Electric power project adjustment method and device, equipment and storage medium

Abstract

The invention discloses an electric power project adjustment method and device, equipment and a storage medium, and belongs to the technical field of new-generation information technologies, and the method comprises the steps: obtaining multidirectional data of an electric power project in a plurality of historical cycles; calculating to obtain a historical multidirectional data mean value corresponding to each historical period; fitting a time data relational expression based on the plurality of historical periods and the corresponding historical multidirectional data mean values; obtaining a predicted multidirectional data mean value of the next period based on the time data relational expression; judging a size relationship between the predicted multidirectional data mean value and a plurality of historical multidirectional data mean values; when the number of the historical multidirectional data mean value greater than the predicted multidirectional data mean value is greater than a preset critical threshold value, determining that the power project is a to-be-adjusted power project; obtaining current multidirectional data of the to-be-adjusted power project in the current period; and determining an adjustment scheme of the to-be-adjusted power project based on the current multidirectional data. Therefore, by implementing the method, the problem of low efficiency of the electric power project in the prior art can be solved.

Description

Technical Field

[0001] The present invention relates to the technical field of new generation information technology, and in particular to a method, device, equipment and storage medium for adjusting a power project. Background Art

[0002] Currently, power projects face two core challenges: First, a lack of real-time defect identification capabilities prevents dynamic determination of project operating anomalies, leading to delayed problem discovery and difficulty in timely initiating adjustment mechanisms. This can cause projects to continue operating in a faulty state, creating safety hazards and the risk of efficiency loss. Second, a weak data support system means the data used for adjustment decisions lacks correlation with the project's current operational data. The lack of precise mapping relationships and dynamic analysis models makes it difficult for adjustment plans to meet the project's true needs, making it easy for "blind adjustments" or "ineffective optimization" to occur, ultimately preventing the overall performance of power projects from reaching their intended targets. These two intertwined issues hinder the entire chain from problem discovery to resolution and optimization, severely restricting the high-quality operation and sustainable development of power projects. Summary of the Invention

[0003] The present invention provides a power project adjustment method, device, equipment and storage medium, which can solve the problem of low power project efficiency in the prior art.

[0004] In order to solve the above technical problems, the present invention provides a power project adjustment method, comprising:

[0005] Acquire multi-directional data of the power project in several historical periods; wherein the multi-directional data includes data of several data types; the data types include revenue, benefited projects and costs;

[0006] Normalize the multi-directional data in each historical period and calculate the mean of the historical multi-directional data corresponding to each historical period;

[0007] Based on several historical periods and the corresponding historical multi-directional data means, fit the time data relationship;

[0008] Determining the predicted multi-directional data mean for the next period based on the time data relationship;

[0009] Determining the magnitude relationship between the predicted multi-directional data mean and a plurality of historical multi-directional data means;

[0010] When the number of times that the historical multi-directional data mean is greater than the predicted multi-directional data mean is greater than a preset critical threshold, determining that the power project is a power project to be adjusted;

[0011] Acquiring current multi-directional data of the power project to be adjusted in the current cycle;

[0012] An adjustment plan for the power project to be adjusted is determined based on the current multi-directional data.

[0013] As a preferred solution, the determining of the adjustment plan for the power project to be adjusted based on the current multi-directional data includes:

[0014] Based on the preset standard data, the data of each data type in the current multi-directional data is scaled to form the current data value corresponding to each data type;

[0015] The data type of the current data value is determined to be a negative number as the adjustment direction;

[0016] An adjustment plan for the power project to be adjusted is determined based on the adjustment direction.

[0017] As a preferred solution, the scaling process is performed on the data of each data type in the current multi-directional data based on the preset standard data to form the current data value corresponding to each data type, including:

[0018] The following formula is used to perform scale transformation to form the current data value:

[0019]

[0020] Where x' i is the current data value of the i-th category; x i is the i-th category data in the current multi-directional data; Preset standard data for category i.

