresponding to each subsystem.

[0019] Another aspect of the present invention provides a group control optimization device for a refrigeration unit of a regional cold source system, wherein the regional cold source system includes a plurality of subsystems, each of which includes a refrigeration unit, and the refrigeration unit is used to deliver chilled water to the end of each building in the target area; the group control optimization device for the refrigeration unit of the regional cold source system includes: for each subsystem: a first building module, which is used to build a refrigeration unit model of the subsystem based on the chilled water outlet temperature of the subsystem and the first load rate of the refrigeration unit corresponding to the subsystem; a second building module, which is used to build a chilled water outlet temperature mixing water constraint equation of the subsystem based on the number of operating refrigeration units corresponding to the subsystem and the chilled water operating flow rate; a third building module, which is used to build a chilled water outlet temperature mixing water constraint equation based on the constraints on the chilled water outlet temperature of the subsystem and The first load rate constraint of the refrigeration unit corresponding to the subsystem determines the safe operation constraint equation of the refrigeration unit corresponding to the subsystem; the first optimization module is used to use the chilled water outlet temperature mixing constraint equation of each subsystem and the safe operation constraint equation of the refrigeration unit corresponding to each subsystem as constraint conditions, to ensure the minimization of the power consumption of the refrigeration unit of the regional cold source system as the optimization goal, and based on the refrigeration unit model of each subsystem, optimize the chilled water outlet temperature of the subsystem to obtain the optimized chilled water outlet temperature of each subsystem; the second optimization module is used to optimize the operating number of the refrigeration unit corresponding to each subsystem based on the particle swarm optimization algorithm to obtain the optimized operating number of the refrigeration unit corresponding to each subsystem.

[0020] According to an embodiment of the present invention, by constructing a refrigeration unit model of a subsystem, the chilled water outlet temperature is optimized and controlled based on the chilled water outlet temperature mixing water constraint and the safe operation constraint of the refrigeration unit. Based on the particle swarm optimization algorithm, the number of operating units of the refrigeration unit is optimized and controlled. Since the chilled water outlet temperature is optimized on the basis of comprehensively considering the load rate of each subsystem in the regional cold source system and the sensitive characteristics of the refrigeration unit, it is possible to ensure that the cold source system operates stably under different load conditions, reduce unnecessary energy consumption, and improve the energy utilization efficiency of the system. In addition, by constructing the chilled water outlet temperature mixing water constraint equation of the subsystem and the safe operation constraint equation of the refrigeration unit corresponding to the subsystem, it is possible to effectively avoid the system imbalance that may occur under extreme working conditions and ensure the long-term efficient and stable operation of the equipment. In addition, the particle swarm optimization algorithm is used to optimize the number of operating units of the refrigeration units of each subsystem of the regional cold source system to improve the operating efficiency of the refrigeration units in the regional cold source system. Combining the optimization control of the chilled water outlet temperature with the optimization control of the number of operating units of the refrigeration unit can be optimized and controlled from different levels to improve the operating efficiency of the regional cold source system, ensure the cold load demand of the terminal of the building, and ensure the safe and stable operation of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings.

[0022] Figure 1 A flow chart of a group control optimization method for a refrigeration unit in a regional cold source system according to an embodiment of the present invention is shown.

[0023] Figure 2 A flow chart is shown for determining a correlation between a chilled water outlet temperature of a subsystem and a first load rate of a refrigeration unit corresponding to the subsystem according to an embodiment of the present invention.

[0024] Figure 3 A flow chart for optimizing the chilled water operating flow rates of multiple refrigeration units in a regional cold source system according to an embodiment of the present invention is shown.

[0025] Figure 4 A block diagram of a group control optimization device for a refrigeration unit in a regional cold source system according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0026] Below, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present invention. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of embodiments of the present invention. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of concepts of the present invention.

[0027] The terms used herein are only for describing specific embodiments and are not intended to limit the present invention. The terms "comprise", "include", etc. used herein indicate the existence of features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0028] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0029] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0030] In the process of realizing the concept of the present invention, it was found that the planning, design and operation control of the regional cold source system need to comprehensively consider multiple factors such as user needs, equipment performance, environmental conditions, etc. to ensure the stable operation of the system and maximize energy efficiency. The regional cold source system includes multiple subsystems, such as: ground source refrigeration unit system, ice storage system, base load refrigeration system, etc. As a key component of the regional cold source system, the operating status and efficiency of the refrigeration unit directly affect the performance of the entire system. Therefore, research and development of efficient group control and optimization methods for refrigeration units in regional cold source systems are of great significance for improving system energy efficiency, reducing operating costs, and promoting sustainable development.

[0031] However, the operation of regional cold source systems also faces many challenges. For example, traditional refrigeration unit systems often find it difficult to accurately adjust the load rate of the refrigeration units of each cold source subsystem, resulting in excessive energy consumption or unstable operation when the system operates under different load conditions. In addition, the outlet temperature of the chilled water is prone to fluctuations, making it difficult to ensure that the system operates within a safe and efficient temperature range.

[0032] Based on this, an embodiment of the present invention provides a group control optimization method for a refrigeration unit of a regional cold source system, wherein the regional cold source system includes a plurality of subsystems, each of which includes a refrigeration unit, and the refrigeration unit is used to deliver chilled water to the end of each building in the target area; the group control optimization method for the refrigeration unit of the regional cold source system includes: for each subsystem: based on the chilled water outlet temperature of the subsystem and the first load rate of the refrigeration unit corresponding to the subsystem, construct a refrigeration unit model of the subsystem; based on the number of operating refrigeration units corresponding to the subsystem and the chilled water operating flow rate of the refrigeration unit, construct a chilled water outlet temperature mixing water constraint equation of the subsystem; based on the constraint conditions on the chilled water outlet temperature of the subsystem and the first load rate of the refrigeration unit corresponding to the subsystem The first load rate constraint of the refrigeration unit is used to determine the safe operation constraint equation of the refrigeration unit corresponding to the subsystem; the chilled water outlet temperature mixing constraint equation of each subsystem and the safe operation constraint equation of the refrigeration unit corresponding to each subsystem are used as constraint conditions, and the chilled water outlet temperature of the refrigeration unit of the regional cold source system subsystem is minimized as the optimization goal. Based on the refrigeration unit model of each subsystem, the chilled water outlet temperature of each subsystem is optimized to obtain the optimized chilled water outlet temperature of each subsystem; and based on the particle swarm optimization algorithm, the operating number of the refrigeration unit corresponding to each subsystem is optimized to obtain the optimized operating number of the refrigeration unit corresponding to each subsystem.

