Power valley and peak analysis method for power big data service and application

Abstract

The invention relates to the technical field of power peak-valley analysis, and discloses a power valley-peak analysis method for power big data business and application. The electric power valley-peak analysis method comprises the following specific steps: collecting electric power data, establishing a three-dimensional model for analysis, performing regional registration planning analysis, performing dynamic division according to time periods, preprocessing the electric power data, and setting a preprocessing scheme. According to the electric power valley-peak analysis method for the electric power big data service and the application, the load characteristics of the electric power system can be more accurately known by analyzing the electric power valley-peak data, so that the allocation strategy of the electric power resources is optimized, the electric power resources are reasonably allocated in the electric power peak period, the load pressure is reduced, and the stable operation of the electric power system is ensured; according to the power valley-peak analysis method, a power enterprise can conveniently overhaul and maintain equipment in a low-peak period, the power failure and maintenance cost caused by equipment faults is reduced, and the overall power consumption and operation cost can be reduced by optimizing the use of power resources.

Description

Technical Field

[0001] The present invention relates to the technical field of power peak-valley analysis, and specifically to a power valley-peak analysis method and application for power big data business. Background Art

[0002] With the rapid development of the power industry, the amount of power data generated has exploded. These data cover multiple links such as power production, transmission, distribution and consumption, providing the power industry with rich information resources. In order to make full use of these resources, the power industry needs to use advanced technical means to deeply mine and analyze power data to reveal the inherent laws and potential value of power data. Power valley peak analysis is a study of the differences in power consumption in different time periods, aiming to provide the power industry with reasonable resource allocation strategies and promote the efficient operation of the power system. Through the analysis of power valley peaks, we can understand the load characteristics of the power system, predict future power demand, and provide decision-making basis for the planning, operation and management of the power system. Power big data technology is the practical application of big data technology in the power industry, involving multiple links such as production, transmission, transformation, distribution, use and adjustment. Power big data technology realizes the rapid processing and analysis of power data through key technologies such as data mining, data visualization, high-performance computing and statistical analysis. These technologies provide strong support for power valley peak analysis, making the analysis process more efficient and accurate. This application now proposes a power valley peak analysis method and application for power big data business Summary of the invention

[0003] Technical Solution

[0004] To achieve the above object, the present invention provides the following technical solution: a method and application for analyzing power valley peaks for power big data business, wherein the specific steps of the power valley peak analysis method are as follows:

[0005] S1. Collect power data and build a three-dimensional model for analysis;

[0006] S2. Conduct regional registration planning analysis;

[0007] S3, dynamic division according to time periods;

[0008] S4, preprocessing the power data and setting a preprocessing scheme;

[0009] The application of the power valley peak analysis method includes power dispatching, electricity price setting, and demand side management.

[0010] Preferably, the collecting of power data and establishing of a three-dimensional model for analysis specifically comprises: collecting power load data, including historical load data and real-time load data; using three-dimensional modeling technology to construct a three-dimensional model of the power load data, so as to more intuitively display and analyze the peak and valley characteristics of the power load.

[0011] Preferably, the regional registration planning analysis is specifically to divide the power load data into regions, classify and organize the load data of different regions, conduct in-depth analysis of the load data of each region, and understand the load characteristics and peak and valley periods of each region.

[0012] Preferably, the dynamic division according to time periods includes setting reasonable time period division standards according to the peak and valley characteristics of the power load and dynamically adjusting the time period division according to actual conditions to adapt to changes in the power load.

[0013] Preferably, the power data is preprocessed and a preprocessing scheme is set: the power load data is preprocessed, including data cleaning and data conversion, to improve the accuracy and efficiency of data analysis, and a pre-judgment and processing scheme for valley-peak abnormal situations is set so that timely response and processing can be carried out when abnormalities occur.

