Automatic control method and system for energy conservation of air conditioner of transformer substation building

Abstract

The invention relates to the technical field of substation control, in particular to a substation building air conditioner energy-saving automatic control method and system. The control method comprises the following steps: acquiring temperature data of a temperature sensor matrix and real-time power data of each device, and calculating thermal load intensity of each grid in the matrix according to the temperature data and the real-time power data; the coverage radius of each air outlet is dynamically calculated and verified, and the effective coverage radius of each air outlet is obtained; establishing an air outlet optimization objective function; solving the air outlet optimization objective function based on an improved genetic algorithm to obtain an enabled air outlet; and dynamically adjusting the air outlet volume of the air outlet according to the thermal load intensity. The air flow sent by the air conditioner can be uniformly diffused in the space in the station, a supercooling environment formed by excessive air flow in part of areas is avoided, and meanwhile the phenomena of heat accumulation and overhigh temperature caused by the fact that the air flow cannot effectively reach a key area close to heating equipment are avoided.

Description

Technical Field

[0001] This invention relates to the field of substation control technology, and in particular to an automatic control method and system for energy saving of substation building air conditioning. Background Technology

[0002] Existing substation buildings use air conditioning to regulate temperature and maintain a suitable environment, reducing energy consumption during equipment operation. However, existing substations use a fixed number of air outlets and a constant airflow rate, meaning all outlets in the substation simultaneously supply air at a constant volume. For example, if a substation has 10 air outlets, all 10 outlets supply air at a constant volume. This approach reveals several drawbacks in actual operation: First, the airflow from the air conditioner is difficult to distribute evenly within the substation, resulting in excessive airflow in some areas, creating an overly cold environment, while critical areas near heat-generating equipment experience heat accumulation and excessively high temperatures because the airflow cannot effectively reach them. Second, to meet the overall temperature control requirements, traditional air conditioning systems often continuously supply air at a large, constant volume, even during periods when some equipment is operating at low load and generating less heat. This excessive airflow not only fails to accurately match the actual heat dissipation needs but also wastes a significant amount of electricity. In addition, when the air conditioner blows cold air directly from a fixed vent, the high-speed cold airflow blows directly onto the surface of electrical equipment, causing a sudden drop in the local temperature of the equipment. Under conditions of large temperature difference, condensation is very likely to occur on the surface of the equipment. The water droplets formed by the condensation may seep into the inside of the equipment, causing faults such as short circuits. At the same time, the drastic temperature change will also generate mechanical stress in the equipment materials, which will accelerate fatigue damage to the equipment components and shorten the service life of the equipment over a long period of time. Summary of the Invention

[0003] The main objective of this invention is to provide an automatic control method and system for energy saving of air conditioning in substation buildings, which aims to solve the problem that the airflow delivered by the air conditioner is difficult to diffuse evenly in the space within the substation.

[0004] To achieve the above objectives, this invention proposes an automatic energy-saving control method for air conditioning in substation buildings, applied to substations. The substation is equipped with several independent air conditioning outlets, and a temperature sensor matrix is ​​deployed within the substation. The method includes:

[0005] Step S1: Obtain the temperature data of the temperature sensor matrix and the rated power data of each device, and calculate the heat load intensity of each grid in the matrix based on the temperature data and rated power data;

[0006] Step S2: Dynamically calculate and verify the coverage radius of each air outlet to obtain the effective coverage radius of each air outlet;

[0007] Step S3: Establish an optimization objective function for the air outlets. The optimization objective function aims to minimize the number of air outlets and maximize the coverage uniformity. The constraints are that all areas with thermal load intensity greater than a preset value must be covered and the distance between two activated air outlets must be greater than the sum of their respective effective coverage radii.

[0008] Step S4: Solve the objective function of the air outlet optimization based on the improved genetic algorithm to obtain the activated air outlet;

[0009] Step S5: Dynamically adjust the air volume of the activated air outlet according to the equipment operating status.

[0010] As described above in the automatic energy-saving control method for air conditioning in substation buildings, step S2 includes:

[0011] Step S21: Calculate the coverage radius of each air outlet according to the revised coverage radius formula;

[0012] Step S22: Perform multi-wind superposition effect compensation. When the coverage areas of multiple air outlets overlap, the coverage radius of the air outlets corresponding to the overlapping coverage areas is reduced to obtain the effective coverage radius. If the air outlets do not have overlapping coverage areas, the coverage radius of the air outlet is the effective coverage radius.

[0013] As described above, in the automatic control method for energy saving of air conditioning in substation buildings, if the temperature in a certain area exceeds the limit for t minutes continuously or if the equipment location changes, step S4 is re-triggered.

[0014] As described above in the automatic energy-saving control method for air conditioning in substation buildings, step S5 includes:

[0015] Step S51: Obtain the heat load level of the area where the grid is located, and obtain the corresponding area weight coefficient;

[0016] Step S52: Correct the heat load intensity of the grid based on the real-time power data of the equipment to obtain the corrected heat load intensity of each grid;

[0017] Step S53: Calculate the theoretical air volume requirement for a single grid based on the area weight coefficient corresponding to the grid and the corrected heat load intensity;

[0018] Step S54: Establish a multi-objective optimization function for air volume. The multi-objective optimization function for air volume aims to minimize total energy consumption and minimize temperature deviation. The constraints are: the air volume of a single activated air outlet is not greater than its own maximum air volume; the air volume range of the damper of a single activated air outlet is between the minimum air volume and the maximum air volume; the supply air temperature of the activated air outlet is higher than the dew point temperature; and the grid cell temperature has a linear relationship with the supply air volume, supply air temperature and the heat load intensity after grid correction.

[0019] Step S55: Use mixed integer linear programming to solve the multi-objective optimization function of air volume to obtain the air volume of each activated air outlet.

[0020] The automatic energy-saving control method for substation building air conditioning, as described above, also includes:

[0021] Step S6: Based on the air volume of each activated air outlet as the target air volume setpoint for the activated air outlet, a fuzzy adaptive PID algorithm and feedforward-feedback composite control are used for closed-loop control and anti-interference of the air valve.

