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Wind power generation has been the fastest-growing energy alternative in recent years, however, it still has to compete with cheaper fossil energy sources. This is one of the motivations to constantly improve the efficiency of wind turbines and develop new Operation and Maintenance (O&M) methodologies. The decisions regarding O&M are based on different types of models, which cover a wide range of scenarios and variables and share the same goal, which is to minimize the Cost of Energy (COE) and maximize the profitability of a wind farm (WF). In this context, this review aims to identify and classify, from a comprehensive perspective, the different types of models used at the strategic, tactical, and operational decision levels of wind turbine maintenance, emphasizing mathematical models (MatMs). The investigation allows the conclusion that even though the evolution of the models and methodologies is ongoing, decision making in all the areas of the wind industry is currently based on artificial intelligence and machine learning models.

Current–voltage (I–V) curve tracers are used for measuring voltage and current in photovoltaic (PV) modules. I–V curves allow identifying certain faults in the photovoltaic module, as well as quantifying the power performance of the device. I–V curve tracers are present in different topologies and configurations, by means of rheostats, capacitive loads, electronic loads, transistors, or by means of DC–DC converters. This article focuses on presenting all these configurations. The paper shows the electrical parameters to which the electronic elements of the equipment are exposed using LTSpice, facilitating the appropriate topology selection. Additionally, a comparison has been included between the different I–V tracers’ topologies, analyzing their advantages and disadvantages, considering different factors such as their flexibility, modularity, cost, precision, speed or rating, as well as the characteristics of the different DC–DC converters.

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