[0033] The following will be passed Figure 1~Figure 3 The group control optimization method of the refrigeration unit of the regional cold source system according to the embodiment of the present invention is described in detail.

[0034] The regional cold source system may include multiple subsystems, each of which may include a refrigeration unit. The number of refrigeration units is not specifically limited in the present invention and may be at least one. The refrigeration unit is used to deliver chilled water to the end of each building in the target area.

[0035] Figure 1 A flow chart of a group control optimization method for a refrigeration unit in a regional cold source system according to an embodiment of the present invention is shown.

[0036] like Figure 1 As shown, the group control optimization method of the regional cold source system refrigeration unit may include operations S110 to S150. It should be noted that operations S110 to S130 are operations performed for each subsystem.

[0037] In operation S110, a refrigeration unit model of the subsystem is constructed based on the chilled water outlet temperature of the subsystem and a first load rate of the refrigeration unit corresponding to the subsystem.

[0038] In operation S120, based on the number of operating refrigeration units corresponding to the subsystem and the operating flow rate of chilled water, a chilled water outlet temperature mixing water constraint equation of the subsystem is constructed.

[0039] In operation S130, a safe operation constraint equation of the refrigeration group corresponding to the subsystem is determined based on a constraint condition on the chilled water outlet temperature of the subsystem and a constraint condition on the first load rate of the refrigeration group corresponding to the subsystem.

[0040] In operation S140, the chilled water outlet temperature mixing constraint equation of each subsystem and the safe operation constraint equation of the refrigeration unit corresponding to each subsystem are used as constraint conditions, and the optimization goal is to minimize the power consumption of the refrigeration unit of the regional cold source system subsystem and the chilled water outlet temperature. Based on the refrigeration unit model of each subsystem, the chilled water outlet temperature of each subsystem is optimized to obtain the optimized chilled water outlet temperature of each subsystem.

[0041] In operation S150, based on a particle swarm optimization algorithm, the number of operating refrigeration units corresponding to each subsystem is optimized to obtain the optimized number of operating refrigeration units corresponding to each subsystem.

[0042] According to an embodiment of the present invention, an equation for refrigeration power may be established based on the chilled water outlet temperature of the subsystem and the first load rate of the refrigeration unit corresponding to the subsystem, and the obtained equation may be determined as the refrigeration unit model.

[0043] According to an embodiment of the present invention, the chilled water outlet temperature mixing water constraint equation of the subsystem can be used to indicate the constraint condition of the state of heat energy of the refrigeration unit corresponding to the subsystem being transmitted with the fluid. For example, the chilled water outlet temperature mixing water constraint equation of the subsystem can be expressed as the product of the chilled water operating flow rate and the chilled water outlet temperature of the refrigeration unit being equal to the product of the subsystem operating flow rate and the chilled water supply set temperature.

[0044] According to an embodiment of the present invention, the constraint condition of the chilled water outlet temperature of the subsystem may include that the chilled water outlet temperature of the subsystem is not greater than the maximum chilled water outlet temperature and not less than the minimum chilled water outlet temperature. The constraint condition of the first load rate of the refrigeration unit corresponding to the subsystem may include that the first load rate of the refrigeration unit corresponding to the subsystem is not greater than the maximum load rate of the refrigeration unit and not less than the minimum load rate of the refrigeration unit. The safe operation constraint equation of the refrigeration unit corresponding to the subsystem may be used to indicate the chilled water outlet temperature of the subsystem and the constraint condition of the first load rate of the refrigeration unit corresponding to the subsystem. According to an embodiment of the present invention, by constructing a refrigeration unit model of the subsystem, the chilled water outlet temperature is optimized and controlled based on the chilled water outlet temperature mixing constraint and the safe operation constraint of the refrigeration unit. Based on the particle swarm optimization algorithm, the number of operating units of the refrigeration unit is optimized and controlled. Since the chilled water outlet temperature is optimized on the basis of comprehensively considering the load rate of each subsystem in the regional cold source system and the sensitive characteristics of the refrigeration unit, it is possible to ensure that the cold source system operates stably under different load conditions, reduce unnecessary energy consumption, and improve the energy utilization efficiency of the system. In addition, by constructing the subsystem's chilled water outlet temperature mixing water constraint equation and the safe operation constraint equation of the refrigeration unit corresponding to the subsystem, it is possible to effectively avoid system imbalances that may occur under extreme working conditions and ensure the long-term efficient and stable operation of the equipment. In addition, the particle swarm optimization algorithm is used to optimize the number of operating refrigeration units in each subsystem of the regional cold source system to improve the operating efficiency of the refrigeration units in the regional cold source system. Combining the optimization control of the chilled water outlet temperature and the number of operating refrigeration units can be optimized and controlled at different levels to improve the operating efficiency of the regional cold source system, ensure the terminal cooling load demand of the building, and ensure the safe and stable operation of the system.

[0045] According to an embodiment of the present invention, the refrigeration unit model of the subsystem can be used to determine the refrigeration power of the refrigeration unit corresponding to the subsystem; The refrigeration unit model of each subsystem can be shown in formula (1):

[0046] (1)

[0047] in, Indicates The cooling power of the refrigeration unit corresponding to each subsystem is: Indicates The rated cooling power of the refrigeration unit corresponding to each subsystem, , …, Sequentially indicates The first to tenth model coefficients in the refrigeration unit model of the subsystem, Indicates The chilled water outlet temperature of each subsystem is Indicates The cooling water outlet temperature of each subsystem is Indicates The first load rate of the refrigeration unit corresponding to the subsystem.

[0048] According to an embodiment of the present invention, The cooling water outlet temperature of each subsystem is a known input parameter.

[0049] According to an embodiment of the present invention, by constructing a refrigeration unit model of the subsystem in which the chilled water outlet temperature of the subsystem is related to the first load rate of the refrigeration unit, the operating load rate and outlet temperature of the refrigeration unit of each subsystem can be accurately calculated and optimized, thereby improving the energy utilization efficiency and operating stability of the system.

[0050] Figure 2 A flow chart is shown for determining a correlation between a chilled water outlet temperature of a subsystem and a first load rate of a refrigeration unit corresponding to the subsystem according to an embodiment of the present invention.

