A remote monitoring method and system for generator sets

Abstract

The present invention relates to the field of equipment management technology, and in particular to a method and system for remote monitoring of generator sets, the method comprising: analyzing the power generation efficiency of each generator based on the equipment parameters of each generator and the corresponding local environmental parameters; identifying high-humidity areas within the generator room based on the humidity distribution data of the generator room; generating corresponding exhaust impact areas based on the location data and historical exhaust flow rate of each generator; spatially superimposing the exhaust impact areas of each generator with the high-humidity areas, and calculating the corresponding heat-humidity coordination degree of each generator in combination with the historical exhaust temperature and historical exhaust flow rate of the corresponding generator; generating a priority ranking table based on the power generation efficiency of each generator and the corresponding heat-humidity coordination degree; and selecting several generators as target generators based on the load power, the rated power of each generator, and the priority ranking table. This solution can reduce dehumidification energy consumption, extend equipment life, and improve power generation efficiency.

Description

Technical Field

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

[0002] With the continuous improvement of industrial automation and the growing demand for energy management, real-time monitoring and intelligent control of the operating status of generator sets, the core power supply equipment of power systems, have become critical for ensuring power system stability and improving energy efficiency. Traditional generator set monitoring technologies rely primarily on localized acquisition and simple logic control of single-unit operating parameters, such as threshold monitoring of basic parameters such as voltage, current, and temperature, and load-based start-stop scheduling strategies. While such methods can meet basic power supply needs, they have significant limitations in adaptability, energy efficiency optimization, and equipment protection under complex operating conditions.

[0003] First, humidity management in the generator set's operating environment is a crucial factor affecting equipment reliability and lifespan. Existing technologies typically use a single ambient humidity sensor to monitor the overall humidity in the equipment room and trigger dehumidification equipment based on a fixed threshold. However, due to factors such as uneven airflow distribution within the generator room, varying heat dissipation from equipment, and water seepage through walls and floors, humidity can easily accumulate in localized areas (such as around high-voltage electrical cabinets and at cooling system air inlets), leading to condensation and corrosion of metal components. Existing technologies' global humidity monitoring models fail to identify such localized anomalies, causing dehumidification equipment to over-operate or ineffectively start and stop. This not only increases energy consumption but also accelerates equipment aging due to delayed humidity control. Furthermore, excessively high ambient humidity can exacerbate the degradation of electrical insulation performance, causing corona discharge or increased contact resistance, directly reducing power generation efficiency.

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

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

[0006] The present invention provides a basic solution 1:

[0007] A method for remote monitoring of a generator set comprises the following steps:

[0008] Obtaining load power, equipment parameters of each generator, local environmental parameters at the location of each generator, and humidity distribution data in the generator room; the equipment parameters include generator location data, historical exhaust flow rate, historical exhaust temperature, and rated power;

[0009] Analyze the power generation efficiency of each generator based on its equipment parameters and corresponding local environmental parameters;

[0010] Based on the humidity distribution data of the generator room, a humidity heat map of the room is constructed to identify high humidity areas in the generator room where the humidity exceeds the preset humidity threshold;

[0011] Based on the location data and historical exhaust flow rate of each generator, the heat diffusion range of each generator's exhaust is analyzed to generate the exhaust impact area of each generator;

[0012] A spatial overlay analysis was performed on the exhaust impact area and high humidity area of each generator. Based on the results of the spatial overlay analysis and the historical exhaust temperature and exhaust flow rate of the corresponding generator, the thermal-humidity synergy of each generator was calculated. The thermal-humidity synergy includes the overlapping area of the exhaust impact area and the high humidity area and the humidity reduction potential coefficient of the generator.

[0013] Generate a priority ranking table based on the power generation efficiency of each generator and the corresponding heat and moisture synergy of each generator;

[0014] According to the load power, the rated power of each generator and the priority ranking table, several generators are selected as target generators, and the target generators are controlled to start and run.

