Remote monitoring method and system for generator set

Abstract

The invention relates to the technical field of equipment management, in particular to a remote monitoring method and system for a generator set, and the method comprises the steps: analyzing the power generation efficiency of each generator according to equipment parameters of each generator and corresponding local environment parameters; identifying a high-humidity area in the generator room according to the humidity distribution data of the generator room; according to the position data and the historical exhaust flow velocity of each generator, generating a corresponding exhaust influence area; performing spatial overlay analysis on the exhaust influence area and the high-humidity area of each generator, and calculating the heat and humidity synergy degree corresponding to each generator in combination with the historical exhaust temperature and the historical exhaust flow rate of the corresponding generator; generating a priority ranking table according to the power generation efficiency of each generator and the corresponding heat and humidity collaboration degree; and screening a plurality of generators as target generators according to the load power, the rated power of each generator and the priority ranking table. According to the scheme, dehumidification energy consumption can be reduced, the service life of equipment is prolonged, and power generation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment management, and particularly to a remote monitoring method and system for a generator set. Background Art

[0002] With the continuous improvement of industrial automation level and the increasing demand for energy management, as the core power supply equipment of the power system, the real-time monitoring and intelligent control management of the operating status of the generator set have become the key links to ensure the stability of the power system and improve the energy utilization efficiency. Traditional generator set monitoring technologies mainly rely on local acquisition of single-unit operating parameters and simple logic control, such as threshold monitoring of basic parameters such as voltage, current, and temperature, and start-stop scheduling strategies based on load power. Although such methods can meet the basic power supply requirements, there are significant limitations in adaptability, energy efficiency optimization, and equipment protection under complex working conditions.

[0003] First of all, the humidity management of the operating environment of the generator set is an important factor affecting the reliability and life of the equipment. Existing technologies usually use a single environmental humidity sensor to monitor the overall humidity of the machine room and trigger the dehumidification equipment based on a fixed threshold. However, due to uneven air flow distribution, equipment heat dissipation differences, wall and floor water seepage and other factors in the generator room, humidity accumulation is likely to occur in local areas (such as around high-voltage electrical cabinets and the air inlet of the cooling system), resulting in condensation or corrosion of metal components. The global humidity monitoring mode of existing technologies cannot identify such local anomalies, causing the dehumidification equipment to operate excessively or start and stop ineffectively, which not only increases energy consumption, but also accelerates equipment aging due to lagging humidity regulation. In addition, too high environmental humidity will exacerbate the decline of electrical insulation performance, cause corona discharge or increase contact resistance, and directly reduce the power generation efficiency.

[0004] Therefore, there is an urgent need to provide a remote monitoring method and system for a generator set, which can reduce dehumidification energy consumption, extend the equipment life, and improve the power generation efficiency. Summary of the Invention

[0005] The present invention provides a remote monitoring method and system for a generator set, which can reduce dehumidification energy consumption, extend the equipment life, and improve the power generation efficiency.

[0006] The first basic solution provided by the present invention: A remote monitoring method for a generator set, comprising the following steps: Obtain the load power, equipment parameters of each generator, local environmental parameters at the location of each generator, and humidity distribution data of the generator room; the equipment parameters include the location data of the generator, historical exhaust gas flow rate, historical exhaust gas temperature, and rated power; Analyze the power generation efficiency of each generator according to the equipment parameters of each generator and the corresponding local environmental parameters; Construct a humidity thermal map of the generator room based on the humidity distribution data of the generator room, and identify high-humidity areas where the humidity value in the generator room exceeds the preset humidity threshold; Analyze the heat diffusion range of the exhaust gas of each generator according to the position data and historical exhaust gas flow rate of each generator, and generate the exhaust gas influence area of each generator; Perform spatial overlay analysis on the exhaust gas influence area of each generator and the high-humidity area respectively, and calculate the heat and humidity synergy degree corresponding to each generator according to the spatial overlay analysis result, the historical exhaust gas temperature and historical exhaust gas flow rate of the corresponding generator; The heat and humidity synergy degree includes the overlapping area of the exhaust gas influence area and the high-humidity area and the humidity reduction potential coefficient of the generator; Generate a priority ranking table according to the power generation efficiency of each generator and the heat and humidity synergy degree corresponding to each generator; Select several generators as target generators according to the load power, the rated power of each generator and the priority ranking table, and control the target generators to start and run.

