Hydropower station underground powerhouse ventilation air conditioner control method, system, equipment and medium

Abstract

The invention relates to the technical field of plant ventilation and energy conservation, and discloses a hydropower station underground plant ventilation and air-conditioning control method, system, device and medium, and the method comprises the steps: obtaining a power generation plan and heat source characterization data of an underground plant, and generating a pre-cooling trigger judgment according to the power generation plan and heat source characterization data; and according to the pre-cooling triggering judgment, the ventilation air conditioner is controlled to carry out double-feedforward pre-cooling operation. On one hand, the air conditioner energy can be regulated and controlled based on the power generation plan, and the problems that in the prior art, an air conditioner control system is always set to be in a high-power-consumption state, so that power consumption is high, and energy is wasted are solved; on the other hand, by controlling the ventilation air conditioner to conduct double-feedforward pre-cooling operation, the frequency of starting a standby air conditioning unit is greatly reduced, and the problems that in the prior art, energy consumption is high, and energy is wasted are solved.

Description

Technical Field

[0001] This invention relates to the field of energy-saving ventilation technology for power plants, and in particular to a method, system, equipment and medium for controlling ventilation and air conditioning in underground power plants of hydropower stations. Background Technology

[0002] The underground powerhouses of large hydropower stations are typically large in size and have high thermal inertia. Their internal ventilation and air conditioning systems need to undertake the task of ventilation and temperature and humidity risk control in key hot areas such as generator floors, busbar rooms, and transformer rooms for a long time.

[0003] In existing technologies, in order to ensure the temperature and humidity requirements are met under extreme conditions such as full operation of all units and the highest summer temperatures, the air conditioning control system is often set to a high power consumption state. However, during most of the operating time, the actual heat load of the plant does not require the air conditioning system to consume too much power, thus causing problems of high power consumption and energy waste due to improper adjustment.

[0004] In addition, due to the significant thermal inertia and time lag of underground power plants, the air conditioning system is usually increased in cooling or ventilation after the detected temperature exceeds the limit. This can easily lead to peak overshoot, especially when multiple standby air conditioning units are started to achieve rapid cooling and ventilation, which in turn leads to high energy consumption and energy waste. Summary of the Invention

[0005] To address the aforementioned problems, this invention proposes a ventilation and air conditioning control method, system, equipment, and medium for underground powerhouses in hydropower stations, which can solve the problems of high energy consumption and energy waste in the prior art.

[0006] The technical solution adopted in this invention is as follows: A method for controlling ventilation and air conditioning in an underground powerhouse of a hydropower station, comprising: Obtain the power generation plan and heat source characterization data of the underground powerhouse, and generate a pre-cooling trigger determination based on the power generation plan and heat source characterization data; The pre-cooling trigger determination is used to control the ventilation and air conditioning system to perform dual feedforward pre-cooling operation.

[0007] Furthermore, a pre-cooling trigger determination is generated based on the power generation plan and heat source characterization data, including: Calculate the estimated arrival time of the load increase event based on the power generation plan; Calculate the heat source amplification based on the heat source characterization data; Determine whether the expected arrival time is within a preset time window, or whether the increase in heat source is greater than the increase threshold; if the determination is no, generate a pre-cooling non-trigger determination; if the determination is yes, generate a pre-cooling trigger determination.

[0008] Furthermore, the method for calculating the increase threshold includes: Historical data of heat source characterization data are collected within a preset training window, and a sample set of non-event periods is obtained based on the historical data. Calculate the relative increase, quantile threshold, mean, and standard deviation based on the sample set from the non-event period; The growth threshold is determined based on the relative growth rate, quantile threshold, and mean and standard deviation.

[0009] Furthermore, the pre-cooling trigger determination includes load event trigger determination, heat source amplitude trigger determination, and dual threshold trigger determination; controlling the ventilation and air conditioning system to perform dual feedforward pre-cooling operation according to the pre-cooling trigger determination includes: In response to the load event trigger determination, first precooling data is generated, and the ventilation and air conditioning system is controlled to perform dual feedforward precooling operation based on the first precooling data; In response to the heat source amplitude trigger determination, second precooling data is generated, and the ventilation and air conditioning system is controlled to perform dual feedforward precooling operation based on the second precooling data; In response to the dual threshold trigger determination, a third precooling data is generated, and the ventilation and air conditioning system is controlled to perform dual feedforward precooling operation based on the third precooling data.

[0010] Furthermore, in response to a load event trigger determination, first precooling data is generated, and the ventilation and air conditioning system is controlled to perform dual feedforward precooling operation based on the first precooling data, including: In response to load event triggering determination, critical areas, secondary critical areas, and non-critical areas are set; Generate the first precooling data, and control the ventilation and air conditioning to perform dual feedforward precooling operation based on the first precooling data, the critical area, the secondary critical area and the non-critical area.

[0011] Furthermore, the step of setting critical areas, secondary critical areas, and non-critical areas in response to a load event trigger determination includes: In response to load event triggering determination, calculate the thermal coupling intensity, heat load intensity, and condensation risk of candidate areas within the underground powerhouse; A comprehensive regional score is generated for candidate regions based on the thermal coupling intensity, the heat load intensity, and the condensation risk. Based on the comprehensive regional score, key areas, secondary key areas, and non-key areas are set.

[0012] Further, the secondary critical area corresponds to the first reduced control coefficient, and the non-critical area corresponds to the second reduced control coefficient; the step of controlling the ventilation and air conditioning system to perform dual feedforward precooling operation based on the first precooling data, the critical area, the secondary critical area, and the non-critical area includes: The pre-cooling data of the secondary critical zone is generated based on the first conversion control coefficient and the first pre-cooling data. Generate non-critical area pre-cooling data for non-critical areas based on the second conversion control coefficient and the first pre-cooling data; Pre-cooling is performed on critical areas based on the first pre-cooling data, on secondary critical areas based on the pre-cooling data of the secondary critical areas, and on non-critical areas based on the pre-cooling data of the non-critical areas.