[0015] Furthermore, based on the spatial superposition analysis results, the historical exhaust temperature and historical exhaust flow rate of the corresponding generator, the heat and humidity synergy corresponding to each generator is calculated, including:

[0016] Based on the results of spatial overlay analysis, the overlap area and location data of the exhaust impact area and the high humidity area are generated;

[0017] Analyze the distance between the generator and the overlapping area based on the generator's position data and the overlapping area's position data;

[0018] A humidity reduction potential coefficient of the generator is calculated based on the overlap area, the separation distance, the historical exhaust temperature, and the historical exhaust flow rate.

[0019] Furthermore, the calculation formula of the humidity reduction potential coefficient is as follows:

[0020]

[0021] Where, is the humidity reduction potential coefficient, is the spatial attenuation coefficient, is the interval distance, is the overlapping area, is the mean value of the historical exhaust flow rate, is the total number of historical exhaust temperature records, The exhaust temperature record The recorded exhaust gas temperature, is the time attenuation coefficient, is the current time, The exhaust temperature record The recording time corresponding to the exhaust temperature.

[0022] Furthermore, a priority ranking table is generated based on the power generation efficiency of each generator and the corresponding heat and moisture synergy of each generator, including:

[0023] Through artificial intelligence, the heat-humidity synergy energy efficiency score of each generator is analyzed based on the power generation efficiency of each generator and the corresponding heat-humidity synergy degree of each generator. The power generation efficiency, overlap area and humidity reduction potential coefficient of the generator are used as the input layer, and the heat-humidity synergy energy efficiency score of the generator is used as the output layer.

[0024] A priority ranking table is generated based on the thermal and moisture synergy energy efficiency score of each generator.

[0025] Furthermore, the local environmental parameters include local environmental temperature and local environmental humidity.

[0026] Furthermore, the power generation efficiency of each generator is analyzed based on the equipment parameters of each generator and the corresponding local environmental parameters, including: analyzing whether the local environmental temperature is within the preset operating temperature range; if so, analyzing the power generation efficiency of the corresponding generator based on the equipment parameters and the local environmental humidity; if not, analyzing the power generation efficiency of the corresponding generator based on the equipment parameters, the local environmental temperature and the local environmental humidity.

[0027] Furthermore, the equipment parameters also include maintenance interval time, start and stop status, and the number of starts and stops within a preset time period.

[0028] Furthermore, the calculation formula of the power generation efficiency is as follows:

[0029]

[0030] Where, For power generation efficiency, is the rated efficiency of the generator under ideal conditions, is the start-stop loss coefficient, Indicates the start / stop status of the generator. If the start / stop status of the generator is starting, then If the generator start-stop state is shutting down, then , is the start-stop frequency influence coefficient, is the number of starts and stops within the preset time period, is the temperature sensitivity coefficient, is the local ambient temperature, For the best working temperature, is the fluctuating temperature value, is the health attenuation coefficient, For maintenance intervals, is the humidity influence coefficient, is the local ambient humidity, The optimal relative humidity.

[0031] The present invention provides a second basic solution: a generator set remote monitoring system, which uses the above-mentioned generator set remote monitoring method.

[0032] The principles and advantages of the present invention are:

[0033] 1. By constructing a heat map of the humidity in the equipment room, we can dynamically identify the location and area of high-humidity areas. Combined with a spatial overlay analysis of the generator exhaust impact range, we prioritize the operation of generators whose exhaust covers high-humidity areas. This allows us to use exhaust heat to dry out high-humidity areas, reusing waste heat and reducing the frequency of starting standalone dehumidification equipment.

[0034] 2. Quantify each generator's ability to reduce humidity through exhaust heat by calculating its humidity reduction potential coefficient. This coefficient incorporates the overlap area, separation distance, historical exhaust temperature, exhaust temperature decay characteristics, and historical exhaust flow rate to accurately assess the contribution of each generator to drying high-humidity areas. A heat-humidity synergy energy efficiency score is generated by combining power generation efficiency and overlap area, enabling targeted generator selection to meet load requirements while maximizing heat-humidity synergy benefits.

[0035] 3. Multiple correction factors, including local ambient temperature, humidity, maintenance interval, start / stop status, and number of starts / stops, are introduced to predict power generation efficiency, improving the accuracy of power generation efficiency assessments. Furthermore, when the local ambient temperature exceeds the optimal operating range, a temperature sensitivity coefficient is used to dynamically correct the efficiency value, avoiding the assessment errors caused by traditional fixed coefficients. Furthermore, by introducing maintenance intervals, the dispatch priority of generators that have not been maintained for a long time is automatically lowered, indirectly indicating maintenance needs and extending equipment life.

