Building energy efficiency improvements and solar PV systems integration

Abstract

Energy efficiency can be applied at all levels, from energy generation to energy end-use, to achieve technical-, economic- and environmental benefits. The solar photovoltaic component size in a five-bedroom duplex residential building in Lagos State, Nigeria, was investigated. The adopted energy management strategy compared two cases - a present (base) case involving inefficient or low energy-efficient appliances, and a proposed efficient case involving more energy-efficient appliances. The energy supply infrastructure (solar PV modules, batteries, and inverters) size had to meet the energy needs of the appliances in the two cases. The appliances fall into three categories, namely lighting, air conditioners, and other appliances. An electronic energy audit and solar sizing (e-EASZ) tool was used for the energy audit, data analysis, and photovoltaic system infrastructure sizing. The study validated the results with the literature. The energy efficiency opportunities identified for retro-commissioning include installing more energy-efficient lighting, replacing existing inefficient air conditioning units with units conforming to the Minimum Energy Performance Standard (MEPS) for electrical appliances, and ensuring that appliances not in use are switched off. The retro-commissioning resulted in a significant reduction in energy demand, energy costs, and solar PV system infrastructure components, for different load scenarios. Energy efficiency measures led to a 42%, 26%, and 20% reduction in the energy demand and cost of lighting, air conditioning, and other appliances, respectively, while the solar PV peak power, battery bank and inverter capacity were reduced by 19%-42%. Correlations were also developed to predict the number of solar PV system components given the energy demand. The predicted results from the correlations excellently agreed with the results of the study. The correlations were determined using the coefficient of variation root mean square error, which ranged from 0.3% to 0.85% at a 95% confidence level. It is anticipated that this e-EASZ tool could also aid in sizing PV system components for larger energy efficiency and microgrid projects.