Multi-Level Material Storage Allocation Control of Smart Power Plant Based on Hesitant Fuzzy Method

In order to improve the ability of multi-level material storage and allocation and dynamic control of smart power plants, a multi-level material storage and allocation control method of smart power plants is proposed based on hesitant fuzzy method, and a material demand parameter analysis model of multi-level material storage and allocation of smart power plants is constructed by using feature selection and multi-model fusion method, and the combined control learning of material storage and allocation control of power grids is realized by using energy efficiency evaluation method. The overall energy efficiency of power plant quality control management system is dynamically evaluated by combination weighting method, the three-level dynamic storage model of power plant is constructed by hesitant fuzzy learning method, the management and fuzzy function are established with the goal of minimizing the cost, the optimal solution of the allocation function is realized by reinforcement learning method, and the trend analysis of its time series can provide research ideas for material demand. In the experimental test, the balance is realized through subjective experience and objective data. The simulation test shows that this method can reduce the cost of material storage in storage, storage and delivery, and obtain the optimal control strategy.