Solar PV rural electrification and energy poverty assessment in Ghana: A principal component analysis

The relationship between solar photovoltaic (PV) rural electrification and energy poverty was assessed using social, economic and environmental indicator-based questionnaires in 96 solar-electrified and 113 non-electrified households in rural Ghana. The purpose was to assess energy-poverty status of households with and without solar PV systems, and to determine the factors that explain energy-poverty in off-grid rural households. Principal component analysis (PCA) was used to construct energy-poverty index scores (EPIS). On the basis of the results of the EPIS, about 80% of the non-electrified households were assessed as relatively energy poor compared with only 10% of the solar-electrified households. Three significant indicators increased linearly with increasing EPIS and therefore explained the variation in EPIS. They are monthly savings on lighting (r2=0.214), number of children who can sit around lighting (r2=0.388) and amount paid to obtain lighting/electricity system (r2=0.261). On the contrary, EPIS decreased linearly with increasing monthly costs of kerosene, candles and dry-cell batteries. This indicates that increasing expenditure on kerosene, candles and dry-cell batteries is likely to affect household savings and investment in quality energy delivery systems that can increase EPIS. To improve EPIS, households should invest a bit more in reliable and quality energy delivery systems, which can help to improve their quality of life. The use of EPIS successfully demonstrated the difference in energy-poverty status between households with and without solar PV. This lays down a basis of understanding the relationship between solar PV rural electrification and energy poverty improvement in off-grid communities

Effects of Thermal Mass, Window Size, and Night-Time Ventilation on Peak Indoor Air Temperature in the Warm-Humid Climate of Ghana

Most office buildings in the warm-humid sub-Saharan countries experience high cooling load because of the predominant use of sandcrete blocks which are of low thermal mass in construction and extensive use of glazing. Relatively, low night-time temperatures are not harnessed in cooling buildings because office openings remain closed after work hours. An optimization was performed through a sensitivity analysis-based simulation, using the Energy Plus (E+) simulation software to assess the effects of thermal mass, window size, and night ventilation on peak indoor air temperature (PIAT). An experimental system was designed based on the features of the most promising simulation model, constructed and monitored, and the experimental data used to validate the simulation model. The results show that an optimization of thermal mass and window size coupled with activation of night-time ventilation provides a synergistic effect to obtain reduced peak indoor air temperature. An expression that predicts, indoor maximum temperature has been derived for models of various thermal masses