Abstract
Energy consumption in buildings especially in offices is alarming and prompts the desire for more energy analysis work to be done in testing models that can estimate the energy situation of commercial buildings, and the key contributing factors are based on human factors, work load, and weather variables like solar radiation and temperature. In the research, the administration block of the University of Energy and Natural Resources, Ghana, was selected and modeled for energy analysis using SketchUp. Daily energy consumption of the building was generated with EnergyPlus indicating the electricity consumption of the block for the year 2018 for which 68.7% was used by equipment in the block, 26.98% on cooling, and the rest on lighting. The Artificial Neural Network model which had weather variable and days as input neurons and cooling, lighting, equipment, and total building electricity consumption as output neurons was modeled in MATLAB. The model after training had R values for training, validation, and testing to be 0.999 and validation performance of 1.7 ∗ 10 − 04 . It was able to predict the energy consumption for lighting, cooling, and equipment very close to the results with minimal. The results from the ANN model prediction were compared with the EnergyPlus simulations. The maximum deviation profile for the following parameters (lighting, cooling, and equipment) is 13%, 8%, and 4%, respectively. The large difference in the lighting and cooling is the difficulty involved in predicting human behaviour and weather conditions. The least value recorded for the equipment is due to its independence on external factors.
Highlights
The residential sector in Ghana accounts for about 47% of total electricity consumption in the country [1], but generally, in the building industry, commercial buildings under construction account for 40% of every nation’s energy consumption [2]
The low solar radiation experienced from October to January of the year usually has an impact on the high power consumed for lighting
The domain selected for the study was well modeled to generate the actual energy consumption of the block
Summary
The residential sector in Ghana accounts for about 47% of total electricity consumption in the country [1], but generally, in the building industry, commercial buildings under construction account for 40% of every nation’s energy consumption [2]. The energy consumption in commercial buildings in Ghana is due to the discomfort people go through as a result of climate factors, building styles, heavy closure, and improper or excessive use of electrical gadgets, among others. The hot climatic conditions allow the use of refrigerators and electrical fans to cool consumables and circulate cold air in buildings, respectively. Design decision making is not sufficiently informed by pertinent expertise pertaining to energy-efficient building design methods” [5]. To this end, heavy closure in buildings prevents daylight from providing enough visibility; people resort to the use of electric lighting during the day
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