Questions by uyost - Page 7
As an engineer for a private contracting company, you are required to test some dry-type transformers to ensure they are functional. The nameplates indicate that all the transformers are 1.2 kVA, 120/480 V single phase dry type. (a) With the aid of a suitable diagram, outline the tests you would conduct to determine the equivalent circuit parameters of the single-phase transformers. (6 marks) (b) The No-Load and Short Circuit tests were conducted on a transformer and the following results were obtained. No Load Test: Input Voltage = 120 V, Input Power = 60 W, Input Current = 0.8 A Short Circuit Test (high voltage side short circuited): Input Voltage = 10 V, Input Power = 30 W, Input Current = 6.0 A Calculate R, X, R and X (6 marks) m eq eq (c) You are expected to predict the transformers' performance under loading conditions for a particular installation. According to the load detail, each transformer will be loaded by 80% of its rated value at 0.8 power factor lag. If the input voltage on the high voltage side is maintained at 480 V, calculate: i) The output voltage on the secondary side (4 marks) ii) The regulation at this load (2 marks) iii) The efficiency at this load
Background: In this programming assignment, you will be responsible for implementing a solver for the system of linear equations Ax = where A is an n x n matrix whose columns are linearly independent XER" .BER" To implement the solver, you must apply the following theorem: THM | QR-Factorization If A e Fmxn matrix with linearly independent columns a, a, ... an. then there exists, 1. an m X n matrix Q whose columns 2, ..., are orthonormal, and 2. an n x n matrix R that is upper triangular and whose entries are defined by, rij = {fwa) for is; 0 for i>j such that A = QR. This referred to as the QR factorization (or decomposition) of matrix A. To find matrices Q and R from the QR Factorization Theorem, we apply Gram-Schimdt process to the columns of A. Then, the columns of Q will be the orthonormal vectors u,u2, ..., un returned by the Gram Schimdt process, and the entries rij of R will be computed using each column u as defined in the theorem. Luckily, you do not need to implement this process. A Python library called numpy contains a module called linalg with a function called or that returns the matrices Q and R in the QR factorization of a matrix A. Try running the following cell to see how it works. Your Task: Assuming A E Rnxn is a Matrix object, and B ER" is a vec object, implement a function solve_gr(a, b) that uses the QR-factorization of A to compute and return the solution to the system Ax = 5.