[0013] A ventilation and air conditioning control system for an underground powerhouse of a hydropower station includes: The precooling trigger determination module is configured to acquire the power generation plan and heat source characterization data of the underground powerhouse, and generate a precooling trigger determination based on the power generation plan and heat source characterization data; The doubly fed precooling execution module is configured to control the ventilation and air conditioning system to perform doubly fed-forward precooling operation based on the precooling trigger determination.

[0014] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the ventilation and air conditioning control method for the underground powerhouse of a hydropower station.

[0015] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the ventilation and air conditioning control method for the underground powerhouse of a hydropower station.

[0016] The beneficial effects of this invention are as follows: 1. This invention generates a pre-cooling trigger determination based on power generation plan and heat source characterization data, and controls the ventilation and air conditioning to perform dual feedforward pre-cooling operation based on the pre-cooling trigger determination. On the one hand, it can regulate the air conditioning energy based on the power generation plan, avoiding the problem of high power consumption and energy waste caused by always setting the air conditioning control system to a high power consumption state in the prior art; on the other hand, by controlling the ventilation and air conditioning to perform dual feedforward pre-cooling operation, it greatly reduces the frequency of using the standby air conditioning unit, solving the problem of high energy consumption and energy waste in the prior art.

[0017] 2. Unlike existing technologies that passively adjust temperatures only after room temperature exceeds limits or perform rough pre-cooling based on fixed time schedules, this invention first analyzes future power generation plans to calculate the expected arrival time of load increase events. Then, it calculates the heat source amplification based on heat source characterization data that indirectly represent heat release, such as bus current, main transformer oil temperature, winding temperature, and cooling water temperature difference. Finally, it combines the expected arrival time and heat source amplification to determine whether pre-cooling should be triggered. Therefore, by making pre-cooling judgments in advance and controlling pre-cooling operations based on the judgment results, this invention can effectively offset time delays in underground power plants with high thermal inertia, avoiding temporary extreme cooling and the need to additionally start the refrigeration unit, thereby achieving energy conservation. Attached Figure Description

[0018] Figure 1This is a flowchart of a ventilation and air conditioning control method for an underground powerhouse of a hydropower station, according to Embodiment 1 of the present invention.

[0019] Figure 2 This is a block diagram of a ventilation and air conditioning control system for an underground powerhouse of a hydropower station, according to Embodiment 2 of the present invention. Detailed Implementation

[0020] To provide a clearer understanding of the technical features, objectives, and effects of the present invention, specific embodiments are now described. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention; that is, the described embodiments are only a part of the embodiments of the invention, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0021] Example 1 like Figure 1 As shown in the figure, this embodiment provides a ventilation and air conditioning control method for an underground powerhouse of a hydropower station, including: Step S100: Obtain the power generation plan and heat source characterization data of the underground powerhouse, and generate a pre-cooling trigger determination based on the power generation plan and heat source characterization data; Step S200: Control the ventilation and air conditioning system to perform dual feedforward precooling operation according to the precooling trigger determination.

[0022] In this embodiment, the dual-feedforward pre-cooling operation is a pre-cooling operation that adjusts the temperature before it is detected to be too high, based on two factors: the power generation plan and heat source characterization data. Based on the dual-feedforward pre-cooling operation, on the one hand, air conditioning energy can be adjusted according to the power generation plan, avoiding the high power consumption and energy waste caused by always setting the air conditioning control system to a high power consumption state in the prior art; on the other hand, by controlling the ventilation and air conditioning to perform dual-feedforward pre-cooling operation, a concept completely opposite to the temperature measurement and control method in the prior art is adopted, realizing the control of air conditioning ventilation and cooling before the temperature rise caused by the heat source, greatly reducing the frequency of using standby air conditioning units, or even eliminating the need to use standby air conditioning units, thus solving the problems of high energy consumption and energy waste in the prior art.

[0023] Preferably, in step S100, generating a pre-cooling trigger determination based on the power generation plan and heat source characterization data includes: Step S110: Calculate the estimated arrival time of the load increase event based on the power generation plan; Step S120: Calculate the heat source amplification based on the heat source characterization data; Step S130: Generate a pre-cooling trigger determination based on the expected arrival time and the heat source amplification.

[0024] Unlike existing technologies that passively adjust temperatures only after they exceed limits or perform rough pre-cooling based on fixed time schedules, this embodiment first analyzes future power generation plans to calculate the estimated arrival time of load increase events. Then, it calculates the heat source amplification based on heat source characterization data that indirectly represent heat release, such as bus current, main transformer oil temperature, winding temperature, and cooling water temperature difference. Finally, it combines the estimated arrival time and the heat source amplification to determine whether pre-cooling should be triggered. Therefore, by making pre-cooling judgments in advance and controlling pre-cooling operations based on the judgment results, time lags can be effectively offset in underground powerhouses with high thermal inertia, avoiding temporary extreme cooling and the need to additionally start the refrigeration unit, thereby achieving energy conservation.

[0025] Since the actual heat release power of the heat source cannot be directly measured, data that indirectly represents the heat release power of the heat source is selected as heat source characterization data. The actual heat release power of the heat source is characterized based on this heat source characterization data. The heat source characterization data is generally selected based on data that is monotonically correlated with the heat release power of the heat source, can be measured quickly, and can be obtained stably. For example, the heat source characterization data includes generator current, bus current, cable current, main transformer oil temperature, air cooler opening degree, fan frequency, etc. The specific selection is determined by those skilled in the art based on actual conditions; this application is merely an example and does not impose limitations.

