A moisture ingress model is developed using the FEM software COMSOL. The model uses Fick’s second law of diffusion to model the diffusion of moisture in the module. The model also reflects the temperature dependent nature of parameters affecting moisture ingress by using an Arrhenius equation. The model is validated with experimental and simulated data from literature showing a good agreement. A brief comparison with alternative models such as analytical models and a simplified numerical model is also made. The model allows to simulate the moisture ingress into different PV modules in different conditions. The moisture ingress in 11 different locations with different climatic conditions is simulated. The moisture ingress is also simulated using 4 different encapsulants and 4 different backsheets. Finally, the model is adapted to simulate the moisture ingress into impermeable backsheet modules.\ These results are used to find a relation between ambient conditions and the results delivered by the COMSOL model. A simplified relationship is found that holds for the different climates and encapsulants. It is found that the effective relative humidity in the environment is the key parameter in determining the amount of water that will be in the module once it reaches equilibrium. The time that it takes for a module to reach its moisture equilibrium content is determined by the temperature. The presence of these simplified relations can help in estimating the moisture ingress behaviour of a model without the need of carrying out a full FEM simulation. However, the dynamics of the system when using different backsheets does not follow the same simplified relations.\ The degradation caused by water in the module is also studied. An analytical model is used to predict the degradation observed during damp heat tests. Due to the properties of the analytical model a different approach has to be followed for real life conditions. The degradation model is used to compare the expected degradation under different conditions. This shows that the expected degradation is larger in hot and humid climates while it is minimized in colder climates. The general degradation trend observed for the different climates is: Tropical > Arid > Temperate > Continental > Polar.

This thesis addresses the imperative need for sustainable energy solutions in the residential sector which is a significant contributor to global energy consumption and greenhouse gas emissions. Focusing on modeling and optimizing residential energy systems, the study explores the integration of photovoltaic (PV) panels, heat pumps, and batteries. The purpose is extending the applications of the Photovoltaic Material and Devices (PVMD) toolbox, offering a framework for future research and advancements. The objective is to enhance energy efficiency, reduce carbon footprints, and contribute to energy security by diversifying energy sources. The research encompasses a comprehensive analysis of heat pump models, emphasizing their role in space heating, space cooling, and domestic hot water functions. Two specific models are chosen for Coefficient of Performance (COP) and Energy Efficiency Ratio (EER) calculations. These models, along with the utilization of the nPro tool, lay the foundation for integrating heat pump systems with PV production and battery storage in residential buildings. The study successfully integrates the model of the battery’s performance and the overall grid-connected energy system. Employing a mathematical modeling approach, each component is systematically incorporated into the system, including the previously developed heat pump model. This integration, coupled with the Alternating Current (AC) output of the PVMD toolbox and the battery, establishes the groundwork for subsequent economic and performance analyses of the system. The study systematically selects various locations with different environmental conditions such as Equivalent Sun Hours (ESH) and average ambient temperature to analyze the economic aspect by checking the Net Present Cost (NPC) and performance aspects by checking Self Consumption Ratio (SCR) and Self Sufficiency Ratio (SSR) of the integration model. The findings emphasize the economic viability of heat pump investments in cities with distinct heating and cooling demands. It has been demonstrated that in colder cities where heating demand is predominant, heat pumps are economically attractive, resulting having heat pumps in optimal scenarios that give the minimum NPC in Amsterdam and Lisbon. Additionally, although the individual components of the system may seem cost-ineffective, their value is derived more from integration in milder cities where heating demand is dominant, resulting having heat pump and PV integrated for the optimal scenario for Lisbon. However, cities dominated by cooling demand face challenges in achieving financially optimal designs because the operational savings for cooling cannot be accurately included such as Cairo and Dakar. The research underscores the importance of considering various system factors, including initial investment costs and electricity tariffs, to achieve financially optimal sizing. As the initial cost of the battery decreases, battery technology becomes economically appealing for Lisbon and Dakar. Moreover, changes in the tariff prove economically favorable for integrating the battery system in Lisbon, Cairo, and Dakar. This work contributes valuable insights to the field of renewable energy, providing practical solutions for the transition towards cleaner and more efficient residential energy systems.

Degradation of PV modules reduces their operational lifetime, resulting in an increased levelised cost of electricity (LCOE) and shortening the useful lifetime of valuable materials. One of the leading cause of degradation is moisture. Understanding how this moisture diffuses through PV materials and in different conditions can help prolong modules’ lifetime. This thesis investigates moisture ingress in PV modules, specifically looking at non-Fickian diffusion and material degradation as alternative, and potentially more accurate, ways of modelling it. To simulate non-Fickian diffusion, a dual-transport method is used; the study finds the approach to deliver more accurate results for EVA, but not for PET. To simulate material degradation, an adapted version of the diffusion coefficient equation is proposed, incorporating a degradation constant based on the materials’ properties. The findings are then used to analyse the behaviour of other PV materials and behaviour in different climates. The simulations find very slow moisture ingress for ionomer under non-Fickian diffusion and a strong deviation from Fickian diffusion. In EVA/PET simulations, non-Fickian behaviour is found to deviate more from Fickian behaviour in warmer climates. Degradation constants are found for the other PV materials. The approach shows promising results for the TPO/PET and ionomer/PET simulations, showing degradation in proportion with their material properties. However, simulations that include EVA appear to strongly limit moisture diffusion, indicating a revision of the EVA degradation constant should be made. TPO/PET degradation simulations in show minimal degradation over 20 years in different climates, but more material degradation in colder climates is found.