[0007] Furthermore, calculate the heat and humidity synergy degree corresponding to each generator according to the spatial overlay analysis result, the historical exhaust gas temperature and historical exhaust gas flow rate of the corresponding generator, including: Generate the overlapping area of the exhaust gas influence area and the high-humidity area and the position data of the overlapping area according to the spatial overlay analysis result; Analyze the interval distance between the generator and the overlapping area according to the position data of the generator and the position data of the overlapping area; Calculate the humidity reduction potential coefficient of the generator according to the overlapping area, the interval distance, the historical exhaust gas temperature and the historical exhaust gas flow rate.

[0008] Furthermore, the calculation formula of the humidity reduction potential coefficient is as follows:

[0009] In the formula, is the humidity reduction potential coefficient, is the spatial attenuation coefficient, is the interval distance, is the overlapping area, is the average value of the historical exhaust gas flow rate, is the total number of records of the historical exhaust gas temperature, is the exhaust gas temperature of the th record in the historical exhaust gas temperature record, is the time attenuation coefficient, is the current time, is the record time corresponding to the exhaust gas temperature of the th exhaust gas temperature in the historical exhaust gas temperature record.

[0010] Further, a priority ranking table is generated according to the power generation efficiency of each generator and the heat and humidity synergy degree corresponding to each generator, including: By means of artificial intelligence, according to the power generation efficiency of each generator and the heat and humidity synergy degree corresponding to each generator, analyze the heat and humidity synergy energy efficiency score of each generator, and use the power generation efficiency, overlapping area and humidity reduction potential coefficient corresponding to the generator as the input of the input layer, and the heat and humidity synergy energy efficiency score of the generator as the output of the output layer; Generate a priority ranking table according to the heat and humidity synergy energy efficiency score of each generator.

[0011] Further, the local environmental parameters include local environmental temperature and local environmental humidity.

[0012] Further, according to the equipment parameters of each generator and the corresponding local environmental parameters, analyze the power generation efficiency of each generator, including: analyzing whether the local environmental temperature is within the preset working temperature range. If so, analyze the power generation efficiency of the corresponding generator according to the equipment parameters and local environmental humidity. If not, analyze the power generation efficiency of the corresponding generator according to the equipment parameters, local environmental temperature and local environmental humidity.

[0013] Further, the equipment parameters also include maintenance interval time, start-stop state and the number of start-stop times within a preset time period.

[0014] Further, the calculation formula of the power generation efficiency is as follows:

[0015] In the formula, is the power generation efficiency, is the rated efficiency of the generator under ideal conditions, is the start-stop loss coefficient, represents the start-stop state of the generator. If the start-stop state of the generator is starting, then ; if the start-stop state of the generator is shutting down, then ; is the start-stop frequency influence coefficient, is the number of start-stop times within a preset time period, is the temperature sensitivity coefficient, is the local environmental temperature, is the optimal working temperature, is the temperature value that can fluctuate, is the health attenuation coefficient, is the maintenance interval time, is the humidity influence coefficient, is the local environmental humidity, is the optimal relative humidity.

[0016] Basic Solution 2 provided by the present invention: A remote monitoring system for a generator set uses the above-mentioned remote monitoring method for a generator set.

[0017] The principle and advantages of the present invention are as follows: 1. By constructing a humidity thermal map of the machine room, the position and area of high-humidity areas can be dynamically identified. Through the spatial superposition analysis of the influence range of the generator exhaust, the generators whose exhaust covers the high-humidity areas are preferentially scheduled to operate. Thus, the exhaust heat can be used to dry the high-humidity areas, realizing waste heat utilization and reducing the startup frequency of independent dehumidification equipment.

