European policy makers have established a set of 20-20-20 targets for the year 2020 in the energy sector, goals based on security of supply, competitive markets and sustainability. The 3 key objectives include a 20% reduction of greenhouse gases (GHG) and CO2 compared to 1990 levels (and up to 80% by 2050), a 20% improvement in energy efficiency and a 20% share of basis energy consumption from renewable sources. On its own, the building sector is responsible for 1/3 of the world’s energy consumption, of which 60% is due to heating and cooling. In the European Union, this proportion achieves 40% of the total energy consumption, of which heating, cooling and domestic hot water account for around 70%. Fossil fuels represent 75% of the primary energy supply for heating and cooling needs whereas renewable energies account for only 18% followed by nuclear energy with 7%. A brief energy context being stated, this work focused on the assessment and the optimization of a heating, ventilation and air conditioning (HVAC) system, coupled with a building integrated photovoltaic and thermal (BIPV/T) system and a simple BIPV system. The objective was to reduce the overall energy consumption of a very well insulated dwelling aiming to make it a net zero energy building (NZEB). This HVAC system incorporated a dual-tank water-to-water heat pump (WWHP), used for space heating and cooling, using the BIPV/T system as a heat source thanks to preheated air. The dwelling is a so-called Deep Performance Dwelling (DPD) developed by the Solar Decathlon team from Canada: TeamMTL. This DPD was used as case study all along this Master thesis. On the one hand, this study aimed at the modelling of both integrated PV systems which were developed firstly with the MATLAB software and then with the TRNSYS software. One of the objectives was to highlight the impact of the thermal recovery from the BIPV/T system on its PV modules efficiency compared to the BIPV system. Furthermore, the same initial and boundary conditions were used to ensure a truthfulness on-site energy production from both BIPV/T and BIPV systems as well as for the validation of these systems, later integrated to the complete DPD modelling. On the other hand, sensitivity analyses were conducted to investigate the effects of various parameters on the NZEB objective and the on-site energy fraction (OEF) covered by the energy produced by the DPD. These parameters included the efficiency of the PV modules, their tilt angle, the materials used for both floors and walls as well as the size and the control strategy used of both electrical and thermal storage. First, even if the comparison of both MATLAB and TRNSYS modellings led to a similar net increase in the BIPV/T average electrical efficiency of + 0.0014 [-] compare to the BIPV one, the TRNSYS one achieved an 11.0% lower yearly electrical generation due to an intrinsic factor used in TRNSYS called Incidence Angle Modifier (IAM). The impact of this factor affected all the more the thermal yield, namely a reduction by 28.6% for the annual thermal production along with a 32.0% lower thermal efficiency of the BIPV/T system compared to the one modelled in MATLAB. However, given that TRNSYS was required to model the transient behaviours of the DPD, not conceivable with MATLAB due to the time constraint of this Master thesis, it was logically concluded to use the TRNSYS modelling of the integrated PV systems. Then, to have a good representativeness of the performances of the DPD, 4 cities with very different climates were chosen. For each location, the DPD was categorized as a nearly zero energy building (nZEB). Then, the simulation results emphasized that an optimal tilt angle adapted to every location, concrete-based floors as well as high efficiency PV modules allowed for reaching the NZEB objective in 3 cities, the 4th one facing low annual irradiation. Moreover, sensitivity analyses were carried out in order to improve the energy performance of the DPD. Based on the interpretation of the results concerning both on-site energy indices and energy outputs, a better configuration than the one of the as-built DPD was suggested for each city. Indeed, the sensitivity analyses indicated that the bigger the electrical storage, the better the electrical OEF index. Then, a 300-litre hot water tank as well as a 150-litre cold water tank led to a better overall OEF index and a lower energy consumption compared to the initial configuration. These results were obtained by applying the initial control strategy relying on price benefits of the grid based on bidirectional power flows between the batteries and the grid. However, a grid-tied configuration with no more batteries-grid connection and not taking anymore advantage of incentive prices of the grid stood out an even better overall electrical OEF index, making a higher use of the on-site power generation. Finally, the proportion between the on-site PV production and the amount of energy supplied by the grid to meet the demand of the DPD were calculated. Besides, the impact of the solar house in terms of CO2 emissions as well as its advantages for the grid were alluded.