[0021] As a preferred solution, determining the adjustment plan for the power project to be adjusted based on the adjustment direction includes:

[0022] Based on the adjustment direction, obtaining an adjustment technology corresponding to the adjustment direction from a preset database;

[0023] An adjustment plan for the power project to be adjusted is formed based on the adjustment technology.

[0024] As a preferred solution, the acquiring, based on the adjustment direction, an adjustment technology corresponding to the adjustment direction from a preset database includes:

[0025] When the adjustment direction is profit, the smart device upgrade technology and the power grid structure optimization technology in the preset database are determined as adjustment technologies;

[0026] When the adjustment direction is to benefit the project, the distribution network coverage expansion technology and the service channel increase technology in the preset database are determined as the adjustment technology;

[0027] When the adjustment direction is cost, the spare parts reduction technology and the equipment detection strategy optimization technology in the preset database are determined as the adjustment technology.

[0028] As a preferred solution, after determining the adjustment plan for the power project to be adjusted based on the adjustment direction, the method further includes:

[0029] Adjusting the power project to be adjusted based on the adjustment plan and obtaining multi-directional data after adjustment;

[0030] According to the preset standard data, respectively performing scale transformation processing on the data of each data type in the adjusted multi-directional data to form adjusted data values ​​corresponding to each data type;

[0031] Calculating a multi-directional data difference based on each current data value of the current multi-directional data and each adjusted data value of the adjusted multi-directional data;

[0032] When the difference of the multi-directional data is less than or equal to a preset difference threshold, the adjustment scheme of the power item to be adjusted is adjusted according to each adjusted data value of the adjusted multi-directional data.

[0033] As a preferred solution, the calculating of the multi-directional data difference based on each current data value of the current multi-directional data and each adjusted data value of the adjusted multi-directional data includes:

[0034] The following formula is used to calculate the multi-directional data difference:

[0035]

[0036] Where θ is the multi-directional data difference; F1i is the i-th current data value; F2i is the i-th adjusted data value; K is the number of data types of multi-directional data.

[0037] Accordingly, the present invention provides a power project adjustment device, comprising: a historical data acquisition module, a mean value calculation module, a fitting module, a prediction module, a judgment module, a project determination module, a current data acquisition module, and a solution determination module;

[0038] The historical data acquisition module is used to acquire multi-directional data of the power project in several historical periods; wherein the multi-directional data includes data of several data types; the data types include revenue, benefited projects and costs;

[0039] The mean calculation module is used to normalize the multi-directional data under each historical period and calculate the mean of the historical multi-directional data corresponding to each historical period;

[0040] The fitting module is used to fit the time data relationship based on several historical periods and corresponding historical multi-directional data means;

[0041] The prediction module is used to obtain the predicted multi-directional data mean of the next period based on the time data relationship;

[0042] The judgment module is used to judge the size relationship between the predicted multi-directional data mean and the mean of a plurality of historical multi-directional data;

[0043] The project determination module is configured to determine that the power project is a power project to be adjusted when the number of times the historical multi-directional data mean is greater than the predicted multi-directional data mean is greater than a preset critical threshold;

[0044] The current data acquisition module is used to acquire the current multi-directional data of the power project to be adjusted in the current cycle;

[0045] The scheme determination module is used to determine an adjustment scheme for the power project to be adjusted based on the current multi-directional data.

[0046] The present invention also provides a terminal device, comprising: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the steps of the power project adjustment method of the present invention are implemented.

[0047] The present invention also provides a computer-readable storage medium item, comprising: a stored computer program, which controls the device where the computer-readable storage medium is located to execute the steps of the power project adjustment method of the present invention when the computer program is running.

