Adoption of energy efficiency and conservation techniques in public buildings in Nigeria is significantly low due to the ignorance of its potential benefits. Consequently, this study presents the prospects of energy saving using different methods in a public building at a Nigerian University. A proposed remodelled students' residential hostel at the University of Lagos, Nigeria was chosen as a pilot study. This research utilized three energy efficient lighting technology alternatives namely; intelligent controlled Incandescent lamp (ICIL), compact fluorescent lamp (CFL), and intelligent controlled CFL (ICCFL) and compared with a base case of conventional incandescent lighting configuration. Energy consumption, at the proposed hostel is analysed and modelled. The effectiveness of each lighting technology alternative and base case in terms of cost is estimated using economic indices such as the net present value (NPV), savings to investment ratio (SIR) and the discounted payback period (DPP). Results show that the CFL lighting technology give 39% cost benefit as compared to ICCFL which gives 11% overall cost benefit. From the study, it is established that adoption of energy efficient lighting techniques save a significant amount of energy, operational cost, electricity bills and consequently reduce emission.

Unalleviated voltage instability frequently results in voltage collapse; which is a cause of concern in power system networks across the globe but particularly in developing countries. This study proposed an online voltage collapse prediction model through the application of a machine learning technique and a voltage stability index called the new line stability index (NLSI_1). The approach proposed is based on a multilayer feed-forward neural network whose inputs are the variables of the NLSI_1. The efficacy of the method was validated using the testing on the IEEE 14-bus system and the Nigeria 330-kV, 28-bus National Grid (NNG). The results of the simulations indicate that the proposed approach accurately predicted the voltage stability index with an R-value of 0.9975 with a mean square error (MSE) of 2.182415x10⁻⁵ for the IEEE 14-bus system and an R-value of 0.9989 with an MSE of 1.2527x10⁻⁷ for the NNG 28 bus system. The results presented in this paper agree with those found in the literature.

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