Loss-of-load probability calculation using learning vector quantization

This paper proposes a new method employing learning vector quantization (LVQ) and Monte Carlo simulation to calculate the loss-of-load probability (LOLP) of power systems. LVQ is a type of classification method whose goal is to use data samples to position the codebook vector in such a way that the nearest neighbor classification method will result in the maximum classification accuracy. The proposed method greatly reduces the computing burden of the loss-of-load probability calculation compared to Monte Carlo simulation only. A case study of the IEEE RTS system is presented, demonstrating the efficiency of this approach