[0022] The second aspect of this invention discloses an automatic energy-saving control system for substation building air conditioning, applied to the automatic energy-saving control method for substation building air conditioning described in the first aspect of this invention, the system comprising:

[0023] The acquisition module is used to acquire temperature data from the temperature sensor matrix and rated power data of each device, and calculate the heat load intensity of each grid in the matrix based on the temperature data and rated power data.

[0024] The coverage radius calculation module is used to dynamically calculate and verify the coverage radius of each air outlet to obtain the effective coverage radius of each air outlet.

[0025] The air outlet optimization objective function establishment module is used to establish the air outlet optimization objective function. The optimization objective function aims to minimize the number of air outlets and maximize the coverage uniformity. The constraints are that all areas with thermal load intensity greater than a preset value must be covered and the distance between two activated air outlets is greater than the sum of their respective effective coverage radii.

[0026] The air outlet solution module is used to solve the air outlet optimization objective function based on an improved genetic algorithm to obtain the activated air outlet.

[0027] The air volume calculation module is used to dynamically adjust the air volume of the activated air outlet according to the heat load intensity.

[0028] As described above in the substation building air conditioning energy-saving automatic control system, the coverage radius calculation module includes:

[0029] The correction unit is used to calculate the coverage radius of each air outlet according to the corrected coverage radius formula;

[0030] The compensation unit is used to compensate for the superposition effect of multiple air outlets. When the coverage areas of multiple air outlets overlap, the coverage radius of the air outlets corresponding to the overlapping coverage areas is reduced to obtain the effective coverage radius. If the air outlets do not have overlapping coverage areas, the coverage radius of the air outlet is the effective coverage radius.

[0031] The substation building air conditioning energy-saving automatic control system described above includes a dynamic re-optimization module, which is used to trigger the air outlet solution module to re-solve the air outlet optimization objective function when the temperature in a certain area exceeds the limit for t minutes for a continuous period of time or when the equipment position changes.

[0032] As described above in the substation building air conditioning energy-saving automatic control system, the air volume calculation module includes:

[0033] The acquisition unit is used to obtain the heat load level of the grid area and obtain the corresponding area weight coefficient.

[0034] The correction unit is used to correct the heat load intensity of the grid based on the real-time power data of the equipment operation, so as to obtain the corrected heat load intensity of each grid.

[0035] The theoretical air volume calculation unit is used to calculate the theoretical air volume requirement of a single grid based on the area weight coefficient corresponding to the grid and the corrected heat load intensity.

[0036] The air volume multi-objective optimization function establishment unit is used to establish the air volume multi-objective optimization function. The air volume multi-objective optimization function aims to minimize the total energy consumption and minimize the temperature deviation. The constraints are: the air volume of a single activated air outlet is not greater than its own maximum air volume; the air volume range of the damper of a single activated air outlet is between the minimum air volume and the maximum air volume; the supply air temperature of the activated air outlet is higher than the dew point temperature; and the grid cell temperature is linearly related to the supply air volume, supply air temperature and the grid-corrected heat load intensity.

[0037] The air volume calculation unit is used to solve the multi-objective optimization function of air volume using mixed integer linear programming to obtain the air volume of each activated air outlet.

[0038] The substation building air conditioning energy-saving automatic control system described above also includes: a damper control module, which uses the air volume of each activated air outlet as the target air volume setpoint for the activated air outlet, and adopts fuzzy adaptive PID algorithm and feedforward-feedback composite control for closed-loop control and anti-interference of the damper.

[0039] The technical solution provided by this invention may include the following beneficial effects:

[0040] In the automatic energy-saving control method for substation building air conditioning provided by this invention, the space is divided into several grids based on a temperature sensor matrix, and the heat load intensity of each grid and the effective coverage radius of each air outlet are calculated. An optimization objective function for the air outlets is constructed based on the heat load intensity of each grid and the effective coverage radius of each air outlet. An improved genetic algorithm is used to solve the optimization objective function to obtain the air outlets to be activated. Finally, the airflow of the activated air outlets is adjusted according to the heat load intensity. This allows for adjustment of the air outlet position and airflow based on indoor conditions. This facilitates the uniform diffusion of airflow from the air conditioner within the station space, avoiding excessive airflow in some areas that could create an overly cold environment. It also prevents heat accumulation and excessively high temperatures in critical areas near heat-generating equipment due to ineffective airflow. Furthermore, when some equipment operates at low loads and generates less heat, the airflow of the air outlets can be adjusted to precisely match the actual heat dissipation needs, avoiding significant energy waste and achieving energy-saving operation and maintenance management. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0042] Figure 1 This is a flowchart illustrating the automatic energy-saving control method for substation building air conditioning according to the present invention.

[0043] Figure 2 This is a schematic diagram illustrating the process of dynamically adjusting the air volume of the activated air outlet according to the heat load intensity of the present invention.

[0044] Figure 3 This is a schematic diagram of the automatic energy-saving control system for substation building air conditioning of the present invention. Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0046] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0047] In this invention, unless otherwise explicitly specified and limited, the terms "connection," "fixed," etc., should be interpreted broadly. For example, "fixed" can mean a fixed connection, a detachable connection, or an integral part; it can mean a mechanical connection or an electrical connection; it can mean a direct connection or an indirect connection through an intermediate medium; it can mean the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0048] Furthermore, in this invention, descriptions involving "first," "second," etc., are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the word "and / or" throughout the text means including three parallel solutions; taking "A and / or B" as an example, it includes solution A, solution B, or a solution that simultaneously satisfies A and B. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0049] The following is combined Figures 1 to 2 This invention describes an automatic energy-saving control method for air conditioning in a substation, applicable to a substation with several independent air conditioning outlets and a temperature sensor matrix deployed within the substation. The method includes:

[0050] Step S1: Obtain the temperature data of the temperature sensor matrix and the rated power data of each device, and calculate the heat load intensity of each grid in the matrix based on the temperature data and rated power data;

[0051] Specifically, in one embodiment, temperature sensors are arranged in a 1m×1m grid within the substation, with the grid density increased to 0.5m×0.5m in key areas such as the main transformer room and GIS room. This achieves the deployment of a temperature sensor matrix within the substation. The temperature sensors can be high-temperature resistant digital temperature sensors (-40℃~120℃) with an accuracy of ±0.5℃, supporting RS-485 or LoRa wireless transmission. The system can acquire rated power data and real-time power data through an equipment operation status monitoring system (such as SCADA) to establish a heat load-temperature mapping table, thus achieving equipment heat source correlation.

