Generator set output power determination method and device, equipment, storage medium and program product

Abstract

The invention relates to an output power determination method and device of a generator set, equipment, a storage medium and a program product. The method comprises the following steps: acquiring power grid load data at a current moment and power grid load data at at least one historical moment; and inputting the power grid load data at the current moment and the power grid load data at the at least one historical moment into a load prediction model to obtain predicted load data at a second moment. And further, determining the output power of the generator set according to the predicted power grid frequency corresponding to the predicted load data and the reference power grid frequency. According to the invention, the accuracy of determining the output power of the generator set can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of power systems, and in particular to a method, device, equipment, storage medium and program product for determining the output power of a generator set. Background Art

[0002] The determination of the output power of the generator set has an important impact on the safety and stability, economic benefits, environmental protection, technical challenges and power market demand of the nuclear power plant. In the operation of the nuclear power plant, it is necessary to accurately determine and optimize the output power of the generator set to ensure the efficient, safe and stable operation of the nuclear power plant. Therefore, how to improve the accuracy of the output power regulation of the generator set is crucial to the power system.

[0003] In the related art, manual setting and adjustment are usually required, relying on manual experience and judgment, and there are certain subjectivity and limitations. This method will result in low accuracy in determining the output power of the generator set. Summary of the invention

[0004] Based on this, it is necessary to provide a method, device, equipment, storage medium and program product for determining the output power of a generator set, which can improve the accuracy of determining the output power of the generator set, in order to address the above technical problems.

[0005] In a first aspect, the present application provides a method for determining the output power of a generator set, the method comprising:

[0006] Obtaining power grid load data at the current moment and power grid load data at at least one historical moment, wherein the current moment and the adjacent moment in the at least one historical moment are separated by a preset time length;

[0007] Inputting the grid load data at the current moment and the grid load data at at least one historical moment into the load forecasting model to obtain the forecasted load data at a second moment, where the second moment is separated from the current moment by a preset time length;

[0008] The output power of the generator set is determined based on the predicted grid frequency corresponding to the predicted load data and the reference grid frequency.

[0009] In one embodiment, determining the output power of the generator set according to the predicted grid frequency corresponding to the predicted load data and the reference grid frequency includes:

[0010] Determine the frequency error according to the predicted grid frequency and the reference grid frequency;

[0011] Based on the frequency error, the output power of the generator set is determined.

[0012] In one embodiment, determining the output power of the generator set based on the frequency error includes:

[0013] Based on the frequency error, determining a cumulative error within a preset time period;

[0014] The frequency error and the cumulative error are weighted and summed to determine the output power of the generator set.

[0015] In one embodiment, before determining the output power of the generator set according to the predicted grid frequency corresponding to the predicted load data and the reference grid frequency, the method further includes:

[0016] Determine the current frequency variable based on the predicted load data and the preset coefficient;

[0017] Obtain the historical average grid frequency;

[0018] The predicted grid frequency is determined based on the current frequency variable and the historical average grid frequency.

[0019] In one embodiment, the generator set includes a multi-energy generator set;

[0020] After determining the output power of the generator set according to the predicted grid frequency corresponding to the predicted load data and the reference grid frequency, the method further includes:

[0021] The output power of each energy generating set is determined based on the output power of the generating set, as well as the capacity limitation and operating cost information of each energy generating set.

[0022] In one embodiment, the output power of each energy generating set is determined according to the output power of the generating set, and the capacity limitation and operation cost information of each energy generating set, including:

[0023] Determine the adjustment priority of each energy generating unit based on the capacity limitation and operation cost information of each energy generating unit;

[0024] The output power of each energy generating set is determined according to each adjustment priority and the output power of the generating set.

[0025] In a second aspect, the present application provides a device for determining output power of a generator set, the device comprising:

[0026] An acquisition module, used to acquire power grid load data at a current moment and power grid load data at at least one historical moment, wherein the current moment and an adjacent moment in at least one historical moment are separated by a preset time length;

[0027] A first determination module is used to input the power grid load data at the current moment and the power grid load data at at least one historical moment into the load prediction model to obtain the predicted load data at a second moment, where the second moment is separated from the current moment by a preset time length;

[0028] The second determination module is used to determine the output power of the generator set according to the predicted grid frequency corresponding to the predicted load data and the reference grid frequency.

[0029] In a third aspect, the present application provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method of the first aspect.

[0030] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method of the first aspect when the computer program is executed by a processor.

[0031] In a fifth aspect, the present application also provides a computer program product, including a computer program, which implements the steps of the method of the first aspect when executed by a processor.

[0032] The above-mentioned method, device, equipment, storage medium and program product for determining the output power of the generator set obtain the grid load data at the current moment and the grid load data at at least one historical moment, and input the grid load data at the current moment and the grid load data at at least one historical moment into the load forecasting model to obtain the predicted load data at the second moment. Further, the output power of the generator set is determined according to the predicted grid frequency corresponding to the predicted load data and the reference grid frequency. Compared with the method that requires manual setting and adjustment in the related art and relies on manual experience and judgment, the embodiment of the present application obtains the grid load data at the current moment, which can ensure the real-time and accuracy of the data and provide a basis for subsequent load forecasting. At the same time, combined with the grid load data at the historical moment, the changing trend of the grid load can be analyzed to provide important reference information for the forecasting model. Further, the above-mentioned grid load data is input into the load forecasting model, which can accurately predict the load data at the future moment and provide a basis for determining the output power of the generator set. Further, the output power of the generator set can be accurately determined by predicting the load data and the grid frequency to adjust the output power of the generator set, ensure the stable operation of the grid, and avoid damage to the power system caused by excessive fluctuations in the grid frequency. The rapid response capability based on load forecasting can ensure that the output power of the generator set can be quickly adjusted to meet the power demand when the grid load changes, thereby improving the accuracy of determining the output power of the generator set. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 A schematic diagram of an implementation environment of a method for determining output power of a generator set in one embodiment of the present application;