[0051] The group control optimization method of the district cold source system refrigeration unit can include the following Figure 1 In addition to the operations S110 to S150 shown, operations S210 to S270 may also be included. It should be noted that operations S210 to S230 are operations performed on each building terminal in the target area.

[0052] In operation S210, a heat capacity ratio and a number of heat transfer units of the fan coil unit are determined based on parameters of the fan coil unit at the end of the building.

[0053] In operation S220, the heat exchange efficiency of the fan coil unit is determined based on the heat capacity ratio and the number of heat transfer units of the fan coil unit.

[0054] In operation S230, the chilled water supply temperature at the end of the building is determined based on the heat exchange efficiency of the fan coil unit, the indoor design temperature at the end of the building, the physical parameters of the chilled water, and the cooling load at the end of the building.

[0055] In operation S240, a total chilled water supply temperature within the target area is determined based on the number of building terminals within the target area and the chilled water supply temperature of each building terminal.

[0056] In operation S250, a load rate of the regional cooling source system is determined according to a cooling source load parameter of the regional cooling source system.

[0057] In operation S260, based on the second load rate of the regional cold source system, the total chilled water supply temperature, and the chilled water temperature sensitivity characteristic of the refrigeration unit, the expected chilled water return temperature of the regional cold source system is determined.

[0058] In operation S270, a correlation is determined based on the expected chilled water return temperature, the rated cooling capacity of the refrigeration unit corresponding to the subsystem, and the chilled water operation flow rate of the refrigeration unit corresponding to the subsystem.

[0059] According to an embodiment of the present invention, the parameters of the fan coil unit at the end of the building may include at least one of the following: effective thermal conductivity of the fan coil unit, designed cold water heat capacity flowing through the fan coil unit, maximum air heat capacity flowing through the fan coil unit, etc.

[0060] According to an embodiment of the present invention, the heat capacity ratio can be determined according to the designed heat capacity of cold water flowing through the fan coil unit and the maximum heat capacity of air flowing through the fan coil unit. The number of heat transfer units of the fan coil unit is determined according to the effective thermal conductivity of the fan coil unit, the designed heat capacity of cold water flowing through the fan coil unit and the maximum heat capacity of air flowing through the fan coil unit.

[0061] According to an embodiment of the present invention, the physical property parameters of chilled water may include density, specific heat capacity, and temperature rise due to heat loss of chilled water.

[0062] According to an embodiment of the present invention, the total chilled water supply temperature in the target area can be used to indicate the most unfavorable terminal chilled water supply temperature under the most unfavorable terminal operation condition of the building.

[0063] According to an embodiment of the present invention, the cold source load parameter may include the regional cold source system design cold load and the regional cold source system cold load, etc.

[0064] According to the embodiments of the present invention, by considering the cooling capacity of the fan coil unit, the heat exchange efficiency and maximum cooling capacity of the fan coil unit can be accurately calculated, thereby achieving accurate cooling capacity matching in the design and scheduling process, avoiding resource waste, and improving the overall efficiency of the refrigeration system. In addition, by determining the chilled water supply temperature at the most unfavorable end of each building, it can be ensured that the most unfavorable end of all building areas can still meet the cooling load demand, avoiding unstable cooling due to insufficient temperature, and improving the reliability of the system.

[0065] According to an embodiment of the present invention, subsystems, the relevant relationships can be shown in equations (2) and (3):

[0066] (2)

[0067] (3)

[0068] in, Indicates The first load rate of the refrigeration unit corresponding to the subsystem is about The first-order coefficient of the chilled water outlet temperature of each subsystem is: represents the density of frozen water, represents the specific heat capacity of chilled water, Indicates The chilled water flow rate of the refrigeration unit corresponding to each subsystem is Indicates The rated cooling capacity of the refrigeration unit corresponding to each subsystem is: Indicates The first load rate of the refrigeration unit corresponding to the subsystem is about The constant coefficient of the chilled water outlet temperature of each subsystem is: Indicates the expected return temperature of chilled water in the district cooling system.

[0069] According to an embodiment of the present invention, by constructing a correlation between the first load rate of the refrigeration unit and the chilled water outlet temperature of the subsystem, it is helpful to simplify the refrigeration unit model of the subsystem, thereby achieving rapid optimization of the chilled water outlet temperature of the subsystem.

[0070] According to an embodiment of the present invention, the heat capacity ratio and the number of heat transfer units of the fan coil unit may be determined, for example, as shown in the following formula (4) and formula (5):

[0071] (4)

[0072] (5)

[0073] in, represents heat capacity ratio; It represents the minimum value between the fan coil unit's cold water heat capacity and the maximum air heat capacity, in units of ; Indicates the maximum value of the fan coil unit's cold water heat capacity and the maximum air heat capacity, in units ; It represents the design cooling water heat capacity flowing through the fan coil unit, in units ; Indicates the maximum heat capacity of air flowing through the fan coil unit, in units ; Indicates the number of heat transfer units of the fan coil; Indicates the effective thermal conductivity of the fan coil unit, in units .

[0074] According to an embodiment of the present invention, the heat exchange efficiency of the fan coil unit may be determined as shown in the following formula (6):

[0075] (6)

[0076] in, Indicates the efficiency of the fan coil heat exchanger.

[0077] According to an embodiment of the present invention, the maximum cooling capacity of the fan coil unit may be determined as shown in the following formula (7):

[0078] (7)

[0079] in, Indicates the maximum cooling capacity of the fan coil unit, in units ; Indicates the indoor design temperature of each building in the target area, in units ; Indicates the chilled water supply temperature of the regional cold source system, in units ; Indicates the temperature rise of chilled water heat loss, unit .

[0080] According to an embodiment of the present invention, the chilled water supply temperature at the end of each building may be determined as shown in the following formula (8), which can meet the most unfavorable end cooling load of each building.

[0081] (8)

[0082] in, Represents a building The most unfavorable terminal chilled water supply temperature, unit ; Indicates the indoor design temperature of each building in the target area, in units ; Indicates the temperature rise of chilled water heat loss, unit ; Represents a building The most unfavorable terminal cooling load, unit ; Represents a building The most unfavorable terminal fan coil heat exchanger efficiency; Represents a building The minimum value of the cold water heat capacity of the most unfavorable terminal fan coil and the maximum air heat capacity, unit .

