WP1 focused on the design of the different components of Reconfigurable Smart PV (RSPV) modules. First of all, the module layout has been investigated, to select few promising topologies able to significantly increase the energy yield under operating scenarios representative of BIPV applications. This investigation has been performed through accurate simulations, in which the irradiation profile over every cell of the PV module is calculated throughout the year. A methodology for the selection of candidate topologies has been developed based on practical manufacturing and financial considerations, then the resulting energy yield of different topologies has evaluated using an accurate and fast simulation framework (further discussed later). The best layout, allowing for highest net financial gain in 20 years (and also for highest energy generation in the simulated shading scenarios) has been selected for demonstration and fabricated. It is made of 120 6-inch half-cut cells, organized in 10 U-shaped strings that can be connected in series-parallel configuration under uniform operating conditions, or in parallel to 4 different local converters. Design of these local converters and realization of a first prototype on PCB has been also part of WP1. With the long-term goal of integration of the converters in the PV module laminate, the space of inductor-less converter topologies has been explored, and a cost-benefit analysis has led to the selection of two best candidates: Dickson topology with conversion ratio 3 and Dickson topology with conversion ratio 4. A fully controllable demo board that can implement both converter topologies has been designed and realized on PCB.
The focus of WP2 has been the development of the control algorithm for the RSPV module. This is based on a digital twin of the module itself that must run on a low-cost controller. Such a digital twin must ensure accuracy, to allow proper selection of the best configuration at run-time, and have limited execution time, to enable real-time reconfiguration. For this reason, the first part of WP2 has been devoted to the adaptation of the imec PV energy yield simulation framework for faster execution. Speed-up of ~190 times has been reached thanks to proper digitalization of the thermal network model and transformation of the electrical network model to remove implicit equations. This new simulation platform, implemented in both MATLAB and Python, is an essential part of current imec PV energy yield simulation framework and it has paved the way towards a collaboration (currently in place) between imec and the Lithuanian company PVcase to develop next-generation yield-simulation software for solar parks. The second task of WP2, to finalize the control algorithm, is to identify the PV module operating conditions with limited number of sensors, in order to use these identified parameters as input for the digital twin. In collaboration with University of Salerno and Tampere University, an identification algorithm has been developed that allows evaluation of irradiation and temperature based only on converter-level electrical measurements, that are also necessary to run the Maximum Power Point Tracking (MPPT) algorithm, and datasheet values.
WP3 and WP4 focused on the validation of the control algorithm and the RSPV module demonstrator. The algorithms developed in WP2 are both implemented in MATLAB, so that MATLAB itself could be used to port the algorithm on a digital device straightforwardly. Also, the different components of the RSPV module have been realized and indoor testing of the RSPV module layout have been performed, that demonstrates the feasibility of the proposed approach. Assembly of the full RSPV module for outdoor validation of its performance is work in progress at the moment this report is being written.
