Distributed Flexible AC Transmission System Research Articles

A Modern Distribution Power Flow Controller With A PID-Fuzzy Approach : Improves The Power Quality

Technological improvements have led to an increase of nonlinear loads, which in turn has a significant impact on the quality of power transmission. It is imperative that the level of energy purity conveyed by a transmission line be elevated. The key factors influencing power transmission are line impedance, sending end voltage, and receiving end voltage. Harmonic currents are made by nonlinear loads, which can cause system resonance, capacitor overloading, less efficiency, and a change in the amount of the voltage. The Distributed Power Flow Controller (DPFC) is a recently developed Flexible AC Transmission System (FACTS) device that utilizes the distributed FACTS (D-FACTS) idea. Unlike the Unified Power Flow Controller (UPFC), which employs a single large-sized three-phase series converter, the DPFC incorporates several small-sized single-phase converters.

Modified Matrix Completion-Based Detection of Stealthy Data Manipulation Attacks in Low Observable Distribution Systems

A composite detection technique against stealthy data manipulations is developed in this paper for distribution networks that are low observable. Attack detection strategies typically rely on state estimation which becomes challenging when limited measurements are available. In this paper, a modified matrix completion approach provides estimates of the system state and its error variances for the locations in the network where measurements are unavailable. Using the error statistics and their corresponding state estimates, bad data detection can be carried out using the chi-squared test. The proposed approach employs a moving target defence strategy (MTD) where the network parameters are perturbed through distributed flexible AC transmission system (D-FACTS) devices such that stealthy data manipulation attacks can be exposed in the form of bad data. Thus, the bad data detection approach developed in this paper can detect stealthy attacks using the MTD strategy. This technique is implemented on 37-bus and 123-bus three-phase unbalanced distribution networks to demonstrate the attack detection accuracy even for a low observable system.

Dynamic Voltage Restorer as a Solution to Voltage Problems in Power Systems: Focus on Sags, Swells and Steady Fluctuations

In this study, the author presents the results of a survey on the utilisation of a dynamic voltage restorer (DVR) in power systems to alleviate voltage problems that result in sags, swells and fluctuations in voltage outside the required steady limits. A methodology based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement is adopted for conducting and reporting on the review, while the Scopus database is used to locate the relevant publications. A total of 68 publications qualify for inclusion in the survey. A bibliometric analysis covering the number of publications per annum, the top 10 most-cited journals and the top 10 most-cited publications is performed. The information from the selected publications is extracted, summarised and categorised into network scenarios for the use of DVRs, topologies and optimisation of DVRs; strategies for DVR controllers; and platforms that evaluate the feasibility of DVR topologies and controllers. Moreover, research trends and gaps are evaluated. Finally, potential areas for future research are proposed. This study provides an overview of the research on the use of a DVR to resolve voltage problems and is a resource for researchers generally interested in distributed flexible AC transmission systems (DFACTSs) and particularly interested in DVRs.

Scaled Conjugate-Artificial Neural Network-Based novel framework for enhancing the power quality of Grid-Tied Microgrid systems

The exponential increase in the dependence on electrical power by rapid industrialization and increasing population has given rise to the need of supplying electric power efficiently and with good power quality (PQ). The evolution of renewable energy sources and their increased penetration into traditional grid systems has increased the complexity of electric power transmission and distribution. The significant increase in the use of complex converters, Flexible AC Transmission System devices and complex nonlinear loads in modern power systems have amplified the issues associated with the production and distribution of electricity having proper PQ. The proper functioning of the power system network requires healthy quality of power, maintained both at the load and source end. The Dynamic Voltage Restorer is a prospective D-FACTS (Distribution Flexible AC Transmission System) device that has been widely incorporated for addressing the PQ issues caused by irregularities in the distribution grid's voltage, current, or frequency. This research article attempts to enhance PQ indices of Photovoltaic, Fuel Cell, DVR and energy storage (battery) based Microgrid systems through a proposed Scaled Conjugate based Artificial Neural Network (SC-ANN) in the Matlab/Simulink architecture. The suggested technique’s effectiveness is verified by introducing severe PQ faults such as sag and swell and numerous power system responses have been comprehensively studied by comparing them with traditional Fuzzy Logic Controller and Proportional Integral controllers. The results obtained validates the efficiency of the proposed controller over FLC and PI methods in maintaining the system power indices constant during the onset of PQ faults by reducing harmonics and oscillations thereby enhancing the overall system reliability, efficiency and stability paving its way for real-time implementation in the areas of MG system.