[0035] Figure 2 A schematic flow chart of a method for determining the output power of a generator set in one embodiment of the present application;

[0036] Figure 3 This is a flow chart of a method for determining the output power of a generator set in another embodiment of the present application;

[0037] Figure 4 This is a flow chart of a method for determining the output power of a generator set in another embodiment of the present application;

[0038] Figure 5 This is a flow chart of a method for determining the output power of a generator set in another embodiment of the present application;

[0039] Figure 6 This is a schematic diagram of the overall process of a method for determining the output power of a generator set in one embodiment of the present application;

[0040] Figure 7 This is a schematic diagram of the structure of a device for determining the output power of a generator set in one embodiment of the present application;

[0041] Figure 8 This is a diagram of the internal structure of a computer device in one embodiment of the present application. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0043] The method, device, equipment, storage medium and program product for determining the output power of a generator set provided in the embodiments of the present application can be applied to the output power determination scenario of the generator set; of course, it can also be applied to scenarios in other power supply systems where output power determination is required, which is not limited to the embodiments of the present application.

[0044] The Automatic Generation Control instruction (AGC instruction) is an instruction in the automatic generation control system, which is used to adjust the output power of the generator set to meet the changes in grid load and maintain the stability of the grid frequency. The AGC system monitors the changes in grid frequency and load, calculates the corresponding power adjustment requirements, and then generates AGC instructions and sends them to each generator set.

[0045] In related technologies, AGC systems usually use control algorithms based on empirical rules. These rules are statically defined and do not take into account the complex grid status and dynamic characteristics. They pay little attention to the high proportion of renewable energy access and environmental impact, which may lead to insufficient utilization of renewable energy such as wind power. The current AGC system usually requires manual setting and adjustment, relying on the experience and judgment of operators, and has certain subjectivity and limitations. Therefore, how to improve the accuracy of the output power regulation of the generator set is crucial to the power system.

[0046] Figure 1 FIG. 1 is a schematic diagram of an implementation environment of a method for determining the output power of a generator set in one embodiment of the present application. Figure 1 As shown, the implementation environment may include: a terminal 101 and a server 102. The terminal 101 may communicate with the server 102 via a network, and the terminal 101 may include but is not limited to various personal computers, laptops, smart phones, and tablet computers. The server 102 may be implemented as an independent server or a server cluster consisting of multiple servers. The data storage system may store information such as the power grid load data at the current moment, the power grid load data at the historical moment, the load forecasting model, and the forecasted load data that the server 102 needs to process. The data storage system may be integrated on the server 102, or may be placed on the cloud or other network servers.

[0047] Combination Figure 1 In the implementation environment shown, in the embodiment of the present application, the computer device can be a server 102, and the server 102 can obtain the grid load data at the current moment and the grid load data at at least one historical moment, and input the grid load data at the current moment and the grid load data at at least one historical moment into the load forecasting model to obtain the predicted load data at the second moment. Further, the server 102 can determine the output power of the generator set according to the predicted grid frequency corresponding to the predicted load data and the reference grid frequency, display the output power of the generator set on the terminal 101, and control the generator set to output the corresponding power according to the output power of the generator set.

[0048] It should be understood that the computer device may also be the terminal 101. The terminal 101 may obtain the grid load data at the current moment and the grid load data at at least one historical moment, and input the grid load data at the current moment and the grid load data at at least one historical moment into the load forecasting model to obtain the forecasted load data at the second moment. Furthermore, the terminal 101 may determine the output power of the generator set according to the forecasted grid frequency corresponding to the forecasted load data and the reference grid frequency.

[0049] In order to solve the problem of low accuracy in determining the output power of the generator set in the related art, the output power determination method, device, equipment, storage medium and program product of the generator set provided in the embodiment of the present application can ensure the real-time and accuracy of the data by obtaining the power grid load data at the current moment, and provide a basis for subsequent load forecasting. At the same time, combined with the power grid load data at the historical moment, the changing trend of the power grid load can be analyzed to provide important reference information for the prediction model. Further, the above-mentioned power grid load data is input into the load prediction model, and the load data at the future moment can be accurately predicted, providing a basis for determining the output power of the generator set. Further, the output power of the generator set can be accurately determined by predicting the load data and the power grid frequency to adjust the output power of the generator set, ensure the stable operation of the power grid, and avoid excessive power grid frequency fluctuations causing damage to the power system. Based on the rapid response capability of load prediction, it can be ensured that the output power of the generator set is quickly adjusted when the power grid load changes to meet the power demand, thereby improving the accuracy of determining the output power of the generator set.

[0050] In one embodiment, Figure 2 The flowchart of the method for determining the output power of a generator set in one embodiment of the present application is shown in FIG. 1 . The present application embodiment takes the method applied to a computer device as an example for explanation, wherein the computer device may include but is not limited to a terminal or a server. Figure 2 As shown, the method of the embodiment of the present application may include the following steps.

