Integrating photovoltaic (PV) systems in urban areas enhances local renewable electricity production but also reduces surface albedo due to the lower reflectivity of PV panels. This albedo reduction increases Earth's energy absorption, resulting in positive radiative forcing (RF), while the displacement of fossil fuels by PV electricity leads to negative RF through avoided CO₂ emissions. This study quantifies the net RF impact of urban rooftop PV deployment using a novel workflow. This proposed workflow combines: (1) a geometric spectral albedo (GSA) model, using LiDAR data and geo-referenced material maps to simulate albedo changes before and after PV integration; and (2) a simplified skyline-based PV model, using LiDAR-derived roof geometry to estimate annual PV electricity generation. The method is applied to the city of Delft, the Netherlands, and the average simulated albedo of Delft is 0.1584, differing by 6.12 % from MODIS observations (0.1493). Full PV integration on all rooftops reduces the city-wide albedo to 0.1557, corresponding to a positive RF of 3.53×10⁻⁸ W/m². This can be offset in about 40 days by negative RF from PV electricity, assuming a grid carbon intensity of 454 gCO₂-eq/kWh. However, under a low-carbon grid scenario (30 gCO₂-eq/kWh), the payback time increases to 623 days, indicating that positive RF from albedo reduction becomes more relevant in future decarbonized scenarios. This study contributes to understanding the climatic implications of urban PV deployment and offers insights into the realistic potential of PV systems in mitigating climate change.

This work presents a practical approach to designing an optical filter for thermal management for photovoltaic modules. The approach emphasizes the practicality of manufacturing over optical performance. Simulation work demonstrates that, for an interdigitated back contact solar cell architecture, complete rejection of infrared radiation offers limited thermal benefits requiring highly complex optical filter designs. An alternative approach consists of reducing thermalization losses by providing reflectance at lower wavelength values. An optical filter design that fulfills this requirement is possible using simple structures based on two materials and taking advantage of the harmonics present in quarter wavelength optical thickness designs. The filter is later optimized for angular performance via second-order algorithms, resulting in a device consisting of only 15 thin-film layers. Performance simulations on two locations, Delft (the Netherlands) and Singapore, estimate a temperature reduction of 2.20°C and 2.45°C, respectively. In a single year, the optical loss produced by the filter is not compensated via temperature reduction. However, improvements in the annual degradation rate show that in Singapore, the overall effect of the filter on the lifetime DC energy yield is positive.

Visible light communication (VLC) is a promising complement considering the rising radio frequency spectrum congestion. However, photodiode receivers degrade rapidly under high ambient light (>200 W/m²). Photovoltaic (PV) cells, designed for outdoor applications, offer an effective alternative. This work studies the fundamental relationship between various LEDs and seven commercial crystalline silicon (c-Si) PV cell architectures to assess simultaneous energy harvesting and communication. The results reveal that increased PV output inversely affects bandwidth. The impact of PV cell architecture on bandwidth is mainly due to bulk doping concentration and metallization design. Higher doping reduces bandwidth at short circuit but increases it at higher operating voltages. At the transmitter end, higher irradiance levels enhance communication, but this effect is minimal at the PV maximum power point (MPP). Additionally, LED color has a negligible impact on PV cell bandwidth. The highest bandwidth is 215 kHz for Al-BSF(5”) under short-circuit, while the lowest is 0.1 kHz for SHJ at MPP. Among the tested c-Si PV architectures, Al-BSF cells exhibit the best communication stability – from 100 kHz to 10 kHz, while SHJ shows the worst – from 100 kHz to 0.1 kHz. TOPCon demonstrates the optimal balance between energy harvesting and communication for Pareto optimality.

Herein, the application of a comprehensive modeling framework that can help optimize the design of multilayered optical filters for coloring photovoltaic (PV) modules is presented based on crystalline silicon solar cells. To overcome technical issues related to the implementation of color filters (CFs) on PV modules, like glare and color instability, colorimetry metrics, such as the hue, chroma, luminance color space, and the quantitative concept of difference between two colors are extensively deployed. It is showcased in this work that designing colored modules with high hue and chroma stability is possible by using a front-side texturing with edged geometry, like V-shaped grooves and inverted pyramids, while obtaining colors with relatively high luminance values, indicating good brightness. Furthermore, it is argued that adapting the rear surface of the front glass with a random textured layout where the CF is applied can improve color and luminance stability without significant loss of chroma while eliminating glare. Finally, the models can be used to optimize the number of layers for a given CF, reducing unnecessary optical losses. Compared to a standard PV module, performance simulation of optimized, bright-colored PV modules predicts relative energy yield losses ranging from 7% to 25%.

Integration of photovoltaics (PV) into the urban environment will play a major role in the energy transition. However, installing PV systems on building roofs can be challenging, particularly for monumental buildings with strict architectural and social value restrictions. Assessing roof surface visibility is, therefore, key to finding as much permitted roof surface area as possible that may be used for PV installation. In this study, a GIS-based large-scale visibility assessment tool is developed that can assist in evaluating roof visibility, using LiDAR, road networks, and cadastral data as inputs. The tool delivers multi-level outputs, including maps of roof binary visibility, roof visual amplitude, roof PV system layout, roof PV system AC yield, and roof PV module visibility. After optimization, an average speed of 0.12 s/m² is achieved. For each roof surface, an additional sensitivity analysis has been conducted. This step determines the optimal values for two visibility analysis parameters: assessment range and observer spacing, balancing the computational demand and result accuracy. Application of this workflow to the monumental buildings on the TU Delft campus revealed that approximately 2.68 GWh/year of electricity could be harvested from imperceptible PV modules, while an additional 0.42 GWh/year of energy is attributed to PV modules with medium visibility, and 0.37 GWh/year of energy is associated with PV modules with high visibility. This modeling workflow supports the multi-criteria decision-making process for urban roof PV planning.

Photovoltaic (PV) technology is the most promising renewable energy source to be integrated on urban building surfaces. Modeling and simulating urban PV systems pose more challenges than the conventional ones installed in open field due to rich urban morphology. Herein, a comprehensive workflow to estimate urban solar PV potential is developed where TU Delft campus is used as a case study. This workflow only requires light detection and ranging data and building footprints as data inputs, and multiple levels of result can be delivered including accurate geo-referenced 3D building models, annual solar irradiation map, annual DC/AC yield maps and classified roof segments according to the specific yield of mounted PV system. The study reports a total of ≈8.1 GWh year⁻¹ of PV energy which can be collected from campus building roofs and facades. Given the total electricity demand on the entire campus being 82.6 GWh/year, this PV potential can cover roughly 10% of the current electricity demand. The results constitute an initial assessment of solar PV potential on TU Delft campus buildings that is currently being used to prioritize PV integration on buildings and accelerate the transition toward a climate-neutral campus.