[0083] Taking into account the most unfavorable terminal operation conditions of all buildings, the most unfavorable terminal chilled water supply temperature, that is, the total chilled water supply temperature in the target area, can be expressed as follows:

[0084] (9)

[0085] in, Indicates the most unfavorable terminal chilled water supply temperature, unit ;n b Indicates the number of buildings in the target area.

[0086] According to an embodiment of the present invention, the water outlet temperature of the regional cold source system is optimized considering the most unfavorable heat exchange characteristics of the terminal cooling equipment, and the load rate of the regional cold source system can be determined, for example, as shown in the following formula (10):

[0087] (10)

[0088] in, Indicates the load rate of the cooling load of the regional cooling source system; Indicates the cooling load of the regional cooling source system, in units ; Indicates the design cooling load of the regional cooling source system, in units .

[0089] According to an embodiment of the present invention, based on the ideal chilled water supply temperature of the chilled water temperature sensitive characteristics of the refrigeration unit, the expected chilled water return temperature of the regional cold source system is determined, which can be shown in the following equations (11) and (12):

[0090] (11)

[0091] (12)

[0092] in, Indicates the set temperature of chilled water supply in the regional cold source system, in °C; It represents the weighted wet-bulb temperature of each building in the area, in °C; Indicates the indoor design wet-bulb temperature of each building in the area, in °C; Indicates the load rate of the cooling load of the regional cooling source system; It represents the first-order coefficient of chilled water sensitivity characteristic considering the refrigeration power of the refrigeration equipment of the regional cold source system; It represents the constant coefficient of chilled water sensitivity characteristic considering the refrigeration power of the refrigeration equipment of the regional cold source system; Indicates the most unfavorable terminal chilled water supply temperature, unit ; Indicates the minimum supply temperature of chilled water in the regional cold source system, in °C; Indicates the maximum temperature of the chilled water supply of the regional cold source system, in °C; It indicates the temperature difference between the supply and return water of the regional energy system chilled water, in °C; It represents the expected return temperature of chilled water in the district energy system, in °C.

[0093] According to the embodiments of the present invention, the cooling capacity and heat exchange efficiency of the fan coil are calculated based on the heat transfer theory, which can provide a basis for subsequent calculations. The cooling load of the fan coil is used to calculate the guaranteed supply temperature of the chilled water of the most unfavorable terminal building to ensure that the building's cooling load demand is met. Based on the heat exchange characteristics of the equipment at the most unfavorable terminal in the regional cold source system, the outlet water temperature is optimized to improve the overall operating efficiency of the system and meet the cooling load demand.

[0094] According to an embodiment of the present invention, Figure 1 The operation S140 shown, taking the chilled water outlet temperature mixing constraint equation of each subsystem and the safe operation constraint equation of the refrigeration unit corresponding to each subsystem as constraint conditions, taking minimizing the power consumption of the refrigeration unit of the regional cold source system subsystem as the optimization target, optimizing the chilled water outlet temperature of each subsystem based on the refrigeration unit model of each subsystem, and obtaining the optimized chilled water outlet temperature of the subsystem, may include the following operations: for each subsystem: based on the correlation between the chilled water outlet temperature of the subsystem and the first load rate of the refrigeration unit corresponding to the subsystem, performing a simplification operation on the refrigeration unit model of the subsystem, and obtaining a simplified form of the refrigeration unit model of the subsystem. Using the constraint conditions and the optimization target, the simplified form of the refrigeration unit model of each subsystem is optimized and solved using the interior point barrier function method, and the optimized chilled water outlet temperature of each subsystem is obtained.

[0095] According to an embodiment of the present invention, based on the correlation between the chilled water outlet temperature of the subsystem and the first load rate of the refrigeration unit corresponding to the subsystem, a simplification operation is performed on the refrigeration unit model of the subsystem to obtain a simplified form of the refrigeration unit model of the subsystem, which may include the following operations: determining an equation for the first load rate of the refrigeration unit corresponding to the subsystem according to the correlation; replacing the equation with the first load rate; The refrigeration unit model of the subsystem The first load rate of the refrigeration unit corresponding to the subsystem is obtained to obtain the replaced refrigeration unit model; and the known items in the replaced refrigeration unit model are simplified to obtain the simplified form of the refrigeration unit model of the subsystem.

[0096] According to an embodiment of the present invention, the equation for the first load rate of the refrigeration unit corresponding to the subsystem may be expressed as follows (13):

[0097] (13)

[0098] in, Indicates The first load rate of the refrigeration unit corresponding to each subsystem; Indicates The chilled water outlet temperature of the refrigeration unit corresponding to each subsystem, in °C.

[0099] According to an embodiment of the present invention, the equation (13) is replaced with the equation (1) The refrigeration unit model of the subsystem The first load rate of the refrigeration unit corresponding to the subsystem can be obtained as shown in the following formula (14) to obtain the replaced refrigeration unit model.

[0100] (14)

[0101] in, Indicates The cooling power of the refrigeration unit corresponding to each subsystem, in kW, Indicates The rated cooling power of the refrigeration unit corresponding to each subsystem, in kW, , …, Sequentially indicates The first to tenth model coefficients in the refrigeration unit model of the subsystem, Indicates The chilled water outlet temperature of the refrigeration unit corresponding to each subsystem, in °C, Indicates The cooling water outlet temperature of the refrigeration unit corresponding to each subsystem.

[0102] According to an embodiment of the present invention, since the outlet temperature of the cooling water of the refrigeration unit corresponding to the subsystem As the input parameters are known, the known items in the replaced refrigeration unit model are simplified, and the simplified form of the refrigeration unit model of the subsystem can be shown as follows (15):

[0103] (15)

[0104] The simplified form of the above formula (15) can be understood as The function of the independent variable can be calculated .

[0105] According to an embodiment of the present invention, the chilled water outlet temperature mixing water constraint equation of the subsystem can be expressed as follows (16):

[0106] (16)

[0107] in, Indicates the operating flow of the regional cooling system, in units ; Indicates The chilled water outlet temperature of the refrigeration unit of each subsystem, in °C; Indicates The number of operating refrigeration units corresponding to each subsystem; Indicates The chilled water flow rate of the refrigeration unit corresponding to each subsystem, unit ; Indicates the chilled water supply set temperature of the regional cold source system, in °C.

