Optimal inventory strategy of electricity meters based on the combination of Holt-Winters and XGBoost

Accurate forecast of electricity meter inventory demand and reasonable formulation of inventory mode are of great significance to reasonably arrange the arrival, verification and distribution of electricity meters and reduce the operation and maintenance cost of the electricity meter storehouse. Under this background, an optimization of energy meter inventory strategy based on the combination of Holt-Winters and XGBoost is proposed. Based on the Holt-Winters and XGBoost algorithm, a linear regression combined forecast model of inventory demand is proposed to predict the inventory demand of electricity meters. Then, an optimization model of electricity meter inventory strategy is proposed to minimize the total cost of operation and maintenance of the meter storehouse, so as to obtain the optimal storage and use strategy of each batch of electricity meters in the meter storehouse. Finally, the proposed model is analyzed and verified by taking the 5-year inventory demand data of a meter storehouse as an example. The results show that the proposed strategy can accurately predict the electricity meter demand and develop a reasonable electricity meter inventory strategy.