Research On Storage Network Layout Optimization Of Power Grid Enterprise

In recent years, with the rapid development of power grid construction and the deepening reformation of electric power system, the present situation of the high cost of logistics and its inefficiencies has seriously restricted the further development of power grid enterprises. Storage network layout planning is the foundation and the core of the enterprise logistics system planning. The article researches on the storage network layout planning of power grid enterprises from this point of view. Its aim is to reduce the cost of logistic operation and construction investment of power grid enterprises, to improve supplying reliability of electric power materials and to shorten response time of material demand. It has important significance to the power grid enterprise logistic development.This paper mainly researches on the power grid enterprise storage network layout optimization problem. Based on extensive surveys on storage network planning methods and experience of constructing storage network of grid enterprises abroad, the article analyzes the problems existed in power grid enterprise’s storage network in China. According to the characteristics of the storage network planning for power grid enterprise, this paper builds a mathematical model minimizing total logistics cost for its objective function, from four aspects like transportation cost, warehouse construction costs, storage costs and penalty cost. The original Fruit Fly Optimization Algorithm (FOA) has the disadvantages of being strict for parameter accuracy and easy to fall into the local optimum, so this paper puts forward multiple populations FOA. The improved FOA decomposes the initial flies population into multiple sub population. It can avoid the algorithm to fall into the local optimum by learning the local optimal individual of sub populations and optimal individual of the whole population. Through empirical analysis of a regional power grid enterprise storage network layout optimization, we can see that the improve FOA is superior to the original one in the aspect of computational accuracy and convergence efficiency. Practice proves that this method can be scientific, reasonable and effective to optimize the power grid enterprise storage network layout. It provides a new approach for the future power grid enterprise storage network layout optimization.