Probabilistic long term load forecast for Nigerian bulk power transmission system expansion planning

Abstract

The paper proposes probabilistic long-term load forecast and algorithm for application on Nigerian transmission system. The paper applied a developed system specific algorithm comprising Monte Carlo, and artificial neural network techniques that considers location's predominant driving factors as population and GDP growth of the Nigerian system. An initial analysis on obtainable historic data for these factors and load is carried out to obtain possible variability characteristics. The algorithm is implemented in MATLAB-Excel workspaces. Normal mode impact of obtained regional forecasts on test system was obtained by long term power flow computation with NEPLAN software. The system time-step responses suggested reinforcement requirements and guide for the existing Nigerian grid and its long term development.