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

Abstract

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. Keywords: Markov Chain, Transition probability, Non-stationary, Power Distribution Electric power distribution is the final stage in the delivery of electric power, it carries electricity from the transmission system to individual consumers. Onochie, et al (2015) said that adequate power supply is the hallmark of a developed economy. Any nation whose energy need is epileptic in supply, prolongs her development and risks losing potential investors. Again, it is an unavoidable prerequisite to any nation's development. Electricity generation, transmission and distribution are the three stages of delivering electricity to consumers. The delivery of electricity to consumers in Nigeria has multidimensional problems (Sule, 2010) focused on capacity of electricity generation in Nigeria and the major factors affecting electricity generation, transmission and distribution in the country. The factors are none diversification of sources of energy used in electricity generation, poor maintenance culture, electrical power transmission line losses due to long distance between generating stations and load centers. Studies have been carried out on electricity consumption around the globe. Ubani, (2009) determined the electricity consumption pattern in south-south geopolitical region of Nigeria. The results showed that there were significant differences in electricity consumption pattern amongst the five states that constitute the south-south geopolitical region. River state had the highest mean of consumption rate, followed in descending order by Delta, Edo, Akwa Ibon and Bayelsa states. He recommended for strategic and systematic distribution of electricity to ensure adequate supply in south-south geopolitical region. Abubakar, (2005) studied Markov chain model with stationary and non-stationary transition probabilities for asthmas disease. The effect of treatment on the disease is also considered. The model could be used to study the condition of asthma patient in the Nigeria environment when the relevant data could be obtained. Mohammed, (2013) modeled the three state Markov model considered for both discrete and continuous time for the reservoir elevation. The effect of the varying season condition was also studied in the model. The model was used to analyse the data obtained from the dam. The res...