Search

After developing the methodology, we applied it to the case of the Netherlands highways. We show that the average irradiation on the Dutch highway network is around 880 kWh/m2/y, 35% less than the potential of an optimally tilted conventional PV system in the south of the Netherlands. Covering the entire 1600 km of the Dutch highways network with solar road modules of poly c-Si, mono c-Si and CIGS would respectively generate 5.2 TWh/y, 6.6 TWh/y, and 3.4 TWh/y of DC electricity. This could be used to fully power the Dutch national public lighting demand. Moreover, to include the effect of traffic on these values, a model was developed to account for the energy potential reduction due to vehicles shading. Using real traffic data from two of the top-four busiest roads in the Netherlands, the A12 and A16, it was found that traffic accounts for an average of 3% reduction of solar road irradiation and DC yield potential. The maximum reduction of 9% was observed in particular locations, such as bridges and nearby ramp roads. The result of such mapping methodology could serve as a useful tool for research advisory, private industry, and governmental projects. [ABSTRACT FROM AUTHOR]

Photovoltaic modules in the urban environment are very often exposed to uneven illumination conditions. The electrical interconnection between solar cells in a photovoltaic module limits the power that a solar module can generate under partial shading conditions. In this article, we introduce a PV module that is able to dynamically reconfigure the interconnection between its solar cells to minimise conduction and mismatch losses according to the irradiance distribution on its surface. Using an accurate simulation framework, it is determined that a reconfigurable PV module can generate over 12% more energy than a standard PV module with fixed topology and six bypass diodes, and as much energy as a fixed series-parallel module with six parallel strings, but at significantly lower currents. Simulation results are validated experimentally using a photovoltaic module with six reconfigurable blocks of cells controlled by a switching matrix on a high-performance solar flash simulator. • A fully reconfigurable series-parallel photovoltaic module is proposed. • The DC yield of the proposed module is compared to fixed shade-tolerant topologies. • Under partial shading, reconfigurable PV modules can boost energy yield over 12%. • Full-scale prototypes of the module and the switching matrix were built. • Experimental validation shows an excellent match with simulation results. [ABSTRACT FROM AUTHOR]

• A quick-scan yield prediction method was developed to assess rooftop PV potential. • It detects 3D roof segments, fits PV modules, and calculates yield automatically. • The method was validated in the Netherlands and can be applied to other countries. A quick-scan yield prediction method has been developed to assess rooftop photovoltaic (PV) potential. The method has three main parts. For each roof, first (i) virtual 3D roof segments were reconstructed using aerial imagery, then, (ii) PV modules were automatically fitted onto roof segments using a fitting algorithm and finally, (iii) expected annual yield was calculated. For each roof, the annual yield was calculated by three different quick yield calculation approaches. Two approaches are commercial software packages of Solar Monkey (SM) and Photovoltaic Geographical Information System (PVGIS) whereas the other one is the simplified skyline-based approach developed in photovoltaic material and devices (PVMD) group of Delft University of Technology. To validate the quick-scan method, a set of 145 roofs and 215 roof segments were chosen in urban areas in the Netherlands. For the chosen roofs, the number of fitted modules and calculated yield were compared with the actual modular layout and the measured yield of existing PV systems. Results showed a satisfactory agreement between the quick-scan yield prediction and measured annual yield per roof, with relative standard deviations of 7.2%, 9.1%, and 7.5% respectively for SM, PVGIS, and PVMD approaches. It was concluded that the obstacle-including approaches (e.g. SM and PVMD) outperformed the approaches which neglect the shading by surrounding obstacles (e.g. PVGIS). Results also showed that 3D roof segments had added value as input for the quick-scan PV yield prediction methods since the precision of yield prediction was significantly lower using only 2D land register data of buildings. [ABSTRACT FROM AUTHOR]