[0014] Preferably, the specific steps of applying the power valley peak analysis method are as follows:

[0015] Step 1:

[0016] Through the power valley peak analysis method, we can understand the peak and valley periods and load characteristics of power load, and provide a scientific basis for power dispatching; during peak hours, we can give priority to dispatching renewable energy and high-efficiency energy to reduce dependence on traditional energy and emissions; during valley hours, we can reasonably arrange the inspection and maintenance of power equipment to improve the reliability and service life of power equipment;

[0017] Step 2:

[0018] Through the power valley-peak analysis method, we can understand the peak-valley characteristics of power load and user electricity consumption behavior, provide a scientific basis for electricity price formulation, and formulate differentiated electricity price policies according to peak-valley periods and load characteristics to guide users to use electricity reasonably and save electricity. Through the leverage of electricity prices, we can promote the healthy development of the power market and the realization of energy conservation and emission reduction goals;

[0019] Step 3:

[0020] Through the electricity peak and valley analysis method, we can understand the users' electricity demand and electricity consumption behavior, provide a scientific basis for demand-side management, and formulate personalized demand-side management plans according to the users' electricity demand and electricity consumption behavior to improve the users' electricity efficiency and satisfaction. Through demand-side management, we can promote the supply and demand balance and sustainable development of the electricity market.

[0021] Compared with the prior art, the present invention provides a method and application for analyzing power valley peaks for power big data business, which has the following beneficial effects:

[0022] 1. The power valley peak analysis method and application for power big data business can more accurately understand the load characteristics of the power system by analyzing the power valley peak data, thereby optimizing the allocation strategy of power resources. During the peak power period, power resources can be reasonably allocated to reduce load pressure and ensure the stable operation of the power system. The power valley peak analysis method helps power companies to carry out equipment inspection and maintenance during off-peak periods, reduce power outages and maintenance costs caused by equipment failures, and reduce overall power consumption and operating costs by optimizing the use of power resources.

[0023] 2. The power valley peak analysis method and its application for power big data business can guide users to use electricity during low-peak hours when electricity prices are lower, thereby reducing power demand during peak hours, helping to reduce carbon emissions and energy consumption of power plants, and conforming to the development trend of green energy. The application of the power valley peak analysis method is helpful to promote the reform and development of the power market. By analyzing the power valley peak data, the supply and demand relationship and price mechanism of the power market can be revealed, providing strong data support for the reform of the power market. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 The figure is a flow chart of the method for analyzing power valley peaks in the power big data business of the present invention. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] A method and application of power valley peak analysis for power big data business, the specific steps of the power valley peak analysis method are as follows:

[0027] S1. Collect power data and build a three-dimensional model for analysis;

[0028] S2. Conduct regional registration planning analysis;

[0029] S3, dynamic division according to time periods;

[0030] S4, preprocessing the power data and setting a preprocessing scheme;

[0031] The application of the power valley peak analysis method includes power dispatching, electricity price setting, and demand side management.

[0032] Furthermore, the collection of power data and establishment of a three-dimensional model for analysis specifically includes: collecting power load data, including historical load data and real-time load data; using three-dimensional modeling technology to construct a three-dimensional model of the power load data, so as to more intuitively display and analyze the peak and valley characteristics of the power load.

[0033] Furthermore, the regional registration planning analysis is specifically to divide the power load data into regions, classify and organize the load data of different regions, conduct in-depth analysis of the load data of each region, and understand the load characteristics and peak and valley periods of each region.

[0034] Furthermore, the dynamic division according to time periods includes setting reasonable time period division standards according to the peak and valley characteristics of the power load and dynamically adjusting the time period division according to actual conditions to adapt to changes in the power load.

[0035] Furthermore, the power data is preprocessed and a preprocessing plan is set: the power load data is preprocessed, including data cleaning and data conversion, to improve the accuracy and efficiency of data analysis, and a pre-judgment and processing plan for valley-peak abnormal situations is set so that timely response and processing can be carried out when abnormalities occur.

[0036] Furthermore, the specific steps of applying the power valley peak analysis method are as follows:

[0037] Step 1:

[0038] Through the power valley peak analysis method, we can understand the peak and valley periods and load characteristics of power load, and provide a scientific basis for power dispatching; during peak hours, we can give priority to dispatching renewable energy and high-efficiency energy to reduce dependence on traditional energy and emissions; during valley hours, we can reasonably arrange the inspection and maintenance of power equipment to improve the reliability and service life of power equipment;

[0039] Step 2:

[0040] Through the power valley-peak analysis method, we can understand the peak-valley characteristics of power load and user electricity consumption behavior, provide a scientific basis for electricity price formulation, and formulate differentiated electricity price policies according to peak-valley periods and load characteristics to guide users to use electricity reasonably and save electricity. Through the leverage of electricity prices, we can promote the healthy development of the power market and the realization of energy conservation and emission reduction goals;

[0041] Step 3:

[0042] Through the electricity peak and valley analysis method, we can understand the users' electricity demand and electricity consumption behavior, provide a scientific basis for demand-side management, and formulate personalized demand-side management plans according to the users' electricity demand and electricity consumption behavior to improve the users' electricity efficiency and satisfaction. Through demand-side management, we can promote the supply and demand balance and sustainable development of the electricity market.

