Cooperative polymerization regulation and control method and system based on house building polymorphic composite energy storage

Abstract

The invention belongs to the field of polymorphic energy storage aggregation scheduling control, and discloses a collaborative aggregation regulation and control method and system based on house building polymorphic composite energy storage, and the method comprises the steps: collecting the internal temperature and outdoor temperature of a machine room at a certain moment, and building an equivalent thermal parameter model based on temperature change; introducing an energy reference zero point, and converting the equivalent thermal parameter model based on temperature change into a dimensionless energy storage state model; according to the dimensionless energy storage state model, the energy change in the virtual standard machine room is expressed, and a standardized control strategy is output based on the energy change in the virtual standard machine room; machine rooms are grouped through a clustering algorithm to form machine room clusters with similar thermal characteristics, and each machine room cluster is subjected to intra-cluster unified control through a standardized control strategy. According to the invention, the cooling load of each machine room can be accurately controlled through the regulation and control mode based on the heat storage state. The house can be equivalent to other polymorphic composite energy storage, has similar characteristics, provides a collaborative optimization method for composite energy storage with differentiated dynamic characteristics and storage duration, effectively reduces energy waste, optimizes load response of a power system, and improves energy utilization efficiency.

Description

Technical Field

[0001] The present invention relates to multi-form energy storage aggregation scheduling control, and in particular to a collaborative aggregation control method and system based on multi-form composite energy storage of buildings. Background Art

[0002] With the continued rapid growth in the number of communication base stations, how to efficiently and intelligently control the cooling load of each base station's computer room has become a technical challenge that the current communications industry urgently needs to overcome. Traditional cooling load control methods often focus on the temperature control of a single computer room and lack a global consideration and coordination mechanism. This control method has many drawbacks: on the one hand, the control strategies of different computer rooms vary greatly, making it difficult to form unified and standardized management specifications, which brings great inconvenience to operation and maintenance work; on the other hand, due to the relatively extensive control methods and low adjustment accuracy, it is often unable to meet the precise requirements of the equipment in the computer room for environmental parameters such as temperature and humidity, thus affecting the stable operation and performance of the equipment.

[0003] More seriously, under traditional control methods, the system's response speed is slow, making it difficult to promptly respond to changes in the internal and external environment of the computer room, such as sudden temperature increases and increased equipment heat generation. This not only reduces the cooling efficiency of the computer room, but can also cause equipment failures due to excessive temperatures, and even lead to safety accidents.

[0004] These issues become particularly acute in the context of centralized control across large-scale computer rooms. As the number and scale of computer rooms increase, traditional control methods are no longer able to cope with such a large and complex system. This not only increases the burden on the power system and reduces energy efficiency, but also makes it difficult to accurately meet the cooling needs of each computer room. Summary of the Invention

[0005] The purpose of the present invention is to provide a collaborative aggregation control method and system based on multi-form composite energy storage in buildings, so as to solve the problems of large differences in control strategies, low adjustment accuracy and slow response in the scenario of large-scale computer room aggregation control.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a collaborative aggregation control method based on multi-modal composite energy storage in buildings, comprising:

[0008] Collect the internal and outdoor temperatures of the equipment room at a certain moment and establish an equivalent thermal parameter model based on temperature changes;

[0009] The energy reference zero point is introduced to transform the equivalent thermal parameter model based on temperature change into a dimensionless energy storage state model;

[0010] The dimensionless energy storage state model is used to express the energy changes inside the virtual standard computer room. Based on the energy changes inside the virtual standard computer room, a standardized control strategy is output under the condition that the heat storage states of the real computer room and the virtual standard computer room are kept synchronized.

[0011] The computer rooms are grouped by clustering algorithms to form computer room clusters with similar thermal characteristics. Each computer room cluster is uniformly controlled within the cluster through a standardized control strategy.

[0012] Optionally, collecting the internal temperature and outdoor temperature of the computer room at a certain moment and establishing an equivalent thermal parameter model based on temperature changes includes:

[0013] The thermal dynamics of the computer room is expressed by a first-order differential equation regarding the indoor temperature:

[0014]

[0015] Where: T i (t) and are the internal temperature and outdoor temperature of the computer room at time t; C i is the equivalent heat capacity of the room shell, reflecting the heat storage capacity of the room; K i is the equivalent thermal conductivity of the computer room shell, reflecting the heat conduction capacity between the computer room and the outside world; is the heat gain of the computer room at time t.

