Research On Optimization Of Multiple Types Coal Stacking And Taking In CoalYard Of A Coal-Fired Power Generation Enterprise

As one of the largest electricity production methods in China’s energy structure,coalfired power generation bears an important responsibility for ensuringthe country’s industrial and urban development.the average fuel cost of thermal power plants in China was 0.25 yuan/kWh,accounting for more than 50%of the total cost of thermal power plants.The level of fuel cost directly affects the production and operation efficiency of thermal power enterprises.In this context,it has become a hot topic for coal-fired power generation enterprises and academia to explore the optimization of coal yard storage and thus improve the waste of resources caused by extensive management of coal storage.Due to the responsibility of guaranteeing supply for coal-fired power generation enterprises,coal yard management has the characteristics of the quantity of coal stored and stored relative to various kinds of coal,overlapping stacking of many kinds of coal,etc.Simply relying on enterprise managers to make decisions based on manual experience will lead to the chaos of coal stacking,unreasonable regional division,difficult precision of coal extraction and other phenomena.If we can reclassify coal yard area scientifically and establish a formal coal yard drawing description model based on the historical data of coal coming and taking,it will effectively improve the management efficiency and economic benefits of coal yard.Therefore,based on k-means clustering,this paper proposes a scientific regional division method of multi-coal coal yards and 3D grid storage optimization of storage yards,and mainly carries out the following research work:Firstly,the paper defines the problem of multiple types of coal in coal yard and summarizes the achievements and shortcomings of existing research.Based on the analysis of the process and equipment involved in coal yard storage in coal-fired power generation enterprises,the existing problems of coal yard regional division and coal storage in coalfired power generation enterprises are summarized,and the impro vement ideas of coal yard regional division and multi-coal storage optimization are put forward.Secondly,in view of the problems ofcomplex coal types and chaotic coal stacking in coal yard of coal-fired power generation enterprises,important indicators of coal quality information of historical coal are selected,and k-means clustering algorithm is used for cluster analysis of imported coal to classify multiple types of imported coal into categories.Based on the frequency and quantity of imported coal,the coal yard area is reclassified and verified.an optimization model of coal stacking,access location scheme and actual state of coal yard was constructed with the goal of minimizing the total coal storage days in the coal yard within the cycle,considering operation restrictions such as stacking height and slope.Finally,according to the real data of coal and coal extraction of A coal-fired power generation enterprise and grid conversion,the calculation and visualization of the stacking scheme of different coal piles for six consecutive days were designed,and the simulated annealing algorithm was compared to verify the accuracy and solvingspeed of the algorithm.The model and the algorithm are solved in the example of randomly generating the initial state of coal yard accordingto the rules of coal yard stacking,and compared with the manual empirical method stacking scheme,to verify the practicability and effectiveness of the model and algorithm.The research work in this paper can provide decision basis and means for managers,and generate visual simulation of coal yard,providing effective decision support for accurate coal taking,coal blending and firing in coal yard.