MMTD: Multistage Moving Target Defense for Security-Enhanced D-FACTS Operation

In recent studies, moving target defense (MTD) has been applied to detect false data injection (FDI) attacks using distributed flexible AC transmission system (D-FACTS) devices. However, the inherent conflict between the security goals of MTD (i.e., detecting FDI attacks) and the economic goals of D-FACTS devices (i.e., reducing power losses) would impede the application of MTD in real systems. Moreover, the detection capabilities of existing MTDs are often insufficient. This paper proposes a multi-stage MTD (MMTD) approach to resolve these two issues by adding a group of designed security-oriented schemes before D-FACTS’ economy-oriented scheme to detect FDI attacks. We keep these security-oriented schemes for a very short time interval and then revert to the economy-oriented scheme for the remaining time to ensure the economic requirements. We prove that a designed MMTD can significantly improve the detection capability compared to existing one-stage MTDs. We find the supremum of MMTD’s detection capability and study its relationship with system topology and D-FACTS deployment. Meanwhile, a greedy algorithm is proposed to search the MMTD strategy to reach this supremum. Simulation results show that the proposed MMTD can achieve the supremum against FDI attacks while outperforming current MTD strategies on economic indicators.

Optimal Deployment in Moving Target Defense against Coordinated Cyber–Physical Attacks via Game Theory

This work proposes a method for the intelligent deployment of distributed flexible AC transmission system (D-FACTS) devices. In recent years, in the field of moving target defense (MTD) strategies to detect coordinated cyber–physical attacks (CCPAs), establishing how to deploy D-FACTS devices has become an important research point. Although some research results have been proposed, the obtained deployment solutions are unintelligent due to not carefully considering smart attackers’ behaviors. A method for achieving the intelligent deployment of D-FACTS devices is proposed in this paper. First, the basic concept of corrupting CCPAs is summarized; second, based on considering practical constraints and the basic concept, a protected transmission line set is confirmed; and third, a zero-sum game model is formulated, and a robust Nash equilibrium solution is computed. Due to the game’s characteristics, this solution reflects the smart attackers’ sense of action. Relying on the solution, those lines that are most likely to be tripped form a new protected transmission line set. Finally, a comprehensive algorithm using a metric proposed in previous studies is proposed for finding an intelligent solution for the deployment of D-FACTS devices. We validated our results through extensive simulations using IEEE 14-bus, 30-bus, and 118-bus power systems provided by MATPOWER and the real-world load profiles from New York State. Our work, in tracking the targets that attackers are most likely to attack, opens up new ideas for the intelligent deployment of D-FACTS devices.

Security Enhancement of Power System State Estimation With an Effective and Low-Cost Moving Target Defense

Moving target defense (MTD) is a new defensive mechanism developed in power systems to thwart false data injection attacks (FDIAs). However, since the MTD works by perturbing the branch parameters with the distributed flexible ac transmission system (D-FACTS), it might cause additional infrastructure and operation costs and affect the system dynamics. This is a complicated problem because it is closely related to which branches should be perturbed and how much they are changed. In this article, we analyze the essentials of MTD and construct an effective and low-cost MTD. To begin with, we provide a sufficient and necessary condition for MTD to protect a bus from being affected by the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">intended FDIA</i> . Based on this result, we propose a new metric to quantify the protection level of MTD and an efficient algorithm to minimize the number of required D-FACTS devices for protecting a specific set of buses. To reduce the operation cost, we develop two strategies to make the increasing operation cost zero for activating the MTD. Furthermore, we analyze the impact of MTD on the system dynamics with a special emphasize on small signal stability. Finally, we conduct extensive simulations to validate our findings with the test cases of power systems in MATPOWER.