[0016] Optionally, the temperature range allowed in the computer room at time t is set to:

[0017]

[0018] Where: T i (t) and are the upper and lower limits of the temperature range allowed for normal operation of the computer room; the heat gain of the computer room at time t in formula (1) is Controllable heat gain and passive heat gain Composition, expressed as:

[0019]

[0020] Where: Controllable heat gain is the air conditioning cooling load, passive heat gain Dissipate heat for solar radiation and equipment inside the computer room; The relationship between the cooling capacity of the air conditioner and the rated power of the air conditioner is expressed as:

[0021]

[0022] Where, is the rated power of the air conditioner; CoP i (t) represents the energy efficiency ratio of different types of air conditioners; Parameters indicating the operating status of the air conditioner.

[0023] Optionally, the introduction of an energy reference zero point to convert the equivalent thermal parameter model based on temperature change into a dimensionless energy storage state model includes:

[0024] definition is the temperature reference zero point of house i, then is the energy reference zero point of house i; for any temperature T i (t), the relative energy of house i at time t is expressed as:

[0025]

[0026] Substituting formula (5) into formula (1), we get the following equivalent energy storage model:

[0027]

[0028] Where, is the net thermal power input to the house, and its specific expression is as follows:

[0029]

[0030] in, is the cooling power of the air conditioner; The heat power passively obtained in the computer room; is the equivalent heat exchange caused by the temperature difference between the inside and outside of the computer room;

[0031] The heat storage state of the computer room is defined as follows:

[0032]

[0033] in, is the heat storage state of the computer room at time t, and is defined as The upper limit of the temperature reference for the equipment room is defined. is the equivalent heat storage capacity of the computer room.

[0034] Optionally, define the house thermal power control signal π i (t)

[0035]

[0036] Substituting formulas (8) and (9) into formula (6), the equivalent thermal parameter model of the house is transformed into the following form:

[0037]

[0038] Where, τ i =C i / K i , is the equivalent time constant of thermal energy change in the house;

[0039] Formula (10) is differentiated and the sampling time is expressed as Δt. Then the dimensionless house equivalent thermal parameter differential equation expressed by formula (10) is expressed as the following differential form:

[0040]

[0041] in:

[0042]

[0043] The energy storage state of the house at time t is obtained from formulas (2), (5), and (8): The value range of is:

[0044]

[0045] For different types of air conditioners, the thermal power control signal π i The value range of (t) can be determined according to formulas (3), (4), and (9) as follows:

[0046]

[0047] in:

[0048]

[0049] Optionally, the step of expressing energy changes within the virtual standard computer room based on the dimensionless energy storage state model and outputting a standardized control strategy based on the energy changes within the virtual standard computer room while synchronizing the heat storage states of the real computer room and the virtual standard computer room includes:

[0050] According to the dimensionless energy storage state model, the energy change inside the virtual standard computer room is expressed by the following formula:

[0051]

[0052] in:

[0053]

[0054] Where, and Respectively represent the heat storage state and heat power control signal of the virtual standard computer room; is its time constant;

[0055]

[0056] Using the virtual standard computer room This set of signals enables efficient and unified control of the cooling load of massive communication base station rooms;

[0057] For any computer room i, its heat storage state Thermal storage status of the virtual standard computer room The error between them is expressed as:

[0058]

[0059] Under the condition that the heat storage state of the real computer room and the virtual standard computer room are kept synchronous, that is, Let both sides of formula (20) be 0, and we get:

[0060]

[0061] Optionally, the computer rooms are grouped by a clustering algorithm to form computer room clusters with similar thermal characteristics, and each computer room cluster is uniformly controlled within the cluster by a standardized control strategy, including:

[0062] The feasible region under the constraint of computer room i is:

[0063]

[0064] Normalized control signal Compatible with the constraints of all base station rooms involved in the control, the actual feasible domain is:

[0065]

[0066] The thermal characteristics of a building are determined by the parameter τ i Characterization, based on the distance of these parameters, the k-means clustering algorithm is used for partitioning. After clustering, there are C base station room clusters. Represents a collection of clustering indexes; for a cluster use represents the set of all computer rooms in the cluster; then, according to formulas (4)-(9), the cooling power of computer room i in cluster c is determined by the normalized control signal The calculation is as follows:

[0067]

[0068] in:

[0069]

[0070]

[0071] In a second aspect, the present invention provides a collaborative aggregation control system based on multi-modal composite energy storage in buildings, comprising:

[0072] The data acquisition module is used to collect the internal and outdoor temperatures of the computer room at a certain moment and establish an equivalent thermal parameter model based on temperature changes;

[0073] Model conversion module, used to introduce energy reference zero point and convert the equivalent thermal parameter model based on temperature change into a dimensionless energy storage state model;

[0074] The strategy output module is used to express the energy changes inside the virtual standard computer room based on the dimensionless energy storage state model. Based on the energy changes inside the virtual standard computer room, it outputs a standardized control strategy under the condition that the heat storage states of the real computer room and the virtual standard computer room are synchronized;

[0075] The grouping control module is used to group computer rooms through clustering algorithms to form computer room clusters with similar thermal characteristics. Each computer room cluster is uniformly controlled within the cluster through a standardized control strategy.

