An Impact of Artificial Intelligence Control on Photovoltaic/Thermal (PVT) - Ground Source Heat Pump (GSHP) Hybrid System

Hybrid renewable energy utilization in residential and commercial building become an important issue in the world. IEA policy on renewable heat says that expanding the use of modem biomass, geothermal energy, solar energy and ambient energy to produce heat and power could contribute substantially to meet energy security objectives and mitigate climate change. Based on that background, in this study, two different renewable energy systems, which are photovoltaic/ thermal (PVT) and ground source heat pump (GSHP) were combined together to produce heating, cooling and electricity simultaneously so-called tri-generation. This hybrid technology has been introduced and analyzed in terms of energy savings compared to the conventional system which uses a boiler and chiller to produce heating, cooling and electricity from the grid. For one house and one office, conventional system consumed 276.7kWh/ m2-yr of energy and the combination of three renewable energy systems save the primary energy up to 97.9kWh/ m2-yr or 35.4% energy reduction. An impact of Advance control system by using artificial neural network and fuzzy logic control system will be explained and analyze in order to achieve better energy savings. By these two techniques, it showed that for one single residential house, 11%-3 6% primary energy reduction by using ANN and 11%-230% primary energy reduction by using Fuzzy Logic control could be achieved.