In this paper, we discuss the compression of waveforms obtained from measurements of power system quantities and analyze the reasons why its importance is growing with the advent of smart grid systems. While generation and transmission networks already use a considerable number of automation and measurement devices, a large number of smart monitors and meters are to be deployed in the distribution network to allow broad observability and real-time monitoring. This situation creates new requirements concerning the communication interface, computational intelligence and the ability to process data or signals and also to share information. Therefore, a considerable increase in data exchange and in storage is likely to occur. In this context, one must achieve an efficient use of channel communication bandwidth and a reduced need of storage space for power system data. Here, we review the main compression techniques devised for electric signal waveforms providing an overview of the achievements obtained in the past decades. Additionally, we envision some smart grid scenarios emphasizing open research issues regarding compression of electric signal waveforms. We expect that this paper will contribute to motivate joint research efforts between electrical power system and signal processing communities in the area of signal waveform compression.

This work outlines important characteristics of hybrid power line/wireless data communication system for Smart Grid (SG) and Internet of Things (IoT) applications. Moreover, we discuss the hybrid systems advantages in comparison to non-hybrid ones. These advantages are demonstrated not only in the technical point of view, but also in the infrastructural perspective. Also, we highlight a connection between the capillarity of IoT and the communication infrastructure provided by SG. Furthermore, we address the environmental influence on wireless and power line communications. Additionally, we present ergodic achievable data rate expressions for the hybrid power line/wireless channel (HPWC) and hybrid power line/wireless single-relay channel (HSRC) and provide performance analyses by considering four different cases, which are associated with the relative relay position in the single-relay channel model. Based on numerical results, we show that HPWC and HSRC offer a more reliable data transmission path when compared to power line or wireless system working alone.

This article focuses on problems and issues related to PQ and power system diagnostics, in particular those where signal processing techniques are extremely important. PQ is a general term that describes the quality of voltage and current waveforms. PQ problems include all electric power problems or disturbances in the supply system that prevent end-user equipment from operating properly.

This paper introduces a new waveform coding technique, based on wavelet transform, for power quality monitoring purposes. The proposed enhanced data compression method (EDCM) presents a complete adaptive signal processing approach to estimate the fundamental sinusoidal component and separate it from the transient ones in the monitored signal. When these nonstationary components are submitted to the compression technique, the sparse representation property of the wavelet transform provides an improvement in the compression ratio. Also, the degradation inserted by the lossy compression process is minimized. Simulation results confirm the effectiveness of the proposed method when compared to the standard solution, characterized by the compression of the whole monitored signal.

This paper describes a phase-locked-loop (PLL)-based power systems harmonic estimation algorithm, which uses an analysis filter bank and multirate processing. The filter bank is composed of bandpass filters. The initial center frequency of each filter is purposely chosen to be equal to harmonic frequencies. However, an adaptation strategy makes it possible to track time-varying frequencies as well as interharmonic components. A downsampler device follows the filtering stage, reducing the computational burden, especially because undersampling operations are performed. Finally, the last stage is composed of a PLL estimator which provides estimates for amplitude, phase, and frequency of the input signal. The proposed method improves the accuracy, computational effort, and convergence time of the previous harmonic estimator based on cascade PLL configuration.

This work focuses on analyses of cooperative protocols to enhance the performance of power line communication systems. Based on a measurement campaign and considering a sum power constraint, achievable data rates for amplify-and-forward (AF) and decode-and-forward (DF) protocols are analyzed. Similar investigations are performed for the maximum data rates attained using Hermitian-symmetric orthogonal frequency division multiplexing (HS-OFDM) together with equal gain combining (EGC), selection combining (SC) and maximal ratio combining (MRC) techniques. The influences of optimally and uniformly allocated transmission power and frequency bandwidth are are also analyzed and the efficiency of combination before and after equalization is compared. Results show that the relative distances among source, relay and destination nodes significantly impact system performance. Also, they reveal a range of total transmission power and bandwidth in which benefits can be verified. Among combining techniques, MRC and SC present similar results, but MRC offers a slightly better performance. In relation to computational complexity, SC is the most favorable. Maximum data rate analyses of HS-OFDM with frequency domain equalization based on zero forcing and minimum mean square error criteria show that the former scheme offers almost the same performance as the latter. Furthermore, it is shown that equalization after combination is more advantageous.