[0048] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0049] The present invention provides a power project adjustment method, which includes obtaining multidirectional data of the power project in multiple historical periods; normalizing the multidirectional data in each historical period, and calculating the mean value of the historical multidirectional data corresponding to each historical period; fitting a time data relationship expression based on multiple historical periods and the corresponding historical multidirectional data means; obtaining a predicted multidirectional data mean value of the next period based on the time data relationship expression; judging the size relationship between the predicted multidirectional data mean value and the means values ​​of multiple historical multidirectional data; determining that the power project is a power project to be adjusted when the number by which the mean value of the historical multidirectional data is greater than the mean value of the predicted multidirectional data is greater than a preset critical threshold; obtaining current multidirectional data of the power project to be adjusted in the current period; and determining an adjustment plan for the power project to be adjusted based on the current multidirectional data. The present invention fits the correlation relationship between the time period and the multi-directional data mean value of the power project in the historical period, and uses the correlation relationship to predict the multi-directional data mean value of the future period, and then judges whether the power project needs to be adjusted according to the prediction result, so that the defects of the power project can be discovered in time; and generates an adjustment plan for the power project that needs to be adjusted according to the multi-directional data actually collected in the current period, thereby improving the correlation between the multi-directional data of the power project and the adjustment plan, thereby improving the effectiveness of the adjustment plan of the power project, and thus improving the efficiency of the power project. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solution of the present application, the following is a brief introduction to the drawings required for use in the implementation. Obviously, the drawings described below are only some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0051] Figure 1 A flow chart of an embodiment of the power project adjustment method provided by the present invention;

[0052] Figure 2 This is a structural schematic diagram of an embodiment of the power project adjustment device provided by the present invention. DETAILED DESCRIPTION

[0053] To make the objectives, technical solutions, and advantages of this application more clear, the technical solutions in this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this application.

[0054] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned figure descriptions are intended to cover non-exclusive inclusions.

[0055] In the description of the embodiments of this application, the technical terms "first" and "second" are used only to distinguish different objects and should not be understood to indicate or imply relative importance or implicitly specify the quantity, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, the meaning of "plurality" is more than two, unless otherwise clearly and specifically defined.

[0056] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0057] In the description of the embodiments of this application, the term "and / or" is simply a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent the following three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0058] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0059] In the description of the embodiments of the present application, unless otherwise expressly specified or limited, technical terms such as "installed," "connected," "connected," and "fixed" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integration; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; internal connections between two components or interactions between two components. Those skilled in the art can understand the specific meanings of the above terms in the embodiments of the present application based on specific circumstances.

[0060] See also Figure 1To solve the problem of low efficiency of power projects in the prior art, an embodiment of the present invention provides a power project adjustment method, which includes steps 101 to 108, each of which is specifically as follows:

[0061] Step 101: Acquire multi-directional data of a power project in several historical periods; wherein the multi-directional data includes data of several data types; the data types include revenue, benefited projects, and costs;

[0062] Step 102: normalize the multi-directional data in each historical period and calculate the mean of the historical multi-directional data corresponding to each historical period;

[0063] Step 103: Fitting a time data relationship based on several historical periods and corresponding historical multi-directional data means;

[0064] Step 104: deriving a predicted multi-directional data mean value for the next period based on the time data relationship;

[0065] Step 105: Determine the magnitude relationship between the predicted multi-directional data mean and the mean of several historical multi-directional data;

[0066] Step 106: When the number of times the historical multi-directional data mean is greater than the predicted multi-directional data mean is greater than a preset critical threshold, determining that the power project is a power project to be adjusted;

[0067] Step 107: obtaining current multi-directional data of the power project to be adjusted in the current cycle;

[0068] Step 108: Determine an adjustment plan for the power project to be adjusted based on the current multi-directional data.

[0069] In an embodiment of the present invention, based on the multidirectional data of the power project in the historical period, an association relationship between the multidirectional data and the time period is constructed. Based on the association relationship, the multidirectional data value of the future period can be predicted. By comparing the multidirectional data value with the multidirectional data of the current period, it can be determined whether the power project has defects and whether it needs adjustment. When it is determined that the power project needs adjustment, an adjustment plan can be formed based on the multidirectional data of the current period, and the adjustment plan can be used to adjust the power project to improve the efficiency of the power project.