[0076] In a third aspect, the present invention provides a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the collaborative aggregation control method based on multi-form composite energy storage of building structures are implemented.

[0077] In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the collaborative aggregation control method based on multi-form composite energy storage of building structures.

[0078] Compared with the prior art, the present invention has the following technical effects:

[0079] The present invention can accurately control the cooling load of each computer room through a control method based on the heat storage state. By introducing the energy reference zero point, the temperature model is converted into a dimensionless energy storage state model, making the control process more intuitive and easy to calculate. The house in the present invention can be equivalent to other multi-form composite energy storage with similar characteristics, providing a collaborative optimization method for composite energy storage with differentiated dynamic characteristics and storage time, effectively reducing energy waste, optimizing the load response of the power system, and improving energy utilization efficiency.

[0080] The introduction of the concept of a virtual standard room provides a unified control signal generation mechanism for a large number of communication base station rooms. By ensuring synchronization of the heat storage status of real and virtual standard rooms, efficient and unified control of cooling loads across a large number of rooms is achieved. This approach avoids the challenges of personalized control due to room-to-room differences in traditional control, improving the accuracy and consistency of overall control.

[0081] This invention enables personalized control based on the thermal characteristics of different computer rooms. Using a clustering algorithm, computer rooms are grouped to form clusters with similar thermal characteristics, and a unified control strategy is developed for each cluster. This approach not only increases control flexibility but also adapts to the needs of different building types and air conditioning equipment, ensuring optimal control results.

[0082] Through efficient control strategies, the present invention effectively reduces the peak load of the power system while meeting the cooling needs of each computer room. This helps alleviate the tight power supply situation, improves the utilization efficiency of power resources, and reduces the operating costs of the power system.

[0083] By establishing an equivalent thermal parameter model based on temperature changes, the dynamic changes in the computer room's heat output are linked to the heat storage state, forming a unified control platform. This approach not only improves the accuracy of control but also makes the control process more efficient. Compared to traditional methods, this invention can respond more quickly to changes in the internal and external environment of the computer room, ensuring the stable operation of the equipment in the computer room.

[0084] By transforming the high-dimensional constrained optimization problem into a low-dimensional one and employing a constraint tightening method using inner approximations, the scale of the optimization problem is reduced. This helps reduce the complexity of the control process and improves its real-time performance and reliability. Furthermore, using ellipsoidal robust constraints instead of complex polyhedral regions further simplifies the control process and makes the control strategy easier to implement.

[0085] In summary, this method, by introducing technologies such as virtual standard computer rooms, clustering and partitioning, and a dimensionless energy storage state model, achieves efficient, unified, and precise control of the cooling load in large-scale communication base station computer rooms. This approach not only improves energy efficiency and reduces the burden on the power system, but also enhances system stability and security, which is of great significance for promoting the sustainable development of the communications industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0086] Figure 1 This is the first-order equivalent thermodynamic model of the base station building of the present invention.

[0087] Figure 2 This is a schematic diagram of the reference temperature selection inside the base station building of the present invention.

[0088] Figure 3Schematic diagram of the constraint tightening of the thermal energy normalization method of the present invention.

[0089] Figure 4 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0090] The present invention is further described below with reference to the accompanying drawings:

[0091] Example 1, please refer to Figure 4 The present invention provides a collaborative aggregation control method based on multi-form composite energy storage of building structures, comprising:

[0092] Collect the internal and outdoor temperatures of the equipment room at a certain moment and establish an equivalent thermal parameter model based on temperature changes;

[0093] The energy reference zero point is introduced to transform the equivalent thermal parameter model based on temperature change into a dimensionless energy storage state model;

[0094] The dimensionless energy storage state model is used to express the energy changes inside the virtual standard computer room. Based on the energy changes inside the virtual standard computer room, a standardized control strategy is output under the condition that the heat storage states of the real computer room and the virtual standard computer room are kept synchronized.

