| While China’s rural power grid is continuously developing,the contradiction between power supply and demand is gradually deepening with time.The analysis of rural short-term power load forecast and rural users’ electricity usage behavior is still of great significance to rural power grid enterprises.The paper mainly considers the short-term forecast of rural load and the analysis of rural electricity use behavior,considers the key factors affecting rural shortterm power load,finds the development relationship of rural power load with time,and analyzes the electricity use behavior of rural users.The means of informationization analyzes rural power load data and visualizes the data.Effective short-term load forecasting for household users’ electricity consumption is convenient for accurately predicting the production,transmission and distribution of electric energy.It is beneficial for the power grid department to develop an economical and reasonable power generation plan for rural users based on actual conditions.Dispatching rural power generation capacity.Based on KNN,K-Means algorithm and lazy multi-label theory,the paper divides the corresponding weights for each cluster of dataset,and proposes a rural short-term load forecasting method based on support vector regression algorithm.It is proved by experiments that the prediction method of this multi-label theory is smaller than the traditional algorithm before the undivided weight in the average absolute error and the root mean square error.The user’s electricity behavior analysis has important significance in power data analysis.The paper uses K-means and fuzzy C-means clustering two clustering algorithms for rural residents through the characteristics of electricity usage and characteristics of rural users.The electric behavior data is classified and compared,which provides data support or reference basis for the grid enterprises to provide differentiated power supply services for rural residents.The improvement of the reliability of rural power grid data is also one of the urgent problems that the county-level power grid department needs to solve.The paper analyzes the real grid data of several power supply stations in a rural area of Changsha,and develops a set of automatic comparison process for power outage information.Together with the power load forecasting and user electricity behavior analysis studied in this paper,it is applied to the rural power data analysis platform.Analyze the real power outage events in each station area and improve the reliability of power outage data from the perspective of technology and information management.At the same time,according to the characteristics of the power load data,appropriate visual analysis methods are used to help users better analyze and understand the data. |