[0018] 2. By calculating the humidity reduction potential coefficient, the ability of each generator to reduce humidity through exhaust heat is quantified. The humidity reduction potential coefficient combines the overlapping area, the distance between intervals, the historical exhaust temperature, the exhaust temperature decay characteristic, and the historical exhaust flow rate, and can accurately evaluate the drying contribution degree of different generators to high-humidity areas. Combining the power generation efficiency and the overlapping area to generate a thermal-humidity synergistic energy efficiency score, so that the selected target generators can not only meet the load requirements but also maximize the thermal-humidity synergistic benefits.

[0019] 3. Multiple correction factors such as the local ambient temperature, local ambient humidity, maintenance interval time, start-stop state, and start-stop times are introduced to predict the power generation efficiency, improving the accuracy of power generation efficiency evaluation. In addition, when the local ambient temperature exceeds the optimal working range, the temperature sensitivity coefficient is used to dynamically correct the efficiency value, avoiding the evaluation error caused by the traditional fixed coefficient. The maintenance interval time can also be introduced to automatically reduce the scheduling priority of generators that have not been maintained for a long time, indirectly prompting the operation and maintenance requirements and extending the service life of the equipment.

[0020] 4. By comprehensively considering the power generation efficiency of each generator and the thermal-humidity synergy degree corresponding to each generator, a priority ranking table is generated, which can quickly screen out the target unit combinations with high load matching degree and excellent thermal-humidity synergy among multiple generators.

[0021] In summary, by adopting this solution, the dehumidification energy consumption can be reduced, the equipment life can be extended, the power generation efficiency can be improved, and the overall improvement of the generator operation efficiency, environmental adaptability, and operation and maintenance economy is realized. Description of the Drawings

[0022] Figure 1 It is a flowchart of an embodiment of a remote monitoring method for a generator set of the present invention. Detailed Description of the Invention

[0023] The following is a more detailed description through specific embodiments: Embodiment 1: Embodiment 1 is basically as shown in the attached Figure 1 figure: A remote monitoring method for a generator set, asFigure 1 As shown in Figure 1 , it includes the following steps (the labels are only for distinguishing the steps and do not limit the execution order of each step): S100, obtain the load power, the equipment parameters of each generator, the local environmental parameters of the location where each generator is located, and the humidity distribution data of the generator room; the equipment parameters include the location data of each generator, the historical exhaust gas flow rate, the historical exhaust gas temperature, the rated power, the maintenance interval time, the start-stop state, and the number of start-stop times within a preset time period; the local environmental parameters include the local environmental temperature and the local environmental humidity.

[0024] In this embodiment, the current load demand of the data center is monitored in real time through an intelligent electricity meter to obtain the load power; the three-dimensional coordinates of each generator are input by the management personnel as the location data (positioning is based on the floor plan of the machine room), and the rated power and the most recent maintenance time of each generator are input. Thus, the interval time from the current time to the last maintenance time can be automatically calculated as the maintenance interval time based on the most recent maintenance time; the exhaust gas flow rate and exhaust gas temperature recorded in the most recent 10 times are used as the historical exhaust gas flow rate and historical exhaust gas temperature respectively, and the previously recorded exhaust gas flow rate and exhaust gas temperature are automatically deleted from the system; the preset time period is within the recent 30 days, and the number of start-stop times within the recent 30 days is obtained.

[0025] In this embodiment, in order to comprehensively obtain the humidity distribution data of the generator room, a temperature and humidity sensor array is arranged in layers on the top, ground, and equipment layer of the machine room. Specifically, industrial-grade digital temperature and humidity sensors are used to arrange the sensor array in a grid layout of 2m×2m, and an RFID position tag is configured for each sensor. A three-dimensional coordinate system is established through the UWB ultra-wideband positioning system to realize the synchronous acquisition of multiple sensors.