[0095] The computer rooms are grouped by clustering algorithms to form computer room clusters with similar thermal characteristics. Each computer room cluster is uniformly controlled within the cluster through a standardized control strategy.

[0096] This method uses data from both the internal and external room temperatures to establish an equivalent thermal parameter model based on temperature variations, accurately reflecting the dynamic changes in heat within the room. This modeling approach enables more precise energy management, allowing for real-time adjustments based on actual environmental conditions and room requirements.

[0097] By introducing an energy reference zero point, the temperature model is converted into a dimensionless energy storage state model, further simplifying the control process. This approach allows for uniform quantification and comparison of heat variations across different computer rooms, facilitating coordinated and aggregated control across large-scale computer rooms.

[0098] This method proposes the concept of a virtual standard computer room. By expressing the energy changes within the virtual standard computer room, it provides a unified control signal generation mechanism for the real computer room. This mechanism ensures that all computer rooms participating in the control can operate according to unified specifications, avoiding the individual differences and confusion in traditional control methods.

[0099] Under the premise of keeping the thermal storage status of the real computer room and the virtual standard computer room synchronized, a standardized control strategy is output. This strategy enables each computer room to be precisely regulated according to its own thermal characteristics and needs, while maintaining coordination with the entire system.

[0100] This method uses a clustering algorithm to group computer rooms into clusters with similar thermal characteristics. This grouping method allows computer rooms with similar thermal characteristics to be grouped together for unified regulation, improving the flexibility and efficiency of regulation.

[0101] For each computer room cluster, this method uses a standardized control strategy to achieve unified control within the cluster. This control strategy not only considers the overall needs of the computer room cluster, but also fully considers the individual differences of each computer room, achieving personalized management under unified control.

[0102] This method uses efficient energy management and control strategies to precisely control the cooling load of each computer room and reduce unnecessary energy waste. This helps to reduce the burden on the power system, lower peak loads, and improve the efficiency of power resource utilization.

[0103] At the same time, through a unified control strategy and signal generation mechanism, this method can also optimize the load response speed and capacity of the power system and improve the stability and reliability of the entire power grid.

[0104] In Example 2, the present invention provides a collaborative aggregation control method based on multi-form composite energy storage in buildings, specifically comprising:

[0105] Cooling load model based on house heat storage state

[0106] Equivalent thermal parameter model based on temperature change

[0107] The communication base station room can be essentially considered a house, so the equivalent thermal parameter model of a house can be used to describe the changes in thermal energy in the room. However, unlike ordinary houses, the communication base station room does not have compartments divided by walls. Its internal space can be considered a unified whole with uniform distribution of media, so there is no heat conduction effect between rooms. The inherent heat storage of the communication base station room can be simplified as Figure 1 The first-order equivalent circuit is shown.

[0108] Since the rate of change of the indoor temperature of the computer room is affected by direct heat gain and heat conduction between the inside and outside of the building, the thermal dynamic process of the computer room can be expressed by a first-order differential equation about the indoor temperature:

[0109]

[0110] Where: T i (t) and are the internal temperature and outdoor temperature of the computer room at time t; C i is the equivalent heat capacity of the room shell, reflecting the heat storage capacity of the room; K i is the equivalent thermal conductivity of the computer room shell, reflecting the heat conduction capacity between the computer room and the outside world; is the heat gain of the computer room at time t.

[0111] The temperature range allowed in the computer room at time t is set as:

[0112]

[0113] Where: T i (t) and These are the upper and lower limits of the temperature range allowed for normal operation of the equipment room.

[0114] It is worth emphasizing that formula (2) provides a general form for setting the room temperature range, and its upper and lower limits can change over time based on people's actual activities. Compared to human body perception, servers are less sensitive to temperature changes, so the upper and lower limits of the temperature in the computer room tend to remain constant over time. This can greatly reduce the heterogeneity of temperature control strategies in different computer rooms, thereby significantly improving the accuracy and efficiency of aggregated control.

[0115] The heat gain of the computer room at time t in formula (1) is Controllable heat gain and passive heat gain Composition, specifically can be expressed as:

[0116]

[0117] Where: Controllable heat gain From cooling loads such as air conditioning, passive heat gain It mainly comes from solar radiation and heat dissipation of equipment inside the room. Assuming that the base station room is cooled by air conditioning, The relationship between the cooling capacity of the air conditioner and the rated power of the air conditioner can be uniformly expressed as:

[0118]

[0119] Where, is the rated power of the air conditioner; CoP i (t) represents the energy efficiency ratio of different types of air conditioners. If it is a fixed-frequency air conditioner, its energy efficiency ratio is a constant value, while the energy efficiency ratio of a variable-frequency air conditioner varies with the frequency; For fixed frequency air conditioners, Indicates the start / stop status of the air conditioner. The value 0 or 1 represents the off / on status respectively. For variable frequency air conditioners, Represents the percentage in cooling mode, that is, the ratio of the air conditioner's operating power to its maximum power.

