Power load prediction system
By designing a power load prediction system containing multiple collaborative working modules, the problem of low load prediction accuracy in the power system is solved, and high accuracy and efficient prediction effects are achieved, supporting the safe, economical and efficient operation of the power system.
Patent Information
- Application Number
- CN202411621089.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-14
- Publication Date
- 2025-03-28
AI Technical Summary
With the expansion of power system scale and the growth of data resources, the accuracy of power load prediction has been affected, and it is difficult for the existing technology to provide high-precision and efficient and convenient prediction systems.
A power load prediction system is designed, including power information acquisition module, external environment information acquisition module, data collection module, transmission module, data integration storage module, prediction model construction module and prediction result analysis module. Through the coordinated work of these modules, power load data can be collected, integrated, predicted and analyzed to form a high-precision prediction model.
It realizes high-precision power load prediction, improves the efficiency and convenience of the prediction system, can more accurately support the scheduling and planning of the power system, and reduces the cost of electricity and electricity prices.
Smart Images
Figure CN119726640A_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the field of electric power technology, and in particular relates to an electric power load forecasting system. Background Art
[0002] Electricity load forecasting refers to estimating the electricity load and power consumption in the next few hours to years. It is an important daily task for the power system dispatching and operation departments, power service departments and power grid planning departments. It is the main basis for formulating power generation plans, transmission plans and power grid construction. Electricity load forecasting is an important part of power system planning. For regional power grids, providing high-precision daily load forecasts for superior dispatchers can enable superior dispatchers to reasonably arrange spinning reserve and cold standby capacity when formulating power generation plans, reduce the number of unit starts and stops, and reduce the amount of electricity traded on the same day, thereby meeting the electricity needs of users while reducing electricity costs and Electricity price; for the power grid itself, daily load forecast data is an important basis for verifying the safety of the power grid, and monthly load forecast data is an important basis for formulating power grid maintenance plans. Therefore, both from an economic and safety perspective, power load forecasting is very important, and its prediction accuracy directly affects the safety, economy and power supply quality of the power system operation; however, with the continuous expansion of the scale of the power system, power data resources have increased dramatically, which has seriously affected the accuracy of power load forecasting; therefore, in order to solve the above problems, it is necessary to develop a power load forecasting system with high prediction accuracy and efficient and convenient use. Summary of the invention
[0003] The purpose of the present invention is to overcome the deficiencies of the prior art and to provide a power load forecasting system which has high prediction accuracy and is efficient and convenient to use.
[0004] The object of the present invention is achieved as follows: a power load forecasting system, comprising a power information acquisition module, an external environment information acquisition module, a data collection module, a transmission module, a data integration storage module, a prediction model construction module and a prediction result analysis module, wherein the power information acquisition module can be used to collect historical load data of the power system; the external environment information acquisition module can be used to detect and acquire external environment data at a time corresponding to the historical load data of the power system; the data collection module can be used to uniformly collect the historical load data of the power system collected by the power information acquisition module and the external environment data detected and collected by the external environment information acquisition module; the transmission module is located between the data collection module and the data integration storage module, and is used for transmitting data information from the data collection module to the data integration storage module; the data integration storage The model is composed of an integration unit and a storage unit, wherein the storage unit can store and back up the data information transmitted to it, and the integration unit can filter and integrate the historical load data of the power system and the external environment data, filter out redundant data, and supplement the missing data information. After that, the historical load data of the power system and its corresponding external environment data are segmented and integrated in units of days, thereby forming multiple data information packets; the prediction model construction module can be based on the data information packet, with historical data as model input and load data of N consecutive moments in the future as model output, to construct the original model, and then use actual historical detection data to train the model to obtain a power load prediction model; the prediction result analysis module can analyze, judge and evaluate the power load data predicted by the power load prediction model, thereby increasing the accuracy of the prediction.
[0005] Furthermore, the external environment data includes but is not limited to daily maximum temperature, daily average temperature, daily minimum temperature, daily rainfall and daily relative humidity.
