A wide literature review of recent advance on monitoring, diagnosis, and power forecasting for photovoltaic systems is presented in this paper. Research contributions are classified into the following five macroareas: (i) electrical methods, covering monitoring/diagnosis techniques based on the direct measurement of electrical parameters, carried out, respectively, at array level, single string level, and single panel level with special consideration to data transmission methods; (ii) data analysis based on artificial intelligence; (iii) power forecasting, intended as the ability to evaluate the producible power of solar systems, with emphasis on temporal horizons of specific applications; (iv) thermal analysis, mostly with reference to thermal images captured by means of unmanned aerial vehicles; (v) power converter reliability especially focused on residual lifetime estimation. The literature survey has been limited, with some exceptions, to papers published during the last five years to focus mainly on recent developments.

The accepted version will be replaced on the Digital Library with the typeset e-First version upon completion of production of the article.

The accepted version will be replaced on the Digital Library with the typeset e-First version upon completion of production of the article.

The ever-increasing development of wind power plants has raised awareness that an appropriate condition monitoring system is required to achieve high reliability of wind turbines. In order to develop an efficient, accurate and reliable condition monitoring system, the operations of wind turbines need to be fully understood. This article focuses on the online condition monitoring of electrical, mechanical and structural components of a wind turbine to diminish downtime due to maintenance. Failure mechanisms of the most vulnerable parts of wind turbines and their root causes are discussed. State-of-the-art condition monitoring methods of the different parts of wind turbine such as generators, power converters, DC-links, bearings, gearboxes, brake systems and tower structure are reviewed. This article addresses the existing problems in some areas of condition monitoring systems and provides a novel method to overcome these problems. In this article, a comparison between existing condition monitoring techniques is carried out and recommendations on appropriate methods are provided. In the analysis of the technical literature, it is noted that the effect of wind speed variation is not considered for traditional condition monitoring schemes.

The majority of electrical failures in wind turbines occur in the semiconductor components (IGBTs) of converters. To increase reliability and decrease the maintenance costs associated with this component, several health-monitoring methods have been proposed in the literature. Many laboratory-based tests have been conducted to detect the failure mechanisms of the IGBT in their early stages through monitoring the variations of thermo-sensitive electrical parameters. The methods are generally proposed and validated with a single-phase converter with an aircored inductive or resistive load. However, limited work has been carried out considering limitations associated with measurement and processing of these parameters in a three-phase converter. Furthermore, looking at just variations of the module junction temperature will most likely lead to unreliable health monitoring as different failure mechanisms have their own individual effects on temperature variations of some, or all, of the electrical parameters. A reliable health monitoring system is necessary to determine whether the temperature variations are due to the presence of a premature failure or from normal converter operation. To address this issue, a temperature measurement approach should be independent from the failure mechanisms. In this paper, temperature is estimated by monitoring an electrical parameter particularly affected by different failure types. Early bond wire lift-off is detected by another electrical parameter that is sensitive to the progress of the failure. Considering two separate electrical parameters, one for estimation of temperature (switching off time) and another to detect the premature bond wire lift-off (collector emitter on-state voltage) enhance the reliability of an IGBT could increase the accuracy of the temperature estimation as well as premature failure detection.