A synchronous generator is one of the key elements of any power system, having a significant impact on the stability and reliability of consumers’ power supply. Nowadays, the power systems emergency and operational control issues are being solved using computational models, the parameters whereof are determined using the reference data, or the data obtained during testing. High dependence of the models’ parameters on various external factors leads to a significant decrease in the accuracy of solving the issues of emergency and operational control. Identification based on the traditional telemetry systems or synchrophasor measurements is used to improve the accuracy of parameters of the power systems’ computational models. The purpose of this research lies in a meta-analysis of the available studies aimed at developing a methodology for determining parameters of a synchronous generator on the basis of measurement data. Russian and foreign studies were analyzed and grouped to achieve this goal. After that, for each group, advantages, disadvantages, and the area of application were identified. As a result, it is shown that the existing methods for determining parameters of synchronous generators based on measurement data cannot adapt to the source dataset and also require significant computing power. As a way to overcome these shortcomings, an adaptive model of a synchronous machine is proposed.