[0026] Preferably, in step S130, generating a pre-cooling trigger determination based on the expected arrival time and the heat source amplification includes: Step S131: Determine whether the expected arrival time is within a preset time window, or whether the heat source increase is greater than the increase threshold. Step S132: If the determination is negative, then generate a pre-cooling non-triggered determination; Step S133: If the determination is yes, then generate a pre-cooling trigger determination.

[0027] In this embodiment, a pre-cooling operation is required when the estimated arrival time is within a preset time window or when the heat source increase exceeds a threshold. Therefore, a pre-cooling determination trigger is generated in both cases. Accurate and comprehensive judgment is achieved by combining the estimated arrival time and the heat source increase, avoiding missed judgments.

[0028] For example, the load increase event in power generation is "Unit 1 grid connection t=14:00", indicating that Unit 1 is connected to the grid at 14:00. If the current time is 13:20, the estimated arrival time is the unit grid connection time 14:00 minus the current time 13:20, which is 40 minutes. The preset time window is set by those skilled in the art based on the actual equipment; different equipment has different settings due to varying heat generation. For example, the preset time window for Unit 1 is 30 to 45 minutes. If the estimated arrival time falls within the preset time window, a pre-cooling trigger determination is generated.

[0029] When the heat source characterization data is the bus current, taking Unit #2 as an example, its rated current is 3000A. The current was 1250A 15 minutes ago, and the current is 1450A, resulting in a difference of 200A. Normalized to the rated current: 200 ÷ 3000 ≈ 6.67%. When the amplification threshold is 4.2%, the heat source amplification exceeds the threshold, at which point a pre-cooling trigger determination is generated.

[0030] Preferably, to more accurately determine whether pre-cooling is needed based on the heat source increase, the duration of the heat source increase is incorporated. Specifically, a pre-cooling trigger is generated only when the heat source increase is greater than an increase threshold and the duration of the heat source increase is greater than a duration threshold. For example, the duration threshold is preset, such as 4 minutes. Unlike the common method in existing technologies where instantaneous boundary crossing triggers the pre-cooling, this embodiment determines whether pre-cooling is triggered by comprehensively considering the duration, thereby effectively distinguishing transient noise from actual temperature rise, avoiding frequent triggering and subsequent reverse backoff, reducing control oscillations, and improving judgment accuracy.

[0031] Preferably, the method further includes a step of adaptively determining the amplification threshold, specifically including: Step S011: Collect historical data of heat source characterization data within a preset training window, and obtain a sample set of non-event periods based on the historical data; Step S012: Calculate the relative increase and quantile threshold based on the sample set from the non-event period. and mean with standard deviation ; Step S013: Based on the relative increase and quantile threshold and mean with standard deviation Determine the increase threshold.

[0032] Preferably, in step S011, historical data of heat source characterization data is collected within a preset training window, and the event periods corresponding to pre-cooling-related events are removed to obtain a sample set of non-event period data. The pre-cooling-related events refer to event periods that may trigger pre-cooling, including unit grid connection, load increase, maintenance tests, and event periods that have already triggered pre-cooling, as well as their preceding and following buffer periods.

[0033] Preferably, in step S012, the non-event period sample set is denoised and smoothed, and a feature quantity for triggering the determination is constructed within the sliding time window. The feature quantity includes a relative increase based on a 15-minute window.

[0034] Preferably, the formula for calculating the relative increase is as follows: ; in, For relative growth rate, The value of the feature quantity at the current moment; The values ​​of the feature values ​​from 15 minutes prior to the current time. The nominal value of the characteristic quantity; The low load value of the characteristic quantity is taken as the 10th to 20th percentile of the most recent 60 to 120 minutes from the current time; To take the rated value of the characteristic quantity and low load values ​​of characteristic quantities The larger value in the range. In this embodiment, the characteristic quantity is the phase current, corresponding to... This is the rated current.

[0035] In calculating the relative increase, the molecules pass through This method provides a higher sensitivity for detecting trends compared to existing technologies that rely solely on the absolute value of the current. In the denominator, if only the rated value is used... If only a low loading value of the characteristic quantity is used, then it may be diluted slightly. If the load is very low recently, the denominator will be too small, resulting in a relatively large increase and causing false alarms. Therefore, the overall rated value should be considered. and low load value The larger values ​​in the range address the issues of small values ​​being easily diluted and false alarms.

[0036] Preferably, the quantile threshold is calculated based on the statistical distribution of all relative increases within the sample set during the non-event period. and mean with standard deviation .

[0037] Preferably, in step S013, the amplification threshold is determined based on the following formula. :

[0038] in, The threshold for the increase; This is the lower limit of the project. Its purpose is to prevent the threshold from being pulled down by occasional small sample anomalies; Indicates the quantile threshold , as well as The larger value in the range.

[0039] In this embodiment, based on quantile threshold as well as By imposing threshold setting constraints, the problems of inaccurate threshold setting and excessively high threshold setting that are easily caused by using only fixed thresholds or single statistical quantities in existing technologies are solved. This reduces the false alarm rate, improves the accuracy of pre-cooling judgment, and indirectly improves the energy-saving control efficiency of air conditioning.

[0040] Preferably, the pre-cooling trigger determination includes load event trigger determination, heat source amplitude trigger determination, and dual threshold trigger determination; in step S200, controlling the ventilation and air conditioning system to perform dual feedforward pre-cooling operation according to the pre-cooling trigger determination includes: Step S210: In response to the load event trigger determination, generate first precooling data, and control the ventilation and air conditioning to perform dual feedforward precooling operation according to the first precooling data; Step S220: In response to the heat source amplitude trigger determination, generate second precooling data, and control the ventilation and air conditioning to perform dual feedforward precooling operation according to the second precooling data; Step S230: In response to the dual threshold trigger determination, generate third precooling data, and control the ventilation and air conditioning to perform dual feedforward precooling operation according to the third precooling data.