[0036] 4. By comprehensively considering the power generation efficiency of each generator and the corresponding thermal and moisture synergy of each generator, a priority ranking table is generated, which can quickly screen out the target unit combination with high load matching and excellent thermal and moisture synergy from multiple generators.

[0037] In summary, the adoption of this solution can reduce dehumidification energy consumption, extend equipment life, and improve power generation efficiency, thereby achieving a comprehensive improvement in generator operating efficiency, environmental adaptability, and operation and maintenance economy. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 The present invention is a flowchart of a method for remotely monitoring a generator set according to an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The following is further described in detail through specific implementation methods:

[0040] Example 1:

[0041] Example 1 is basically as shown in the attached Figure 1 As shown:

[0042] A remote monitoring method for a generator set, such as Figure 1 As shown, the following steps are included (the numbers are only used to distinguish the steps, and do not limit the execution order of the steps):

[0043] S100, obtain the load power, equipment parameters of each generator, local environmental parameters of the location of each generator, and humidity distribution data of the generator room; the equipment parameters include the location data of each generator, historical exhaust flow rate, historical exhaust temperature, rated power, maintenance interval, start and stop status, and the number of starts and stops within a preset time period; the local environmental parameters include local ambient temperature and local ambient humidity.

[0044] In this embodiment, the current load demand of the data center is monitored in real time by a smart meter to obtain the load power; the management personnel input the three-dimensional coordinates of each generator as the location data (positioned according to the floor plan of the computer room), and input the rated power of each generator and the most recent maintenance time. Thus, the interval between the current time and the last maintenance time can be automatically calculated based on the most recent maintenance time as the maintenance interval time; the exhaust flow rate and exhaust temperature recorded in the last 10 times are used as the historical exhaust flow rate and historical exhaust temperature, respectively, and the previously recorded exhaust flow rate and exhaust temperature are automatically deleted in the system; the preset time period is within the past 30 days, and the number of starts and stops within the past 30 days is obtained.

[0045] In this embodiment, in order to comprehensively obtain the humidity distribution data of the generator room, temperature and humidity sensor arrays are arranged in layers on the top, ground and equipment layers of the room. Specifically, industrial-grade digital temperature and humidity sensors are used to arrange the sensor array in a 2m×2m grid layout, and an RFID location tag is configured for each sensor. A three-dimensional coordinate system is established through the UWB ultra-wideband positioning system to achieve synchronous acquisition of multiple sensors.

[0046] S200 analyzes the power generation efficiency of each generator based on its device parameters and corresponding local environmental parameters. This specifically includes the following steps: analyzing whether the local ambient temperature is within a preset operating temperature range; if so, analyzing the power generation efficiency of the corresponding generator based on the device parameters and the local ambient humidity; if not, analyzing the power generation efficiency of the corresponding generator based on the device parameters, the local ambient temperature, and the local ambient humidity. This allows the temperature parameter to be used to dynamically modify the efficiency value when the local ambient temperature exceeds the optimal operating range, avoiding the evaluation errors caused by traditional fixed coefficients.

[0047] The calculation formula of the power generation efficiency is as follows:

[0048]

[0049] Where, For power generation efficiency, is the rated efficiency of the generator under ideal conditions, is the start-stop loss coefficient, Indicates the start / stop status of the generator. If the start / stop status of the generator is starting, then If the generator start-stop state is shutting down, then , , is the start-stop frequency influence coefficient, is the number of starts and stops within the preset time period, is the temperature sensitivity coefficient, is the local ambient temperature, For the best working temperature, is the fluctuating temperature value, is the health attenuation coefficient, For maintenance intervals, is the humidity influence coefficient, is the local ambient humidity, The optimal relative humidity.