[0051] S201, obtaining power grid load data at a current moment and power grid load data at at least one historical moment.

[0052] Among them, grid load data refers to the electricity demand or power consumption in the grid at a certain moment, usually expressed in power units such as kilowatts (kW) or megawatts (MW).

[0053] The current moment refers to the time point when the system or device requests grid load data; the historical moment refers to a time point in the past that is different from the current moment. In grid data analysis, grid load data at historical moments are used for comparison, trend analysis, and prediction.

[0054] Optionally, a preset time interval is provided between the current moment and at least one adjacent moment in the historical moment. The preset time interval may be a pre-set time interval.

[0055] In this step, the computer device can obtain the grid load data at the current moment and the grid load data at at least one historical moment according to the preset acquisition method. It can be seen that by obtaining the grid load data at the current moment, the computer device can monitor the operation status of the grid in real time and discover potential problems in time. Based on historical data, a prediction algorithm can be used to predict future grid loads, providing a basis for subsequent load predictions.

[0056] It should be noted that the preset acquisition method may be to obtain the grid load data at regular intervals from a preset database, or to obtain the grid load data in real time by calling a real-time interface of a grid management system, and there is no limitation to this.

[0057] S202, inputting the power grid load data at the current moment and the power grid load data at at least one historical moment into a load prediction model to obtain predicted load data at a second moment.

[0058] There may be a preset time interval between the second moment and the current moment.

[0059] Exemplarily, the load forecasting model refers to a pre-trained forecasting model, which is used to forecast the forecasted load data at a second moment based on the input power grid load data at the current moment and the power grid load data at at least one historical moment. The forecasting model can be constructed based on machine learning, God General Network or other forecasting algorithms, which are not limited here.

[0060] Exemplarily, the computer device can obtain load data of the past 7 days as historical load data, for example, the historical load data is [100, 120, 110, 115, 105, 130, 125], and input the power grid load data into the long short-term memory network model to obtain the predicted load data for the next day.

[0061] In this step, the computer device can input the power grid load data at the current moment and the power grid load data at at least one historical moment into the load prediction model, so as to obtain the predicted load data at the second moment.

[0062] It can be seen that by inputting the grid load data at the current moment and the grid load data at at least one historical moment into the load forecasting model, the grid load data at the future moment can be accurately predicted, providing a basis for determining the output power of the generator set. Furthermore, predicting the grid load data at the future moment is also conducive to optimizing the management and operation of the distribution network, avoiding the situation of overload or power shortage of the distribution network, and thus improving the efficiency and reliability of power supply.

[0063] The following is an illustrative description of the training process of the load forecasting model.

[0064] The computer device can obtain the power grid load data at historical moments; preprocess the power grid load data at historical moments, which may include data cleaning, removing outliers, data conversion, etc. Furthermore, the computer device can train the initial load forecasting model based on the power grid load data at historical moments, and adjust the parameters of the load forecasting model through an optimization algorithm (such as gradient descent) so that the load forecasting model can better fit the historical data, thereby obtaining a load forecasting model.

[0065] S203, determining the output power of the generator set according to the predicted grid frequency corresponding to the predicted load data and the reference grid frequency.

[0066] Among them, the predicted grid frequency refers to the expected operating frequency of the grid at the predicted moment (i.e. the second moment) calculated based on the predicted load data and other relevant factors (such as grid topology, line impedance, generator type, etc.).

[0067] Reference grid frequency refers to a fixed or preset grid frequency value, which usually corresponds to the standard operating frequency of the grid and is used as a benchmark value for comparison with the predicted grid frequency to determine the deviation and stability of the grid frequency.

[0068] The output power of a generator set refers to the power output generated by the generator set under specific conditions (such as grid frequency, load demand, etc.), which can be adjusted according to the needs of the grid and dispatch instructions to ensure the stable operation of the grid and the balance of supply and demand.

[0069] In this step, the computer device can determine the predicted grid frequency corresponding to the preset load data based on the predicted load data, and further determine the output power of the generator set based on the predicted grid frequency and the reference grid frequency.

[0070] It can be seen that by comparing the predicted grid frequency with the reference grid frequency, computer equipment can promptly detect the deviation of the grid frequency and correct the frequency deviation by adjusting the output power of the generator set, thereby improving the stability of the grid and helping to avoid excessive or insufficient power supply, thereby improving the utilization efficiency of resources.

[0071] The following is an exemplary explanation of the relevant contents of determining the output power of the generator set.

[0072] In one possible implementation, the computer device may determine the frequency error based on the predicted grid frequency and the reference grid frequency, and further determine the output power of the generator set based on the frequency error.

[0073] In this implementation, the computer equipment can directly calculate the frequency error between the predicted grid frequency and the reference grid frequency to intuitively understand the degree of deviation of the grid frequency. Once the frequency error is determined, the generator set can respond immediately and make corresponding power adjustments, which is conducive to quickly and accurately correcting the deviation of the grid frequency and maintaining the stable operation of the grid.

[0074] In another possible implementation, the computer device can input the predicted grid frequency and the reference grid frequency into a preset neural network model, and output the output power of the generator set based on the preset trained neural network model.

[0075] In this implementation, the computer equipment can predict and determine the output power of the generator set by comprehensively considering multiple factors (such as load forecasting, weather conditions, equipment status, etc.) through a preset neural network model, reducing the need for human intervention and obtaining more accurate and detailed prediction results.

