With maturity of advanced technologies and urgent requirement for maintaining a healthy environment with reasonable price, India is moving towards a trend of generating electricity from renewable resources. Wind energy production, with its relatively safer and positive environmental characteristics, has evolved from a marginal activity into a multibillion dollar industry today. Wind energy power plants, also known as wind farms, comprise multiple wind turbines. Though there are several wind-mill clusters producing energy in different geographical locations across the world, evaluating their performance is a complex task and is an important focus for stakeholders. In this work an attempt is made to estimate the performance of wind clusters employing a multicriteria approach. Multiple factors that affect wind farm operations are analyzed by taking experts opinions, and a performance ranking of the wind farms is generated. The weights of the selection criteria are determined by pairwise comparison matrices of the Analytic Hierarchy Process (AHP). The proposed methodology evaluates wind farm performance based on technical, economic, environmental, and sociological indicators. Both qualitative and quantitative parameters were considered. Empirical data were collected through questionnaire from the selected wind farms of Belagavi district in the Indian State of Karnataka. This proposed methodology is a useful tool for cluster analysis.

Power generation quantity from wind sector is increasing at much faster rate day by day in the scenario of power systems, which obviously needs reliable operation. Therefore, accurate monitoring and error diagnosis are almost mandatory. This paper aims to identify important errors that affect the performance and can easily detect the faults of wind turbine generators (WTGs). Wind turbines are subjected to different sort of failures; thus, before starting to identify various kinds of errors, it is necessary to identify what kind of failures can be found in the real world which causes healthy operation of WTGs. Out of different errors, error that is caused by the operation of gearbox could stop or reduce the generation of power from WTGs for a long time. Recently, several condition monitoring and fault diagnosis techniques have been introduced in order to minimize downtime and maintenance cost while increasing energy availability and life time service of the wind farms. Different types of sensors have been used for long time in wind turbine fault diagnosis or monitoring systems to collect data of the generator health. Many researchers analyzed wind turbine failures using different software. The present study uses different approaches and prepares a multicriteria decision-making framework using analytic hierarchy process (AHP). The analysis of the data under AHP frame work revealed overspeed guard/turbine out of control error got the top most impediment to the healthy operation of WTGs, and high brake temperature fits in the fifth position among the five different error groups considered.

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