The deep integration of sensor, computer, and communication networks has dramatically improved the efficiency and operational performance of the electric grid. However, it also exposes the grid to rising threats of cyber-physical attacks. False data injection attack (FDIA) is one of the most representative attacks. To improve the security of grid operation, we propose a Hellinger-distance-based FDIA detection method by tracking the dynamic characteristics of measurement variations at adjacent moments. First, the irrelevant components of measured data are sieved out by empirical modal decomposition. Second, the image transform algorithms are used to deal with the mapping of measurement variations to refine the distribution characteristics. Last, the discrepancies between the probability distributions are derived based on Hellinger distance to determine whether FDIA exists. Concerning state-variable attacks on different nodes, the method is tested using the IEEE 14-bus system. The results indicate that the proposed scheme has high-level detection precision for false data injection attacks.

The results of measurements of the harmonics components of the current, voltage, power of harmonics at the point of connection of electric receivers with a non-linear voltage-current characteristic are considered. It is shown that the amount of electric energy including the non-sinusoidality of the currents and voltages consumed by the non-linear load is less than the amount of the fundamental frequency energy. The difference between them is the harmonic distortion energy that causes extra losses to the electric networks. The voltage harmonic distortions at the measurement point exceed the normative values for 0.4 kV electric networks.

Electrical power networks consist of numerous energy control zones connected by tie-lines, with the addition of nonconventional sources resulting in considerable variations in tie-line power and frequency. Under these circumstances, a load frequency control (LFC) loop gives constancy and security to interconnected power systems (IPSs) by supplying all consumers with high-quality power at a nominal frequency and tie-line power change. This article proposes employing a proportional–integral–derivative (PID) controller to effectively control the frequency in a one-area multi-source power network comprising thermal, solar, wind, and fuel cells and in a thermal two-area tie-line IPS. The particle swarm optimization (PSO) technique was utilized to tune the PID controller parameters, with the integral time absolute error being utilized as an objective function. The efficacy and stability of the PSO-PID controller methodology were further tested in various scenarios for proposed networks. The frequency fluctuations associated with the one-area multi-source power source and with the two-area tie-line IPS’s area 1 and area 2 frequency variations were 59.98 Hz, 59.81 Hz, and 60 Hz, respectively, and, in all other investigated scenarios, they were less than that of the traditional PID controller. The results clearly show that, in terms of frequency responses, the PSO-PID controller performs better than the conventional PID controller.

The use of frequency-controlled electric drives in industry and municipal services is accompanied by the problem of their negative impact on the distribution network. As examples, the results of measurements of power quality indices in the power supply system of an oil producing enterprise and on the supply input of a railway traction substation are given. It is shown that the voltage subgroup total harmonic distortions (THDS) can exceed their rated permitted values in 100% of the measurement time.

The report reflects the promising solutions for the creation of adaptive protection means and emergency automatics in the implementation of methods of identification of dynamic systems. Presented original research assigned at directly addressing the causes of the sensitivity lack of the transformer equipment protection - compensation for the magnetizing current of the power transformers by linearizing their transfer characteristics.