[0041] In this embodiment, the load event trigger determination is generated only based on the expected arrival time being within a preset time window. The heat source amplitude trigger determination is generated only based on the heat source increase being greater than an increase threshold. The dual threshold trigger determination is generated when the expected arrival time is within a preset time window and the heat source increase is greater than an increase threshold.

[0042] Preferably, the load event trigger determination, the heat source amplitude trigger determination, and the dual threshold trigger determination each correspond to different precooling trigger levels, specifically the first level, the second level, and the third level. The first level, the second level, and the third level correspond to the first precooling data, the second precooling data, and the third precooling data, respectively.

[0043] Preferably, the first precooling data, the second precooling data, and the third precooling data correspond to medium-confidence, low-confidence, and high-confidence judgments, respectively. For example, the second precooling data represents a step-by-step reduction of the target supply air temperature by 0.5℃-1.0℃ and an increase in supply air volume of 5%-15%. The first precooling data represents a step-by-step reduction of the target supply air temperature by 1.0℃-1.5℃ and an increase in supply air volume of 10%-15%. The third precooling data represents a step-by-step reduction of the target supply air temperature by 1.5℃-2.0℃ and an increase in supply air volume of 15%-20%. Afterward, the temperature is maintained for 15 minutes, then gradually reduced by 0.5℃ every 10 minutes, with a 5% decrease in air volume.

[0044] Preferably, the second pre-cooling data is based on heat source determination, specifically derived from indirect representations of actual heat source release. It is significantly affected by sensor noise, localized operations, maintenance, and testing. Even if an upward trend appears, the likelihood of it subsequently translating into a stable load increase remains uncertain, hence it is assigned a low confidence level. The first pre-cooling data is generated based on load determination, with its determination rooted in the power generation plan. It represents the source of heat generation and is the direct cause of the increase in heat source. However, due to the possibility of plan cancellations, it is only set to a medium confidence level. The third pre-cooling data is based on a comprehensive determination of both heat source and power generation plan, hence it is set to a high confidence level.

[0045] Unlike existing technologies that use single-condition triggering, fixed lead time, or uniform precooling across the entire area, which can easily lead to high energy consumption, this embodiment divides precooling triggering into load event triggering, heat source amplitude triggering, and dual threshold triggering, and configures different air supply temperatures and different air supply volumes for each, thereby minimizing power consumption under different triggering conditions.

[0046] Preferably, in step S210, in response to the load event trigger determination, first precooling data is generated, and the ventilation and air conditioning system is controlled to perform dual feedforward precooling operation according to the first precooling data, including: Step S211: In response to the load event trigger determination, set the critical area, secondary critical area and non-critical area; Step S212: Generate first precooling data, and control the ventilation and air conditioning system to perform dual feedforward precooling operation based on the first precooling data, the critical area, the secondary critical area and the non-critical area.

[0047] Preferably, in step S211, in response to the load event trigger determination, setting critical areas, secondary critical areas, and non-critical areas includes: Step S021: In response to the load event trigger determination, calculate the thermal coupling intensity, heat load intensity and condensation risk of the candidate area in the underground powerhouse; Step S022: Generate a comprehensive regional score for candidate regions based on the thermal coupling strength, the heat load intensity, and the condensation risk; Step S023: Set key areas, secondary key areas and non-key areas according to the comprehensive regional score.

[0048] In this embodiment, a heat source is determined in response to a load event trigger determination. Once the heat source is determined, steps S021 to S023 can be executed based on the current heat source. The heat source is determined from the power generation plan. Taking the load increase event in the power generation plan corresponding to the previous example as "Unit 1 grid connection t=14:00" as an example, the heat source at this time is Unit 1. Therefore, the corresponding critical area, secondary critical area and non-critical area are set based on Unit 1.

[0049] Similarly, in step S220, in response to the heat source amplitude trigger determination, the heat source is determined from the heat source characterization data. If the heat source characterization data mentioned in the previous example is the bus current of Unit 2, then Unit 2 is the heat source. Therefore, Unit 2 is also used as the heat source to set the corresponding critical zone, secondary critical zone, and non-critical zone. This allows for real-time setting of the critical zone, secondary critical zone, and non-critical zone, enabling targeted pre-cooling operations.

[0050] Preferably, in step S220 or S210, in response to a load event trigger determination or a heat source amplitude trigger determination, pre-cooling operations are performed on the critical, secondary critical, and non-critical areas corresponding to the power generation plan and heat source characterization data, respectively. In step S230, when responding to a dual-threshold trigger determination, if the heat sources corresponding to the power generation plan and heat source characterization data are the same, there is only one set of critical, secondary critical, and non-critical areas. If the heat sources corresponding to the power generation plan and heat source characterization data are different, there are two sets of critical, secondary critical, and non-critical areas. If the two sets of critical, secondary critical, and non-critical areas do not overlap, pre-cooling can be performed separately. If the two sets of critical, secondary critical, and non-critical areas overlap, a pre-cooling upgrade operation is performed on the overlapping areas. For example, when the target supply air temperature is reduced by 1.5℃-2.0℃ in stages and the supply air volume is increased by 15%-20%, after the precooling upgrade operation, the third precooling data is 2.0℃-2.5℃ and the supply air volume is increased by 20%-25%. This ensures a matching relationship where the heat source has a large impact and the precooling operation level is high.

[0051] Steps S021-S023 are further explained as follows: In this embodiment, the thermal coupling intensity represents the degree to which the candidate area is affected by the main heat sources in the underground powerhouse. The main heat sources include, but are not limited to, generating units, main transformers, and busbars. The main heat sources primarily affect the candidate area through spatial distance, building structure, and ventilation connectivity. A higher thermal coupling intensity indicates that the heat released by the heat sources more easily and quickly affects the candidate area.