[0043] Embodiment 1:

[0044] A method and application of power valley peak analysis for power big data business, the specific steps of the power valley peak analysis method are as follows:

[0045] S1. Collect power data and build a three-dimensional model for analysis;

[0046] S2. Conduct regional registration planning analysis;

[0047] S3, dynamic division according to time periods;

[0048] S4, preprocessing the power data and setting a preprocessing scheme;

[0049] The application of the power valley peak analysis method includes power dispatching, electricity price setting, and demand side management.

[0050] Embodiment 2:

[0051] According to a method and application for analyzing power valley and peak values ​​for power big data business proposed in Example 1, power data is collected and a three-dimensional model is established for analysis. Specifically, power load data is collected, including historical load data and real-time load data; a three-dimensional model of power load data is constructed using three-dimensional modeling technology to more intuitively display and analyze the peak and valley characteristics of power load. Constructing a three-dimensional model of power load data can more intuitively display and analyze the peak and valley characteristics of power load, which is helpful to discover the load change rules and problems in the power system; the collected power load data is preprocessed, including data cleaning, data conversion and other steps to ensure that the data is suitable for three-dimensional modeling, and select appropriate The three-dimensional modeling software or tool imports the processed power load data into the software to construct the three-dimensional model, optimizes and adjusts the constructed three-dimensional model to ensure the accuracy and reliability of the model. Through the analysis and calculation of the three-dimensional model, the power load changes in the future can be predicted, providing a decision-making basis for the dispatching and planning of the power system. Regional registration planning analysis is of great significance for the optimized operation and efficient management of the power system. Through detailed regional division, load data classification and in-depth load characteristic analysis, the load characteristics and peak and valley periods of each region can be fully understood, providing a scientific basis and decision-making support for the dispatching, planning and operation of the power system.

[0052] Embodiment three:

[0053] According to the method and application of power valley peak analysis for power big data business proposed in Example 1, regional registration planning analysis is specifically to divide the power load data into regions, classify and organize the load data of different regions, conduct in-depth analysis of the load data of each region, understand the load characteristics and peak and valley time periods of each region, and dynamically divide according to time periods. It is an efficient and flexible power load management strategy, which sets reasonable time period division standards based on the peak and valley characteristics of power load, and dynamically adjusts according to actual conditions to adapt to changes in power load. This strategy helps to balance the load of the power grid, improve the utilization efficiency of power resources, and ensure the stable operation of the power system.

[0054] Embodiment 4:

[0055] According to the power valley-peak analysis method and application for power big data business proposed in Example 1, dynamic division according to time periods includes setting reasonable time period division standards according to the peak-valley characteristics of the power load and dynamically adjusting the time period division according to actual conditions to adapt to changes in the power load. Dynamic division according to time periods is an important strategy in power load management. It sets reasonable time period division standards based on the peak-valley characteristics of the power load and dynamically adjusts the time period division according to actual conditions to adapt to changes in the power load. This strategy helps to balance the power grid load, improve the utilization efficiency of power resources and ensure the stable operation of the power system.

[0056] Embodiment five:

[0057] According to the power valley peak analysis method and application for power big data business proposed in Example 1, the power data is preprocessed and a preprocessing scheme is set: the power load data is preprocessed, including data cleaning and data conversion, to improve the accuracy and efficiency of data analysis, and a pre-judgment and processing scheme for valley peak abnormalities is set so that timely response and processing can be carried out when abnormalities occur. By preprocessing the power load data and setting a pre-judgment and processing scheme for valley peak abnormalities, the accuracy and efficiency of data analysis can be improved to ensure the stable operation of the power system. In actual applications, the preprocessing scheme needs to be adjusted and optimized according to the specific situation to adapt to different business needs and scenarios.

