Generation system reliability evaluation based on convolution algorithm and data modeling

The reliability of an electric supply system has been defined as the probability of providing the users with continuous service of satisfactory quality. Generation system reliability indices have been used as a standard for measuring system reliability. Therefore, it becomes essential to predict how these indices vary as system annual peak increases. In this paper, a convolution algorithm has been used to build a risk model by convoluting the load model and the capacity model. The constructed model has been used to calculate the reliability indices of Benghazi North Power Plant (BNPP) using data of one year period (stage I). The same model has been used to determine these indices values after some capacity has been installed (stage II). Testing this model using data from two year period show that the suggested method is effective in calculating the reliability indices and predicting the required installed capacity.