[0052] Step S2: Dynamically calculate and verify the coverage radius of each air outlet to obtain the effective coverage radius of each air outlet;

[0053] Step S3: Establish an optimization objective function for the air outlets. The optimization objective function aims to minimize the number of air outlets and maximize the coverage uniformity. The constraints are that all areas with thermal load intensity greater than a preset value must be covered and the distance between two activated air outlets must be greater than the sum of their respective effective coverage radii.

[0054] Step S4: Solve the objective function of the air outlet optimization based on the improved genetic algorithm to obtain the activated air outlet;

[0055] Step S5: Dynamically adjust the air volume of the activated air outlet according to the heat load intensity.

[0056] In the automatic energy-saving control method for substation building air conditioning provided by this invention, the space is divided into several grids based on a temperature sensor matrix, and the heat load intensity of each grid and the effective coverage radius of each air outlet are calculated. An optimization objective function for the air outlets is constructed based on the heat load intensity of each grid and the effective coverage radius of each air outlet. This objective function is then solved using an improved genetic algorithm to determine the air outlets to be activated. Finally, the airflow of the activated air outlets is adjusted according to the heat load intensity. This allows for adjustment of the air outlet position and airflow based on indoor conditions. The optimization objective function for the air outlets aims to maximize coverage uniformity, which facilitates the uniform diffusion of airflow from the air conditioner within the station space. This avoids excessive airflow in some areas, resulting in an overly cold environment, and also prevents heat accumulation and excessively high temperatures in critical areas near heat-generating equipment due to ineffective airflow. Furthermore, when some equipment operates at low loads and generates less heat, the airflow of the air outlets can be adjusted to precisely match the actual heat dissipation needs, avoiding significant energy waste and achieving energy-saving operation and maintenance management.

[0057] For example, in step S1, the formula for calculating the heat load intensity of each grid is:

[0058]

[0059] Among them, P i，j Q represents the heat load intensity of grid (i, j). 设备，k d is the rated power of the k-th device; i，j，k Let be the Euclidean distance from grid (i, j) to the k-th device; α and β are the weighting coefficients, respectively; Δ is to prevent the denominator from being a minimum zero; and T is the correction term for the ambient temperature on the heat load.

[0060] As an optional embodiment, step S2 includes:

[0061] Step S21: Calculate the coverage radius of each air outlet according to the modified coverage radius formula. The modified coverage radius formula is derived from the physical model of the effective coverage radius of a single air outlet, simplified based on the unsteady-state thermal diffusion equation and engineering experience. The physical model of the effective coverage radius of a single air outlet, based on the unsteady-state thermal diffusion equation, describes the diffusion law of a free jet or isothermal free jet under ideal conditions. Real-world air conditioning scenarios are extremely complex and differ significantly from the ideal physical model. The modification makes the calculated coverage radius closer to engineering reality. For example, the modified coverage radius formula is:

[0062]

[0063] Where R is the coverage radius; η is the vent correction factor (ranging from 0.7 to 0.9, related to duct resistance); k is the correction factor calibrated through CFD simulation and actual measurement; Q is the vent cooling capacity; ΔT is the supply air temperature difference, i.e., the difference between the set temperature and the return air temperature; ρ is the air density, which is taken as 1.2 kg / m³ under standard operating conditions. 3 C ρ The specific heat capacity of air at constant pressure;

[0064] Step S22: Perform multi-wind superposition effect compensation. When the coverage areas of multiple air outlets overlap, the coverage radius of the air outlets corresponding to the overlapping coverage areas is reduced to obtain the effective coverage radius. If the air outlets do not have overlapping coverage areas, the coverage radius of the air outlet is the effective coverage radius.

[0065] Specifically, the attenuation formula is:

[0066] R'=R·e -λN ;

[0067] Where R' is the effective coverage radius after attenuation, N is the number of overlapping air vents, and λ is the attenuation coefficient.

[0068] The revised coverage radius formula calculates the case of a single air outlet. However, in the station space, there are multiple air outlets that affect each other. This embodiment compensates for the superposition effect of multiple airflows by attenuating the air outlets in overlapping coverage areas, making the effective coverage radius of the air outlets more consistent with the actual situation and improving the accuracy of control.

[0069] For example, in step S3, the objective function for optimizing the air outlet is:

[0070] The expression for the minimum number of air vents is: x m ∈{0,1}; where x m This is a binary variable (0 or 1) indicating whether the air outlet at the m-th candidate location is enabled; for example, x m =0 indicates that the air outlet at the m-th candidate location is closed; x m =1 indicates that the air outlet at the m-th candidate position is open;

[0071] The expression for maximizing coverage uniformity is: Among them, T i，j The temperature of grid cell (i,j) represents the actual temperature of that grid cell under the influence of the air outlet layout; T set To set the temperature;

[0072] Constraint (a): All areas with thermal load intensities greater than a preset value must be covered. The expression for constraint (a) is: P i，j >P threshold P i,j P represents the heat load intensity of the grid (i,j); threshold A preset threshold for heat load intensity; a heat load intensity of a grid cell exceeding the preset threshold is considered a "high load region"; a m，i，j The coverage coefficient, defined as a binary variable (0 or 1), indicates whether the m-th candidate location's air outlet can cover the grid (i,j) if it is enabled; for example, a m,i,j =1 indicates that the air outlet at the m-th candidate location can cover the grid (i,j) when it is enabled; a m,i,j =0 indicates that the air outlet at the m-th candidate position cannot cover the grid (i,j) when it is enabled;

[0073] Constraint (b): The distance between two active air outlets is greater than the sum of their respective effective coverage radii. The expression for constraint (b) is: D a，b ≥R' a +R' b

[0074] D a,bR is the distance between the activated air outlet a and the activated air outlet b. a R' is the effective coverage radius of the activated air outlet a. b The effective coverage radius of the activated air outlet b.

