Distribution system is very essential to load centre or service mains. This is because it is the final section of electric power system (EPS) to supply the consumers. Once this section is compromised, low voltage consumers will be denied of a reliable supply of electricity. One way to make supply to low voltage consumers reliable is by bringing generation close to them through distributed generators. However, location of distributed generator is very important with respect to the entire EPS security. In this study, power network structural topology (PNST) is proposed to optimally locate distributed generator within distribution system which results in minimal loss as well as maintaining voltage profile within constraint limits. 5bus IEEE test system was used as case study to show the feasibility of the proposed method. Results obtained for both test systems were validated through the results from power world simulation tool.In this section, power network structural topology (PNST) and power world simulation software are considered. The PNST is the proposed approach in this study while power world simulation software is used to validate the result obtained from PNST. Power network structural TopologyPower network structural topology (PNST) is an approach that considers the inherent characteristic of electric power circuitry in order solve power system problems. PNST approach proposed in this study, is based on the two-port network technique which has been reported in previous works [15][16][17].

Wind energy potentials of some selected high altitude and coastal areas in Nigeria are assessed for possible utilization for the generation of electricity. The main aim is to provide pragmatic insight that will enhance the investment in wind energy conversion systems in an optimal manner. The data used in this present study were obtained from the Nigeria Meteorological Agency, which includes average wind speeds per day of four locations across the country, measured at the anemometer height of 10 m over a period of 11 years. With the sites classified based on their wind power densities, the capacity factor estimation value was used to select the most suitable turbine for the selected sites, and the present value cost method was employed to estimate the unit cost of energy of the turbine at various hub-heights. The results obtained from this study reveal that Jos, Kano and Ikeja are economically viable as well as having excellent wind resources integration into the grid, while P/H is viable for a standalone application. The outcome of the study provides useful information that will aid renewable energy policymakers in Nigeria for wind energy development.

Cocoa and kolanut harvest wastes of 681,000 and 90,000 tons respectively, are generated in Nigeria annually. HHVs of the two agro-residues are 15.19 and 13.87 MJ/kg respectively, with their blends having values within this range. The optimal blend composition of the two agro-residues has electric power generation potential estimated at 29,000 MW.

Energy is a key component in the overall growth of every nation. Insufficient energy delivery hinders political growth, restricts social growth, limits economic growth, and negatively affects the standard of living of citizens, both in urban and rural areas. Sufficient energy delivery increases food production, improves the standards of living of citizens, improves healthcare and enhancements in other human services, enhances industrial output, provides effective and efficient transportation not forgetting adequate shelter to the citizens of the nation. Currently, there is a significant level of deficiency in Nigeria's energy sector. This study seeks to address this issue by analysing cost implications of conventional energy source and solar energy source. This study brings to focus the payback period of a solar powered home and the return on investment that might accrue during this time to the residential homeowners. Furthermore, the best cost-effective load sharing option for residential owners considering two energy sources is also obtained.

The process of speech recognition is such that a speech signal from a client or user is received by the system through a microphone, then the system analyses this signal and extracts useful information from the signal which is converted to text. This study focuses on the design and implementation of a speech recognition system integrated with internet of thing (IoT) to control electrical appliances and door with raspberry pi as a core element. To design the speech recognition system, digital signal processing (DSP) technique and hidden Markov model were fully considered for processing, extraction and high predictive accuracy of the system. The Google application programming interface (API) was used as a cloud server to store command and give the system to assess to the internet. With 150 speech samples on the system, a high level of accuracy of over 80% was obtained.