E3S Web Conf.
Volume 64, 20182018 3rd International Conference on Power and Renewable Energy
|Number of page(s)||5|
|Section||Electrical Theory and New Technology|
|Published online||27 November 2018|
Study on Reliability Evaluation Method Based on Improved Monte Carlo Method
1 State Grid Shanghai Electric Power Research Institute, Shanghai, China
2 Shanghai University of Engineering Science, Shanghai, China
The advancement in science and technology comes with continuously expanding power system scale, increasingly complex system operation condition and higher requirements for accuracy and speed of power system reliability evaluation, but actual calculation methods cannot meet the needs. Therefore, there is need to improve the reliability of conventional power distribution network so that requirements of calculation speed and calculation accuracy can be met. In this paper, reliability of the power distribution network will be evaluated using improved Monte Carlo method with uniform sampling. The average value is obtained through calculation of state of multiple sub-intervals and test functions, which effectively improves calculation accuracy, and further increases the utilization of random numbers. By improving the uniform sampling method, the Monte Carlo simulation variance is reduced, and evaluation and calculation efficiency is improved. At the same time, unqualified power grid is selected for analysis. Based on the simulation results, qualified power distribution networks are compared to point out where the requirements are not met. Also, comparative analysis is made on the effect of power distribution network grid structure etc. on the user’s power supply. Finally, suggestions for improving power distribution network reliability are given from equipment reliability, grid structure.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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