[0076] In this way, the output power of the generator set can be obtained through any of the above implementation methods.

[0077] In the above-mentioned method for determining the output power of the generator set, the computer device can obtain the grid load data at the current moment and the grid load data at at least one historical moment, and input the grid load data at the current moment and the grid load data at at least one historical moment into the load forecasting model to obtain the predicted load data at the second moment. Further, the computer device determines the output power of the generator set according to the predicted grid frequency corresponding to the predicted load data and the reference grid frequency. In the embodiment of the present application, the computer device can ensure the real-time and accuracy of the data by obtaining the grid load data at the current moment, and provide a basis for subsequent load forecasting. At the same time, combined with the grid load data at the historical moment, the changing trend of the grid load can be analyzed to provide important reference information for the forecasting model. Further, the computer device inputs the above-mentioned grid load data into the load forecasting model, and can accurately predict the load data at the future moment, providing a basis for determining the output power of the generator set. Further, the computer device can accurately determine the output power of the generator set by predicting the load data and the grid frequency, so as to adjust the output power of the generator set, ensure the stable operation of the grid, and avoid the damage to the power system caused by excessive fluctuations in the grid frequency. The rapid response capability based on load forecasting can ensure that the output power of the generator set can be quickly adjusted to meet the power demand when the grid load changes, thereby improving the accuracy of determining the output power of the generator set.

[0078] In one embodiment, based on the above embodiment, Figure 3This is a flow chart of a method for determining the output power of a generator set in another embodiment of the present application. In the embodiment of the present application, the relevant contents of "determining the output power of the generator set according to the predicted grid frequency corresponding to the predicted load data and the reference grid frequency" in step S203 involved in the above embodiment are exemplarily introduced and explained. The method of the embodiment of the present application may include the following steps.

[0079] S2031, determining a frequency error according to the predicted grid frequency and the reference grid frequency.

[0080] The frequency error refers to the difference between the predicted grid frequency and the reference grid frequency.

[0081] Exemplarily, the calculation formula of the frequency error can be expressed as:

[0082] (1)

[0083] in, Indicates frequency error; represents a reference grid frequency. For example, the reference grid frequency may be set to 50 Hz; Represents the predicted grid frequency at the second moment.

[0084] Of course, the calculation formula for the frequency error can also be expressed as other variations or equivalent formulas of the above formula (1).

[0085] In this step, the computer device may determine the frequency error based on the predicted grid frequency and the reference grid frequency.

[0086] It can be seen that the frequency error can intuitively reflect the degree to which the grid frequency deviates from the reference value, allowing the operation and maintenance personnel or the automation system to clearly understand the operating status of the grid. The calculation of the frequency error is based on real-time or near real-time predicted grid frequency data, so it can reflect the changes in grid frequency in real time, providing a basis for timely adjustment of the output power of the generator set.

[0087] S2032: Determine the output power of the generator set based on the frequency error.

[0088] In this step, the computer device can determine the cumulative error within a preset time period based on the frequency error, thereby accurately determining the output power of the generator set. It can be seen that the computer device can more comprehensively consider the long-term change trend of the power grid frequency through the calculation of the cumulative error, rather than just the current instantaneous error, which is conducive to more accurately predicting and adjusting the output power of the generator set, thereby improving the stability of the power grid.

[0089] The following is an exemplary introduction to the content related to determining the output power of the generator set based on the frequency error.

[0090] The computer device may determine a cumulative error within a preset time period based on the frequency error.

[0091] The cumulative error refers to the total error caused by the cumulative effect of frequency deviation (i.e. the difference between the actual frequency and the reference frequency) within a preset time period. The cumulative error is caused by the frequency deviation persisting over a period of time and may have a long-term impact on the stability and performance of the system.

[0092] Exemplarily, the calculation formula of the cumulative error can be expressed as:

[0093] (2)

[0094] in, Indicates any time The frequency error of Indicates the accumulated error within the preset time period; is the start time, is the preset time length; the integral term is used to calculate the cumulative sum of the frequency error within the preset time length.

[0095] Of course, the calculation formula of the cumulative error can also be expressed as other variations or equivalent formulas of the above formula (2).

[0096] Furthermore, the computer device may perform a weighted summation of the frequency error and the cumulative error to determine the output power of the generator set.

[0097] The output power of the generator set may be an output power adjustment amount of the generator set.

[0098] For example, the calculation formula of the generator set output power can be expressed as:

[0099] (3)

[0100] in, is the proportional control parameter; is the integral control parameter; is the output power of the generator set.

[0101] Optionally, the proportional control parameter and the integral control parameter determine the response speed and stability of the generator set to frequency deviations. A larger proportional control parameter value is used to indicate that the generator set needs a faster response speed, but will cause frequency fluctuations, while a larger integral control parameter value is used to indicate that the generator set has a better ability to compensate for long-term frequency deviations. The selection of the proportional control parameter and the integral control parameter can be adjusted according to actual conditions and historical data, and there is no limitation on this.

[0102] Of course, the calculation formula for the output power of the generator set can also be expressed as other variations or equivalent formulas of the above formula (3).