[0058] Embodiment six:

[0059] According to a method and application of power valley peak analysis for power big data business proposed in the first embodiment, the specific steps of applying the power valley peak analysis method are as follows:

[0060] Step 1:

[0061] Through the power valley peak analysis method, we can understand the peak and valley periods and load characteristics of power load, and provide a scientific basis for power dispatching; during peak hours, we can give priority to dispatching renewable energy and high-efficiency energy to reduce dependence on traditional energy and emissions; during valley hours, we can reasonably arrange the inspection and maintenance of power equipment to improve the reliability and service life of power equipment;

[0062] Step 2:

[0063] Through the power valley-peak analysis method, we can understand the peak-valley characteristics of power load and user electricity consumption behavior, provide a scientific basis for electricity price formulation, and formulate differentiated electricity price policies according to peak-valley periods and load characteristics to guide users to use electricity reasonably and save electricity. Through the leverage of electricity prices, we can promote the healthy development of the power market and the realization of energy conservation and emission reduction goals;

[0064] Step 3:

[0065] Through the electricity peak and valley analysis method, we can understand the users' electricity demand and electricity consumption behavior, provide a scientific basis for demand-side management, and formulate personalized demand-side management plans according to the users' electricity demand and electricity consumption behavior to improve the users' electricity efficiency and satisfaction. Through demand-side management, we can promote the supply and demand balance and sustainable development of the electricity market.

[0066] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method and application for analyzing power valley peaks for power big data business, characterized by: The specific steps of the power valley peak analysis method are as follows: S1. Collect power data and build a three-dimensional model for analysis; S2. Conduct regional registration planning analysis; S3, dynamic division according to time periods; S4, preprocessing the power data and setting a preprocessing scheme; The application of the power valley peak analysis method includes power dispatching, electricity price setting, and demand side management.

2. According to claim 1, a method and application for analyzing power valley peaks for power big data services, characterized in that: The collecting of power data and establishing a three-dimensional model for analysis specifically includes: collecting power load data, including historical load data and real-time load data; using three-dimensional modeling technology to construct a three-dimensional model of the power load data, so as to more intuitively display and analyze the peak and valley characteristics of the power load.

3. According to the method and application of power valley peak analysis for power big data business of claim 1, it is characterized by: The regional registration planning analysis specifically involves dividing the power load data into regions, classifying and sorting the load data of different regions, and conducting in-depth analysis of the load data of each region to understand the load characteristics and peak and valley periods of each region.

4. According to claim 1, a method and application for analyzing power valley peaks for power big data services, characterized in that: The dynamic division according to time periods includes setting reasonable time period division standards according to the peak and valley characteristics of the power load and dynamically adjusting the time period division according to actual conditions to adapt to changes in the power load.

5. According to claim 1, a method and application for analyzing power valley peaks for power big data services, characterized in that: The power data is preprocessed and a preprocessing scheme is set: the power load data is preprocessed, including data cleaning and data conversion, to improve the accuracy and efficiency of data analysis, and a pre-judgment and processing scheme for valley-peak abnormal situations is set so that timely response and processing can be carried out when abnormalities occur.

6. The method and application of power valley peak analysis for power big data business according to claim 1, characterized in that: The specific steps of applying the power valley peak analysis method are as follows: Step 1: Through the power valley peak analysis method, we can understand the peak and valley periods and load characteristics of power load, and provide a scientific basis for power dispatching; during peak hours, we can give priority to dispatching renewable energy and high-efficiency energy to reduce dependence on traditional energy and emissions; during valley hours, we can reasonably arrange the inspection and maintenance of power equipment to improve the reliability and service life of power equipment; Step 2: Through the power valley-peak analysis method, we can understand the peak-valley characteristics of power load and user electricity consumption behavior, provide a scientific basis for electricity price formulation, and formulate differentiated electricity price policies according to peak-valley periods and load characteristics to guide users to use electricity reasonably and save electricity. Through the leverage of electricity prices, we can promote the healthy development of the power market and the realization of energy conservation and emission reduction goals; Step 3: Through the electricity peak and valley analysis method, we can understand the users' electricity demand and electricity consumption behavior, provide a scientific basis for demand-side management, and formulate personalized demand-side management plans according to the users' electricity demand and electricity consumption behavior to improve the users' electricity efficiency and satisfaction. Through demand-side management, we can promote the supply and demand balance and sustainable development of the electricity market.

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