[0052] The thermal coupling intensity is generated by combining the distance grading score, the enclosure structure score, the air duct connectivity score, and the heat source intensity coefficient. The distance grading score, the enclosure structure score, the air duct connectivity score, and the heat source intensity coefficient are all dimensionless data.

[0053] The distance score is derived from the distance between the candidate area and the heat source. When the candidate area and the heat source are in the same or adjacent compartments, the distance score is 1. When the candidate area and the heat source are on the same floor and, for example, 5-7 meters apart, the distance score is 0.7. When the distance between the candidate area and the heat source is greater than 15 meters or on different floors, the distance score is 0.3. The distance data between the candidate area and the heat source is obtained from the as-built drawings.

[0054] The enclosure construction score reflects the degree of attenuation of walls, fire compartments, or insulation layers. When there is a visible partition, the enclosure construction score is 0.7. When there is no visible partition, the enclosure construction score is 1.

[0055] The air duct connectivity score is 1 when the candidate area and the heat source are on the same air supply branch, and 0.7 when the candidate area and the heat source are on different branches. The air supply branch data is obtained based on the ventilation and air conditioning system diagram.

[0056] The heat source intensity coefficient is categorized according to the rated heat dissipation of the heat source. For example, the heat source intensity coefficients for the main transformer, busbar, and generator layers are 0.9, 1.0, and 0.7, respectively. The rated heat dissipation data is obtained from the equipment nameplate and then the coefficients are set by the equipment management personnel.

[0057] Finally, the maximum value among the distance grading score, enclosure structure score, air duct connectivity score, and heat source intensity coefficient is set as the value of the thermal coupling intensity.

[0058] Preferably, a weighted average method can also be used to obtain the thermal coupling intensity. Specifically, weighting coefficients are assigned to the distance grading score, the enclosure structure score, the air duct connectivity score, and the heat source intensity coefficient, respectively. These weighting coefficients are then multiplied by each of these coefficients, and the resulting value is the thermal coupling intensity. This calculation method incorporates superposition attenuation. Of course, the thermal coupling intensity is not limited to the two methods described above; any method that can represent the degree to which the candidate area is affected by the main heat source in the underground powerhouse is acceptable.

[0059] The heat load intensity is used to represent the tendency of a candidate region to heat up when subjected to a heat source during the statistical period. In layman's terms, it is used to measure the degree and amount of heat rise that a candidate region is prone to when affected by a heat source.

[0060] Preferably, the dry-bulb air temperature of the candidate regions during the statistical period is first obtained, and the dry-bulb air temperatures are arranged from smallest to largest. Then, the 90th percentile is calculated. and 50th percentile Based on the 90th percentile and 50th percentile Calculate the heat load intensity:

[0061] in, Heat load intensity; For reference temperature difference, it is set in advance by those skilled in the art based on historical data or engineering experience; for example, it is set to 3°C. This represents a dimensionless value that is cropped to [0,1].

[0062] 50th percentile Represents the normal baseline, 90th percentile Representing the high-load baseline, the difference between the two indicates the amount by which the temperature in the candidate region rises above the normal temperature under high load. This temperature rise originates from the influence of the heat source on the candidate region. The influence of the heat source stems from two aspects: the intensity of the heat source and the frequency of high load events caused by the heat source. A stronger heat source results in a higher temperature increase (90th percentile). The larger the value, the better the overall The larger the difference, the more times the heat source causes high loads, resulting in more high-temperature samples, which in turn leads to the 90th percentile... The larger the value, the better. Therefore, based on the setting of the heat load intensity, it is possible to determine whether the candidate area is more likely to heat up when affected by the heat source. If it is more likely to heat up, then more attention should be paid to its pre-cooling, that is, to determine whether it is a critical area.

[0063] In addition, if the overall outdoor temperature rises, such as in summer, the 90th percentile and 50th percentile The upward movement is approximately equal in magnitude, therefore The difference remains essentially unchanged. This situation is due to seasonality, therefore it should not be included in the judgment of the warming trend of candidate areas. The settings effectively avoid errors caused by seasonality.

[0064] Furthermore, if the intensity of the heat source increases and the frequency of high loads caused by the heat source increases, the 90th percentile, which is in a high quantile, will be affected. The increase is at the 50th percentile of the median. Faster, at this point, although at the 90th percentile and 50th percentile Both moved upwards, but A larger difference indicates a stronger tendency for the candidate region to warm up under the influence of a heat source during the statistical period.

[0065] The condensation risk represents the likelihood of condensation and is used to quantify the condensation risk level of a candidate area during the statistical period. The condensation risk increases significantly when the surface temperature of the walls or equipment within the candidate area is close to or below the air dew point temperature. The higher the condensation risk value, the more priority is given to increasing ventilation.

[0066] Preferably, the condensation risk is calculated using the following formula:

[0067]

[0068] in, For dew point safety margin, A value greater than 0 indicates safety. The smaller the value, the closer it is to condensation; The surface temperature of the wall in the candidate area or the surface temperature of the equipment in the candidate area is obtained by a temperature monitoring sensor that is pre-installed on the surface of the wall or equipment. The dew point temperature is calculated from the dry-bulb temperature and relative humidity of the air, based on information collected by a preset temperature and humidity sensor. To mitigate the risk of condensation; As a safety margin threshold, it is set in advance by those skilled in the art based on the actual situation; for example, it is set to 2°C. This indicates the 10th percentile within the statistical period, which is preferably the last 30 days. It represents the standard performance data for the worst tenths place. This indicates that data will be recorded continuously over a period of approximately 30 days. After sorting from smallest to largest, the quantiles are calculated based on the Type-7 quantile method. This represents the dimensionless risk score that is cropped to [0,1].

