Optimization Of The Number And Location Of Traction Substations Based On Improved Particle Swarm Algorithm

As China gradually enters a new stage of development,the concept of energy-saving,lowcarbon and green development is gradually gaining popularity.The railroad sector has also entered the key stage of "cost saving and consumption reduction" from the past rough development mode.High-speed railroads have obvious advantages over other modes of transportation,but in the process of operation,there are significant problems of wasted capacity of large equipment and increased primary investment costs.The capacity,numbers and locations of traction substations and sub-stations and AT stations in the system are optimized to improve the utilization rate of equipment.Therefore,in this paper,the study of the number and location optimization of large substations along the line is conducted.The details are as follows:(1)Based on the force analysis of the rolling stock,the mechanical equations under different operating conditions and different road conditions are analyzed.On the basis of this analysis,the power relations of the rolling stock are analyzed and the power equations are established.The SIMULINK software platform was used to build the simulation model of the Fu-xing train set and the train groups simulator in accordance with the train operating diagram.Combined with the traction network simulation model in the previous research work,the "joint traction network-train group simulator" was set up to realize the online acquisition of current,voltage,active power,reactive power and other values of the flow of the rolling stock from the line,and after repeated cycles,an interactive system was finally obtained in which all the aforementioned values could be acquired.(2)Based on the establishment of the "traction network-train group" interaction system,the research object is to take each large pavilion along the electrified railroad line.The multiobjective optimization function is established to minimize the capacity along the line and minimize the investment construction and maintenance costs of the large pavilions,and the number and location of the large pavilions along the line are used as the optimization variables,and the electrical conditions to maintain the normal transportation of the electrified railroad are used as the constraints.The results are compared with those of the other two optimization algorithms commonly used by scholars to prove the effectiveness and superiority of the algorithm used in this paper.(3)After proving the feasibility of the used algorithms,the corresponding cases are designed.The existing scheme,is the initial scheme,is chosen as the study route for the domestic Baolan passenger line,and the three algorithms are also used to solve the complete problem separately,and the complete solution results are given in the form of tables and graphs,respectively.The solution results show that the multi-objective particle swarm algorithm with mixed multi-strategy as described in this paper can not only reduce the number of traction stations,AT stations and sub-stations,but also make the distribution of their locations more in line with the geological conditions,and make the construction and subsequent maintenance costs significantly reduced;the optimized results are verified by the hot spot temperature and life loss of the winding of the traction transformer,which are two significant indexes.On the one hand,it verifies the effectiveness of the capacity reduction measures taken by the traction institute to improve the capacity utilization of the traction transformer after adopting the aforementioned optimization method,and on the other hand,it also compares the performance of the three calculation methods commonly used to calculate these two indicators,and gives the corresponding reasons.The advantages and disadvantages of the two billing modes are initially discussed from the capacity and demand perspectives,and how to choose the billing method to save more money is quantified.