[0120] Equivalent thermal parameter model based on energy change

[0121] The equivalent thermal parameter model based on temperature change, expressed by formula (1), can effectively characterize the thermal energy changes within a single communication base station room. However, since temperatures cannot be superimposed, the temperature model cannot intuitively represent the aggregation process when faced with the problem of aggregated control of massive communication base station rooms. To address this problem, an equivalent thermal parameter model based on energy change is derived, which characterizes the dynamic changes in thermal energy within the room using an energy storage model.

[0122] First define is the temperature reference zero point of house i, then is the energy reference zero point of house i. For any temperature T i (t), the relative energy of house i at time t is measured by the following formula:

[0123]

[0124] Substituting formula (5) into formula (1), we can obtain the following equivalent energy storage model:

[0125]

[0126] Where, is the net thermal power input to the house, and its specific expression is as follows:

[0127]

[0128] Among them, the first item is the cooling power of the air conditioner; the second item is the heat power passively obtained in the computer room, such as solar radiation and heat dissipation of the server; the third item can be understood as the equivalent heat exchange caused by the temperature difference between the inside and outside of the computer room.

[0129] The building materials of houses are diverse, and the heat energy transfer efficiency of walls, windows, roofs, etc. between different houses varies greatly, which is expressed as the equivalent heat capacity C between different houses i in formula (1): i , equivalent thermal conductivity K i The vast differences create several constraints that affect the scope of unified control signal delivery. These constraints vary widely, necessitating the sacrifice of the control signal's feasible domain area to ensure that the control signal meets the temperature requirements of all rooms. However, base station rooms are typically constructed of reinforced concrete or steel. These rooms are constructed in the same batch using the same materials and are constructed according to unified standards. Therefore, the boundaries of different base station rooms converge, resulting in similar internal and external boundaries, effectively preserving the control signal's feasible domain.

[0130] Analogous to the concept of the state of charge (SoC) of an energy storage battery, the heat storage state of a computer room is defined as follows:

[0131]

[0132] in, is the heat storage state of the computer room at time t. Definition The upper limit of the temperature reference for the equipment room is defined. is the equivalent heat storage capacity of the computer room. For a given computer room, to ensure the heat storage state The value of is in the interval [0,1] and can be 0 and 1.

[0133] Next, define the house thermal power control signal π i (t), this signal is the core optimization variable of the house equivalent thermal parameter model based on energy change proposed in this paper. i (t), the air conditioning load of massive communication base stations can be controlled in real time and efficiently to meet the needs of the power system operation level and the cooling needs of individual base stations.

[0134]

[0135] Substituting formulas (8) and (9) into formula (6), the equivalent thermal parameter model of the house is transformed into the following form:

[0136]

[0137] Where, τ i =C i / K i , is the equivalent time constant of thermal energy change in the house.

[0138] Performing differential processing on formula (10), using Δt to represent the sampling time, the dimensionless house equivalent thermal parameter differential equation represented by formula (10) can be expressed in the following differential form:

[0139]

[0140] in:

[0141]

[0142] From formulas (2), (5), and (8), we can derive the energy storage state of the house at time t: The value range of is:

[0143]

[0144] In addition, for different types of air conditioners, the thermal power control signal π iThe value range of (t) can be determined according to formulas (3), (4), and (9) as follows:

[0145]

[0146] in:

[0147]

[0148] Therefore, the equivalent thermal parameter model of the house based on energy change is further transformed into a dimensionless form represented by formulas (8)-(16).

[0149] Aggregate control of cooling load in massive communication base station rooms

[0150] Normalized control signal

[0151] Massive communication base stations can be equivalent to a virtual power plant. When traditional virtual power plants regulate the distributed resources they manage, they need to decompose the overall response indicators based on the real-time status of the resources and generate an independent control signal for each resource (group) participating in the response. First, a virtual standard communication base station room is defined for generating virtual power plant control signals. Based on the dimensionless form of the energy-variable equivalent thermal parameter model of the house derived earlier, the energy variation within this virtual standard room can be expressed as follows:

[0152]

[0153] in:

[0154]

[0155] Where, and They respectively represent the heat storage status and heat power control signal of the virtual standard computer room. Its time constant is. In order to make the virtual standard computer room universal, The average time constant of all real computer rooms involved in the control is selected as:

[0156]

[0157] Using the virtual standard computer room This set of signals enables efficient and unified control of the cooling load of massive communication base station computer rooms, and ensures that the cooling constraints of each computer room are not broken.