[0108] No. The number of operating refrigeration units in each subsystem can be expressed as follows (17):

[0109] (17)

[0110] in, Indicates The chilled water flow rate of each subsystem, unit ; Indicates The rated operating chilled water flow rate of the refrigeration unit corresponding to each subsystem, unit .

[0111] No. The chilled water flow rate of the refrigeration unit corresponding to each subsystem can be expressed as follows (18):

[0112] (18)

[0113] According to an embodiment of the present invention, the safe operation constraint equation of the refrigeration unit corresponding to the subsystem can be shown in the following equations (19) to (22):

[0114] (19)

[0115] (20)

[0116] (twenty one)

[0117] (twenty two)

[0118] in, Indicates The minimum chilled water outlet temperature of the refrigeration unit corresponding to each subsystem, in °C; Indicates The maximum chilled water outlet temperature of the refrigeration unit corresponding to each subsystem, in °C; Indicates The minimum load rate of the refrigeration unit corresponding to each subsystem; Indicates The maximum load rate of the refrigeration unit corresponding to each subsystem is Indicates The first load rate of the refrigeration unit corresponding to the subsystem is about The first-order coefficient of the chilled water outlet temperature of each subsystem is: Indicates The first load rate of the refrigeration unit corresponding to the subsystem is about The chilled water outlet temperature constant coefficient of each subsystem.

[0119] According to an embodiment of the present invention, by constructing a refrigeration unit model of each subsystem, the relationship between factors such as the chilled water outlet temperature, the cooling water outlet temperature and the load rate is analyzed, and the refrigeration unit model is simplified by combining the correlation between the load rate of the chilled water refrigeration unit and the chilled water outlet temperature to ensure that the system operates safely within a reasonable range.

[0120] According to an embodiment of the present invention, the simplified form of the refrigeration unit model of each subsystem is optimized and solved using the interior point barrier function method with constraints and optimization objectives to obtain the optimized chilled water outlet temperature of each subsystem, which may include the following operations: determining a nonlinear optimization problem based on the refrigeration unit model and optimization objectives of the subsystem; constructing a barrier function for the nonlinear optimization problem; combining the optimization objective with the barrier function to obtain an objective function with a penalty term; and performing constrained optimization solution on the objective function based on Newton's method and constraints until the iteration converges to obtain the optimized chilled water outlet temperature of each subsystem.

[0121] According to an embodiment of the present invention, the nonlinear optimization problem of the chilled water outlet temperature of each subsystem of the cold source system is solved by using the interior point barrier function method as shown in the following formula (23):

[0122] (twenty three)

[0123] Among them, f(T chws,hp ) indicates that T chws,hp is a function of the independent variable, which is used to determine the power consumption of the refrigeration unit of the regional cold source system. ~ as well as are constraint functions for the chilled water outlet temperature of each subsystem.

[0124] The barrier function of the nonlinear optimization problem is shown in equation (24):

[0125] (twenty four)

[0126] Among them, t represents the penalty factor of the barrier function, and m represents 1~4.

[0127] The objective function can be With barrier function Combined to form an objective function with a penalty term , as shown in the following formula (25):

[0128] (25)

[0129] After sorting out, the optimization objective function with the barrier function introduced can be shown as follows (26):

[0130] (26)

[0131] The solution process can be solved by Newton's method to solve the constrained optimization problem. During the iterative calculation process, as t increases, the influence of the barrier function decreases, and the solution gradually approaches the solution of the nonlinear optimization problem along the "Centrol Path", thereby obtaining .

[0132] According to an embodiment of the present invention, the interior point barrier function method is used to solve the chilled water outlet temperature of each subsystem of the cold source system, and internal optimization is used to obtain the optimized chilled water outlet temperature of the subsystem. The load rate of the cold source system and the sensitive characteristics of the chilled water refrigeration unit are comprehensively considered to ensure that the system operates stably within a reasonable working range.

[0133] According to an embodiment of the present invention, Figure 1 The operation S150 shown, based on the particle swarm optimization algorithm, optimizes the operating number of the refrigeration units corresponding to each subsystem to obtain the optimized operating number of the refrigeration units corresponding to each subsystem, and may include the operations of: optimizing the chilled water operating flow of the refrigeration units corresponding to each subsystem based on the particle swarm optimization algorithm to obtain the optimized chilled water operating flow of the refrigeration units corresponding to each subsystem; and obtaining the optimized operating number of the refrigeration units corresponding to each subsystem based on the ratio of the optimized chilled water operating flow of the refrigeration units corresponding to each subsystem and the rated operating condition chilled water operating flow of the refrigeration units corresponding to each subsystem.

[0134] According to an embodiment of the present invention, the optimal solution can be found in a multidimensional space by simulating a particle swarm, and the chilled water flow rate of the refrigeration unit corresponding to each subsystem can be automatically adjusted. The speed and position of the particles are updated through iterative calculation, and the optimal chilled water flow rate of the refrigeration unit corresponding to each subsystem is finally determined.

[0135] According to an embodiment of the present invention, the optimized chilled water outlet temperature of the subsystem and the optimized chilled water operating flow rate of the refrigeration unit corresponding to the subsystem can be used as the optimization results of the group control optimization method of the refrigeration unit of the regional cold source system of the present invention to guide the actual operation and control of the regional cold source system.

[0136] According to an embodiment of the present invention, a particle swarm optimization algorithm is used to optimize the chilled water operating flow of the refrigeration units of each subsystem of the regional cold source system, and the flow distribution is intelligently adjusted to improve the overall performance of the refrigeration units.

[0137] Figure 3 A flow chart for optimizing the chilled water operating flow rates of multiple refrigeration units in a regional cold source system according to an embodiment of the present invention is shown.

[0138] like Figure 3 As shown, in this embodiment, optimizing the chilled water operating flow rates of multiple refrigeration units in the regional cold source system may include operations S310 to S330.

[0139] In operation S310, position information and velocity information of a plurality of particles are randomly initialized.

[0140] In operation S320, the position information and the speed information are input into a fitness function, and the fitness of each particle is output.

[0141] In operation S330, based on the fitness of each particle, the chilled water operating flow of the refrigeration group corresponding to each subsystem is iteratively optimized until the number of iterations reaches a preset number of iterations, thereby obtaining the optimized chilled water operating flow of the refrigeration group corresponding to each subsystem.