[0075] Furthermore, in step S4, the improved genetic algorithm uses binary encoding, the gene length is the number of candidate air outlets, and a gene bit of 1 indicates that the air outlet is enabled.

[0076] The fitness function is:

[0077]

[0078] Where F is the fitness, and w1, w2, and w3 are the weights; by default, w1 is 0.5, w2 is 0.3, and w3 is 0.2; the uniformity index refers to the degree of uniformity of temperature / velocity distribution in the target area (working area). The smaller the index, the better the uniformity; the coverage rate is the percentage (%) of the actual temperature in the target area that meets the grid requirements within the allowable deviation range of the set temperature.

[0079]

[0080]

[0081] Where ΔT is the allowable temperature deviation (e.g., ±0.5℃) and N is the mesh element.

[0082] Using a single-point crossover method, the initial adaptive mutation rate was 0.1, which decreased to 0.02 after iteration;

[0083] The termination condition is that the fitness change is less than a threshold for N consecutive generations or the maximum number of iterations is reached. N is a non-zero positive integer. In an optional embodiment, the termination condition is that the fitness change is less than 0.1 for 10 consecutive generations or the maximum number of iterations, 200, is reached.

[0084] Alternatively, step S4 may be retried if the temperature in a certain area exceeds the limit for t minutes continuously or if the location of the equipment changes.

[0085] In this embodiment, a re-optimization mechanism is employed. If the temperature in a certain area exceeds the limit for t consecutive minutes, or if the equipment location changes, step S4 is re-triggered. This allows for adjustment of the air outlet position based on temperature or equipment location changes, achieving precise temperature control and improving the substation's operational reliability. For example, the upper temperature limit is 2°C higher than the set temperature; the lower temperature limit is 3°C lower than the set temperature. If the temperature in a certain area exceeds the upper or lower temperature limit for 5 consecutive minutes, step S4 is re-triggered. More preferably, a local optimization strategy can be used, recalculating only the affected area to reduce the computational load.

[0086] As an optional embodiment, step S5 includes:

[0087] Step S51: Obtain the heat load level of the area where the grid is located and obtain the corresponding area weight coefficient; In an optional embodiment of the invention, the substation is divided into key areas (such as main transformer room, GIS room), secondary key areas (such as switch cabinet room), and ordinary areas (corridor, control room) according to the power facilities. The weight coefficient of the key area is 1.5, the weight coefficient of the secondary key area is 1.2, and the weight coefficient of the ordinary area is 1.0.

[0088] Step S52: Correct the heat load intensity of the grid based on the actual power data of the equipment operation to obtain the corrected heat load intensity of each grid; the correction formula is:

[0089]

[0090] Among them, P' i，j P represents the corrected heat load intensity for grid (i, j). i，j Let I be the heat load intensity of the grid (i,j). actual I represents the actual current of the equipment. rated γ is the rated current of the equipment; γ is the heat load correction factor.

[0091] Step S53: Calculate the theoretical air volume requirement for a single grid based on the area weighting coefficients corresponding to the grid and the corrected heat load intensity; the formula for calculating the theoretical air volume requirement for a single grid is:

[0092]

[0093] In the formula: w k ζ represents the regional weight; ζ is the airflow attenuation coefficient (default 0.1 / m), d i，j Distance from the grid to the air vent; T set To set the temperature, T in Return air temperature;

[0094] Linearization of the airflow-temperature relationship refers to how the temperature of a single grid point is linearly affected by the airflow from multiple air outlets:

[0095]

[0096] In the formula: α k,i,j To enable the airflow-temperature transfer coefficient (related to distance and airflow attenuation) of outlet k to grid (i, j); β i,j This is the static heat load baseline (including heat generated by equipment and transferred to the environment, which is not dynamically corrected).

[0097] Step S54: Establish a multi-objective optimization function for air volume. The multi-objective optimization function for air volume aims to minimize total energy consumption and minimize temperature deviation. The functions include: the air volume of a single activated air outlet is not greater than its own maximum air volume; the air volume range of the damper of a single activated air outlet is between the minimum air volume and the maximum air volume; and the supply air temperature of the activated air outlet is higher than the dew point temperature.

[0098] Specifically, the multi-objective optimization function for air volume is:

[0099] Minimize total energy consumption: Among them, Q K ΔP represents the airflow of the Kth activated air outlet. K The power consumption per unit airflow for the Kth activated air outlet valve;

[0100] Minimize temperature deviation: If T i,j The closer to the set temperature T set The more uniform the system, the smaller the objective function value;

[0101] Constraints: Single air volume limit ∑Q K ≤Q max Airflow range Q for a single air valve min ≤Q k ≤Q max Anti-condensation constraint on air outlet supply temperature T out,k ≥T dew +2℃, T dew For example, the supply air temperature at the dew point is at least 2°C higher than the dew point temperature; the grid cell temperature T i,j With air volume Q K Supply air temperature T out The heat load intensity P' after grid (i, j) correction i,j A linear relationship exists. γ is a coefficient, and c is a constant; it refers to how the temperature in the entire system is affected by the combined linear influence of air volume, supply air temperature, and heat load, quantifying the coupled influence of dynamic heat load and air volume, and is used to respond to sudden changes in equipment power and avoid control failure.

[0102] Step S55: Use mixed integer linear programming to solve the multi-objective optimization function of air volume to obtain the air volume of each activated air outlet.