[0158] For any computer room i, its heat storage state Thermal storage status of the virtual standard computer room The error between them can be expressed as:

[0159]

[0160] In order to synchronize the heat storage status of all real computer rooms with the virtual standard computer room, Let both sides of formula (20) be 0, then we can get:

[0161]

[0162] Formula (21) gives the equation of any computer room under a known control signal According to this strategy, the cooling state of each actual computer room and the virtual standard computer room is always synchronized. It should be emphasized that the synchronization of the cooling state does not mean that the temperature of each computer room is always consistent. Because the cooling state defined in this article is related to the reference temperature selected by each computer room, such as Figure 2 As shown, the reference temperature of the computer room is related to its own set temperature range, and the temperature range of different computer rooms needs to be determined according to factors such as the operating requirements of their working equipment and economic indicators.

[0163] The control strategy (21) is essentially a deadbeat control. The cooling state of each base station room is Adjusted to the normalized cold storage state within a single time step And keep synchronization in the following time. It is worth noting that the actual cooling power control signal π of each base station room i (t) can be controlled from the normalized control signal according to its current heat storage state and inherent thermal parameters Demodulated out.

[0164] Virtual power plant aggregation control method based on normalized control signals

[0165] The resource aggregation of virtual power plants is essentially to solve the overall response range of all participating control resources, that is, the feasible domain of control instructions. The actual control signal π demodulated from i (t) feasibility, and Π i (t) must be able to meet the constraints of each computer room, that is, formulas (13)-(16), so, The feasible region under the constraint of computer room i is:

[0166]

[0167] Normalized control signal It is necessary to be compatible with the constraints of all base station rooms involved in the control, so its actual feasible domain is:

[0168]

[0169] Due to the diversity of buildings, the parameter τ i may be significantly different. This heterogeneous property inevitably limits the scope of the feasible region and leads to conservatism. In order to obtain a normalized dimensionless thermal energy model A less conservative feasible region of , , is used to partition the buildings and tailor the required response to the capabilities of the building subgroups. Each cluster of buildings is extracted and controlled by an associated normalized dimensionless thermal model. The thermal characteristics of the buildings are determined by the parameter τ i Characterization can be partitioned using the k-means clustering algorithm based on the distance of these parameters.

[0170] Assume that there are C base station room clusters after clustering. Represents a collection of clustering indexes. use represents the set of all computer rooms in the cluster. Then, according to formulas (4)-(9), the cooling power of computer room i in cluster c can be obtained by the normalized control signal The calculation is as follows:

[0171]

[0172] in:

[0173]

[0174] In order to reduce the scale of the optimization problem, an approximation of the feasible region is proposed to reduce the computational burden of the high-dimensional constrained optimization problem. The outer approximation usually overestimates the flexibility of the aggregate, while the inner approximation cannot capture all the aggregate flexibility. Since the main disadvantage of the outer approximation is that not all elements of the collection can be decomposed between individual flexibilities, this patent adopts a constraint tightening method based on the inner approximation, such as Figure 3 shown.

[0175] Due to the geometric properties, the exact volume calculation of the polyhedron is challenging, so the volume of the inscribed ellipsoid is used to represent the size of the polyhedron. For a given fixed-dimensional polyhedron, the volume of its inscribed ellipsoid is maximized to approximate the feasible area. As more buildings are clustered into a subgroup, the number of sides forming the feasible area of ​​the original polyhedron (the outer polygon surrounded by the effective constraint boundary) may increase dramatically, which will bring more constraints to the energy optimization problem of the distribution system operator (DSO). Then, the ellipsoid robust constraint in the figure is used to replace the complex polyhedron area. However, since the ellipsoid constraint is not linear, a fixed-dimensional inscribed polyhedron (blue) is used to further approximate the ellipsoid area. The higher the dimension of the polyhedron, the less conservative the approximation of the ellipsoid, but this will lead to higher computational complexity.

[0176] At this point, the temperature control power of all buildings can be adjusted with a small number of standardized signals. Individual thermal comfort needs can be well met, and the dynamic equations of the standardized dimensionless thermal energy model can be integrated into the operational optimization problem of the DSO.