[0103] For example, the proportional control parameter of the generator set is preset to 0.8, and the integral control parameter is preset to 0.05; the output power of the generator set (i.e., the output power adjustment amount) is calculated based on the difference between the predicted grid frequency and the reference grid frequency. For example, the predicted grid frequency is 49.7 Hz; the reference grid frequency is 50 Hz; the value of the preset integral term is 0.02, and according to the above calculation formula (3) for the output power of the generator set, it can be obtained is 0.035MW; further, the computer equipment can adjust Add it to the current generator set output power to get the new generator set output power.

[0104] In the embodiment of the present application, the computer device can more comprehensively evaluate the fluctuation of the power grid frequency by comprehensively considering the frequency error and the cumulative error, which is conducive to more accurately adjusting the output power of the generator set, thereby improving the stability of the power grid. Since the cumulative error is taken into account, the generator set can respond more quickly to the long-term change trend of the power grid frequency. When the power grid frequency deviates greatly, the computer device can quickly adjust the output power of the generator set to maintain the stable operation of the power grid. By adjusting the weights of the frequency error and the cumulative error, the computer device can be flexibly configured according to different application scenarios and needs.

[0105] In one embodiment, based on the above embodiment, Figure 4 This is a flow chart of a method for determining the output power of a generator set in another embodiment of the present application, and the present embodiment of the present application exemplarily introduces and explains the relevant contents before "determining the output power of the generator set according to the predicted grid frequency corresponding to the predicted load data and the reference grid frequency" in step S202 involved in the above embodiment. The method of the embodiment of the present application may include the following steps.

[0106] S401, determining the current frequency variable according to the predicted load data and the preset coefficient.

[0107] The preset coefficient refers to a pre-set value used to adjust the impact of the predicted load data on the current frequency variable. In actual applications, the value of the preset coefficient can vary according to specific needs and can be based on system characteristics, historical data, experience values ​​or other factors.

[0108] Exemplarily, the calculation formula of the current frequency variable can be expressed as:

[0109] (4)

[0110] in, Indicates the current frequency variable; represents a preset coefficient. For example, the preset coefficient can be set to 100; Forecasted load data can be presented.

[0111] Of course, the calculation formula of the current frequency variable can also be expressed as other variations or equivalent formulas of the above formula (4).

[0112] In this step, the computer equipment calculates the current frequency variable based on the predicted load data, which can respond to load changes in real time, thereby more accurately determining the frequency of the power grid.

[0113] S402, obtaining the historical average grid frequency.

[0114] In this step, the computer device can obtain the average value of the power grid frequency at multiple historical moments, providing an accurate theoretical basis for the subsequent determination of the predicted power grid frequency.

[0115] S403, determining a predicted grid frequency according to the current frequency variable and the historical average grid frequency.

[0116] Among them, the predicted grid frequency refers to the future grid frequency value calculated based on the current frequency variable and the historical average grid frequency forecast.

[0117] For example, the calculation formula for predicting the grid frequency can be expressed as:

[0118] (5)

[0119] in, Indicates the current frequency variable; Represents the historical average grid frequency.

[0120] Of course, the calculation formula for predicting the grid frequency can also be expressed as other variations or equivalent formulas of the above formula (5).

[0121] In this step, the computer device can sum the current frequency variable and the historical average grid frequency, so as to accurately determine the predicted grid frequency.

[0122] It can be seen that computer equipment can predict the grid frequency and detect potential frequency fluctuations or abnormal conditions in advance, so as to take corresponding measures to prevent or correct them. Based on the predicted grid frequency, the output power of the generator set can be determined more accurately, so that the power system can more accurately formulate the dispatch plan of the generator set to ensure the stable operation of the grid.

[0123] In the embodiment of the present application, the computer device can respond to load changes in real time based on the predicted load data, so that the frequency of the power grid can be determined more accurately. The computer device can obtain the average value of the power grid frequency at multiple historical moments, providing an accurate theoretical basis for the subsequent determination of the predicted power grid frequency. Furthermore, the computer device can more accurately determine the output power of the generator set based on the predicted power grid frequency, so that the power system can more accurately formulate the dispatch plan of the generator set.

[0124] In one embodiment, based on the above embodiment, the present application embodiment provides an exemplary description of the relevant contents after "determining the output power of the generator set according to the predicted grid frequency corresponding to the predicted load data and the reference grid frequency" in step S202 involved in the above embodiment. The generator set may include multiple energy generator sets, and the method of the present application embodiment may include the following steps.

[0125] The output power of each energy generating set is determined based on the output power of the generating set, as well as the capacity limitation and operating cost information of each energy generating set.

[0126] Exemplarily, the types of energy generator sets may include, but are not limited to, traditional generator sets, thermal power generator sets, nuclear power generator sets, wind power generator sets, photovoltaic generator sets, and the like.

[0127] Among them, capacity limit refers to the maximum power limit that each energy generator can output at a specific time or under specific conditions. Capacity limit can be based on a variety of factors, such as the physical design of the generator set, technical specifications, environmental conditions (such as temperature, humidity, wind speed, etc.), safety regulations, etc.

[0128] Optionally, the capacity limits may be different for different types of energy generators. For example, the capacity limit of a wind generator may depend on wind speed and wind direction, while the capacity limit of a thermal generator may be more related to fuel supply and the operating status of the generator.

[0129] Operation cost information refers to cost data related to the operation of energy generator sets. Operation cost information may include but is not limited to fuel costs, maintenance costs, labor costs, equipment depreciation, etc. These cost information are crucial to determining the output power of the generator set and can directly affect the operating efficiency and economic benefits of the generator set. By comprehensively considering the operation cost information, it is possible to determine which energy generator set has the lowest operating cost under different operating conditions, thereby selecting the optimal output power configuration.