[0070] In an embodiment of the present invention, one hour can be set as a cycle, and the multi-directional data of the power project in the historical cycle is the data basis for constructing the time data relationship. Among them, the multi-directional data includes data of different data types such as income, benefited projects and costs. Among them, income is the income value of the power project in one cycle. Benefited projects are the amount of project data that is positively affected by the power project during the operation of the power project in one cycle. For example, after running power project A for one cycle, the income of power project B and power project C increases or the cost decreases, then it is determined that power project B and power project C are both benefited projects of power project A, and the number of benefited projects of power project A is 2. Cost is the cost value of operating the power system in one cycle.

[0071] In an embodiment of the present invention, the data dimensions of different data types in the multi-directional data of the power project vary greatly. Therefore, when analyzing the multi-directional data, it is necessary to normalize the data of different data types. The data can be linearly mapped to a specified range to eliminate the impact of differences in the dimensions and value ranges of different variables on the analysis results.

[0072] In an embodiment of the present invention, after obtaining the normalized value representation of the multi-directional data corresponding to each historical period, the normalized values ​​of each type of data are averaged for each historical period to obtain the normalized value mean corresponding to each historical period.

[0073] In the embodiment of the present invention, the normalized mean value of each historical period is used as the data basis for the formula fitting, and the correlation relationship between the time period and the multi-directional data mean can be fitted. The form of the correlation relationship can be combined with the form of the sine function and the linear trend term, for example, Where y(t) is the mean of the multi-directional data, t is the time period, and a, b, c, and d are the parameters to be fitted. a is the baseline value; b is the linear growth coefficient, which reflects the growth trend; c is the fluctuation amplitude; and d is the phase offset.

[0074] In an embodiment of the present invention, after fitting a time-data relationship equation based on historical data, a predicted multi-directional data mean for the next cycle can be predicted. The predicted multi-directional data mean is compared with the historical multi-directional data means of multiple historical cycles, primarily to determine the number of times the predicted multi-directional data mean exceeds the historical multi-directional data mean. This number is then compared with a preset critical threshold to determine whether the power project is a power project to be adjusted. For example, the predicted multi-directional data mean is compared with four historical multi-directional data means, with a preset critical threshold of 3. If two historical multi-directional data means are greater than the predicted multi-directional data mean, and two historical multi-directional data means are less than the predicted multi-directional data mean, then the number of times the historical multi-directional data means exceed the predicted multi-directional data mean is 2, which is less than the preset critical threshold, and the power project is not a power project to be adjusted. If all four historical multi-directional data means are greater than the predicted multi-directional data mean, then the number of times the historical multi-directional data means exceed the predicted multi-directional data mean is 4, which is greater than the preset critical threshold, and the power project is a power project to be adjusted.

[0075] In an embodiment of the present invention, after determining that a power project is a power project to be adjusted, multi-directional data of the current cycle is obtained in real time, and an adjustment plan for the power project to be adjusted is determined by analyzing the multi-directional data of the current cycle, so as to adjust the power project using the adjustment plan.

[0076] As a preferred solution of this embodiment, determining an adjustment plan for the power project to be adjusted based on the current multi-directional data includes:

[0077] Based on the preset standard data, the data of each data type in the current multi-directional data is scaled to form the current data value corresponding to each data type;

[0078] The data type of the current data value is determined to be a negative number as the adjustment direction;

[0079] An adjustment plan for the power project to be adjusted is determined based on the adjustment direction.

[0080] In an embodiment of the present invention, after obtaining conceptual multi-directional data for the current cycle of the power project to be adjusted, the data of each data type in the current multi-directional data is first scaled according to preset standard data to standardize the data and form current data values, thereby improving the accuracy of subsequent data analysis. By determining whether each current data value is positive or negative, it is possible to determine which data type of the power project to be adjusted has defects. The defective data type is determined as the adjustment direction, and an adjustment plan for the power project to be adjusted can be formed based on this adjustment direction.

