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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. This work explores the potential use of practical optical filters for thermal management of photovoltaic modules. Aiming for simplified designs, the temperature reduction is achieved by rejecting light at low and high wavelength values, albeit incurring optical losses. Performance simulation results show that the added optical loss is not compensated by the cooling effect. However, this effect can increase the lifetime of a PV module such that in certain locations, the overall performance effect is positive. [ABSTRACT FROM AUTHOR]

The surface of the vessels, as moving tiny islands, can be utilized to implement vehicle‐integrated photovoltaics (VIPV). Herein, a methodology is reported to calculate the power generated by a fleet of urban vessels as a function of time. Then, the result is shown for the largest European shipping fleet, using sailing data of 2746 Dutch general cargo vessels. Results show that the studied fleet can produce ≈ 226 GWh of energy per year, which corresponds to ≈ 6.5% of the whole fleet's energy demand. Next, this research validates the model with three week experimental data gathered by a test vessel sailing through the Netherlands. The validation phase reveals that the model can predict within a 4% error range. Finally, as an interesting finding, it is experimentally shown that the energy production profile of a fleet of urban vessels follows a Weibull distribution, quantified by scale (λ) and shape (k) parameters: λ = 880 Wh Wp−1 and k = 27 for the Dutch fleet. A sensitivity analysis shows that the parameters of the Weibull distribution are a function of urban fabric roughness and the climate. Such probability distribution can be extended to other urban fleets, such as solar cars, and help estimate the financial feasibility of integrating PV into vehicles. [ABSTRACT FROM AUTHOR]

Machine learning is arising as a major solution for the photovoltaic (PV) power prediction. Despite the abundant literature, the effect of climate on yield predictions using machine learning is unknown. This work aims to find climatic trends by predicting the power of 48 PV systems around the world, equally divided into four climates. An extensive data gathering process is performed and open‐data sources are prioritized. A website www.tudelft.nl/open-source-pv-power-databases has been created with all found open data sources for future research. Five machine learning algorithms and a baseline one have been trained for each PV system. Results show that the performance ranking of the algorithms is independent of climate. Systems in dry climates depict on average the lowest Normalized Root Mean Squared Error (NRMSE) of 47.6 %, while those in tropical present the highest of 60.2 %. In mild and continental climates the NRMSE is 51.6 % and 54.5 %, respectively. When using a model trained in one climate to predict the power of a system located in another climate, on average systems located in cold climates show a lower generalization error, with an additional NRMSE as low as 5.6 % depending on the climate of the test set. Robustness evaluations were also conducted that increase the validity of the results. [ABSTRACT FROM AUTHOR]

Temperature rising is a negative factor in almost all systems. It could cause by self heating or ambient temperature. In solar photovoltaic cells this temperature rising affects on the behavior of cells. In reality, it affects on components of equivalent circuit. This paper tries to analyze temperature effect using binary coding method and introduces a manner to reduce temperature negative effect on solar cells at shadow condition. MATLAB software has been used for simulation. Results show that more parallel bypass diodes could reduce thermal effect at partial shading and produce more power. Additionally, it could prevent early ageing of photovoltaic panels. [ABSTRACT FROM AUTHOR]

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/m 2). 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. • A trade-off exists between simultaneous energy harvesting and communication. • Higher LED irradiance leads to better communication performance of PV cells. • LED color has no significant impact on the communication performance of PV cells. • Higher bulk doping concentration and optimized metallization design are beneficial. • TOPCon architecture optimally balances communication with power production. [ABSTRACT FROM AUTHOR]