[0103] Specifically, the mixed integer linear programming (MILP) solution uses the air volume of the vent and the opening degree of the vent damper as the decision capacity; linearization process: the nonlinear heat balance equation is discretized into piecewise linear functions, and the Gurobi or CPLEX solver is called to achieve real-time optimization (computation delay < 5 seconds).

[0104] In this embodiment, the air volume is designed to minimize total energy consumption. This embodiment also aims to minimize temperature deviation to avoid the impact of drastic temperature changes. Furthermore, by constraining the supply air temperature, the supply air temperature at the outlet is kept below the dew point temperature to prevent condensation on the equipment surface. This prevents water droplets from seeping into the equipment and causing short circuits or other malfunctions.

[0105] As an optional embodiment, the control method further includes:

[0106] Step S6: Based on the air volume of each activated air outlet as the target air volume setpoint for the activated air outlet, a fuzzy adaptive PID algorithm and feedforward-feedback composite control are used for closed-loop control and anti-interference of the air valve.

[0107] A closed-loop control system for the air valve is constructed to achieve precise dynamic airflow adjustment and disturbance suppression.

[0108] The fuzzy adaptive PID algorithm includes a fuzzy rule base design:

[0109] Input variables: temperature deviation e(t), rate of change of deviation Output variable: PID parameter correction ΔP K ΔP i ΔP d Example rule: If e(t) is "positive" and If the result is "negative neutral", then ΔPd = +0.2, ΔKi = -0.1; Control law update:

[0110]

[0111] u(t) is the final output signal of the controller, Kp is the initial proportional parameter, ΔPk is the dynamic adjustment value of the fuzzy rule, Ki is the initial integral parameter, ΔPi is the dynamic adjustment value of the fuzzy rule, Kd is the initial derivative parameter, and ΔPd is the dynamic adjustment value of the fuzzy rule.

[0112] The feedforward-feedback composite control includes feedforward compensation and feedback suppression of oscillations.

[0113] Feedforward compensation: Adjust the air volume in advance based on sudden power changes in the equipment (such as circuit breaker tripping). The adjustment formula is as follows:

[0114]

[0115] Among them, Q f The adjusted air volume, ΔP step denoted as , where is the step change in heat load; μ is the feedforward gain, ranging from 0.8 to 1.2.

[0116] Feedback to suppress oscillation: Introduce PID control with dead zone, pause integral control when |e(t)| < 0.5℃| to prevent overshoot.

[0117] like Figure 3 As shown, the second aspect of the present invention also discloses an automatic energy-saving control system for substation building air conditioning, applied to the automatic energy-saving control method for substation building air conditioning of the first aspect of the present invention, the system comprising:

[0118] The acquisition module 101 is used to acquire temperature data of the temperature sensor matrix and rated power data of each device, and calculate the heat load intensity of each grid in the matrix based on the temperature data and rated power data.

[0119] Specifically, in one embodiment, temperature sensors are arranged in a 1m×1m grid within the substation, with the grid density increased to 0.5m×0.5m in key areas such as the main transformer room and GIS room. This achieves the deployment of a temperature sensor matrix within the substation. The temperature sensors can be high-temperature resistant digital temperature sensors (-40℃~120℃) with an accuracy of ±0.5℃, supporting RS-485 or LoRa wireless transmission. The system can acquire rated power data and real-time power data through an equipment operation status monitoring system (such as SCADA) to establish a heat load-temperature mapping table, thus achieving equipment heat source correlation.

[0120] The coverage radius calculation module 102 is used to dynamically calculate and verify the coverage radius of each air outlet to obtain the effective coverage radius of each air outlet.

[0121] The air outlet optimization objective function establishment module 103 is used to establish the air outlet optimization objective function. The optimization objective function aims to minimize the number of air outlets and maximize the coverage uniformity, with constraints such as all areas with thermal load intensity greater than a preset value must be covered and the distance between two activated air outlets being greater than the sum of their respective effective coverage radii.

[0122] The air outlet solution module 104 is used to solve the air outlet optimization objective function based on the improved genetic algorithm to obtain the activated air outlet;

[0123] The air volume calculation module 105 is used to dynamically adjust the air volume of the activated air outlet according to the heat load intensity.

[0124] In the substation building air conditioning energy-saving automatic control system provided by this invention, the space is divided into several grids based on a temperature sensor matrix, and the heat load intensity of each grid and the effective coverage radius of each air outlet are calculated. An optimization objective function for the air outlets is constructed based on the heat load intensity of each grid and the effective coverage radius of each air outlet. An improved genetic algorithm is used to solve the optimization objective function to obtain the air outlets to be activated. Finally, the airflow of the activated air outlets is adjusted according to the heat load intensity. This allows for adjustment of the air outlet position and airflow based on indoor conditions. This facilitates the uniform diffusion of the airflow from the air conditioner within the station space, avoiding excessive airflow in some areas that could create an overly cold environment. It also prevents heat accumulation and excessively high temperatures in critical areas near heat-generating equipment due to ineffective airflow. Furthermore, when some equipment operates at low loads and generates less heat, the airflow of the air outlets can be adjusted to precisely match the actual heat dissipation needs, avoiding significant energy waste and achieving energy-saving operation and maintenance management.

[0125] For example, the formula for calculating the heat load intensity of each grid is as follows:

[0126]

[0127] Among them, P i，j Q represents the heat load intensity of grid (i, j). 设备，k d is the rated power of the k-th device; i，j，k Let be the Euclidean distance from grid (i, j) to the k-th device; α and β are the weighting coefficients, respectively; ∈ to prevent the denominator from being a tiny number of zero; T is the correction term for the heat load due to ambient temperature.