[0177] Efficient load control: Through a control method based on thermal storage status, the cooling load of each computer room can be precisely controlled, reducing energy waste and optimizing the load response of the power system.

[0178] Unified control strategy: The introduction of virtual standard rooms and clustering zoning methods ensures unified and precise cooling load control in large-scale communication base station rooms, avoiding the individual differences in traditional control.

[0179] Flexible adaptability: This method can be personalized according to the thermal characteristics of different computer rooms, and can achieve good control effects in different types of buildings and air-conditioning equipment.

[0180] Reducing the burden on the power system: Through efficient control strategies, the present invention can reduce the peak load of the power system while meeting the cooling needs of each computer room and improve the utilization efficiency of power resources.

[0181] In yet another embodiment of the present invention, a collaborative aggregation control system based on multi-modal composite energy storage in buildings is provided, which can be used to implement the above-mentioned collaborative aggregation control method based on multi-modal composite energy storage in buildings. Specifically, the system includes:

[0182] The data acquisition module is used to collect the internal and outdoor temperatures of the computer room at a certain moment and establish an equivalent thermal parameter model based on temperature changes;

[0183] Model conversion module, used to introduce energy reference zero point and convert the equivalent thermal parameter model based on temperature change into a dimensionless energy storage state model;

[0184] The strategy output module is used to express the energy changes inside the virtual standard computer room based on the dimensionless energy storage state model. Based on the energy changes inside the virtual standard computer room, it outputs a standardized control strategy under the condition that the heat storage states of the real computer room and the virtual standard computer room are synchronized;

[0185] The grouping control module is used to group computer rooms through clustering algorithms to form computer room clusters with similar thermal characteristics. Each computer room cluster is uniformly controlled within the cluster through a standardized control strategy.

[0186] The module division in the embodiments of the present invention is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in various embodiments of the present invention may be integrated into a single processor, exist physically as separate modules, or two or more modules may be integrated into a single module. The integrated modules may be implemented in either hardware or software functional modules.

[0187] In another embodiment of the present invention, a computer device is provided, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of the collaborative aggregation control method based on multi-form composite energy storage of building buildings.

[0188] In another embodiment of the present invention, the present invention further provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It is understandable that the computer-readable storage medium here can include both built-in storage media in the computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides a storage space that stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space. These instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the collaborative aggregation control method based on multi-morphic composite energy storage of building buildings in the above embodiment.

[0189] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0190] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0191] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0192] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0193] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A collaborative aggregation control method based on multi-form composite energy storage in buildings, characterized in that: include: Collect the internal and outdoor temperatures of the equipment room at a certain moment and establish an equivalent thermal parameter model based on temperature changes; The energy reference zero point is introduced to transform the equivalent thermal parameter model based on temperature change into a dimensionless energy storage state model; The dimensionless energy storage state model is used to express the energy changes inside the virtual standard computer room. Based on the energy changes inside the virtual standard computer room, a standardized control strategy is output under the condition that the heat storage states of the real computer room and the virtual standard computer room are kept synchronized. The computer rooms are grouped by clustering algorithms to form computer room clusters with similar thermal characteristics. Each computer room cluster is uniformly controlled within the cluster through a standardized control strategy.

2. The collaborative aggregation control method based on multi-form composite energy storage of buildings according to claim 1 is characterized in that: The collecting of the internal temperature and the outdoor temperature of the equipment room at a certain moment and establishing an equivalent thermal parameter model based on temperature changes include: The thermal dynamics of the computer room is expressed by a first-order differential equation regarding the indoor temperature: Where: T i (t) and are the internal temperature and outdoor temperature of the computer room at time t; C i is the equivalent heat capacity of the room shell, reflecting the heat storage capacity of the room; K i is the equivalent thermal conductivity of the computer room shell, reflecting the heat conduction capacity between the computer room and the outside world; is the heat gain of the computer room at time t.

3. The collaborative aggregation control method based on multi-form composite energy storage of buildings according to claim 2 is characterized in that: The temperature range allowed in the computer room at time t is set as: Where: T i (t) and They are the upper and lower limits of the temperature range allowed for normal operation of the equipment room; The heat gain of the computer room at time t in formula (1) Controllable heat gain and passive heat gain Composition, expressed as: Where: Controllable heat gain is the air conditioning cooling load, passive heat gain Dissipate heat from solar radiation and equipment inside the computer room; The relationship between the cooling capacity of the air conditioner and the rated power of the air conditioner is expressed as: Where, is the rated power of the air conditioner; CoP i (t) represents the energy efficiency ratio of different types of air conditioners; Parameters indicating the operating status of the air conditioner.