[0050] Take the equipment parameters and local environmental parameters corresponding to generator G1 as an example for calculation: rated power 1200kw; start-stop state is starting, The number of starts and stops within the preset time period is 3; the local ambient temperature is 36°C; the optimal operating temperature is 30°C, with a temperature fluctuation of 5°C (i.e., the optimal operating temperature range based on the optimal operating temperature is 25°C to 35°C); the maintenance interval is 150 days; the local ambient humidity is 72% RH, with an optimal relative humidity of 60% RH. Introduced parameters: 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:

[0051]

[0052] It can be seen that the power generation efficiency of generator G1 is significantly lower than its rated efficiency, which is mainly affected by high temperature, high humidity and overdue maintenance.

[0053] S300: Based on the humidity distribution data of the generator room, a humidity heat map of the room is constructed to identify high humidity areas in the generator room where the humidity value exceeds the preset humidity threshold. Specifically, the humidity data of each location in the room is collected in real time through a distributed sensor network to form a spatial distribution data set. The discrete humidity data is converted into a continuous heat map using an interpolation algorithm to generate a humidity heat map of the room. The area of the high humidity area in the generator room is identified as 15 .

[0054] S400: Based on the location data and historical exhaust flow rate of each generator, the heat diffusion range of each generator's exhaust is analyzed to generate the exhaust impact area of each generator. In this embodiment, taking generator G1 as an example, the coordinates of generator G1 are (14m, 3m), the exhaust port faces due east, and the average exhaust flow rate calculated based on the historical exhaust flow rate of generator G1 is 3.8m / s. CFD simulation determines that the heat diffusion range extends 8m to the east, forming a fan-shaped area (angle 60°, radius 8m).

[0055] S500: Perform spatial overlay analysis on the exhaust impact area and high humidity area of each generator. Calculate the thermal-humidity synergy for each generator based on the results of the spatial overlay analysis and the historical exhaust temperature and exhaust flow rate of the corresponding generator. The thermal-humidity synergy includes the overlapping area of the exhaust impact area and the high humidity area and the humidity reduction potential coefficient of the generator. S500 includes:

[0056] S501: Generate the overlapped area and position data of the exhaust gas affected area and the high humidity area according to the spatial superposition analysis results; in this embodiment, the overlapped area of the exhaust gas affected area and the high humidity area of the generator G1 is 6 , the position data of the overlapping area is the coordinates x∈[5m,10m], y∈[2m,5m]; in other embodiments of the present application, since the exhaust impact area and the high humidity area may be irregular polygons, GIS can also be used to perform spatial intersection operations on the exhaust impact area and the high humidity area to output the geometric shape and vertex coordinates of the overlapping area.

[0057] S502: Analyze the distance between the generator and the overlapping area based on the generator's position data and the overlapping area's position data. In this embodiment, the distance is 6.08 m (from the generator G1 coordinates (14 m, 3 m) to the center of the overlapping area (8 m, 4 m)). The overlapping area is a trapezoidal area with vertex coordinates of (10 m, 2 m), (10 m, 5 m), (14 m, 5 m), and (14 m, 2 m).

[0058] S503, calculating the humidity reduction potential coefficient of the generator based on the overlap area, the spacing distance, the historical exhaust temperature, and the historical exhaust flow rate. The calculation formula of the humidity reduction potential coefficient is as follows:

[0059]

[0060] Where, is the humidity reduction potential coefficient, is the spatial attenuation coefficient, is the interval distance, is the overlapping area, is the mean value of the historical exhaust flow rate, is the total number of historical exhaust temperature records, The exhaust temperature record The recorded exhaust gas temperature, is the time attenuation coefficient, is the current time, The exhaust temperature record The recording time corresponding to the exhaust temperature.

[0061] Therefore, the ability of each generator to reduce humidity through exhaust heat can be quantified by calculating the humidity reduction potential coefficient. The higher the humidity reduction potential coefficient, the higher the generator's ability to reduce humidity through exhaust heat.

[0062] S600: Generate a priority ranking table based on the power generation efficiency of each generator and the heat and humidity coordination degree corresponding to each generator. S600 includes:

[0063] S601, through artificial intelligence, analyzes the thermal-humidity synergy energy efficiency score of each generator based on the power generation efficiency of each generator and the corresponding thermal-humidity synergy degree of each generator, and uses the corresponding power generation efficiency, overlapping area and humidity reduction potential coefficient of the generator as the input of the input layer, and the thermal-humidity synergy energy efficiency score of the generator as the output of the output layer.