[0142] According to an embodiment of the present invention, particles are used to indicate the refrigeration group corresponding to each subsystem, position information is used to indicate the chilled water flow rate of the refrigeration group corresponding to each subsystem, and speed information can be used to indicate the speed of the particles.

[0143] According to an embodiment of the present invention, the fitness function may be determined based on the optimization objective and the equality constraint penalty term, and the equality constraint penalty term may be determined by the equality constraint penalty coefficient and the chilled water operating flow rate of each refrigeration unit.

[0144] According to an embodiment of the present invention, a particle swarm optimization algorithm (PSO) can effectively and automatically adjust the chilled water flow rate of the refrigeration units corresponding to each subsystem of the regional cold source system under various complex constraints. .

[0145] The particle swarm position can be used as the optimization variable group As shown in the following formula (27):

[0146] (27)

[0147] in, Indicates The position of each particle, including the chilled water flow rate of the refrigeration unit corresponding to each subsystem, unit .

[0148] Particle swarm speed As shown in the following formula (28):

[0149] (28)

[0150] in, Indicates The speed of a particle.

[0151] Individual optimal solution of particle swarm As shown in the following formula (29):

[0152] (29)

[0153] in, Indicates The individual optimal solution of each particle, that is, the optimal solution of the chilled water flow rate of the refrigeration unit corresponding to each individual subsystem, unit .

[0154] Global optimal solution of particle swarm , that is, the optimal solution of the chilled water flow rate of the refrigeration unit corresponding to each subsystem globally, unit .

[0155] Can be based on , the optimization objective function value of the chilled water outlet temperature optimization (internal iteration) of each subsystem in the regional cold source system and the equality constraint penalty The sum of is used as the fitness function as shown in formula (30):

[0156] (30)

[0157] The positions of particles can be randomly initialized and speed . Calculate the fitness of each particle according to the fitness function Update individual optimal and global optimal: If the fitness of the current particle position is better than its historical optimal position, update the individual optimal position of the particle ; If the fitness of the current particle position is better than the optimal solution among all particles, update the global optimal position The particle velocity and position are updated as shown in equations (31) and (32). Update the penalty factor of the equality constraint , as shown in formula (33).

[0158] (31)

[0159] (32)

[0160] (33)

[0161] Where k represents the number of iterations; represents the inertia factor; c1 represents the learning factor 1, which specifically refers to the attraction of the particle to the individual optimal solution; r1 represents the random number 1, which ranges from [0,1] and increases the randomness of the algorithm; c2 represents the learning factor 2, which specifically refers to the attraction of the particle to the global optimal solution; r2 represents the random number 2, which ranges from [0,1] and increases the randomness of the algorithm.

[0162] If k reaches the maximum number of iterations set , that is, the preset number of iterations, the algorithm stops and the global optimal solution is output . Global optimal solution Includes the optimized chilled water operating flow of the refrigeration unit corresponding to each subsystem.

[0163] According to an embodiment of the present invention, a particle swarm optimization algorithm is used to optimize the chilled water operating flow of the refrigeration units corresponding to each subsystem of the regional cold source system. The flow can be automatically adjusted according to the load characteristics of the subsystem to reduce excessive or inefficient operation, thereby improving the operating efficiency of the overall system and reducing maintenance costs.

[0164] According to the embodiments of the present invention, by accurately optimizing the various parameters of the regional cold source system, the energy consumption of the cold source system can be effectively reduced, and the unnecessary burden on the refrigeration unit can be reduced, thereby reducing the negative impact on the environment while providing a comfortable environment, which is in line with the sustainable development goal of energy conservation and emission reduction.

[0165] According to the embodiments of the present invention, the regional cold source system provided by the present invention has strong adaptability and is applicable to regional cold source systems of different scales. The group control optimization method of the refrigeration unit of the regional cold source system provided by the present invention has strong adaptability and can be flexibly adjusted according to the scale and actual needs of different regional cold source systems. It is not only applicable to large commercial building complexes, but can also be effectively applied to small and medium-sized regional cold source systems, and has broad application prospects.

[0166] According to the embodiments of the present invention, the group control optimization method of the refrigeration unit of the regional cold source system provided by the present invention not only improves the operating efficiency of the regional cold source system, but also ensures the stability and safety of the system, and provides theoretical support and technical guarantee for the intelligent and energy-saving development of the regional cold source system. The focus is on solving the problems of low energy efficiency and insufficient control accuracy in the operation of the existing regional cold source system.

[0167] Figure 4 A block diagram of a group control optimization device for a refrigeration unit in a regional cold source system according to an embodiment of the present invention is shown.

[0168] like Figure 4 As shown, the group control optimization device of the regional cold source system refrigeration unit may include a first building module 410, a second building module 420, a third building module 430, a first optimization module 440 and a second optimization module 450. The first building module 410, the second building module 420 and the third building module 430 are for each subsystem.

[0169] The first construction module 410 is used to construct a refrigeration unit model of the subsystem based on the chilled water outlet temperature of the subsystem and the first load rate of the refrigeration unit corresponding to the subsystem. The second construction module 420 is used to construct a chilled water outlet temperature mixed water constraint equation of the subsystem based on the number of operating refrigeration units corresponding to the subsystem and the chilled water operating flow of the refrigeration unit. The third construction module 430 is used to determine the safe operation constraint equation of the refrigeration unit corresponding to the subsystem based on the constraint conditions on the chilled water outlet temperature of the subsystem and the constraint on the first load rate of the refrigeration unit corresponding to the subsystem. The first optimization module 440 is used to optimize the chilled water outlet temperature of the subsystem based on the refrigeration unit model of each subsystem, and obtain the optimized chilled water outlet temperature of each subsystem, with the chilled water outlet temperature mixed water constraint equation of each subsystem and the safe operation constraint equation of the refrigeration unit corresponding to each subsystem as the constraint conditions, in order to ensure the construction of the minimization of the power consumption of the refrigeration unit of the regional cold source system as the optimization goal. The second optimization module 450 is used to optimize the number of operating refrigeration units corresponding to each subsystem based on a particle swarm optimization algorithm to obtain the optimized number of operating refrigeration units corresponding to each subsystem.

[0170] According to an embodiment of the present invention, a refrigeration unit is used to deliver chilled water to the end of each building in the target area; the group control optimization device 400 of the refrigeration unit of the regional cold source system also includes: a first determination module, a second determination module, a third determination module, a fourth determination module, a fifth determination module, a sixth determination module and a seventh determination module.