[0081] As a preferred solution of this embodiment, based on preset standard data, scaling processing is performed on data of each data type in the current multi-directional data to form current data values ​​corresponding to each data type, including:

[0082] The following formula is used to perform scale transformation to form the current data value:

[0083]

[0084] Where x' i is the current data value of the i-th category; x i is the i-th category data in the current multi-directional data; Preset standard data for category i.

[0085] In an embodiment of the present invention, the data of each data type in the current multi-directional data is scaled using the preset standard data. The difference between the two data types can be divided by the preset standard data using the above formula to obtain the current data value. When calculating the difference, the preset standard data is subtracted from the current multi-directional data. This allows the magnitude relationship between the multi-directional data and the preset standard data to be determined by determining whether the current data value is positive or negative.

[0086] In an embodiment of the present invention, after calculating multiple current data values ​​of the current multi-directional data, the negative current data values ​​are filtered out, and the data type corresponding to this part of the current data values ​​is determined to be defective. Determining this data type as the adjustment direction can form an adjustment plan for the power project to be adjusted.

[0087] As a preferred solution of this embodiment, determining an adjustment plan for the power project to be adjusted based on the adjustment direction includes:

[0088] Based on the adjustment direction, obtaining an adjustment technology corresponding to the adjustment direction from a preset database;

[0089] An adjustment plan for the power project to be adjusted is formed based on the adjustment technology.

[0090] In this embodiment of the present invention, a preset database contains corresponding adjustment technologies for different data types, such as revenue, benefited projects, and cost data. Therefore, after determining the adjustment direction, the preset database can be searched for the corresponding adjustment technology. By integrating and coordinating the adjustment technologies corresponding to each adjustment direction, an adjustment plan for the power project to be adjusted can be formed.

[0091] As a preferred solution of this embodiment, based on the adjustment direction, obtaining an adjustment technology corresponding to the adjustment direction from a preset database includes:

[0092] When the adjustment direction is profit, the smart device upgrade technology and the power grid structure optimization technology in the preset database are determined as adjustment technologies;

[0093] When the adjustment direction is to benefit the project, the distribution network coverage expansion technology and the service channel increase technology in the preset database are determined as the adjustment technology;

[0094] When the adjustment direction is cost, the spare parts reduction technology and the equipment detection strategy optimization technology in the preset database are determined as the adjustment technology.

[0095] In an embodiment of the present invention, a preset database stores multiple adjustment techniques corresponding to different data types. When benefits are limited, they can be increased by upgrading intelligent devices and optimizing the power grid structure. For example, upgrading distribution automation systems (such as FTU and DTU terminals) can achieve automatic fault location and isolation, reducing manual troubleshooting time and maintenance labor costs, while also improving power restoration efficiency and minimizing user losses from power outages. Introducing intelligent inspection robots and smart sensors to monitor equipment status in real time reduces the frequency of manual inspections and lowers long-term maintenance costs, thereby upgrading intelligent devices. Renovating high-loss distribution lines (such as replacing old conductors and adjusting transformer capacity) can reduce line losses and improve energy transmission efficiency, indirectly increasing power supply benefits. When benefit-sharing projects are limited, the number of benefit-sharing projects can be increased by expanding distribution network coverage and adding service channels. For example, adding distribution lines and transformers to remote areas or areas with new users can improve distribution network coverage, and increasing service channels for promoting power projects can expand the number of benefit-sharing projects. When costs are limited, reducing spare parts and optimizing equipment testing strategies can reduce costs. For example, standardizing the models and specifications of O&M equipment required for power projects reduces the number of spare parts and, in turn, inventory costs. Furthermore, digital O&M platforms integrate inspection and maintenance tasks, rationally allocating O&M personnel and vehicles, avoiding idle resources or duplicate dispatch, and reducing labor and transportation costs.

