Photovoltaic (PV) installations have experienced significant growth in the past 20 years. During this period, the solar industry has witnessed technological advances, cost reductions, and increased awareness of renewable energy’s benefits. As more than 90% of the commercial solar cells in the market are made from silicon, in this work we will focus on silicon-based solar cells. As PV research is a very dynamic field, we believe that there is a need to present an overview of the status of silicon solar cell manufacturing (from feedstock production to ingot processing to solar cell fabrication), including recycling and the use of artificial intelligence. Therefore, this work introduces the silicon solar cell value chain with cost and sustainability aspects. It provides an overview of the main manufacturing techniques for silicon ingots, specifically Czochralski and directional solidification, with a focus on highlighting their key characteristics. We discuss the major challenges in silicon ingot production for solar applications, particularly optimizing production yield, reducing costs, and improving efficiency to meet the continued high demand for solar cells. We review solar cell technology developments in recent years and the new trends. We briefly discuss the recycling aspects, and finally, we present how digitalization and artificial intelligence can aid in solving some of the current PV industry challenges.

This article presents new analytical expressions for the temperature coefficients of the voltage, current, and power of a solar cell at its maximum power point (MPP). A new analytical expression of the temperature coefficient of the fill factor is also derived. The new expressions are written as functions of photovoltaic (PV) metrics that can be obtained from i-V measurements. Nonideal diode behavior is partially accounted for through a temperature dependent ideality factor. The recombination parameter $\gamma$, which has been shown to account for the thermal sensitivity of all mechanisms determining the open-circuit voltage, appears to play a role also for the temperature coefficient of the MPP. The expressions are tested against experimental data, which covers measurements from 18 multicrystalline silicon solar cells with different bulk resistivities and cell architectures. It is found that the new model captures the essence of the temperature variation shown by the investigated PV metrics.

This paper presents new analytical expressions for the maximum power point voltage, current, and power that have an explicit dependence on the series resistance. An explicit expression that relates the series resistance to well-known solar cell parameters was also derived. The range of the validity of the model, as well as the mathematical assumptions taken to derive it are explained and discussed. To test the accuracy of the derived model, a numerical single-diode model with solar cell parameters whose values can be found in the latest installment of the solar cell efficiency tables was used. The accuracy of the derived model was found to increase with increasing bandgap and to decrease with increasing series resistance. An experimental validation of the analytical model is provided and its practical limitations addressed. The new expressions predicted the maximum power obtainable by the studied cells with estimated errors below $0.1\%$ compared to the numerical model, for typical values of the series resistance.