Investigated in this study is harnessing the heat energy absorbed by photovoltaic (PV) solar cells for electricity generation, in order to boost the electric power output of rooftop PV power system, without expending on cooling the energy conversion devices. An experiment was carried out in which a metallic plate was attached to the back of a low rate rooftop PV installation to capture the waste heat of the PV array and evenly distribute the heat to the conversion devices. Four commercial thermoelectric generator (TEG) modules were attached to the plate for the conversion of the heat to electricity. The modules were passively cooled and connected in parallel. Outputs of the PV array and the TEG bundle were obtained on a data logger while the experiment lasted for 11 weeks during a sunny season in Nigeria. Voltage and current up to 2.5 V and 4 A, respectively, were obtained from the harvested heat, while the PV-TEG combination operated at higher efficiency than that of the PV alone. Potential of rooftop PV system in hot climates is thus maximized by the passive cooling. The approach could be improved further using metal plate with higher conductivity.

This paper presents a method for managing congestion constraints in a hydro-thermal optimal power flow solution procedure. The congestion constraint is handled in this paper as an active power generation constraint. To achieve this solution, a power flow tracing technique is used to detect the generators contributing to line congestion to penalize them by reducing their outputs. The congestion is then removed by setting the maximum power of the affected generators to the penalized value. The proposed algorithm is implemented using MATLAB software. Finally, the performance of the proposed algorithm is tested and the results for the 5-bus, 30-bus, and 34-bus Nigerian power networks are presented.

Entrepreneurship is the major solution to the unemployment problem that has resulted to multifaceted socio-economic challenges in the developing worlds.  If engineer becomes entrepreneur, this will not only create jobs but promote technological development and a sustainable national economic growth is guaranteed. The process of entrepreneurship starts from the development of intention to embark on such a venture, hence this study assessed the entrepreneurial intentions of the engineering students in the universities. To accomplish this task, Ajzen theory of planned behaviour is applied. A survey was conductor at the faculty of engineering, Osun State University, Osogbo, Nigeria through a structured questionnaire administered to 470 engineering students in 2021. The data collected was analysed using Statistical Product and Service Solution (SPSS) version 20. The results of the descriptive and regression analyses using the SPSS show that engineering courses are mostly study by the male gender and further revealed that entrepreneurial intentions could be statistically investigated using the Ajzen theory. The results specifically revealed that personal attitude, subjective norms and perceived behavioural control are statistically significant in determining the entrepreneurial intentions of engineering students, while the level of study is insignificant. Based on these results, recommendations for the government, heads of engineering faculty, educators in the fields of engineering and entrepreneurship were provided

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This study aims at providing an experimental sizing procedure for a rooftop PV-based solar power system for an engineering laboratory. This was achieved by monitoring the peak power and energy delivered by an installed 20W solar panel into an 18 Ah battery. Knowledge of the average daily peak power and energy was used to determine the percentage rated capacity available for use and the sun hour. A load consumption comparison was also carried out with and without the connection of a load to inverter. In addition to this, the monitoring of the no-load consumption of the inverter was carried out. This was carried-out to ascertain the contribution of the inverter to the system. With the knowledge of the average daily energy deliverable, sun hour and the no-load power of the inverter, a sample sizing for basic electronic laboratory loads was done. The findings of the study reveals that the average available power is 89.35% of the solar panel rated capacity while the average sun hour is 4.38 h. It has also been shown that an approximate difference of 20 W exists between the power consumption of the load with and without its connection to the inverter. This value (i.e., 20W) has been recorded as the approximate no-load power for the inverter. The sample sizing done has shown that, the solar panel energy requirement of the system with inverter may be considerably higher than that without inverter.