[0130] In the embodiment of the present application, the computer device can determine the output power of each energy generator set according to the output power of the generator set, as well as the capacity limit and operating cost information of each energy generator set. It can be seen that the computer device determines the output power of each energy generator set by comprehensively considering the capacity limit and operating cost information, which can ensure that while meeting the needs of the power grid, the operating cost is reduced as much as possible and the economic benefits are improved. When determining the output power of each energy generator set, the use of renewable energy generator sets can be given priority, which is conducive to promoting the development and application of renewable energy and promoting the optimization and upgrading of the energy structure. Through reasonable output power configuration and giving priority to the use of renewable energy, the negative impact on the environment can be reduced, such as reducing greenhouse gas emissions and reducing noise pollution.

[0131] In one embodiment, based on the above embodiment, Figure 5 This is a flow chart of a method for determining the output power of a generator set in another embodiment of the present application. In the embodiment of the present application, the relevant contents of "determining the output power of each energy generator set according to the output power of the generator set, and the capacity limit and operating cost information of each energy generator set" involved in the above embodiment are exemplarily introduced and explained. The generator set may include multiple energy generator sets, and the method of the embodiment of the present application may include the following steps.

[0132] S501, determining the adjustment priority of each energy generating unit according to the capacity limitation and operation cost information of each energy generating unit.

[0133] Among them, the adjustment priority of each energy generating unit refers to the order in which each generating unit adjusts its output power when power demand, system stability or other factors change.

[0134] In this step, the computer device can determine the adjustment priority of each energy generating unit according to the capacity limitation and operation cost information of each energy generating unit.

[0135] It can be seen that computer equipment can optimize resource allocation and improve energy efficiency by giving priority to generators with lower operating costs or larger capacity adjustment space. When power demand or other factors change, computer equipment can quickly and effectively adjust the output power of the generator set according to the pre-determined adjustment priority to adapt to the new situation.

[0136] S502: Determine the output power of each energy generating set according to each adjustment priority and the output power of the generating set.

[0137] In this step, the computer device can identify one or more generator sets with the highest priority from all energy generator sets according to the predetermined adjustment priority of each energy generator set. Furthermore, the computer device can allocate corresponding output power to these energy generator sets according to certain weight rules to ensure that the capacity limitation and operation cost-effectiveness of the generator sets are taken into account while meeting the power demand of the system.

[0138] It can be seen that by adjusting the priority and weight rules to allocate output power, computer equipment can ensure that resources are used more efficiently. Generators with higher priorities will get more or priority output opportunities, while generators with lower priorities will be supplemented when necessary. When power demand or other factors change, computer equipment can quickly adjust the output power of each generator set according to the predetermined adjustment priority and weight rules, which helps to ensure that the system can respond quickly to changes and maintain the stability and reliability of power supply.

[0139] In the embodiment of the present application, the computer device determines the adjustment priority of each energy generator set by giving priority to generator sets with lower operating costs or larger capacity adjustment space. Generator sets with higher priorities will obtain more or priority output opportunities, while generator sets with lower priorities will be supplemented when necessary. The computer device can quickly adjust the output power of each generator set according to the predetermined adjustment priority and weight rules, which is conducive to ensuring that the system can respond quickly to changes.

[0140] In one embodiment, based on the above embodiment, Figure 6 FIG. 1 is a schematic diagram of the overall flow of a method for determining the output power of a generator set in one embodiment of the present application. Figure 6 As shown, the method may include the following steps.

[0141] S601, a computer device obtains power grid load data at a current moment and power grid load data at at least one historical moment.

[0142] The current moment and at least one adjacent moment in the historical moment are separated by a preset time duration.

[0143] S602, the computer device inputs the power grid load data at the current moment and the power grid load data at at least one historical moment into a load prediction model to obtain predicted load data at a second moment.

[0144] The second moment is separated from the current moment by a preset time interval.

[0145] S603, the computer device determines the current frequency variable according to the predicted load data and the preset coefficient.

[0146] S604, the computer device obtains the historical average power grid frequency.

[0147] S605, the computer device determines the predicted grid frequency according to the current frequency variable and the historical average grid frequency.

[0148] S606, the computer device determines a frequency error according to the predicted grid frequency and the reference grid frequency.

[0149] S607: The computer device determines the accumulated error within a preset time period based on the frequency error.

[0150] S608, the computer device performs weighted summation of the frequency error and the cumulative error to determine the output power of the generator set.

[0151] S609, the computer device determines the adjustment priority of each energy generating unit according to the capacity limit and operation cost information of each energy generating unit.

[0152] S610, the computer device determines the output power of each energy generating set according to each adjustment priority and the output power of the generating set.

[0153] It should be noted that the achievable methods and technical effects of each step in the embodiments of the present application can refer to the relevant contents in the above embodiments and will not be repeated here.

[0154] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0155] Based on the same inventive concept, the embodiment of the present application also provides a device for determining the output power of a generator set for implementing the above-mentioned method for determining the output power of a generator set. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above-mentioned method, so the specific limitations in the embodiments of the device for determining the output power of one or more generator sets provided below can refer to the limitations of the method for determining the output power of a generator set above, and will not be repeated here.