[0006] Furthermore, the prediction model construction module is internally provided with an image generation unit, which can be used to draw a power load curve graph, and the image generation unit is externally connected to a display component, through which the power load curve graph can be displayed.
[0007] Furthermore, an alarm unit is provided inside the prediction result analysis module, and the alarm unit can be used to send a warning message corresponding to the load to the power system when the prediction data exceeds a preset threshold.
[0008] Furthermore, the power information acquisition module is composed of a data acquisition device and a monitoring component, and the acquisition of historical load data is completed through the cooperation of the data acquisition device and the monitoring component.
[0009] The beneficial effects of the present invention are as follows: the present invention sets an electric power information acquisition module and an external environment information acquisition module, which can be used to respectively collect and detect the historical load data and external environment data of the electric power system; sets a data collection module, a transmission module and a data integration storage module, the data collection module can be used to uniformly collect the collected and detected data, the transmission module can be used to realize the transmission of data, the data integration storage module can be used to store and back up the data, and at the same time, the historical load data of the electric power system and its corresponding external environment data are segmented and integrated on a daily basis, thereby forming a plurality of data information packets; sets a prediction model construction module, which can be used to construct an original model based on the data information packet, with historical data as the model input and load data of N consecutive moments in the future as the model output, and then the original model is trained to obtain an electric power load prediction model; sets a prediction result analysis module, which can be used to analyze, judge and evaluate the electric power load data predicted by the electric power load prediction model, thereby increasing the accuracy of the prediction; in general, the present invention has the advantages of high prediction accuracy and efficient and convenient use. BRIEF DESCRIPTION OF THE DRAWINGS
[0010] Figure 1 It is a structural flow chart of the present invention. DETAILED DESCRIPTION
[0011] The present invention will be further described below in conjunction with the accompanying drawings.
[0012] Example: Figure 1 As shown, a power load forecasting system includes a power information acquisition module, an external environment information acquisition module, a data collection module, a transmission module, a data integration and storage module, a prediction model construction module and a prediction result analysis module, wherein the power information acquisition module is composed of a data acquisition device and a monitoring component, and the acquisition of historical load data is completed through the cooperation of the data acquisition device and the monitoring component; the external environment information acquisition module can be used to detect and acquire external environment data at the time corresponding to the historical load data of the power system, wherein the external environment data includes but is not limited to daily maximum temperature, daily average temperature, daily minimum temperature, daily rainfall and daily relative humidity.
[0013] The data collection module can be used to uniformly collect the historical load data of the power system collected by the power information collection module and the external environment data detected and collected by the external environment information acquisition module; the transmission module is located between the data collection module and the data integration and storage module, and is used for transmitting data information from the data collection module to the data integration and storage module; the data integration and storage module is composed of an integration unit and a storage unit, wherein the storage unit can store and back up the data information transmitted to it, and the integration unit can filter and integrate the historical load data of the power system and the external environment data, filter out redundant data, and supplement missing data information. Afterwards, the historical load data of the power system and its corresponding external environment data are segmented and integrated in units of days, thereby forming multiple data information packets.
[0014] The prediction model construction module can construct an original model based on the data information package, with historical data as the model input and load data of N consecutive moments in the future as the model output. After that, the model is trained using actual historical detection data to obtain a power load prediction model. At the same time, the prediction model construction module is internally provided with an image generation unit, which can be used to draw a power load curve graph, and the image generation unit is externally connected to a display component, and the power load curve graph can be displayed through the display component. The prediction result analysis module can analyze, judge and evaluate the power load data predicted by the power load prediction model, thereby increasing the accuracy of the prediction, and the prediction result analysis module is internally provided with an alarm unit, which can send a warning message corresponding to the load to the power system when the predicted data exceeds a preset threshold.