[0026] S200, analyze the power generation efficiency of each generator according to the equipment parameters of each generator and the corresponding local environmental parameters. Specifically, it includes the following steps: analyze whether the local environmental temperature is within the preset working temperature range. If so, analyze the power generation efficiency of the corresponding generator according to the equipment parameters and the local environmental humidity. If not, analyze the power generation efficiency of the corresponding generator according to the equipment parameters, the local environmental temperature, and the local environmental humidity. Thus, when the local environmental temperature exceeds the optimal working range, the temperature parameter can be introduced to dynamically correct the efficiency value, avoiding the evaluation error caused by the traditional fixed coefficient.

[0027] The calculation formula of the power generation efficiency is as follows:

[0028] In the formula, is the power generation efficiency, is the rated efficiency of the generator under ideal conditions, is the start-stop loss coefficient, Indicates the start-stop state of the generator. If the start-stop state of the generator is in the starting process, then , if the start-stop state of the generator is in the shutdown process, then , , is the start-stop frequency influence coefficient, is the number of start-stops within a preset time period, is the temperature sensitivity coefficient, is the local ambient temperature, is the optimal operating temperature, is the temperature value that can fluctuate, is the health attenuation coefficient, is the maintenance interval time, is the humidity influence coefficient, is the local ambient humidity, is the optimal relative humidity.

[0029] Taking the equipment parameters and local ambient parameters corresponding to generator G1 as an example for calculation: rated power 1200kw; start-stop state is in the starting process, ; the number of start-stops within a preset time period is 3 times; the local ambient temperature is 36°C; the optimal operating temperature is 30°C, and the temperature value that can fluctuate is 5°C (that is, the optimal operating temperature range based on the optimal operating temperature is 25°C to 35°C); the maintenance interval time is 150 days; the local ambient humidity is 72%RH, and the optimal relative humidity is 60%RH. Introduce parameters: the rated efficiency of the generator under ideal conditions ; start-stop loss coefficient ; start-stop frequency influence coefficient ; temperature sensitivity coefficient ; health attenuation coefficient ; humidity influence coefficient . Substitute into the formula:

[0030] It can be seen that the power generation efficiency of generator G1 is significantly lower than its rated efficiency, mainly affected by high temperature, high humidity and overdue maintenance.

[0031] S300. According to the humidity distribution data of the generator room, construct a humidity heat map of the machine room and identify the high-humidity areas in the generator room where the humidity value exceeds the preset humidity threshold. Specifically, collect the humidity data of each location in the machine room in real time through a distributed sensing network to form a spatial distribution data set, and use an interpolation algorithm to convert the discrete humidity data into a continuous heat map to generate the humidity heat map of the machine room. It is identified that the area of the high-humidity area in the generator room is 15 .

[0032] S400. Analyze the thermal diffusion range of the exhaust gas of each generator based on the position data and historical exhaust gas flow rate of each generator, and generate the exhaust gas influence area of each generator. In this embodiment, taking generator G1 as an example, the coordinates of generator G1 are (14m, 3m), the orientation of the exhaust port is due east, and the average exhaust gas flow rate is calculated to be 3.8m / s based on the historical exhaust gas flow rate of generator G1. The CFD simulation is used to determine that its thermal diffusion range extends 8m eastward, forming a fan-shaped area (angle 60°, radius 8m).

[0033] S500. Perform a spatial overlay analysis on the exhaust gas influence area of each generator and the high-humidity area respectively, and calculate the thermal-humidity coordination degree corresponding to each generator according to the spatial overlay analysis result, the historical exhaust gas temperature and the historical exhaust gas flow rate of the corresponding generator; the thermal-humidity coordination degree includes the overlapping area between the exhaust gas influence area and the high-humidity area and the humidity reduction potential coefficient of the generator. S500 includes: S501. Generate the overlapping area between the exhaust gas influence area and the high-humidity area and the position data of the overlapping area according to the spatial overlay analysis result; in this embodiment, the overlapping area between the exhaust gas influence area of generator G1 and the high-humidity area is 6 , and the position data of the overlapping area is the coordinate x ∈ [5m, 10m], y ∈ [2m, 5m]; in other embodiments of the present application, since both the exhaust gas influence area and the high-humidity area may be irregular polygons, therefore, GIS can also be used to perform a spatial intersection operation on the exhaust gas influence area and the high-humidity area, and output the geometric shape and vertex coordinates of the overlapping area.