[0096] As a preferred solution of this embodiment, after determining the adjustment plan for the power project to be adjusted based on the adjustment direction, the method further includes:

[0097] Adjusting the power project to be adjusted based on the adjustment plan and obtaining multi-directional data after adjustment;

[0098] According to the preset standard data, respectively performing scale transformation processing on the data of each data type in the adjusted multi-directional data to form adjusted data values ​​corresponding to each data type;

[0099] Calculating a multi-directional data difference based on each current data value of the current multi-directional data and each adjusted data value of the adjusted multi-directional data;

[0100] When the difference of the multi-directional data is less than or equal to a preset difference threshold, the adjustment scheme of the power item to be adjusted is adjusted according to each adjusted data value of the adjusted multi-directional data.

[0101] In an embodiment of the present invention, after determining an adjustment plan for a power project to be adjusted, the power project to be adjusted is adjusted according to the adjustment plan, and multi-directional data after the adjustment plan is collected to form adjusted multi-directional data. The adjusted multi-directional data also includes data of different data types, such as revenue, benefited projects, and costs. This adjusted multi-directional data is also scaled based on preset standard data, scaling it to the same dimension as the current data value to form the adjusted data value, thereby improving the accuracy of subsequent analysis of the current data value and the adjusted data value.

[0102] As a preferred solution of this embodiment, calculating the multi-directional data difference based on each current data value of the current multi-directional data and each adjusted data value of the adjusted multi-directional data includes:

[0103] The following formula is used to calculate the multi-directional data difference:

[0104]

[0105] Where θ is the multi-directional data difference; F1i is the i-th current data value; F2i is the i-th adjusted data value; K is the number of data types of multi-directional data.

[0106] In an embodiment of the present invention, after obtaining the current data value and the adjusted data value, by calculating the multi-directional data difference, it is possible to reflect the data changes of the item to be adjusted before and after the adjustment, and to analyze the effect of the adjustment plan for the item to be adjusted. According to the above formula, the multi-directional data difference can be calculated, and the multi-directional data difference is compared with the preset difference threshold. When the multi-directional data difference is greater than the preset difference threshold, it means that the effect of the adjustment plan for the item to be adjusted is good, and there is no need to adjust the adjustment plan. When the multi-directional data difference is less than or equal to the preset difference threshold, it means that the effect of the adjustment plan for the item to be adjusted is not good, and at this time, the adjustment plan for the item to be adjusted needs to be adjusted.

[0107] In an embodiment of the present invention, an adjustment scheme for a power project to be adjusted can be adjusted based on the adjusted data values ​​of the adjusted multi-directional data. Specifically, negative adjusted data values ​​are first screened out from the adjusted data values, and the data types corresponding to these adjusted data values ​​are determined to be defective. Based on the defective data types, a corresponding adjustment technique is determined in a preset database, and the adjustment scheme for the power project to be adjusted is adjusted.

[0108] The implementation of the above embodiment has the following effects:

[0109] The present invention provides a power project adjustment method, which includes obtaining multidirectional data of the power project in multiple historical periods; normalizing the multidirectional data in each historical period, and calculating the mean value of the historical multidirectional data corresponding to each historical period; fitting a time data relationship expression based on multiple historical periods and the corresponding historical multidirectional data means; obtaining a predicted multidirectional data mean value of the next period based on the time data relationship expression; judging the size relationship between the predicted multidirectional data mean value and the means values ​​of multiple historical multidirectional data; determining that the power project is a power project to be adjusted when the number by which the mean value of the historical multidirectional data is greater than the mean value of the predicted multidirectional data is greater than a preset critical threshold; obtaining current multidirectional data of the power project to be adjusted in the current period; and determining an adjustment plan for the power project to be adjusted based on the current multidirectional data. The present invention fits the correlation relationship between the time period and the multi-directional data mean value of the power project in the historical period, and uses the correlation relationship to predict the multi-directional data mean value of the future period, and then judges whether the power project needs to be adjusted according to the prediction result, so that the defects of the power project can be discovered in time; and generates an adjustment plan for the power project that needs to be adjusted according to the multi-directional data actually collected in the current period, thereby improving the correlation between the multi-directional data of the power project and the adjustment plan, thereby improving the effectiveness of the adjustment plan of the power project, and thus improving the efficiency of the power project.