[0128] Optionally, the coverage radius calculation module 102 includes:

[0129] The correction unit calculates the coverage radius of each air outlet based on the corrected coverage radius formula. This formula is derived from a simplified physical model of the effective coverage radius of a single air outlet, based on the unsteady-state thermal diffusion equation and engineering experience. The unsteady-state thermal diffusion equation describes the diffusion characteristics of a free jet or isothermal free jet under ideal conditions. However, real-world air conditioning scenarios are extremely complex and differ significantly from the ideal physical model. The correction makes the calculated coverage radius closer to actual engineering conditions. For example, the corrected coverage radius formula is:

[0130]

[0131] Where R is the coverage radius; η is the vent correction factor (ranging from 0.7 to 0.9, related to duct resistance); k is the correction factor calibrated through CFD simulation and actual measurement; Q is the vent cooling capacity; ΔT is the supply air temperature difference, i.e., the difference between the set temperature and the return air temperature; ρ is the air density, which is taken as 1.2 kg / m³ under standard operating conditions. 3 C ρ The specific heat capacity of air at constant pressure;

[0132] The compensation unit is used to compensate for the superposition effect of multiple air outlets. When the coverage areas of multiple air outlets overlap, the coverage radius of the air outlets corresponding to the overlapping coverage areas is reduced to obtain the effective coverage radius. If the air outlets do not have overlapping coverage areas, the coverage radius of the air outlet is the effective coverage radius.

[0133] Specifically, the attenuation formula is:

[0134] R'=R·e -λN ;

[0135] Where R' is the effective coverage radius after attenuation, N is the number of overlapping air vents, and λ is the attenuation coefficient.

[0136] The revised coverage radius formula calculates the case of a single air outlet. However, in the station space, there are multiple air outlets that affect each other. This embodiment compensates for the superposition effect of multiple airflows by attenuating the air outlets in overlapping coverage areas, making the effective coverage radius of the air outlets more consistent with the actual situation and improving the accuracy of control.

[0137] For example, the objective function for optimizing the air outlet is:

[0138] The expression for the minimum number of air vents is: x m ∈{0,1}; where x m This is a binary variable (0 or 1) indicating whether the air outlet at the m-th candidate location is enabled; for example, x m =0 indicates that the air outlet at the m-th candidate location is closed; x m =1 indicates that the air outlet at the m-th candidate position is open;

[0139] The expression for maximizing coverage uniformity is: Among them, T i，j The temperature of grid cell (i,j) represents the actual temperature of that grid cell under the influence of the air outlet layout; T set To set the temperature;

[0140] Constraint (a): All areas with thermal load intensities greater than a preset value must be covered. The expression for constraint (a) is: P i，j >Pthreshold P i，j P represents the heat load intensity of the grid (i,j); threshold A preset threshold for heat load intensity; a heat load intensity of a grid cell exceeding the preset threshold is considered a "high load region"; a m，i，j The coverage coefficient, defined as a binary variable (0 or 1), indicates whether the m-th candidate location's air outlet can cover the grid (i,j) if it is enabled; for example, a m,i,j =1 indicates that the air outlet at the m-th candidate location can cover the grid (i,j) when it is enabled; a m,i,j =0 indicates that the air outlet at the m-th candidate position cannot cover the grid (i,j) when it is enabled;

[0141] Constraint (b): The distance between two active air outlets is greater than the sum of their respective effective coverage radii. The expression for constraint (b) is: D a，b ≥R' a +R' b D a,b R' is the distance between the activated air outlet a and the activated air outlet b. a R' is the effective coverage radius of the activated air outlet a. b The effective coverage radius of the activated air outlet b.

[0142] Optionally, the improved genetic algorithm uses binary encoding, with the gene length being the number of candidate air outlets, and a gene bit of 1 indicating that the air outlet is enabled;

[0143] The fitness function is:

[0144]

[0145] Where F is the fitness, and w1, w2, and w3 are the weights; by default, w1 is 0.5, w2 is 0.3, and w3 is 0.2; the uniformity index refers to the degree of uniformity of temperature / velocity distribution in the target area (working area). The smaller the index, the better the uniformity; the coverage rate is the percentage (%) of the actual temperature in the target area that meets the grid requirements within the allowable deviation range of the set temperature.

[0146]

[0147] Where ΔT is the allowable temperature deviation (e.g., ±0.5℃) and N is the mesh element.

[0148] Using a single-point crossover method, the initial adaptive mutation rate was 0.1, which decreased to 0.02 after iteration;

[0149] The termination condition is that the fitness change is less than a threshold for N consecutive generations or the maximum number of iterations is reached. N is a non-zero positive integer. In an optional embodiment, the termination condition is that the fitness change is less than 0.1 for 10 consecutive generations or the maximum number of iterations, 200, is reached.

[0150] Further optionally, a dynamic re-optimization module is included, which is used to trigger the air outlet solution module 104 to re-solve the air outlet optimization objective function when the temperature in a certain area exceeds the limit for t minutes for a continuous period of time or when the location of the equipment changes.

[0151] In this embodiment, a re-optimization mechanism is employed. If the temperature in a certain area exceeds the limit for t consecutive minutes, or if the equipment location changes, step S4 is re-triggered. This allows for adjustment of the air outlet position based on temperature or equipment location changes, achieving precise temperature control and improving the substation's operational reliability. For example, the upper temperature limit is 2°C higher than the set temperature; the lower temperature limit is 3°C lower than the set temperature. If the temperature in a certain area exceeds the upper or lower temperature limit for 5 consecutive minutes, step S4 is re-triggered. More preferably, a local optimization strategy can be used, recalculating only the affected area to reduce the computational load.

[0152] Optionally, the air volume calculation module 105 includes:

[0153] The acquisition unit is used to acquire the heat load level of the area where the grid is located and obtain the corresponding area weight coefficient. In an optional embodiment of the invention, the substation is divided into key areas (such as main transformer room, GIS room), secondary key areas (such as switch cabinet room), and ordinary areas (corridor, control room) according to the power facilities. The weight coefficient of the key area is 1.5, the weight coefficient of the secondary key area is 1.2, and the weight coefficient of the ordinary area is 1.0.

[0154] The correction unit is used to correct the heat load intensity of the grid based on the actual power data of the equipment operation, thereby obtaining the corrected heat load intensity for each grid; the correction formula is:

[0155]

[0156] Among them, P' i，j P represents the corrected heat load intensity for grid (i, j). i，j Let I be the heat load intensity of the grid (i,j). actual I represents the actual current of the equipment. rated γ is the rated current of the equipment; γ is the heat load correction factor.

