Reconfiguration of PV arrays is one of the most suitable options to face issues affecting the power produced by panels, such as partial shading. This paper presents a reconfiguration procedure based on a genetic algorithm. The execution times obtained with the proposed approach validate its good performance compared with a traditional brute force algorithm. Finally, different shading patterns are considered in the simulations.

The integration of renewable energy sources to create microgrids is drawing growing interest to address current energy-related challenges around the globe. Nevertheless, microgrids must be analyzed using specialized tools that allow to conduct operation, technical and economic studies. In that regard, this paper presents a case study in which the software HOMER Energy Pro was implemented to design and analyze the performance of a microgrid. Such microgrid comprises a photovoltaic system, a wind system and a diesel plant. The parameters of the energy systems are based on information about local weather conditions available in databases. Finally, this analysis is performed under two conditions: stand-alone and grid-tied.

Photovoltaic (PV) arrays can be connected following regular or irregular connection patterns to form regular configurations (e.g., series-parallel, total cross-tied, bridge-linked, etc.) or irregular configurations, respectively. Several reported works propose models for a single configuration; hence, making the evaluation of arrays with different configuration is a considerable time-consuming task. Moreover, if the PV array adopts an irregular configuration, the classical models cannot be used for its analysis. This paper proposes a modeling procedure for PV arrays connected in any configuration and operating under uniform or partial shading conditions. The procedure divides the array into smaller arrays, named sub-arrays, which can be independently solved. The modeling procedure selects the mesh current solution or the node voltage solution depending on the topology of each sub-array. Therefore, the proposed approach analyzes the PV array using the least number of nonlinear equations. The proposed solution is validated through simulation and experimental results, which demonstrate the proposed model capacity to reproduce the electrical behavior of PV arrays connected in any configuration.

Photovoltaic panels can be affected by partial shading, which causes some shaded cells to consume the energy generated by other cells of the panel. That is, shaded cells stop operating in the first quadrant and start operating in the second quadrant, with negative voltage at their terminals, causing power losses and other negative effects in the cells. The Bishop model is an accurate representation of the cells behavior at the second quadrant, but estimating its parameters is not a trivial task. Therefore, this paper presents a procedure to estimate the parameters of the Bishop model by using the Chu–Beasley optimization technique. The effectiveness of this procedure was evaluated using different accuracy measures such as RMSE and MAPE, obtaining values lower than 0.5%. In addition, the results of this study demonstrate that it is essential to estimate all the parameters of the Bishop model, illustrate the variation in the parameters according to the cell technology and show the strong influence of the shunt resistance into the behavior at the second quadrant.

This article addresses the application of building-integrated photovoltaic (BIPV) systems through the analysis of a case study with different operating conditions and geospatial locations. The research is carried out with customer-made photovoltaic modules supported by computational aids. The results obtained from real-life BIPV installation are contrasted, simulated, and improved through different scenarios where aspects such as software deviation, shadowing influence, installed capacity, and project profitability are analyzed to establish viability pathways for BIPV projects. As a result, the most relevant factors to improve the technical and economic conditions of the BIPV system are the total capacity installed, the use of the available area, and the strategic location of the modules to avoid shading surfaces. In this way, this work addresses the analysis of BIPV systems through the assessment of a case study implemented in a real residential structure in Colombia. The proposed methodology includes simulations to evaluate the solar energy potential considering the elements in the neighborhood of the BIPV system and technical aspects, such as the wiring and power interface, an economical study to find the feasibility of the project, and an analysis of different operating scenarios. As a result, the most important factors that affect the operation of BIPV systems under Colombian weather conditions were identified: total installed capacity, use of the available area, and strategic location of the modules to avoid shading surfaces. Such factors can then be considered in the early stage of designing for future BIPV applications.