[0015] When the present invention is used, first, the historical load data is acquired through the cooperation of the data acquisition device and the monitoring component. After that, the external environment data of the time corresponding to the historical load data of the power system is detected and acquired through the external environment information acquisition module, wherein the external environment data includes but is not limited to the daily maximum temperature, daily average temperature, daily minimum temperature, daily rainfall and daily relative humidity. Then, the historical load data of the power system collected by the power information acquisition module and the external environment data detected and collected by the external environment information acquisition module are uniformly collected through the data collection module, and after the collection is completed, the data information is transmitted from the data collection module to the data integration storage module by the transmission module; then, the storage unit inside the data integration storage module is used to store and back up the data information transmitted to it, and then, the integration unit inside the data integration storage module is used to filter and integrate the historical load data of the power system and the external environment data, and while filtering out redundant data and supplementing missing data information, the power system is integrated on a daily basis. The historical load data and the corresponding external environment data are processed in segments and integrated to form a plurality of data information packets; finally, the original model is constructed based on the data information packet by the prediction model construction module, with the historical data as the model input and the load data of N consecutive moments in the future as the model output, and then, the model is trained with the actual historical detection data to obtain the power load prediction model. In this process, the image generation unit provided in the prediction model construction module can be used to draw the power load curve graph, and after the drawing is completed, the power load curve graph is displayed through its external display component. After completing the above operations, the power load data predicted by the power load prediction model is analyzed, judged and evaluated by the prediction result analysis module, so as to increase the accuracy of the prediction, and in this process, the alarm unit in the prediction result analysis module can be used to send a warning message corresponding to the load to the power system when the prediction data exceeds the preset threshold; in general, the present invention has the advantages of high prediction accuracy and efficient and convenient use.
[0016] The above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, a person skilled in the art should understand that the specific implementation modes of the present invention can still be modified or replaced by equivalents, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be included in the scope of the claims of the present invention.
Claims
1. A power load forecasting system, comprising a power information acquisition module, an external environment information acquisition module, a data collection module, a transmission module, a data integration and storage module, a forecasting model construction module and a forecasting result analysis module, characterized in that: The power information collection module can be used to collect historical load data of the power system; The external environment information acquisition module can be used to detect and acquire the external environment data at the time corresponding to the historical load data of the power system; The data collection module can be used to uniformly collect the historical load data of the power system collected by the power information collection module and the external environment data detected and collected by the external environment information acquisition module; The transmission module is located between the data collection module and the data integration storage module, and is used for transmitting data information from the data collection module to the data integration storage module; The data integration storage module is composed of an integration unit and a storage unit, wherein the storage unit can store and back up the data information transmitted to it, and the integration unit can filter and integrate the historical load data of the power system and the external environment data, filter out redundant data, and supplement the missing data information. After that, the historical load data of the power system and its corresponding external environment data are segmented and integrated on a daily basis, thereby forming multiple data information packages; The prediction model building module can build an original model based on the data information package, using historical data as model input and load data of N consecutive moments in the future as model output, and then train the model using actual historical detection data to obtain a power load prediction model; The prediction result analysis module can analyze, judge and evaluate the power load data predicted by the power load prediction model, thereby increasing the accuracy of the prediction.
2. A power load forecasting system as claimed in claim 1, characterized in that: The external environment data includes but is not limited to daily maximum temperature, daily average temperature, daily minimum temperature, daily rainfall and daily relative humidity.
3. The power load forecasting system according to claim 1, characterized in that: The prediction model building module is internally provided with an image generation unit, which can be used to draw a power load curve graph, and the image generation unit is externally connected to a display component, through which the power load curve graph can be displayed.
4. The power load forecasting system according to claim 1, characterized in that: The prediction result analysis module is internally provided with an alarm unit, and the alarm unit can be used to send a warning message corresponding to the load to the power system when the prediction data exceeds a preset threshold.
5. The power load forecasting system according to claim 1, characterized in that: The power information acquisition module is composed of a data acquisition device and a monitoring component. The acquisition of historical load data is completed through the cooperation of the data acquisition device and the monitoring component.