[0171] It should be noted that the first determination module, the second determination module and the third determination module are for each end of a building in the target area.

[0172] The first determination module is used to determine the heat capacity ratio and the number of heat transfer units of the fan coil unit based on the parameters of the fan coil unit at the end of the building. The second determination module is used to determine the heat exchange efficiency of the fan coil unit based on the heat capacity ratio and the number of heat transfer units of the fan coil unit. The third determination module is used to determine the chilled water supply temperature at the end of the building based on the heat exchange efficiency of the fan coil unit, the indoor design temperature at the end of the building, the physical parameters of the chilled water, and the cooling load at the end of the building. The fourth determination module is used to determine the total chilled water supply temperature in the target area based on the number of building ends in the target area and the chilled water supply temperature at the end of each building. The fifth determination module is used to determine the load rate of the regional cold source system according to the cold source load parameters of the regional cold source system. The sixth determination module is used to determine the expected chilled water return temperature of the regional cold source system based on the second load rate of the regional cold source system, the total chilled water supply temperature, and the cold water temperature sensitivity characteristics of the refrigeration unit. The seventh determination module is used to determine the correlation based on the expected chilled water return temperature, the rated cooling capacity of the refrigeration unit corresponding to the subsystem, and the chilled water operating flow of the refrigeration unit corresponding to the subsystem.

[0173] According to an embodiment of the present invention, any multiple modules of the first building module 410, the second building module 420, the third building module 430, the first optimization module 440, and the second optimization module 450 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present invention, at least one of the first building module 410, the second building module 420, the third building module 430, the first optimization module 440, and the second optimization module 450 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in any appropriate combination of any of them. Alternatively, at least one of the first building module 410, the second building module 420, the third building module 430, the first optimization module 440 and the second optimization module 450 can be at least partially implemented as a computer program module, which can perform corresponding functions when executed.

[0174] It should be noted that the group control optimization device part of the regional cold source system refrigeration unit in the embodiment of the present invention corresponds to the group control optimization method part of the regional cold source system refrigeration unit in the embodiment of the present invention. The description of the group control optimization device part of the regional cold source system refrigeration unit specifically refers to the group control optimization method part of the regional cold source system refrigeration unit, which will not be repeated here.

[0175] It will be appreciated by those skilled in the art that the features described in the various embodiments of the present invention may be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in the present invention. In particular, without departing from the spirit and teachings of the present invention, the features described in the various embodiments of the present invention may be combined and / or combined in various ways. All of these combinations and / or combinations fall within the scope of the present invention.

[0176] The embodiments of the present invention are described above. However, these embodiments are only for the purpose of illustration, and are not intended to limit the scope of the present invention. Although each embodiment is described above, it does not mean that the measures in each embodiment cannot be used in combination advantageously. Without departing from the scope of the present invention, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present invention.

Claims

1. A group control optimization method for a refrigeration unit in a regional cold source system, characterized in that: The regional cold source system includes a plurality of subsystems, each of which includes a refrigeration unit, and the refrigeration unit is used to deliver chilled water to the end of each building in the target area; The group control optimization method comprises: For each of the subsystems: constructing a refrigeration unit model of the subsystem based on the chilled water outlet temperature of the subsystem and a first load rate of the refrigeration unit corresponding to the subsystem; Based on the number of operating refrigeration units corresponding to the subsystem and the operating flow rate of chilled water, a chilled water outlet temperature mixing water constraint equation of the subsystem is constructed; Determining a safe operation constraint equation of the refrigeration unit corresponding to the subsystem based on the constraint condition on the chilled water outlet temperature of the subsystem and the constraint condition on the first load rate of the refrigeration unit corresponding to the subsystem; Taking the chilled water outlet temperature mixing constraint equation of each subsystem and the safe operation constraint equation of the refrigeration unit corresponding to each subsystem as constraint conditions, taking minimizing the power consumption of the refrigeration unit of the regional cold source system as the optimization goal, based on the refrigeration unit model of each subsystem, optimizing the chilled water outlet temperature of each subsystem, and obtaining the optimized chilled water outlet temperature of each subsystem; Based on the particle swarm optimization algorithm, the operating number of the refrigeration groups corresponding to each of the subsystems is optimized to obtain the optimized operating number of the refrigeration groups corresponding to each of the subsystems.

2. The group control optimization method according to claim 1, characterized in that: The method uses the chilled water outlet temperature mixing constraint equation of each subsystem and the safe operation constraint equation of the refrigeration unit corresponding to each subsystem as constraint conditions, takes minimizing the power consumption of the refrigeration unit of the regional cold source system as the optimization goal, and optimizes the chilled water outlet temperature of each subsystem based on the refrigeration unit model of each subsystem to obtain the optimized chilled water outlet temperature of each subsystem, including: For each of the subsystems: based on the correlation between the chilled water outlet temperature of the subsystem and the first load rate of the refrigeration unit corresponding to the subsystem, a simplification operation is performed on the refrigeration unit model of the subsystem to obtain a simplified form of the refrigeration unit model of the subsystem; Based on the constraint conditions and the optimization target, the simplified form of the refrigeration unit model of each subsystem is optimized and solved using the interior point barrier function method to obtain the optimized chilled water outlet temperature of each subsystem.

3. The group control optimization method according to claim 2, characterized in that: The group control optimization method also includes: For each of the building ends in the target area: Determining the heat capacity ratio and the number of heat transfer units of the fan coil unit based on the parameters of the fan coil unit at the end of the building; Determining the heat exchange efficiency of the fan coil unit based on the heat capacity ratio and the number of heat transfer units of the fan coil unit; Determining the chilled water supply temperature at the end of the building based on the heat exchange efficiency of the fan coil unit, the indoor design temperature at the end of the building, the physical properties of the chilled water, and the cooling load at the end of the building; Determining a total chilled water supply temperature within the target area based on the number of building terminals within the target area and the chilled water supply temperature at each building terminal; Determining a load rate of the regional cooling source system according to a cooling source load parameter of the regional cooling source system; Determining an expected return temperature of chilled water of the regional cold source system based on a second load rate of the regional cold source system, the total chilled water supply temperature, and a chilled water temperature sensitivity characteristic of the refrigeration unit; The correlation is determined based on the expected return water temperature of the chilled water, the rated cooling capacity of the refrigeration unit corresponding to the subsystem, and the chilled water operating flow rate of the refrigeration unit corresponding to the subsystem.