[0157] The theoretical air volume calculation unit is used to calculate the theoretical air volume requirement for a single grid cell based on the area weighting coefficient corresponding to the grid and the corrected heat load intensity. The formula for calculating the theoretical air volume requirement for a single grid cell is as follows:

[0158]

[0159] In the formula: w k ζ represents the regional weight; ζ is the airflow attenuation coefficient (default 0.1 / m), d i,j Distance from the grid to the air vent; T set To set the temperature, T in Return air temperature;

[0160] Linearization of the airflow-temperature relationship refers to how the temperature of a single grid point is linearly affected by the airflow from multiple air outlets:

[0161]

[0162] In the formula: α k,i,j To enable the airflow-temperature transfer coefficient (related to distance and airflow attenuation) of outlet k to grid (i, j); β i,j This is the static heat load baseline (including heat generated by equipment and transferred to the environment, which is not dynamically corrected).

[0163] The air volume multi-objective optimization function establishment unit is used to establish the air volume multi-objective optimization function. The air volume multi-objective optimization function aims to minimize the total energy consumption and minimize the temperature deviation, with the air volume of a single activated air outlet not exceeding its own maximum air volume, the air volume range of the damper of a single activated air outlet being between the minimum air volume and the maximum air volume, and the supply air temperature of the activated air outlet being higher than the dew point temperature.

[0164] Specifically, the multi-objective optimization function for air volume is:

[0165] Minimize total energy consumption: Among them, Q K ΔP represents the airflow of the Kth activated air outlet. K The power consumption per unit airflow for the Kth activated air outlet valve;

[0166] Minimize temperature deviation: min = ∑ i，j |T i，j -T set |, if T i,j The closer to the set temperature T set The more uniform the system, the smaller the objective function value;

[0167] Constraints: Single air volume limit ∑Q K ≤Q max Airflow range Q for a single air valve min ≤Q k ≤Q max Anti-condensation constraint on air outlet supply temperature T out，k ≥T dew +2℃, T dew Dew point temperature; grid cell temperature Ti,j With air volume Q K Supply air temperature T out The heat load intensity P' after grid (i, j) correction i,j A linear relationship exists. γ is a coefficient, and c is a constant; it refers to how the temperature in the entire system is affected by the combined linear influence of air volume, supply air temperature, and heat load, quantifying the coupled influence of dynamic heat load and air volume, and is used to respond to sudden changes in equipment power and avoid control failure.

[0168] The air volume calculation unit is used to solve the multi-objective optimization function of air volume using mixed integer linear programming to obtain the air volume of each activated air outlet.

[0169] Specifically, the mixed integer linear programming (MILP) solution uses the air volume of the vent and the opening degree of the vent damper as the decision capacity; linearization process: the nonlinear heat balance equation is discretized into piecewise linear functions, and the Gurobi or CPLEX solver is called to achieve real-time optimization (computation delay < 5 seconds).

[0170] In this embodiment, the air volume is designed to minimize total energy consumption. This embodiment also aims to minimize temperature deviation to avoid the impact of drastic temperature changes. Furthermore, by constraining the supply air temperature, the supply air temperature at the outlet is kept below the dew point temperature to prevent condensation on the equipment surface. This prevents water droplets from seeping into the equipment and causing short circuits or other malfunctions.

[0171] Optionally, the damper control module is used to use the air volume of each activated air outlet as the target air volume setpoint for the activated air outlet, and employs fuzzy adaptive PID algorithm and feedforward-feedback composite control for closed-loop control and anti-interference of the damper.

[0172] A closed-loop control system for the air valve is constructed to achieve precise dynamic airflow adjustment and disturbance suppression.

[0173] The fuzzy adaptive PID algorithm includes a fuzzy rule base design:

[0174] Input variables: temperature deviation e(t), rate of change of deviation Output variable: PID parameter correction ΔP K ΔP i ΔP d Example rule: If e(t) is "positive" and If the result is "negative neutral", then ΔPd = +0.2, ΔKi = -0.1; Control law update:

[0175]

[0176] u(t) is the final output signal of the controller, Kp is the initial proportional parameter, and ΔP is the final output signal of the controller. k ΔKi is the dynamic adjustment value of the fuzzy rule, Ki is the initial integral parameter, ΔKi is the dynamic adjustment value of the fuzzy rule, Kd is the initial differential parameter, and ΔKd is the dynamic adjustment value of the fuzzy rule.

[0177] ΔP K ΔP i ΔP d Yes, it is the output of fuzzy logic, representing the dynamic adjustment of the original PID parameters.

[0178] The feedforward-feedback composite control includes feedforward compensation and feedback suppression of oscillations.

[0179] Feedforward compensation: Adjust the air volume in advance based on sudden power changes in the equipment (such as circuit breaker tripping). The adjustment formula is as follows:

[0180]

[0181] Among them, Q f The adjusted air volume, ΔP step denoted as , where is the step change in heat load; μ is the feedforward gain, ranging from 0.8 to 1.2.

[0182] Feedback to suppress oscillation: Introduce PID control with dead zone, pause integral control when |e(t)| < 0.5℃| to prevent overshoot.

[0183] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. All equivalent structural transformations made under the concept of the present invention using the contents of the present invention specification and drawings, or direct / indirect applications in other related technical fields, are included within the patent protection scope of the present invention.

Claims

1. An automatic energy-saving control method for air conditioning in a substation, applied to a substation, wherein the substation is equipped with several independent air conditioning outlets, and a temperature sensor matrix is ​​deployed within the substation; characterized in that: The method includes: Step S1: Obtain the temperature data of the temperature sensor matrix and the rated power data of each device, and calculate the heat load intensity of each grid in the matrix based on the temperature data and rated power data; Step S2: Dynamically calculate and verify the coverage radius of each air outlet to obtain the effective coverage radius of each air outlet; Step S3: Establish an optimization objective function for the air outlets. The optimization objective function aims to minimize the number of air outlets and maximize the coverage uniformity. The constraints are that all areas with thermal load intensity greater than a preset value must be covered and the distance between two activated air outlets must be greater than the sum of their respective effective coverage radii. Step S4: Solve the objective function of the air outlet optimization based on the improved genetic algorithm to obtain the activated air outlet; Step S5: Dynamically adjust the air volume of the activated air outlet according to the equipment operating status.