[0064] In this embodiment, BP neural network technology is used to score the heat-humidity synergy energy efficiency of the generator. Specifically, a three-layer BP neural network model is first constructed, including an input layer, a hidden layer, and an output layer. In this embodiment, the power generation efficiency, overlap area, and humidity reduction potential coefficient corresponding to the generator are used as inputs of the input layer, so the input layer has three nodes, and the output is the heat-humidity synergy energy efficiency score of the generator (0-100), so there is a total of one node. For the hidden layer, this embodiment uses the following formula to determine the number of hidden layer nodes: ; Wherein, 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, a is a number between 1 and 10, and in this embodiment, it is taken as 6, so there are 8 nodes in the hidden layer. BP neural networks usually use Sigmoid differentiable functions and linear functions as the excitation functions of the network. This embodiment selects the S-type tangent function tansig as the excitation function of the hidden layer neurons. The prediction model selects the S-type logarithmic function tansig as the excitation function of the output layer neurons. 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 the historical operation data training is completed can obtain more accurate evaluation results.

[0065] S602: Generate a priority ranking table based on the heat-humidity synergy energy efficiency score of each generator.

[0066] S700: Based on the load power, the rated power of each generator, and the priority ranking table, several generators are selected as target generators, and the target generators are controlled to start operation. Specifically, N generators are selected from the priority ranking table in sequence, ensuring that the ratio of the sum of the rated power of the selected generators to the load power is greater than a preset ratio threshold, while also ensuring that the number of generators activated is minimized. This prevents excessive load factors on the generators and reduces the number of generators that need to be activated.

[0067] In other embodiments of the present application, the heat and moisture synergy energy efficiency may be scored only for the generators that have been turned on to generate a priority ranking table, and then the load of each generator may be adjusted according to the priority ranking list.

[0068] Example 2:

[0069] A generator set remote monitoring system, using the above generator set remote monitoring method, comprises:

[0070] A data acquisition module acquires load power, equipment parameters of each generator, local environmental parameters of the location of each generator, and humidity distribution data of the generator room; the equipment parameters include the location data of each generator, historical exhaust flow rate, historical exhaust temperature, and rated power;

[0071] The efficiency analysis module analyzes the power generation efficiency of each generator based on its equipment parameters and the corresponding local environmental parameters;

[0072] The high humidity area analysis module constructs a humidity heat map of the generator room based on the humidity distribution data of the generator room and identifies high humidity areas in the generator room where the humidity value exceeds the preset humidity threshold;

[0073] The exhaust analysis module analyzes the heat diffusion range of each generator's exhaust based on the generator's location data and historical exhaust flow rate, and generates the exhaust impact area of each generator;

[0074] The heat-humidity synergy analysis module performs a spatial overlay analysis on each generator's exhaust impact area and high humidity area. Based on the results of the spatial overlay analysis and the corresponding generator's historical exhaust temperature and exhaust flow rate, it calculates the heat-humidity synergy for each generator. The heat-humidity synergy includes the overlapping area of the exhaust impact area and the high humidity area, and the generator's humidity reduction potential coefficient.

[0075] A ranking table generation module generates a priority ranking table based on the power generation efficiency of each generator and the heat and humidity coordination degree corresponding to each generator;

[0076] The generator screening module selects several generators as target generators according to the load power, the rated power of each generator and the priority sorting table, and controls the target generators to start and run.

