The condition of synchronous generators (SGs) is a matter of great attention, because they can be seen as equipment and also as fundamental elements of power systems. Thus, there is a growing interest in new technologies to improve SG protection and maintenance schemes. In this context, electrical signature analysis (ESA) is a non-invasive technique that has been increasingly applied to the predictive maintenance of rotating electrical machines. However, in general, the works applying ESA to SGs are focused on isolated machines. Thus, this paper presents a study on the condition monitoring of SGs in bulk electric systems by using ESA. The main contribution of this work is the practical results of ESA for fault detection in in-service SGs interconnected to a power system. Two types of faults were detected in an SG at a Brazilian hydroelectric power plant by using ESA, including stator electrical unbalance and mechanical misalignment. This paper also addresses peculiarities in the ESA of wound rotor SGs, including recommendations for signal analysis, how to discriminate rotor faults on fault patterns, and the particularities of two-pole SGs.

This paper presents an air-gap torque (AGT)-based method for efficiency estimation of induction motors. A new concept of stator resistance that includes the mechanical losses effect is proposed. This new stator resistance is estimated through a particle swarm optimization approach based on the stator flux equations and minimization of torque error at the rated operation point. Then, the obtained stator resistance is used in the AGT equations to estimate the shaft torque and then the efficiency. Moreover, the rotor speed is estimated using induction motor current signature analysis. Thus, the proposed methodology for induction motor efficiency estimation relies only on line currents, line voltages, and nameplate data, being appropriate for in-service applications. Finally, the simulation and experimental results are presented to validate the proposed method at different load conditions.

Induction motors consume a great portion of the generated electrical energy. Moreover, most of them work at underloaded conditions, so they have low efficiencies and waste a lot of energy. Because of this, the efficiency estimation of in-service induction motors is a matter of great importance. This efficiency estimation is usually performed through indirect methods, which do not require invasive measurements of torque or speed. One of these methods is the modified Air-Gap Torque (AGT) method, which only requires voltage and current data, the stator resistance value, and the mechanical losses. This paper approaches the computation of a modified stator resistance including the mechanical losses effect to be applied in the AGT method for torque and efficiency estimation of induction motors. Some improvements are proposed in the computation of this resistance by using a direct method, as well as the possibility to estimate this parameter directly from the nameplate data of the induction motor. The proposed methodology only relies on line voltages, currents, and nameplate data and is not intrusive. The proposed methodology is analyzed through simulation and validated through experimental results with three-phase induction motors. Also, a comparison of methods for in-service induction motors efficiency estimation is presented for the tested motors.

Smart grids are a reality in distribution systems. They have assisted in the operation, control, and most of all, the protection of urban networks, significantly solving the contingencies of these networks. This paper treats the initial stage of implementing smart grid switching devices in distribution networks. In this stage, smart grid technologies need to operate with the traditional protection elements (such as fuses, reclosers, and sectionalizers). This fact can create trouble in the protection schemes because there are two distinctive philosophies. In some companies, especially those without substantial capital, these two protection philosophies can run together for many years. The most popular intelligent electronic devices (IEDs) available in the market are studied to verify their features and the possibility to incorporate techniques to allow the two philosophies to work together. After that, the proposed approach shows how the existing IEDs can interact with the traditional devices. Special functions can also be incorporated to inform the control center of an operational problem, increasing the observability of the network. With the proposed approach, the IEDs are transformed into intelligent agents. Practical examples using real distribution systems are presented and discussed, proving the efficacy of the proposed methodology.

This paper proposes a methodology for torque and efficiency estimation of in-service induction motors based on the Air-Gap Torque (AGT) method. The proposed methodology only relies on induction motor stator voltages, currents and nameplate data. A modified stator resistance is estimated including the mechanical losses effect. This modified stator resistance is estimated by using a Differential Evolution (DE) based algorithm. The DE procedure estimates the modified stator resistance by using the stator flux equations, minimizing the torque error at the rated operation point. The estimated stator resistance is applied in the AGT method equations to compute the induction motor torque and efficiency. Simulation tests were performed to validate the proposed methodology.