2. The automatic energy-saving control method for air conditioning in substation buildings according to claim 1, characterized in that: Step S2 includes: Step S21: Calculate the coverage radius of each air outlet according to the revised coverage radius formula; Step S22: Perform compensation for the superposition effect of multiple air outlets. When the coverage areas of multiple air outlets overlap, the coverage radius of the air outlets corresponding to the overlapping coverage areas is reduced to obtain the effective coverage radius. If the air outlets do not have overlapping coverage areas, the coverage radius of the air outlet is the effective coverage radius.

3. The automatic energy-saving control method for air conditioning in substation buildings according to claim 1, characterized in that: If the temperature in a certain area exceeds the limit for t minutes continuously, or if the location of the equipment changes, step S4 will be triggered again.

4. The automatic energy-saving control method for air conditioning in substation buildings according to claim 1, characterized in that: Step S5 includes: Step S51: Obtain the heat load level of the area where the grid is located, and obtain the corresponding area weight coefficient; Step S52: Correct the heat load intensity of the grid based on the real-time power data of the equipment operation to obtain the corrected heat load intensity of each grid; Step S53: Calculate the theoretical air volume requirement for a single grid based on the area weight coefficient corresponding to the grid and the corrected heat load intensity; Step S54: Establish a multi-objective optimization function for air volume. The multi-objective optimization function for air volume aims to minimize total energy consumption and minimize temperature deviation. The constraints are: the air volume of a single activated air outlet is not greater than its own maximum air volume; the air volume range of the damper of a single activated air outlet is between the minimum air volume and the maximum air volume; the supply air temperature of the activated air outlet is higher than the dew point temperature; and the grid cell temperature has a linear relationship with the supply air volume, supply air temperature and the heat load intensity after grid correction. Step S55: Use mixed integer linear programming to solve the multi-objective optimization function of air volume to obtain the air volume of each activated air outlet.

5. The automatic energy-saving control method for air conditioning in a substation building according to claim 1, characterized in that: Also includes: Step S6: Based on the air volume of each activated air outlet as the target air volume setpoint for the activated air outlet, a fuzzy adaptive PID algorithm and feedforward-feedback composite control are used for closed-loop control and anti-interference of the air valve.

6. An automatic energy-saving control system for substation building air conditioning, applied to the automatic energy-saving control method for substation building air conditioning as described in any one of claims 1-5, characterized in that: The system includes: The acquisition module is used to acquire temperature data from the temperature sensor matrix and rated power data of each device, and calculate the heat load intensity of each grid in the matrix based on the temperature data and rated power data. The coverage radius calculation module is used to dynamically calculate and verify the coverage radius of each air outlet to obtain the effective coverage radius of each air outlet. The air outlet optimization objective function establishment module is used to establish the air outlet optimization objective function. The optimization objective function aims to minimize the number of air outlets and maximize the coverage uniformity. The constraints are that all areas with thermal load intensity greater than a preset value must be covered and the distance between two activated air outlets is greater than the sum of their respective effective coverage radii. The air outlet solution module is used to solve the air outlet optimization objective function based on an improved genetic algorithm to obtain the activated air outlet. The air volume calculation module is used to dynamically adjust the air volume of the activated air outlet according to the equipment operating status.

7. The automatic energy-saving control system for substation building air conditioning according to claim 1, characterized in that: The coverage radius calculation module includes: The correction unit is used to calculate the coverage radius of each air outlet according to the corrected coverage radius formula; The compensation unit is used to compensate for the superposition effect of multiple air outlets. When the coverage areas of multiple air outlets overlap, the coverage radius of the air outlets corresponding to the overlapping coverage areas is reduced to obtain the effective coverage radius. If the air outlets do not have overlapping coverage areas, the coverage radius of the air outlet is the effective coverage radius.

8. The automatic energy-saving control system for substation building air conditioning according to claim 1, characterized in that: It includes a dynamic re-optimization module, which is used to trigger the air outlet solution module to re-solve the air outlet optimization objective function when the temperature in a certain area exceeds the limit for t minutes for a continuous period of time or when the location of the equipment changes.

9. The automatic energy-saving control system for substation building air conditioning according to claim 1, characterized in that: The air volume calculation module includes: The acquisition unit is used to obtain the heat load level of the grid area and obtain the corresponding area weight coefficient. The correction unit is used to correct the heat load intensity of the grid based on the real-time power data of the equipment operation, so as to obtain the corrected heat load intensity of each grid. The theoretical air volume calculation unit is used to calculate the theoretical air volume required for a single grid based on the area weight coefficient corresponding to the grid and the corrected heat load intensity. The air volume multi-objective optimization function establishment unit is used to establish the air volume multi-objective optimization function. The air volume multi-objective optimization function aims to minimize the total energy consumption and minimize the temperature deviation. The constraints are: the air volume of a single activated air outlet is not greater than its own maximum air volume; the air volume range of the damper of a single activated air outlet is between the minimum air volume and the maximum air volume; the supply air temperature of the activated air outlet is higher than the dew point temperature; and the grid cell temperature is linearly related to the supply air volume, supply air temperature and the grid-corrected heat load intensity. The air volume calculation unit is used to solve the multi-objective optimization function of air volume using mixed integer linear programming to obtain the air volume of each activated air outlet.

10. The automatic energy-saving control system for substation building air conditioning according to claim 7, characterized in that: The air valve control module is used to set the target air volume of each activated air outlet as the air volume setpoint for the activated air outlet. It employs a fuzzy adaptive PID algorithm and feedforward-feedback composite control for closed-loop control and anti-interference of the air valve.

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