[0077] The above are only embodiments of the present invention. Common knowledge such as the known specific structures and characteristics in the scheme are not described in detail here. Ordinary technicians in the field are aware of all common technical knowledge in the technical field of the invention before the application date or priority date, can obtain all existing technologies in the field, and have the ability to apply conventional experimental means before that date. Ordinary technicians in the field can improve and implement this scheme in combination with their own abilities under the inspiration given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several variations and improvements can be made, which should also be regarded as the scope of protection of the present invention. These will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A method for remote monitoring of a generator set, characterized by: The following steps are involved: Obtaining load power, equipment parameters of each generator, local environmental parameters at the location of each generator, and humidity distribution data in the generator room; the equipment parameters include generator location data, historical exhaust flow rate, historical exhaust temperature, and rated power; Analyze the power generation efficiency of each generator based on its equipment parameters and corresponding local environmental parameters; Based on the humidity distribution data of the generator room, a humidity heat map of the room is constructed to identify high humidity areas in the generator room where the humidity exceeds the preset humidity threshold; Based on the location data and historical exhaust flow rate of each generator, the heat diffusion range of each generator's exhaust is analyzed to generate the exhaust impact area of each generator; A spatial overlay analysis was performed on the exhaust impact area and high humidity area of each generator. Based on the results of the spatial overlay analysis and the historical exhaust temperature and exhaust flow rate of the corresponding generator, the thermal-humidity synergy of each generator was calculated. The thermal-humidity synergy includes the overlapping area of the exhaust impact area and the high humidity area and the humidity reduction potential coefficient of the generator. Generate a priority ranking table based on the power generation efficiency of each generator and the corresponding heat and moisture synergy of each generator; According to the load power, rated power of each generator and priority ranking table, several generators are selected as target generators, and the target generators are controlled to start operation; Based on the spatial superposition analysis results, the historical exhaust temperature and historical exhaust flow rate of the corresponding generator, the heat and humidity coordination degree corresponding to each generator is calculated, including: Based on the results of spatial overlay analysis, the overlap area and location data of the exhaust impact area and the high humidity area are generated; Analyze the distance between the generator and the overlapping area based on the generator's position data and the overlapping area's position data; The humidity reduction potential coefficient of the generator is calculated based on the overlap area, the spacing distance, the historical exhaust temperature, and the historical exhaust flow rate. The calculation formula of the humidity reduction potential coefficient is as follows: Where, is the humidity reduction potential coefficient, is the spatial attenuation coefficient, is the interval distance, is the overlapping area, is the mean value of the historical exhaust flow rate, is the total number of historical exhaust temperature records, The exhaust temperature record The recorded exhaust gas temperature, is the time attenuation coefficient, is the current time, The exhaust temperature record The recording time corresponding to the exhaust temperature.

2. The method for remote monitoring of a generator set according to claim 1, characterized in that: Based on the power generation efficiency of each generator and the corresponding heat and humidity coordination degree of each generator, a priority ranking table is generated, including: Through artificial intelligence, the heat-humidity synergy energy efficiency score of each generator is analyzed based on the power generation efficiency of each generator and the corresponding heat-humidity synergy degree of each generator. The power generation efficiency, overlap area and humidity reduction potential coefficient of the generator are used as the input layer, and the heat-humidity synergy energy efficiency score of the generator is used as the output layer. A priority ranking table is generated based on the thermal and moisture synergy energy efficiency score of each generator.

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

4. The method for remote monitoring of a generator set according to claim 3, characterized in that: The power generation efficiency of each generator is analyzed based on the equipment parameters of each generator and the corresponding local environmental parameters, including: analyzing whether the local environmental temperature is within a preset operating temperature range; if so, analyzing the power generation efficiency of the corresponding generator based on the equipment parameters and the local environmental humidity; if not, analyzing the power generation efficiency of the corresponding generator based on the equipment parameters, the local environmental temperature, and the local environmental humidity.

5. The method for remote monitoring of a generator set according to claim 4, characterized in that: The equipment parameters also include maintenance interval, start and stop status, and the number of starts and stops within a preset time period.

6. The method for remote monitoring of a generator set according to claim 5, characterized in that: The calculation formula of the power generation efficiency is as follows: Where, For power generation efficiency, is the rated efficiency of the generator under ideal conditions, is the start-stop loss coefficient, Indicates the start / stop status of the generator. If the start / stop status of the generator is starting, then If the generator start-stop state is shutting down, then , is the start-stop frequency influence coefficient, is the number of starts and stops within the preset time period, is the temperature sensitivity coefficient, is the local ambient temperature, For the best working temperature, is the fluctuating temperature value, is the health attenuation coefficient, For maintenance intervals, is the humidity influence coefficient, is the local ambient humidity, The optimal relative humidity.

7. A remote monitoring system for a generator set, characterized by: The remote monitoring method for a generator set according to any one of claims 1 to 6 is used.

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