A Gradient-Based Optimizer with a Crossover Operator for Distribution Static VAR Compensator (D-SVC) Sizing and Placement in Electrical Systems

A gradient-based optimizer (GBO) is a recently inspired meta-heuristic technique centered on Newton’s gradient-based approach. In this paper, an advanced developed version of the GBO is merged with a crossover operator (GBOC) to enhance the diversity of the created solutions. The merged crossover operator causes the solutions in the next generation to be more random. The proposed GBOC maintains the original Gradient Search Rule (GSR) and Local Escaping Operator (LEO). The GSR directs the search to potential areas and aids in its convergence to the optimal answer, while the LEO aids the searching process in avoiding local optima. The proposed GBOC technique is employed to optimally place and size the distribution static VAR compensator (D-SVC), one of the distribution flexible AC transmission devices (D-FACTS). It is developed to maximize the yearly energy savings via power losses concerning simultaneously different levels of the peak, average, and light loadings. Its relevance is tested on three distribution systems of IEEE 33, 69, and 118 nodes. Based on the proposed GBOC, the outputs of the D-SVCs are optimally varying with the loading level. Furthermore, their installed ratings are handled as an additional constraint relating to two compensation levels of 50% and 75% of the total reactive power load to reflect a financial installation limit. The simulation applications of the proposed GBOC declare great economic savings in yearly energy losses for the three distribution systems with increasing compensation levels and iterations compared to the initial case. In addition, the effectiveness of the proposed GBOC is demonstrated compared to several techniques, such as the original GBO, the salp swarm algorithm, the dwarf mongoose algorithm, differential evolution, and honey badger optimization.

Robust Moving Target Defence Against False Data Injection Attacks in Power Grids

Recently, moving target defence (MTD) has been proposed to thwart the false data injection (FDI) attacks in power system state estimation by proactively triggering the distributed flexible AC transmission system (D-FACTS) devices. One of the key challenges for MTD in power grid is to design its real-time implementation with performance guarantees against unknown attacks. Converting from the noiseless assumptions in the literature, this paper investigates the MTD design problem in a noisy environment and proposes, for the first time, the concept of robust MTD to guarantee the worst-case detection rate against all unknown attacks. We theoretically prove that, for any given MTD strategy, the minimal principal angle between the Jacobian subspaces corresponds to the worst-case performance against all potential attacks. Based on this finding, robust MTD algorithms are formulated for the systems with both complete and incomplete configurations. Extensive simulations using standard IEEE benchmark systems demonstrate the improved average and worst-case performances of the proposed robust MTD against state-of-the-art results.

Multi-area distribution grids optimization using D-FACTS devices by M-PSO algorithm

This paper presents a model for the optimization of a multi-area distribution grid considering the high penetration levels of photovoltaic (PV) resources and electric vehicle charging station (EVCSs) based on distributed flexible AC transmission system (D-FACTS) devices including on-load tap changer (OLTC) transformers and step voltage regulator (SVR) tap control and shunt capacitor (SC) and shunt reactor (ShR) to reduce losses and voltage deviation. The overarching research aim was to avoid the overvoltage caused by power injection by PV sources and the voltage drop caused by charging EVs in distribution grids. The proposed model was designed based on distribution network load flow and was optimized using a modified particle swarm optimization (M-PSO) algorithm. Two different test networks were tested under different scenarios to analyze the proposed model, revealing the efficiency of the proposed model.