[0110] like Figure 2 As shown, based on the above method embodiment, a corresponding device embodiment is provided;

[0111] An embodiment of the present invention provides a power project adjustment device, comprising: a historical data acquisition module, a mean value calculation module, a fitting module, a prediction module, a judgment module, a project determination module, a current data acquisition module, and a solution determination module;

[0112] The historical data acquisition module is used to acquire multi-directional data of the power project in several historical periods; wherein the multi-directional data includes data of several data types; the data types include revenue, benefited projects and costs;

[0113] The mean calculation module is used to normalize the multi-directional data under each historical period and calculate the mean of the historical multi-directional data corresponding to each historical period;

[0114] The fitting module is used to fit the time data relationship based on several historical periods and corresponding historical multi-directional data means;

[0115] The prediction module is used to obtain the predicted multi-directional data mean of the next period based on the time data relationship;

[0116] The judgment module is used to judge the size relationship between the predicted multi-directional data mean and the mean of a plurality of historical multi-directional data;

[0117] The project determination module is configured to determine that the power project is a power project to be adjusted when the number of times the historical multi-directional data mean is greater than the predicted multi-directional data mean is greater than a preset critical threshold;

[0118] The current data acquisition module is used to acquire the current multi-directional data of the power project to be adjusted in the current cycle;

[0119] The scheme determination module is used to determine an adjustment scheme for the power project to be adjusted based on the current multi-directional data.

[0120] It can be understood that the above-mentioned device embodiment corresponds to the method embodiment of the present invention, and can implement any one of the above-mentioned method embodiments of the present invention to provide a power project adjustment method.

[0121] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. Furthermore, in the drawings of the device embodiments provided by the present invention, the connection relationship between modules indicates that they have a communication connection, which may be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement the present invention without inventive effort.

[0122] Based on the above-mentioned embodiment of the power project adjustment method, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the power project adjustment method of any embodiment of the present invention is implemented.

[0123] For example, in this embodiment, the computer program may be divided into one or more modules, which are stored in the memory and executed by the processor to implement the present invention. The one or more module elements may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program in the terminal device.

[0124] The terminal device may be a computing device such as a desktop computer, a notebook computer, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0125] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, connecting various parts of the entire terminal device using various interfaces and lines.

[0126] Based on the above method embodiments, another embodiment of the present invention provides a computer-readable storage medium, including a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the power project adjustment method described in any one of the above method embodiments of the present invention.

[0127] Wherein, the module / unit integrated in the device / terminal equipment, if implemented in the form of a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, it can implement the steps of the above-mentioned various method embodiments. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0128] The specific embodiments described above further illustrate the objectives, technical solutions, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for adjusting a power project, characterized in that: include: Acquire multi-directional data of the power project in several historical periods; wherein the multi-directional data includes data of several data types; the data types include revenue, benefited projects and costs; Normalize the multi-directional data in each historical period and calculate the mean of the historical multi-directional data corresponding to each historical period; Based on several historical periods and the corresponding historical multi-directional data means, fit the time data relationship; Determining the predicted multi-directional data mean for the next period based on the time data relationship; Determining the magnitude relationship between the predicted multi-directional data mean and a plurality of historical multi-directional data means; When the number of times that the historical multi-directional data mean is greater than the predicted multi-directional data mean is greater than a preset critical threshold, determining that the power project is a power project to be adjusted; Acquiring current multi-directional data of the power project to be adjusted in the current cycle; An adjustment plan for the power project to be adjusted is determined based on the current multi-directional data.