[0069] Based on the above ,like Greater than or equal to This ensures that the dew point safety margin is maintained for at least 90% of the statistical period. Not less than the safety margin threshold .like Less than This ensures a dew point safety margin for at least 10% of the statistical period. Less than the safety margin threshold At this point, a relatively stable risk of condensation is identified. It should be understood that at least one in ten time segments is in a vulnerable state very close to the condensation line. Therefore, energy allocation should prioritize increasing ventilation and cautiously lowering the temperature in this area to achieve energy conservation without increasing the risk of condensation.

[0070] Preferably, the formula for calculating the comprehensive regional score is as follows:

[0071] in, For comprehensive regional scoring, Thermal coupling strength; Heat load intensity; To mitigate the risk of condensation; , and The preset weighting coefficients represent the proportions of thermal coupling intensity, heat load intensity, and condensation risk in calculating the comprehensive regional score. For example, , and The values ​​are 0.2, 0.4, and 0.4, respectively. It should be noted that in this embodiment... , and The value is only an example for ease of understanding and is not a limitation.

[0072] Preferably, in step S023, when the comprehensive regional score is greater than or equal to a first threshold, the candidate region is set as a key region; when the comprehensive regional score is greater than or equal to a second threshold but less than the first threshold, the candidate region is set as a secondary key region; when the comprehensive regional score is less than the second threshold, the candidate region is set as a non-key region. The second threshold and the first threshold are preset. For example, the second threshold and the first threshold are 0.4 and 0.6, respectively. For setting the values ​​of the second threshold and the first threshold, an initial threshold is first loaded, and regional determination is performed based on the initial threshold. Then, a target proportion of key regions is set, such as 25%, meaning that 25% of all regions should be considered key regions. At the end of each month, the actual proportion of key regions is statistically analyzed to see if it conforms to 25% of all regions. If so, the initial threshold remains unchanged. If the actual proportion is greater than 25%, the first threshold in the initial threshold is increased to ensure that the key region proportion in the following month is as close to 25% as possible; conversely, the first threshold in the initial threshold is decreased. Over time, a threshold suitable for the current state is obtained. It should be noted that the above methods and values ​​are for illustrative purposes only. Those skilled in the art can use other methods to set different values, as long as they can achieve the effect of distinguishing key areas.

[0073] Preferably, the secondary critical area corresponds to the first calculated control coefficient, and the non-critical area corresponds to the second calculated control coefficient; in step S212, first precooling data is generated, and ventilation and air conditioning are controlled to perform dual feedforward precooling operation based on the first precooling data, the critical area, the secondary critical area, and the non-critical area, including: Step S2121: Generate pre-cooling data for the secondary critical zone based on the first conversion control coefficient and the first pre-cooling data; Step S2122: Generate non-critical area pre-cooling data for non-critical areas based on the second conversion control coefficient and the first pre-cooling data; Step S2123: Pre-cool the critical area according to the first pre-cooling data, pre-cool the secondary critical area according to the secondary critical area pre-cooling data, and pre-cool the non-critical area according to the non-critical area pre-cooling data.

[0074] In this embodiment, the critical area corresponds to the first pre-cooling data, and the values ​​of both the first and second conversion control coefficients are less than 1. For example, the values ​​of the first and second conversion control coefficients are 0.7 and 0.3, respectively. This configuration causes the pre-cooling intensity to decrease progressively from the critical area to the secondary critical area and non-critical area, enabling different intensities of pre-cooling operations for different regions. Compared to the global cooling used in existing technologies, this application achieves targeted air conditioning cooling control, achieving efficient ventilation and cooling while also saving energy.

[0075] For example, if the first pre-cooling data is a step-by-step reduction of the supply air temperature target by 1.0℃-1.5℃ and an increase in supply air volume by 10%-15%, then the pre-cooling data for the secondary critical area should ideally be a step-by-step reduction of the supply air temperature target by 0.7℃-1.05℃ and an increase in supply air volume by 7%-10.5%. However, due to the impossibility of achieving perfect precision, the actual pre-cooling data for the secondary critical area is a step-by-step reduction of the supply air temperature target by 0.5℃-1.0℃ and an increase in supply air volume by 5%-10%. For the pre-cooling data for the non-critical area, no adjustment is made when the step-by-step reduction of the supply air temperature target is less than 0.5℃ and the increase in supply air volume is less than 5%.

[0076] Preferably, instead of setting a first and second conversion control coefficient, the system can directly downgrade the cooling level, i.e., pre-set the pre-cooling level. The critical area, secondary critical area, and non-critical area correspond to the first, second, and third levels, respectively. Taking the first pre-cooling data as an example, the first pre-cooling data corresponds to the first level, while the second and third levels are set and pre-set based on the first pre-cooling data in a downward trend. Therefore, by setting the pre-cooling level, energy-saving control of air conditioning can also be achieved based on the pre-cooling needs of a region.

[0077] Similarly, in steps S220 and S230, pre-cooling operations are performed on different regions based on the above method. Those skilled in the art should know how to control these operations, so this application will not elaborate further.

[0078] It should be noted that regardless of the area of ​​the underground plant where the dual feedforward precooling operation is performed, it must be carried out under the premise of zero condensation.

[0079] Preferably, the method further includes: Step S310: Determine whether the dual feedforward precooling operation is complete; Step S320: If the determination is yes, then control the ventilation and air conditioning to perform a pre-cooling callback operation.

[0080] Preferably, step S310 specifically includes: Step S311: Determine whether the temperature of the pre-cooled area is stable within the target temperature zone, and whether the dew point safety margin of the pre-cooled area is not less than 2°C; Step S312: If the determination is yes, then the dual feedforward precooling operation is completed; Step S313: If the determination is negative, then the dual feedforward precooling operation is not completed.

[0081] In this embodiment, the pre-cooled area is the area undergoing dual feedforward pre-cooling operation, including a critical area, a secondary critical area, and a non-critical area. The target temperature band is preset and corresponds to the critical, secondary critical, and non-critical areas. Each area has a temperature range that needs to be maintained, i.e., the target temperature band. After a period of dual feedforward pre-cooling operation, the temperature data of the pre-cooled area is monitored in real time. When it is determined that the temperature of the pre-cooled area is stable within the target temperature band, and the dew point safety margin of the pre-cooled area is not less than 2°C, it indicates that the pre-cooling operation is complete; otherwise, it is determined that it is incomplete.

