The integration of improved control techniques with advanced information technologies enables the rapid development of smart grids. The necessity of having an efficient, reliable, and flexible communication infrastructure is achieved by enabling real-time data exchange between numerous intelligent and traditional electrical grid elements. The performance and efficiency of the power grid are enhanced with the incorporation of communication networks, intelligent automation, advanced sensors, and information technologies. Although smart grid technologies bring about valuable economic, social, and environmental benefits, testing the combination of heterogeneous and co-existing Cyber-Physical-Smart Grids (CP-SGs) with conventional technologies presents many challenges. The examination for both hardware and software components of the Smart Grid (SG) system is essential prior to the deployment in real-time systems. This can take place by developing a prototype to mimic the real operational circumstances with adequate configurations and precision. Therefore, it is essential to summarize state-of-the-art technologies of industrial control system testbeds and evaluate new technologies and vulnerabilities with the motivation of stimulating discoveries and designs. In this paper, a comprehensive review of the advancement of CP-SGs with their corresponding testbeds including diverse testing paradigms has been performed. In particular, we broadly discuss CP-SG testbed architectures along with the associated functions and main vulnerabilities. The testbed requirements, constraints, and applications are also discussed. Finally, the trends and future research directions are highlighted and specified.

This paper proposes an automatic algorithm for the on-line implementation of a robust static state estimator on large power systems. The proposed algorithm maximizes the number of outliers and cyber-attacks that the estimator can resist while giving reliable estimates. The large power system is decomposed in several islands or subsystems, and a highly robust regression estimator, namely the least trimmed squares estimator (LTS), is implemented on each island to detect bad data. Executing the estimators in parallel will greatly reduce the computation time of the robust static state estimator. The introduced method is compared with two cycle detection graph-theory approaches, namely depth-first search (DFS) and minimum spanning tree (MST), which have been adapted here for power state estimation. Simulations on IEEE 14, 30, 57, 118, 145, and 300 bus systems show the superior performance of the proposed algorithm over the adapted DFS and MST. The algorithm could reduce significantly the number and size of cycles in the system. Furthermore, the number of detected outliers, and attacks is maximized while the observability of the system is ensured. Attacks or outliers on both measurements, and topology of the grid are detected as well.

Superimposed quantities, also known as delta quantities, are the transient signatures of fault currents and voltages that can be utilized by protective relays to achieve fast fault detection for electric power grid applications. With the installation of superconducting fault current limiters (SFCLs) on power transmission lines, the profiles of superimposed quantities in power system faults are affected due to the altered impedance properties at transmission line terminals, which may further affect protective relay performance. In this article, we investigate the impact of a resistive SFCL on superimposed quantity profiles. The equivalent circuit of a resistive SFCL connected to an electric power transmission system is first illustrated based on which the simulation model is established in an electromagnetic transients program. Various types of power transmission line faults are simulated. The superimposed current and voltage quantities at transmission line terminals are obtained. The simulation results demonstrate that the acquired superimposed quantities are significantly affected by the SFCL. Possible consequences to protection functions are discussed.

This paper examines the impact of false data injection (FDI) cyber-attacks on distribution system state estimation (DSSE) and the resulting distribution locational marginal price (DLMP) in power markets. Two robust high-breakdown regression estimators, namely S- and MM- estimators, are implemented to provide resistance against FDI attacks targeting measurements and grid topology, creating leverage points. The introduced estimators are compared to the weighted least squares (WLS) with a bad data detection and rejection module (BDD) and the robust Huber M-estimator. The proposed estimators are shown to be effective and compare favorably to both existing Huber M- and the WLS with BDD in the presence of topology FDI attacks. Both the S- and MM-estimators provide good performance in the case of clean and corrupted measurements. Their performance is comparable in this case to the Huber M- and the WLS, followed by a BDD module. The simulation considered a modified distribution IEEE 13 and 34-bus systems where the impact of FDI attack scenarios is shown on the state and the DLMP pricing in the presence of distributed generation.

The growth of renewable energy generation in the power grid brings attention to high-voltage direct current (HVDC) transmission as a valuable solution for stabilizing the system. Robust hybrid power system state estimation could enhance the resilience of the control of these systems. This paper proposes a two-stage, highly robust least-trimmed squares (LTS)-based estimator. The first step combines the supervisory control and data acquisition (SCADA) measurements using the robust LTS-based estimator. The second step merges the obtained state results with the available phasor measurement units (PMUs) measurements using a robust Huber M-estimator. The proposed robust LTS-based estimator shows good performance in the presence of Gaussian measurement noise. The proposed estimator is shown to resist and correct the effect of false data injection (FDI) attacks and random errors on the measurement vector and the Jacobian matrix. The state estimation (SE) is executed on a modified version of the CIGRE bipole LCC-HVDC benchmark model integrated into the IEEE 12-bus AC dynamic test system. The obtained simulation results confirm the effectiveness and robustness of the proposed two-stage LTS-based SE.