2. The power project adjustment method according to claim 1, characterized in that: The determining of the adjustment plan for the power project to be adjusted based on the current multi-directional data includes: Based on the preset standard data, the data of each data type in the current multi-directional data is scaled to form the current data value corresponding to each data type; The data type of the current data value is determined to be a negative number as the adjustment direction; An adjustment plan for the power project to be adjusted is determined based on the adjustment direction.

3. The power project adjustment method according to claim 2, characterized in that: The scaling process is performed on the data of each data type in the current multi-directional data based on the preset standard data to form the current data value corresponding to each data type, including: The following formula is used to perform scale transformation to form the current data value: Where x' i is the current data value of the i-th category; x i is the i-th category data in the current multi-directional data; Preset standard data for category i.

4. The power project adjustment method according to claim 3, characterized in that: The determining of the adjustment plan for the power project to be adjusted based on the adjustment direction includes: Based on the adjustment direction, obtaining an adjustment technology corresponding to the adjustment direction from a preset database; An adjustment plan for the power project to be adjusted is formed based on the adjustment technology.

5. The power project adjustment method according to claim 4, characterized in that: The acquiring, based on the adjustment direction, an adjustment technology corresponding to the adjustment direction from a preset database includes: When the adjustment direction is profit, the smart device upgrade technology and the power grid structure optimization technology in the preset database are determined as adjustment technologies; When the adjustment direction is to benefit the project, the distribution network coverage expansion technology and the service channel increase technology in the preset database are determined as the adjustment technology; When the adjustment direction is cost, the spare parts reduction technology and the equipment detection strategy optimization technology in the preset database are determined as the adjustment technology.

6. The power project adjustment method according to claim 5, characterized in that: After determining the adjustment plan for the power project to be adjusted based on the adjustment direction, the method further includes: Adjusting the power project to be adjusted based on the adjustment plan and obtaining multi-directional data after adjustment; According to the preset standard data, respectively performing scale transformation processing on the data of each data type in the adjusted multi-directional data to form adjusted data values ​​corresponding to each data type; Calculating a multi-directional data difference based on each current data value of the current multi-directional data and each adjusted data value of the adjusted multi-directional data; When the difference of the multi-directional data is less than or equal to a preset difference threshold, the adjustment scheme of the power item to be adjusted is adjusted according to each adjusted data value of the adjusted multi-directional data.

7. The power project adjustment method according to claim 6, characterized in that: The calculating of the multi-directional data difference based on each current data value of the current multi-directional data and each adjusted data value of the adjusted multi-directional data includes: The following formula is used to calculate the multi-directional data difference: Where θ is the multi-directional data difference; F1i is the i-th current data value; F2i is the i-th adjusted data value; K is the number of data types of multi-directional data.

8. A power project adjustment device, characterized in that: include: Historical data acquisition module, mean calculation module, fitting module, prediction module, judgment module, project determination module, current data acquisition module and solution determination module; The historical data acquisition module is used to acquire multi-directional data of the power project in several historical periods; wherein the multi-directional data includes data of several data types; the data types include revenue, benefited projects and costs; The mean calculation module is used to normalize the multi-directional data under each historical period and calculate the mean of the historical multi-directional data corresponding to each historical period; The fitting module is used to fit the time data relationship based on several historical periods and corresponding historical multi-directional data means; The prediction module is used to obtain the predicted multi-directional data mean of the next period based on the time data relationship; The judgment module is used to judge the size relationship between the predicted multi-directional data mean and the mean of a plurality of historical multi-directional data; The project determination module is configured to determine that the power project is a power project to be adjusted when the number of times the historical multi-directional data mean is greater than the predicted multi-directional data mean is greater than a preset critical threshold; The current data acquisition module is used to acquire the current multi-directional data of the power project to be adjusted in the current cycle; The scheme determination module is used to determine an adjustment scheme for the power project to be adjusted based on the current multi-directional data.

9. A terminal device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the method for adjusting a power project according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that include: A stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the power project adjustment method according to any one of claims 1 to 7.

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