4. The group control optimization method according to claim 2, characterized in that: The refrigeration unit model of the subsystem is used to determine the refrigeration power of the refrigeration unit corresponding to the subsystem; No. The refrigeration unit model of each subsystem includes the following formula (1): （1） in, Indicates The cooling power of the refrigeration unit corresponding to each subsystem is: Indicates The rated cooling power of the refrigeration unit corresponding to each subsystem, , …, In turn, the The first to tenth model coefficients in the refrigeration unit model of the subsystem, Indicates The chilled water outlet temperature of each subsystem is Indicates The cooling water outlet temperature of each subsystem is Indicates The first load rate of the refrigeration unit corresponding to the subsystem.

5. The group control optimization method according to claim 4, characterized in that: The method of performing a simplification operation on the refrigeration unit model of the subsystem based on the correlation between the chilled water outlet temperature of the subsystem and the first load rate of the refrigeration unit corresponding to the subsystem to obtain a simplified form of the refrigeration unit model of the subsystem includes: Determine, according to the correlation, an equation for the first load rate of the refrigeration unit corresponding to the subsystem; Substituting the equation The refrigeration unit model of the subsystem The first load rate of the refrigeration unit corresponding to the subsystem is used to obtain the refrigeration unit model after replacement; The known items in the replaced refrigeration unit model are simplified to obtain a simplified form of the refrigeration unit model of the subsystem.

6. The group control optimization method according to claim 2, characterized in that: For the subsystems, the correlation is shown in equations (2) and (3): （2） （3） in, Indicates The first load rate of the refrigeration unit corresponding to the subsystem is about The linear coefficient of the chilled water outlet temperature of each subsystem is: represents the density of frozen water, represents the specific heat capacity of chilled water, Indicates The chilled water flow rate of the refrigeration unit corresponding to each subsystem is Indicates The rated cooling capacity of the refrigeration unit corresponding to each subsystem is: Indicates The first load rate of the refrigeration unit corresponding to the subsystem is about The constant coefficient of the chilled water outlet temperature of the subsystem, Indicates the expected return temperature of chilled water in the regional cold source system.

7. The group control optimization method according to claim 2, characterized in that: The method of optimizing and solving the simplified form of the refrigeration unit model of each subsystem using the constraint conditions and the optimization target by using the interior point barrier function method to obtain the optimized chilled water outlet temperature of each subsystem includes: Determining a nonlinear optimization problem based on the refrigeration unit model of the subsystem and the optimization target; Constructing a barrier function for the nonlinear optimization problem; Combining the optimization objective with the barrier function to obtain an objective function with a penalty term; Based on Newton's method and the constraint conditions, the objective function is subjected to constrained optimization and solution until iteration converges, thereby obtaining the optimized chilled water outlet temperature of each subsystem.

8. The group control optimization method according to any one of claims 1 to 7, characterized in that: The method of optimizing the number of operating refrigeration units corresponding to each of the subsystems based on the particle swarm optimization algorithm to obtain the optimized number of operating refrigeration units corresponding to each of the subsystems includes: Based on the particle swarm optimization algorithm, the chilled water operating flow rate of the refrigeration unit corresponding to each of the subsystems is optimized to obtain an optimized chilled water operating flow rate of the refrigeration unit corresponding to each of the subsystems; According to the ratio of the optimized chilled water operating flow rate of the refrigeration group corresponding to each of the subsystems and the rated operating condition chilled water operating flow rate of the refrigeration group corresponding to each of the subsystems, the optimized operating number of the refrigeration group corresponding to each of the subsystems is obtained.

9. The group control optimization method according to claim 8, characterized in that: The method of optimizing the chilled water operation flow of the refrigeration unit corresponding to each of the subsystems based on the particle swarm optimization algorithm to obtain the optimized chilled water operation flow of the refrigeration unit corresponding to each of the subsystems includes: Randomly initialize the position information and speed information of a plurality of particles, wherein the particles are used to indicate the refrigeration unit corresponding to each of the subsystems, the position information is used to indicate the chilled water running flow of the refrigeration unit corresponding to each of the subsystems, and the speed information is used to indicate the speed of the particles; Inputting the position information and the speed information into a fitness function, and outputting the fitness of each particle, wherein the fitness function is determined based on the optimization objective and an equality constraint penalty term, and the equality constraint penalty term is determined by an equality constraint penalty coefficient and the chilled water operating flow rate of the refrigeration unit; Based on the fitness of each of the particles, the chilled water operating flow of the refrigeration group corresponding to each of the subsystems is iteratively optimized until the number of iterations reaches a preset number of iterations, thereby obtaining the optimized chilled water operating flow of the refrigeration group corresponding to each of the subsystems.

10. A group control optimization device for a refrigeration unit in a regional cold source system, characterized in that: The regional cold source system includes a plurality of subsystems, each of which includes a refrigeration unit, and the refrigeration unit is used to deliver chilled water to the end of each building in the target area; The group control optimization device comprises: For each of the subsystems described: A first construction module, configured to construct a refrigeration unit model of the subsystem based on a chilled water outlet temperature of the subsystem and a first load rate of the refrigeration unit corresponding to the subsystem; A second construction module is used to construct a chilled water outlet temperature mixing water constraint equation of the subsystem based on the number of operating refrigeration units and the chilled water operating flow rate corresponding to the subsystem; A third building module is used to determine a safe operation constraint equation of the refrigeration unit corresponding to the subsystem based on the constraint condition of the chilled water outlet temperature of the subsystem and the constraint of the first load rate of the refrigeration unit corresponding to the subsystem; The first optimization module is used to optimize the chilled water outlet temperature of each subsystem based on the chilled water outlet temperature mixing water constraint equation and the safe operation constraint equation of the refrigeration unit corresponding to each subsystem as constraint conditions, to ensure that the power consumption of the refrigeration unit of the regional cold source system is minimized as the optimization goal, and based on the refrigeration unit model of each subsystem, to obtain the optimized chilled water outlet temperature of each subsystem; The second optimization module is used to optimize the operating number of the refrigeration groups corresponding to each of the subsystems based on a particle swarm optimization algorithm to obtain the optimized operating number of the refrigeration groups corresponding to each of the subsystems.

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