潮流不同排序方案的比较毕业论文文献翻译中英文对照
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1、外文翻译(原 文) 1 中文 4900 字 A Comparison of Power Flow by Different Ordering Schemes AbstractNode ordering algorithms, aiming at keeping sparsity as far as possible, are widely used today. In such algorithms, their influence on the accuracy of the solution is neglected because it wont make significant dif
2、ference in normal systems. While, along with the development of modern power systems, the problem will become more ill-conditioned and it is necessary to take the accuracy into count during node ordering. In this paper we intend to lay groundwork for the more rationality ordering algorithm which cou
3、ld make reasonable compromising between memory and accuracy. Three schemes of node ordering for different purpose are proposed to compare the performance of the power flow calculation and an example of simple six-node network is discussed detailed. Keywordspower flow calculation; node ordering; spar
4、sity; accuracy; Newton-Raphson method ; linear equations I. INTRODUCTION Power flow is the most basic and important concept in power system analysis and power flow calculation is the basis of power system planning, operation, scheduling and control 1.Mathematically speaking, power flow problem is to
5、 find a numerical solution of nonlinear equations. Newton method is the most commonly used to solve the problem and it involves repeated direct solutions of a system of linear equations. The solving efficiency and precision of the linear equations directly influences the performance of Newton-Raphso
6、n power flow algorithm. Based on numerical mathematics and physical characteristics of power system in power flow calculation, scholars dedicated to the research to improve the computational efficiency of linear equations by reordering nodes number and received a lot of success which laid a 外文翻译(原 文
7、) 2 solid foundation for power system analysis. Jacobian matrix in power flow calculation, similar with the admittance matrix, has symmetrical structure and a high degree of sparsity. During the factorization procedure, nonzero entries can be generated in memory positions that correspond to zero ent
8、ries in the starting Jacobian matrix. This action is referred to as fill-in. If the programming terms is used which processed and stores only nonzero terms, the reduction of fill-in reflects a great reduction of memory requirement and the number of operations needed to perform the factorization. So
9、many extensive studies have been concerned with the minimization of the fill-ins. While it is hard to find efficient algorithm for determining the absolute optimal order, several effective strategies for determining near-optimal orders have been devised for actual applications 2, 3. Each of the stra
10、tegies is a trade-off between results and speed of execution and they have been adopted by much of industry. The sparsity-programmed ordered elimination mentioned above, which is a breakthrough in power system network computation, dramatically improving the computing speed and storage requirements o
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