[0156] In one embodiment, Figure 7: is a schematic diagram of the structure of a device for determining the output power of a generator set in one embodiment of the present application. The device for determining the output power of a generator set provided in the embodiment of the present application can be applied to a computer device, wherein the computer device can be a terminal or a server. Figure 7 As shown, the output power determination device of the generator set in the embodiment of the present application may include: an acquisition module 701, a first determination module 702 and a second determination module 703, wherein:

[0157] The acquisition module 701 is used to acquire the power grid load data at the current moment and the power grid load data at at least one historical moment, and the interval between the current moment and the adjacent moment in the at least one historical moment is a preset time length;

[0158] The first determination module 702 is used to input the power grid load data at the current moment and the power grid load data at at least one historical moment into the load prediction model to obtain the predicted load data at a second moment, where the second moment is separated from the current moment by a preset time length;

[0159] The second determination module 703 is used to determine the output power of the generator set according to the predicted grid frequency corresponding to the predicted load data and the reference grid frequency.

[0160] In one embodiment, the second determining module 703 may include: a first determining unit and a second determining unit, wherein:

[0161] A first determining unit, configured to determine a frequency error according to a predicted grid frequency and a reference grid frequency;

[0162] The second determining unit is used to determine the output power of the generator set based on the frequency error.

[0163] In one embodiment, the second determining unit is specifically configured to:

[0164] Based on the frequency error, determining a cumulative error within a preset time period;

[0165] The frequency error and the cumulative error are weighted and summed to determine the output power of the generator set.

[0166] In one embodiment, before the second determination module 703, the output power determination device of the generator set further includes a third determination module, a second acquisition module and a fourth determination module, wherein:

[0167] A third determination module is used to determine the current frequency variable according to the predicted load data and the preset coefficient;

[0168] The second acquisition module is used to obtain the historical average power grid frequency;

[0169] The fourth determination module is used to determine the predicted grid frequency according to the current frequency variable and the historical average grid frequency.

[0170] In one embodiment, the generator set includes multiple energy generator sets. After the second determination module 703, the output power determination device of the generator set further includes a fifth determination module, wherein:

[0171] The fifth determination module is used to determine the output power of each energy generating set according to the output power of the generating set, as well as the capacity limitation and operation cost information of each energy generating set.

[0172] In one embodiment, the fifth determining module is specifically configured to:

[0173] Determine the adjustment priority of each energy generating unit based on the capacity limitation and operation cost information of each energy generating unit;

[0174] The output power of each energy generating set is determined according to each adjustment priority and the output power of the generating set.

[0175] The device for determining the output power of a generator set provided in this embodiment can execute the above method embodiment, and its implementation principle and technical effect are similar, which will not be repeated here.

[0176] Each module in the above-mentioned device for determining the output power of a generator set can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0177] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 8As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store information such as the power grid load data at the current moment, the power grid load data at the historical moment, the load prediction model and the predicted load data that need to be processed. The input / output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the output power determination method of the generator set provided in the above-mentioned embodiment of the present application is implemented.

[0178] Those skilled in the art will understand that Figure 8 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0179] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0180] Obtaining power grid load data at the current moment and power grid load data at at least one historical moment, wherein the current moment and the adjacent moment in the at least one historical moment are separated by a preset time length;

[0181] Inputting the grid load data at the current moment and the grid load data at at least one historical moment into the load forecasting model to obtain the forecasted load data at a second moment, where the second moment is separated from the current moment by a preset time length;

[0182] The output power of the generator set is determined based on the predicted grid frequency corresponding to the predicted load data and the reference grid frequency.

[0183] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0184] Determine the frequency error according to the predicted grid frequency and the reference grid frequency;

[0185] Based on the frequency error, the output power of the generator set is determined.

[0186] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0187] Based on the frequency error, determining a cumulative error within a preset time period;

[0188] The frequency error and the cumulative error are weighted and summed to determine the output power of the generator set.

[0189] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0190] Determine the current frequency variable based on the predicted load data and the preset coefficient;

[0191] Obtain the historical average grid frequency;

[0192] The predicted grid frequency is determined based on the current frequency variable and the historical average grid frequency.

[0193] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0194] The output power of each energy generating set is determined based on the output power of the generating set, as well as the capacity limitation and operating cost information of each energy generating set.

[0195] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0196] Determine the adjustment priority of each energy generating unit based on the capacity limitation and operation cost information of each energy generating unit;

[0197] The output power of each energy generating set is determined according to each adjustment priority and the output power of the generating set.

[0198] The computer device provided in this embodiment can execute the technical solution in the above-mentioned method for determining the output power of the generator set. Its implementation principle and technical effect are similar and will not be repeated here.

[0199] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0200] Obtaining power grid load data at the current moment and power grid load data at at least one historical moment, wherein the current moment and the adjacent moment in the at least one historical moment are separated by a preset time length;

[0201] Inputting the grid load data at the current moment and the grid load data at at least one historical moment into the load forecasting model to obtain the forecasted load data at a second moment, where the second moment is separated from the current moment by a preset time length;

[0202] The output power of the generator set is determined based on the predicted grid frequency corresponding to the predicted load data and the reference grid frequency.

[0203] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0204] Determine the frequency error according to the predicted grid frequency and the reference grid frequency;

[0205] Based on the frequency error, the output power of the generator set is determined.

[0206] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0207] Based on the frequency error, determining a cumulative error within a preset time period;

[0208] The frequency error and the cumulative error are weighted and summed to determine the output power of the generator set.

