Seasonal Variation of Power Distribution in Niger State of Nigeria using Markov Model with Non-Stationary Transition Probabilities

This paper presents the application of markov chain model with non-stationary transition probabilities to study the monthly data of the power distribution in niger state in the wet, dry-hot and hamatten/dryhot seasons. the result indicates an optimal power distribution of over 150,000mwwith probability 0.49 during the wet season, 0.25 during the hot-dry season and 0.19 in the hot-cold season respectively. the variation of power distribution directly affects the electricity consumers. markov chain model could be used as a predictive tool for determining the power distribution pattern at different seasons in the study area. these predictions might be used for the management of (ncc) for effective distribution of megawatts.