[0034] S502. Analyze the interval distance between the generator and the overlapping area according to the position data of the generator and the position data of the overlapping area; in this embodiment, the interval distance is 6.08m (from the coordinates of generator G1 (14m, 3m) to the center of the overlapping area (8m, 4m)); the overlapping area is a trapezoidal area, and the vertex coordinates are (10m, 2m), (10m, 5m), (14m, 5m), (14m, 2m).

[0035] S503. Calculate the humidity reduction potential coefficient of the generator according to the overlapping area, the interval distance, the historical exhaust gas temperature and the historical exhaust gas flow rate. The calculation formula of the humidity reduction potential coefficient is as follows:

[0036] In the formula, is the humidity reduction potential coefficient, is the spatial attenuation coefficient, is the interval distance, is the overlapping area, is the average value of the historical exhaust gas flow rate, is the total number of records of the historical exhaust gas temperature, is the exhaust gas temperature of the th record in the historical exhaust gas temperature record, is the time decay coefficient, is the current time, is the record time corresponding to the th exhaust gas temperature in the historical exhaust gas temperature record.

[0037] Thus, by calculating the humidity reduction potential coefficient, the ability of each generator to reduce humidity through exhaust heat can be quantified. The higher the humidity reduction potential coefficient, the higher the ability of the generator to reduce humidity through exhaust heat.

[0038] S600 generates a priority ranking table according to the power generation efficiency of each generator and the thermal-humidity synergy degree corresponding to each generator. S600 includes: S601, in an artificial intelligence manner, analyzes the thermal-humidity synergy energy efficiency scores of each generator according to the power generation efficiency of each generator and the thermal-humidity synergy degree corresponding to each generator, takes the power generation efficiency, overlapping area, and humidity reduction potential coefficient corresponding to the generator as the inputs of the input layer, and takes the thermal-humidity synergy energy efficiency score of the generator as the output of the output layer.

[0039] In this embodiment, the BP neural network technology is used to score the thermal-humidity synergy energy efficiency of the generator. Specifically, first, a three-layer BP neural network model is constructed, including an input layer, a hidden layer, and an output layer. In this embodiment, the power generation efficiency, overlapping area, and humidity reduction potential coefficient corresponding to the generator are used as the inputs of the input layer. Therefore, the input layer has 3 nodes, and the output is the thermal-humidity synergy energy efficiency score (0-100) of the generator. Therefore, there is a total of 1 node. For the hidden layer, the following formula is used in this embodiment to determine the number of nodes in the hidden layer: ; where L is the number of nodes in the hidden layer, n is the number of nodes in the input layer, m is the number of nodes in the output layer, and a is a number between 1 and 10. In this embodiment, it is taken as 6. Therefore, the hidden layer has a total of 8 nodes. The BP neural network usually uses the Sigmoid differentiable function and the linear function as the activation functions of the network. In this embodiment, the S-shaped tangent function tansig is selected as the activation function of the hidden layer neurons. The S-shaped logarithmic function tansig is selected as the activation function of the output layer neurons for the prediction model. After the BP network model is constructed, 500 groups of samples are generated using historical operation data to train the model. The evaluation model obtained after training with historical operation data can obtain relatively accurate evaluation results.

[0040] S602 generates a priority ranking table according to the thermal-humidity synergy energy efficiency scores of each generator.

