Research On Rural Distribution Network Planning Based On Electricity Load Security

At present,most of China’s rural areas are facing a series of difficulties and safety hazards in the construction and operation of the distribution network,and there are big changes in the demand for electricity in rural areas.With the national energy strategy adjustment and "coal to electricity" policy,in order to meet the requirements of safe,efficient and environmental protection power supply,we must update and upgrade the power supply facilities of rural distribution network,and the whole process of scientific planning of rural distribution network is the primary premise and important link.The study of the characteristics and laws of rural power demand,the corresponding power demand supply strategy,and the formulation of a series of scientific distribution network planning programs,so as to improve the rural distribution network operating environment,improve the reliability and safety of rural power supply,in order to bring greater benefits to rural economic development and people’s lives.Taking Qu Xinzhuang Village,an administrative village in Renze District,Xingtai City,Hebei Province,as an example,this paper conducts a rural distribution network planning study from the perspective of electricity load security,using UAV image acquisition technology and mathematical prediction model,combined with U-Net network model,K-means algorithm and optimized ant colony algorithm,from image acquisition.The research is carried out in depth from several aspects such as image acquisition,power load prediction,transformer siting and line planning.The main research contents and results are as follows.(1)UAV aerial photography is used to obtain image map data in rural areas,and high-precision orthophoto images are generated through image pre-processing,and semantic segmentation is used to identify features.The overall accuracy of the model reached 0.904 and the average cross-merge ratio reached 0.832,indicating that the constructed semantic segmentation model can effectively segment the UAV orthophoto image and accurately identify the rural distribution network planning constraints.(2)The analysis of transformer load in the village reveals that there are 7transformers overloaded in the village,and the highest load ratio reaches 110.6%.The Kmeans clustering algorithm is used to partition the power supply users and divide the range of existing transformers radiating users for this current situation.Then,two single models,gray GM(1,1)and quadratic moving average method,were used to forecast the power supply in the village,and the weights of the two models were determined to be0.59 and 0.41 respectively by error test and weighted average,and the forecast results were revised according to the trend of electricity consumption growth in the past years and subjective policy influence to obtain the load growth rate of the village from 2021 to2030.Based on the load forecast results,the power supply and demand situation is calculated,and the area with imbalance between supply and demand is re-planned to determine the capacity and number of new transformers,and the K-means algorithm is used to determine the final location of transformers.(3)The traditional ant colony algorithm is optimized,and the guided and ascending mechanisms are proposed to make the artificial ants search towards the end point in a directional manner by controlling the pheromone concentration,while reducing the transmission line map raster dimension to avoid problems such as circuitous line situation and long search time.Meanwhile,based on the constraint layer,the line planning of the new transformer in the village to access the main distribution network is completed by using the optimized ant colony algorithm with the new transformer as the starting point and the current grid as the access point as the end point.The research results show that the planning results of the new transformers as well as the access lines can effectively alleviate the local power load,improve the planning efficiency and operational safety of the rural distribution network,and provide a certain reference for intelligent,efficient and safe planning and construction in the process of upgrading the rural power grid.