[0082] Preferably, in step S320, after determining that precooling has been completed, it is necessary to revert to the previous state as soon as possible to avoid the problem of high energy consumption caused by prolonged precooling. However, during the revert to the previous state, it is necessary to ensure that the precooled area is not affected.

[0083] Preferably, the ventilation and air conditioning system is controlled to perform a pre-cooling callback operation, and the specific steps are as follows: First, increase the air supply setting by 0.2°C to 0.3°C every 5 minutes. After raising the temperature, observe for 5 to 10 minutes to confirm that the temperature does not rebound. Then, increase the setting again until it reaches the normal air conditioning air supply setting before the incident. Gradually decrease the air supply volume by 2%-3% every 3 minutes. If the temperature rises by more than 0.5°C or the slope exceeds 0.05°C per minute within 10 minutes, immediately return to the previous setting. Otherwise, gradually adjust to the normal air conditioning air supply setting.

[0084] Therefore, pre-cooling is performed first. After pre-cooling is completed, the temperature and air volume are gradually reduced to the normal air conditioning air supply setting. This achieves targeted pre-cooling and energy saving after pre-cooling, avoiding the problem of increased power and excessive energy consumption caused by the need to run more air conditioning units due to sudden temperature rise.

[0085] Similarly, the pre-cooling pullback operation must be performed under the premise of zero condensation.

[0086] In summary, compared to existing building air conditioning controls based on weather and schedules, which are prone to problems such as pre-cooling being too early or too late, this method uses two-factor feedforward control based on power generation plans and heat source characterization data to achieve pre-cooling operations based on the estimated arrival time and tiered settings. This significantly improves pre-cooling accuracy, pre-cooling effect, and energy-saving performance. Furthermore, this method accurately controls the pre-cooling area by calculating the affected area in real time based on the heat source, and achieves even higher energy efficiency through post-pre-cooling callback control.

[0087] Example 2 like Figure 2 As shown in the figure, this embodiment provides a ventilation and air conditioning control method for an underground powerhouse of a hydropower station, including: The pre-cooling trigger determination module is used to acquire the power generation plan and heat source characterization data of the underground powerhouse, and generate a pre-cooling trigger determination based on the power generation plan and heat source characterization data; The doubly fed precooling execution module is used to control the ventilation and air conditioning system to perform doubly fed-forward precooling operation based on the precooling trigger determination.

[0088] Preferably, the pre-cooling trigger determination module is further configured to: calculate the estimated arrival time of the load increase event based on the power generation plan; calculate the heat source increase based on the heat source characterization data; and generate a pre-cooling trigger determination based on the estimated arrival time and the heat source increase. Preferably, the pre-cooling trigger determination module is further configured to: determine whether the expected arrival time is within a preset time window, or whether the heat source increase is greater than the increase threshold; if the determination is no, a pre-cooling non-trigger determination is generated; if the determination is yes, a pre-cooling trigger determination is generated.

[0089] Preferably, the pre-cooling trigger determination module is further configured to: collect historical data of heat source characterization data within a preset training window, obtain a non-event period sample set based on the historical data; calculate the relative increase, quantile threshold, mean, and standard deviation based on the non-event period sample set; and determine the increase threshold based on the relative increase, quantile threshold, mean, and standard deviation.

[0090] Preferably, the precooling trigger determination includes load event trigger determination, heat source amplitude trigger determination, and dual threshold trigger determination; the doubly-fed precooling execution module is further configured to: generate first precooling data in response to the load event trigger determination, and control the ventilation and air conditioning system to perform dual-feedforward precooling operation according to the first precooling data; generate second precooling data in response to the heat source amplitude trigger determination, and control the ventilation and air conditioning system to perform dual-feedforward precooling operation according to the second precooling data; generate third precooling data in response to the dual threshold trigger determination, and control the ventilation and air conditioning system to perform dual-feedforward precooling operation according to the third precooling data.

[0091] Preferably, the doubly fed precooling execution module is further configured to: in response to a load event trigger determination, set a critical zone, a secondary critical zone, and a non-critical zone; generate first precooling data, and control the ventilation and air conditioning system to perform a doubly fed-forward precooling operation based on the first precooling data, the critical zone, the secondary critical zone, and the non-critical zone.

[0092] Preferably, the doubly fed precooling execution module is further configured to: in response to a load event trigger determination, calculate the thermal coupling intensity, heat load intensity, and condensation risk of candidate areas within the underground plant; generate a comprehensive regional score for the candidate areas based on the thermal coupling intensity, the heat load intensity, and the condensation risk; and set critical areas, secondary critical areas, and non-critical areas based on the comprehensive regional score.

[0093] Preferably, the secondary critical area corresponds to a first conversion control coefficient, and the non-critical area corresponds to a second conversion control coefficient; the doubly-fed precooling execution module is further configured to: generate secondary critical area precooling data for the secondary critical area based on the first conversion control coefficient and the first precooling data; generate non-critical area precooling data for the non-critical area based on the second conversion control coefficient and the first precooling data; precool the critical area based on the first precooling data, precool the secondary critical area based on the secondary critical area precooling data, and precool the non-critical area based on the non-critical area precooling data.

[0094] Preferably, the doubly fed precooling execution module is further configured to: determine whether the doubly fed-forward precooling operation is completed; if the determination is yes, control the ventilation and air conditioning to perform a precooling callback operation.

[0095] Preferably, the doubly fed precooling execution module is further configured to: determine whether the temperature of the precooled area is stable within the target temperature band and the dew point safety margin of the precooled area is not less than 2°C; if the determination is yes, then the doubly fed precooling operation is completed; if the determination is no, then the doubly fed precooling operation is not completed.