[0041] S700 selects several generators as target generators according to the load power, the rated power of each generator, and the priority ranking table, and controls the target generators to start and operate. Specifically, N generators are sequentially selected from the priority ranking table. While ensuring that the ratio of the sum of the rated powers of the selected generators to the load power is greater than a preset ratio threshold, it is also necessary to ensure that the number of generators to be started is minimized. Thus, it is possible to prevent the load rate of the generators from being too high and at the same time reduce the number of generators to be started.

[0042] In other embodiments of the present application, it is also possible to only score the thermal and humidity co - energy efficiency for the generators that have been started to generate a priority ranking table, and then adjust the load of each generator according to the priority ranking table.

[0043] Embodiment 2: A remote monitoring system for a generator set uses the above - mentioned remote monitoring method for a generator set, and includes: A data acquisition module that acquires the load power, the equipment parameters of each generator, the local environmental parameters of the location of each generator, and the humidity distribution data of the generator room; the equipment parameters include the location data, the historical exhaust gas flow rate, the historical exhaust gas temperature, and the rated power of each generator; An efficiency analysis module that analyzes the power generation efficiency of each generator according to the equipment parameters of each generator and the corresponding local environmental parameters; A high - humidity area analysis module that constructs a humidity thermal map of the machine room according to the humidity distribution data of the generator room and identifies high - humidity areas in the generator room where the humidity value exceeds a preset humidity threshold; An exhaust analysis module that analyzes the thermal diffusion range of the exhaust gas of each generator according to the location data and the historical exhaust gas flow rate of each generator, and generates an exhaust influence area for each generator; A thermal - humidity synergy degree analysis module that respectively performs a spatial overlay analysis of the exhaust influence area of each generator and the high - humidity area, and calculates the corresponding thermal - humidity synergy degree of each generator according to the spatial overlay analysis result, the historical exhaust gas temperature, and the historical exhaust gas flow rate of the corresponding generator; the thermal - humidity synergy degree includes the overlapping area between the exhaust influence area and the high - humidity area and the humidity reduction potential coefficient of the generator; A ranking table generation module that generates a priority ranking table according to the power generation efficiency of each generator and the corresponding thermal - humidity synergy degree of each generator; A generator screening module that selects several generators as target generators according to the load power, the rated power of each generator, and the priority ranking table, and controls the target generators to start and operate.

[0044] The above are only embodiments of the present invention. Common general knowledge such as specific structures and characteristics known in the art is not described in detail herein. Those of ordinary skill in the art know all the general technical knowledge in the technical field to which the invention pertains before the filing date or the priority date, are able to learn all the prior art in this field, and have the ability to apply conventional experimental means before this date. Those of ordinary skill in the art can, with the inspiration given in this application and in combination with their own abilities, complete and implement this solution. Some typical well-known structures or well-known methods should not become an obstacle for those of ordinary skill in the art to implement this application. It should be noted that for those skilled in the art, without departing from the structure of the present invention, several modifications and improvements can still be made, and these should also be regarded as the protection scope of the present invention, and these will not affect the implementation effect of the present invention and the practicality of the patent. The protection scope claimed in this application should be based on the content of its claims, and the specific implementation manners described in the specification can be used to interpret the content of the claims.

Claims

1. A remote monitoring method for a generator set, characterized in that: Including the following steps: Obtain the load power, equipment parameters of each generator, local environmental parameters of the location where each generator is located, and humidity distribution data of the generator room; the equipment parameters include the location data of the generator, historical exhaust gas flow rate, historical exhaust gas temperature, and rated power; Analyze the power generation efficiency of each generator according to the equipment parameters of each generator and the corresponding local environmental parameters; Construct a humidity thermal map of the generator room based on the humidity distribution data of the generator room, and identify high-humidity areas in the generator room where the humidity value exceeds the preset humidity threshold; Analyze the heat diffusion range of the exhaust gas of each generator according to the location data and historical exhaust gas flow rate of each generator, and generate the exhaust gas influence area of each generator; Perform a spatial overlay analysis of the exhaust gas influence area of each generator and the high-humidity area respectively, and calculate the heat and humidity coordination degree corresponding to each generator according to the spatial overlay analysis result, the historical exhaust gas temperature and historical exhaust gas flow rate of the corresponding generator; the heat and humidity coordination degree includes the overlapping area of the exhaust gas influence area and the high-humidity area and the humidity reduction potential coefficient of the generator; Generate a priority ranking table according to the power generation efficiency of each generator and the heat and humidity coordination degree corresponding to each generator; Select several generators as target generators according to the load power, the rated power of each generator, and the priority ranking table, and control the target generators to start and operate.

