Design and implementation of test paper auto-generation strategy for electric energy measurement

With the establishment of the standard for “strong and smart electric grid”, various kinds of intelligent metering equipments are gradually produced and adopted in practice. A set of training and examination systems is thus urgently needed in the electric power industry for the staffs to measure their level of measuring electric energy. In this paper, based on the practical requirement of a training system for the electric energy measurement in some electric company, combining the thoughts of both the random selection method and the backtracking search method, a test paper auto-generation strategy is designed. The presented strategy has two main advantages. One is that this strategy can automatically calculate the difficulty proportion for the test papers by utilizing the normal distribution function according to the expectation distribution of the test scores. In this way, the efficiency of generating paper can be greatly improved. The other is that the importance of different knowledge in electric energy measurement is different. Therefore, the knowledge required in the test papers is classified into different importance level to meet the requirement of the electric energy measurement test.