[0096] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiment. For details on their specific functions and technical effects, please refer to the method embodiment section. They will not be repeated here.

[0097] Example 3 This embodiment is based on embodiment 1: This embodiment provides a computer device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the ventilation and air conditioning control method for an underground powerhouse of a hydropower station according to Embodiment 1. The computer program can be in the form of source code, object code, executable file, or some intermediate form.

[0098] Example 4 This embodiment is based on embodiment 1: This embodiment provides a computer-readable storage medium storing a computer program. When executed by a processor, this computer program implements a ventilation and air conditioning control method for an underground powerhouse in a hydropower station according to Embodiment 1. The computer program can be in the form of source code, object code, executable file, or some intermediate form. The storage medium includes any entity or device capable of carrying computer program code, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0099] The above description is merely a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the concept described herein through the above teachings or related technologies or knowledge. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

[0100] It should be noted that, for the sake of simplicity, the foregoing method embodiments are described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Secondly, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application. Furthermore, the terms "first," "second," and "third," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance.

Claims

1. A method for controlling ventilation and air conditioning in an underground powerhouse of a hydropower station, characterized in that, include: Obtain the power generation plan and heat source characterization data of the underground powerhouse, and generate a pre-cooling trigger determination based on the power generation plan and heat source characterization data; The pre-cooling trigger determination is used to control the ventilation and air conditioning system to perform dual feedforward pre-cooling operation.

2. The ventilation and air conditioning control method for underground powerhouse of a hydropower station according to claim 1, characterized in that, Based on the power generation plan and heat source characterization data, a pre-cooling trigger determination is generated, including: Calculate the estimated arrival time of the load increase event based on the power generation plan; Calculate the heat source amplification based on the heat source characterization data; Determine whether the expected arrival time is within a preset time window, or whether the increase in heat source is greater than the increase threshold; if the determination is no, generate a pre-cooling non-trigger determination; if the determination is yes, generate a pre-cooling trigger determination.

3. The ventilation and air conditioning control method for underground powerhouse of a hydropower station according to claim 2, characterized in that, The calculation method for the increase threshold includes: Historical data of heat source characterization data are collected within a preset training window, and a sample set of non-event periods is obtained based on the historical data. Calculate the relative increase, quantile threshold, mean, and standard deviation based on the sample set from the non-event period; The growth threshold is determined based on the relative growth rate, quantile threshold, and mean and standard deviation.

4. The ventilation and air conditioning control method for underground powerhouse of a hydropower station according to claim 2, characterized in that, The precooling trigger determination includes load event trigger determination, heat source amplitude trigger determination, and dual threshold trigger determination; Based on the pre-cooling trigger determination, the ventilation and air conditioning system is controlled to perform dual feedforward pre-cooling operations, including: In response to the load event trigger determination, first precooling data is generated, and the ventilation and air conditioning system is controlled to perform dual feedforward precooling operation based on the first precooling data; In response to the heat source amplitude trigger determination, second precooling data is generated, and the ventilation and air conditioning system is controlled to perform dual feedforward precooling operation based on the second precooling data; In response to the dual threshold trigger determination, a third precooling data is generated, and the ventilation and air conditioning system is controlled to perform dual feedforward precooling operation based on the third precooling data.

5. The ventilation and air conditioning control method for underground powerhouse of a hydropower station according to claim 4, characterized in that, In response to a load event trigger determination, first precooling data is generated, and the ventilation and air conditioning system is controlled to perform dual feedforward precooling operation based on the first precooling data, including: In response to load event triggering determination, critical areas, secondary critical areas, and non-critical areas are set; Generate the first precooling data, and control the ventilation and air conditioning to perform dual feedforward precooling operation based on the first precooling data, the critical area, the secondary critical area and the non-critical area.

6. The ventilation and air conditioning control method for an underground powerhouse of a hydropower station according to claim 5, characterized in that, The response to the load event trigger determination, setting critical areas, secondary critical areas, and non-critical areas, includes: In response to load event triggering determination, calculate the thermal coupling intensity, heat load intensity, and condensation risk of candidate areas within the underground powerhouse; A comprehensive regional score is generated for candidate regions based on the thermal coupling intensity, the heat load intensity, and the condensation risk. Based on the comprehensive regional score, key areas, secondary key areas, and non-key areas are set.

7. The ventilation and air conditioning control method for underground powerhouse of a hydropower station according to claim 6, characterized in that, The secondary critical area corresponds to the first conversion control coefficient, and the non-critical area corresponds to the second conversion control coefficient; The dual feedforward precooling operation, which controls ventilation and air conditioning based on the first precooling data, critical zone, secondary critical zone, and non-critical zone, includes: The pre-cooling data of the secondary critical zone is generated based on the first conversion control coefficient and the first pre-cooling data. Generate non-critical area pre-cooling data for non-critical areas based on the second conversion control coefficient and the first pre-cooling data; Pre-cooling is performed on critical areas based on the first pre-cooling data, on secondary critical areas based on the pre-cooling data of the secondary critical areas, and on non-critical areas based on the pre-cooling data of the non-critical areas.

8. A ventilation and air conditioning control system for an underground powerhouse of a hydropower station, characterized in that, include: The precooling trigger determination module is configured to acquire the power generation plan and heat source characterization data of the underground powerhouse, and generate a precooling trigger determination based on the power generation plan and heat source characterization data; The doubly fed precooling execution module is configured to control the ventilation and air conditioning system to perform doubly fed-forward precooling operation based on the precooling trigger determination.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the ventilation and air conditioning control method for underground powerhouses of hydropower stations as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the ventilation and air conditioning control method for underground powerhouses of hydropower stations as described in any one of claims 1-7.

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