Research on distribution network spare parts demand forecasting and inventory quota

Due to the professionalism and particularity of the power equipment, a reasonable inventory equipment quota forecasting and purchasing plan can guarantee the electrical power construction and maintenance work smoothly. Furthermore, an accurate quota forecasting can also save a large volume of liquid funds for the power companies. This paper establishes a reasonable spare parts demand forecasting and inventory quota model based on SVM algorithm which takes material historical demand, repair schedule, the failure rate of the equipment and operating environment into full consideration. Moreover, the spare parts of electrical equipment in distribution network are divided into Class A, Class B1 and Class B2 through the activity based classification, through which the inventory quota method based on the different types of inventory management model is established. Finally, the calculation results of actual distribution power network show that the proposed SVM model is of high prediction accuracy, providing a simple and effective solution for inventory equipment management of electricity equipment.