2. The remote monitoring method for a generator set according to claim 1, characterized in that: Calculate the heat and humidity coordination degree corresponding to each generator according to the spatial overlay analysis result, the historical exhaust gas temperature and historical exhaust gas flow rate of the corresponding generator, including: Generate the overlapping area of the exhaust gas influence area and the high-humidity area and the location data of the overlapping area according to the spatial overlay analysis result; Analyze the interval distance between the generator and the overlapping area according to the location data of the generator and the location data of the overlapping area; Calculate the humidity reduction potential coefficient of the generator according to the overlapping area, interval distance, historical exhaust gas temperature, and historical exhaust gas flow rate.

3. The remote monitoring method for a generator set according to claim 2, characterized in that: The calculation formula of the humidity reduction potential coefficient is as follows: In the formula, is the humidity reduction potential coefficient, is the spatial attenuation coefficient, is the interval distance, is the overlapping area, is the average value of the historical exhaust gas flow rate, is the total number of records of the historical exhaust gas temperature, is the th exhaust gas temperature in the historical exhaust gas temperature records, is the time attenuation coefficient, is the current time, is the th recording time corresponding to the exhaust gas temperature in the historical exhaust gas temperature records.

4. The remote monitoring method for a generator set according to claim 1, characterized in that: Generate a priority ranking table according to the power generation efficiency of each generator and the heat and humidity coordination degree corresponding to each generator, including: Through artificial intelligence, analyze the heat and humidity coordination energy efficiency score of each generator according to the power generation efficiency of each generator and the heat and humidity coordination degree corresponding to each generator, use the power generation efficiency, overlapping area, and humidity reduction potential coefficient corresponding to the generator as the input of the input layer, and the heat and humidity coordination energy efficiency score of the generator as the output of the output layer; Generate a priority ranking table according to the heat and humidity coordination energy efficiency score of each generator.

5. The remote monitoring method for a generator set according to claim 1, characterized in that: The local environmental parameters include local environmental temperature and local environmental humidity.

6. The remote monitoring method of the generator set according to claim 5, characterized in that: Analyze the power generation efficiency of each generator according to the equipment parameters of each generator and the corresponding local environmental parameters, including: analyze whether the local environmental temperature is within the preset working temperature range, if so, analyze the power generation efficiency of the corresponding generator according to the equipment parameters and local environmental humidity, if not, analyze the power generation efficiency of the corresponding generator according to the equipment parameters, local environmental temperature, and local environmental humidity.

7. The remote monitoring method for a generator set according to claim 6, characterized in that: The equipment parameters also include the maintenance interval time, start-stop status, and start-stop times within a preset time period.

8. The remote monitoring method for a generator set according to claim 7, characterized in that: The calculation formula of the power generation efficiency is as follows: Wherein, is the power generation efficiency, is the rated efficiency of the generator under ideal conditions, is the start-stop loss coefficient, represents the start-stop state of the generator. If the start-stop state of the generator is in the starting process, then , if the start-stop state of the generator is in the shutdown process, then , is the start-stop frequency influence coefficient, is the number of start-stops within a preset time period, is the temperature sensitivity coefficient, is the local ambient temperature, is the optimal operating temperature, is the temperature value that can fluctuate, is the health attenuation coefficient, is the maintenance interval time, is the humidity influence coefficient, is the local ambient humidity, is the optimal relative humidity.

9. A remote monitoring system for a generator set, characterized in that: The remote monitoring method for a generator set according to any one of claims 1 to 8 above is used.

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