Degradation of PV modules reduces their operational lifetime, resulting in an increased levelised cost of electricity (LCOE) and shortening the useful lifetime of valuable materials. One of the leading cause of degradation is moisture. Understanding how this moisture diffuses through PV materials and in different conditions can help prolong modules’ lifetime. This thesis investigates moisture ingress in PV modules, specifically looking at non-Fickian diffusion and material degradation as alternative, and potentially more accurate, ways of modelling it. To simulate non-Fickian diffusion, a dual-transport method is used; the study finds the approach to deliver more accurate results for EVA, but not for PET. To simulate material degradation, an adapted version of the diffusion coefficient equation is proposed, incorporating a degradation constant based on the materials’ properties. The findings are then used to analyse the behaviour of other PV materials and behaviour in different climates. The simulations find very slow moisture ingress for ionomer under non-Fickian diffusion and a strong deviation from Fickian diffusion. In EVA/PET simulations, non-Fickian behaviour is found to deviate more from Fickian behaviour in warmer climates. Degradation constants are found for the other PV materials. The approach shows promising results for the TPO/PET and ionomer/PET simulations, showing degradation in proportion with their material properties. However, simulations that include EVA appear to strongly limit moisture diffusion, indicating a revision of the EVA degradation constant should be made. TPO/PET degradation simulations in show minimal degradation over 20 years in different climates, but more material degradation in colder climates is found.

Increasing the energy yield per unit area of Photovoltaic (PV) modules is one of the main challenges the PV technology is currently facing. In search of ways to address this issue, solar tracking systems are a favorable solution, which according to literature can enhance the energy yield by up to 45%. Another way is to opt for high-efficiency solar cells. Tandem cells have emerged as a promising technology, achieving efficiencies of over 30%. The integration of these tandem cells with sun-tracking techniques suggests high-performing solar modules. The present work develops a solar tracking model to simulate the performance of tracking PV systems equipped with tandem modules. The model will be incorporated into the PVMD toolbox, a PV modeling software developed within the PVMD group. This software can predict the energy yield of PV systems using self-consistent models for each aspect of the energy conversion. The current version of the toolbox makes it impractical to include solar tracking due to the time-consuming nature of ray tracing used to compute the irradiance. Ray tracing generates sensitivity values that illustrate how sensitive is the module to incoming irradiance from any direction in the skydome. Initially, this work focuses on substituting ray tracing with an alternative faster approach to express sensitivity based on view factors. The view factor and ray tracing method are compared with respect to computational time and extent of agreement. It was found that the view factor can significantly reduce the computational time from over 12 minutes, as required in ray tracing, to a few milliseconds for a single module orientation. Additionally, the view factor method generates sensitivity values closely matching those from ray tracing. For instance, a mean RMSE of 1.2% between the two methods is achieved, for an albedo of 0.2 and module tilt of 30 degrees. Sun tracking aims to locate the module orientation that maximizes the in-plane irradiance. Directly calculating the irradiance for every orientation to identify the optimal, is not a viable option, as it requires substantial time. Thus, sun tracking was expressed as an optimization problem and algorithms were employed to address it. Based on the prevailing sky conditions three optimization case studies were defined on an hourly basis: sunny, cloudy, and intermediate hours. Multiple algorithms were compared across the three cases with selected criteria the convergence to the optimum and runtime. Matlab’s surrogate solver and an author-developed algorithm were selected, as a satisfying solution, compromising those two criteria. Finally, energy yield simulations were performed on perovskite-silicon tandem modules mounted on a dual-axis tracking system. Four locations were selected, representing different real-world conditions: Stockholm, Athens, Bombay and Bogota. Results show the module’s tilt dynamic adaptability to sky conditions: increas- ing nearly to the sun’s zenith when direct light dominates, and lowering when diffuse light is prevalent. Furthermore, the seasonal fluctuations of the energy gain of tracking systems are explored, with locations further from the equator such as Stockholm exhibiting the highest variability of 19% in winter to 36.9% in summer. In addition, the annual energy gained among the locations was found to span between 24.8% (Bogota) and 34.1% (Bombay). An important finding is the direct proportionality in gains from absorbed irradiance to DC and AC yields, illustrating a 1:1:1 ratio. Then, the effect of tracking technology on mismatch losses of tandem modules was examined. Results indicated that tracking has little impact on both the current and power mismatch. For example, the power mismatch losses slightly increased from 1.10-1.46% in static PV systems to 1.29-1.77% for tracking topologies in the locations examined. Moreover, the tandem’s annual energy gain is compared to silicon heterojunction modules. The analysis showed similar gains across locations for both cell technologies.