[0209] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0210] Determine the current frequency variable based on the predicted load data and the preset coefficient;

[0211] Obtain the historical average grid frequency;

[0212] The predicted grid frequency is determined based on the current frequency variable and the historical average grid frequency.

[0213] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0214] The output power of each energy generating set is determined based on the output power of the generating set, as well as the capacity limitation and operating cost information of each energy generating set.

[0215] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0216] Determine the adjustment priority of each energy generating unit based on the capacity limitation and operation cost information of each energy generating unit;

[0217] The output power of each energy generating set is determined according to each adjustment priority and the output power of the generating set.

[0218] The computer program in the computer-readable storage medium provided in this embodiment can be used to execute the technical solution in the above-mentioned method for determining the output power of the generator set when the computer program is executed by the processor. Its implementation principle and technical effect are similar and will not be repeated here.

[0219] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0220] Obtaining power grid load data at the current moment and power grid load data at at least one historical moment, wherein the current moment and the adjacent moment in the at least one historical moment are separated by a preset time length;

[0221] Inputting the grid load data at the current moment and the grid load data at at least one historical moment into the load forecasting model to obtain the forecasted load data at a second moment, where the second moment is separated from the current moment by a preset time length;

[0222] The output power of the generator set is determined based on the predicted grid frequency corresponding to the predicted load data and the reference grid frequency.

[0223] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0224] Determine the frequency error according to the predicted grid frequency and the reference grid frequency;

[0225] Based on the frequency error, the output power of the generator set is determined.

[0226] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0227] Based on the frequency error, determining a cumulative error within a preset time period;

[0228] The frequency error and the cumulative error are weighted and summed to determine the output power of the generator set.

[0229] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0230] Determine the current frequency variable based on the predicted load data and the preset coefficient;

[0231] Obtain the historical average grid frequency;

[0232] The predicted grid frequency is determined based on the current frequency variable and the historical average grid frequency.

[0233] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0234] The output power of each energy generating set is determined based on the output power of the generating set, as well as the capacity limitation and operating cost information of each energy generating set.

[0235] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0236] Determine the adjustment priority of each energy generating unit based on the capacity limitation and operation cost information of each energy generating unit;

[0237] The output power of each energy generating set is determined according to each adjustment priority and the output power of the generating set.

[0238] The computer program in the computer program product provided in this embodiment can be used to execute the technical solution in the above-mentioned method for determining the output power of a generator set when the computer program is executed by a processor. Its implementation principle and technical effect are similar and will not be repeated here.

[0239] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The processor involved in each embodiment provided in this application can be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, etc., but is not limited thereto.

[0240] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0241] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for determining the output power of a generator set, characterized in that: The method comprises: Acquire power grid load data at a current moment and power grid load data at at least one historical moment, wherein the current moment and an adjacent moment in the at least one historical moment are separated by a preset time length; Inputting the power grid load data at the current moment and the power grid load data at at least one historical moment into a load forecasting model to obtain forecast load data at a second moment, where the second moment is separated from the current moment by the preset time length; The output power of the generator set is determined according to the predicted grid frequency corresponding to the predicted load data and the reference grid frequency.

2. The method according to claim 1, characterized in that The step of determining the output power of the generator set according to the predicted grid frequency corresponding to the predicted load data and the reference grid frequency comprises: Determining a frequency error according to the predicted grid frequency and the reference grid frequency; Based on the frequency error, the output power of the generator set is determined.

3. The method according to claim 2, characterized in that The step of determining the output power of the generator set based on the frequency error comprises: Based on the frequency error, determining a cumulative error within the preset time period; The frequency error and the cumulative error are weightedly summed to determine the output power of the generator set.

4. The method according to claim 1, characterized in that: Before determining the output power of the generator set according to the predicted grid frequency corresponding to the predicted load data and the reference grid frequency, the method further includes: Determining a current frequency variable according to the predicted load data and a preset coefficient; Obtain the historical average grid frequency; The predicted grid frequency is determined according to the current frequency variable and the historical average grid frequency.

5. The method according to any one of claims 1 to 4, characterized in that: The generator sets include various energy generator sets; After determining the output power of the generator set according to the predicted grid frequency corresponding to the predicted load data and the reference grid frequency, the method further includes: The output power of each of the energy generating sets is determined according to the output power of the generating sets, as well as the capacity limitation and operation cost information of each of the energy generating sets.

6. The method according to claim 5, characterized in that Determining the output power of each energy generating set according to the output power of the generating set, as well as the capacity limitation and operation cost information of each energy generating set, comprises: Determining the adjustment priority of each of the energy generating sets according to the capacity limit and operation cost information of each of the energy generating sets; The output power of each of the energy generating sets is determined according to the adjustment priorities and the output power of the generating sets.

7. A device for determining the output power of a generator set, characterized in that: The device comprises: An acquisition module, used to acquire power grid load data at a current moment and power grid load data at at least one historical moment, wherein the current moment and an adjacent moment in the at least one historical moment are separated by a preset time length; A first determination module is used to input the power grid load data at the current moment and the power grid load data at at least one historical moment into a load prediction model to obtain predicted load data at a second moment, where the second moment is separated from the current moment by the preset time length; The second determination module is used to determine the output power of the generator set according to the predicted grid frequency corresponding to the predicted load data and the reference grid frequency.

8. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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