4. The collaborative aggregation control method based on multi-form composite energy storage of buildings according to claim 2 is characterized in that: The introduction of the energy reference zero point converts the equivalent thermal parameter model based on temperature change into a dimensionless energy storage state model, including: definition is the temperature reference zero point of house i, then is the energy reference zero point of house i; for any temperature T i (t), the relative energy of house i at time t is expressed as: Substituting formula (5) into formula (1), we get the following equivalent energy storage model: Where, is the net thermal power input to the house, and its specific expression is as follows: in, is the cooling power of the air conditioner; The heat power passively obtained in the computer room; is the equivalent heat exchange caused by the temperature difference between the inside and outside of the computer room; The heat storage state of the computer room is defined as follows: in, is the heat storage state of the computer room at time t, and is defined as The upper limit of the temperature reference for the equipment room is defined. is the equivalent heat storage capacity of the computer room.

5. The collaborative aggregation control method based on multi-form composite energy storage of buildings according to claim 4 is characterized in that: Define the house heat power control signal π i (t) Substituting formulas (8) and (9) into formula (6), the equivalent thermal parameter model of the house is transformed into the following form: Where, τ i =C i / K i , is the equivalent time constant of thermal energy change in the house; Formula (10) is differentiated and the sampling time is expressed as Δt. Then the dimensionless house equivalent thermal parameter differential equation expressed by formula (10) is expressed as the following differential form: in: The energy storage state of the house at time t is obtained from formulas (2), (5), and (8): The value range of is: For different types of air conditioners, the thermal power control signal π i The value range of (t) can be determined according to formulas (3), (4), and (9) as follows: in:

6. The collaborative aggregation control method based on multi-form composite energy storage of buildings according to claim 5 is characterized in that: The dimensionless energy storage state model is used to express the energy changes inside the virtual standard computer room. Based on the energy changes inside the virtual standard computer room, a standardized control strategy is output under the condition that the heat storage states of the real computer room and the virtual standard computer room are synchronized, including: According to the dimensionless energy storage state model, the energy change inside the virtual standard computer room is expressed by the following formula: in: Where, and Respectively represent the heat storage state and heat power control signal of the virtual standard computer room; is its time constant; Using the virtual standard computer room This set of signals enables efficient and unified control of the cooling load of massive communication base station rooms; For any computer room i, its heat storage state Thermal storage status of the virtual standard computer room The error between them is expressed as: Under the condition that the heat storage state of the real computer room and the virtual standard computer room are kept synchronous, that is, Let both sides of formula (20) be 0, and we get:

7. The collaborative aggregation control method based on multi-form composite energy storage of buildings according to claim 6 is characterized in that: The clustering algorithm is used to group computer rooms to form computer room clusters with similar thermal characteristics. Each computer room cluster is uniformly controlled within the cluster through a standardized control strategy, including: The feasible region under the constraint of computer room i is: Normalized control signal Compatible with the constraints of all base station rooms involved in the control, the actual feasible domain is: The thermal characteristics of a building are determined by the parameter τ i Characterization, based on the distance of these parameters, the k-means clustering algorithm is used for partitioning. After clustering, there are C base station room clusters. Represents a collection of clustering indexes; for a cluster use represents the set of all computer rooms in the cluster; then, according to formulas (4)-(9), the cooling power of computer room i in cluster c is determined by the normalized control signal The calculation is as follows: in:

8. A collaborative aggregation control system based on multi-form composite energy storage for buildings, characterized by: include: The data acquisition module is used to collect the internal and outdoor temperatures of the computer room at a certain moment and establish an equivalent thermal parameter model based on temperature changes; Model conversion module, used to introduce energy reference zero point and convert the equivalent thermal parameter model based on temperature change into a dimensionless energy storage state model; The strategy output module is used to express the energy changes inside the virtual standard computer room based on the dimensionless energy storage state model. Based on the energy changes inside the virtual standard computer room, it outputs a standardized control strategy under the condition that the heat storage states of the real computer room and the virtual standard computer room are synchronized; The grouping control module is used to group computer rooms through clustering algorithms to form computer room clusters with similar thermal characteristics. Each computer room cluster is uniformly controlled within the cluster through a standardized control strategy.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the collaborative aggregation control method based on multi-form composite energy storage of building buildings as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the collaborative aggregation control method based on multi-form composite energy storage of building structures as described in any one of claims 1 to 7 are implemented.

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