A Double-Benefit Moving Target Defense Against Cyber–Physical Attacks in Smart Grid

The smart grid (SG), as one of the largest evolutionary critical infrastructures, witnesses the deep integration of electricity facilities and Internet of Things (IoT). But recent events show that the vulnerabilities exposed in IoT devices can be exploited by adversaries to construct the cyberattacks on SG. To address this threat, plenty of countermeasures have been proposed to enhance the SG’s security. However, the additional costs introduced by some countermeasures make the utilities hesitate to implement them practically. To alleviate this concern, in this article, we propose a double-benefit moving target defense (dB-MTD) to protect the SG from cyber–physical attacks (CPAs) and also gain generation-cost benefits. The dB-MTD enables the prevention of stealthy CPAs on the transmission lines by perturbing the reactances with the distributed flexible AC transmission system (D-FACTS). To reduce the infrastructure cost, we minimize the number of required D-FACTS devices for a specific protection goal. Although it needs investment on D-FACTS, we find that the utility can make profits from the generation costs by appropriately setting the reactance perturbations. Therefore, we formulate an optimization problem to compute the optimal reactance perturbations to maximize the generation-cost benefits, without sacrificing the protection performance of dB-MTD. Finally, using the real-world load profiles, we conduct extensive simulations to evaluate the impact of CPA on the system operation and the benefits obtained by the dB-MTD from the aspects of the D-FACTS deployment and the generation-cost profits.

Boosting Transmission System Flexibility in Network-Constrained Unit Commitment by Incorporating Distributed Series Reactors

In the recent decade, renewable energy sources (RES) such as wind and photovoltaic (PV) power generations gained more attention. However, despite their proven role in the reduction of operating costs of the network, their integration has some serious challenges such as the inherent uncertainties and the energy balance at the power grid. Some options to face these challenges, as well as to enhance the network’s flexibility, are demand response (DR), distributed FACTS (D-FACTS) devices, and energy storage systems (ESS). This paper focuses on the solution of the unit commitment (UC) problem in such a way that in addition to increasing the transmission network’s flexibility, the operation cost of the network decreases. To do this, distributed series reactors (DSRs) are employed as promising D-FACTS devices to enhance the transmission network’s flexibility. The uncertainty of RES is handled by the scenario-based stochastic programming technique. A mixed-integer linear programming (MILP) approach is developed, with a guaranteed global optimal solution, by developing a convex model for power flow in the presence of DSRs. The proposed UC model is implemented on the IEEE RTS 24-bus system, and the obtained results in different cases show the ability of the abovementioned flexibilities to reduce the operation cost of the network.

Voltage Stability Constrained Moving Target Defense Against Net Load Redistribution Attacks

Moving target defense (MTD) using distributed flexible AC transmission system (D-FACTS) devices is a promising defense strategy to detect stealthy false data injection (FDI) attacks against the power system state estimation. However, all existing studies myopically perturb the reactance of D-FACTS lines without considering the system voltage stability. In this paper, we first illustrate voltage instability induced by MTDs in a three-bus system. To address this issue, we further propose a novel MTD framework that explicitly considers system voltage stability by using continuation power flow and voltage stability indices. We mathematically derive the sensitivity matrix of voltage stability index to line impedance, on which an optimization problem for maximizing voltage stability index is formulated. This framework is tested on the IEEE 14-bus and the IEEE 118-bus transmission systems, in which net load redistribution attacks are launched by sophisticated attackers. The simulation results show the effectiveness of the proposed framework in circumventing the voltage instability while maintaining the detection effectiveness of MTD. We conduct case studies with and without the proposed framework under different MTD planning and operational methods. The impacts of the proposed two methods on attack detection effectiveness and system economic metrics are also revealed.

Strategic Protection Against FDI Attacks With Moving Target Defense in Power Grids

Moving target defense (MTD) is a new defensive strategy protecting the power system state estimation from cyberattacks. Using the distributed flexible ac transmission system (D-FACTS), MTD works by actively perturbing the branch parameters that are needed to construct the false data injection (FDI) attacks. Although there are many pioneer works on MTD, the relationship between the construction of MTD and detection of FDI attacks has not been revealed. In this article, we reveal the correlation between MTD design and FDI detection and optimize MTD’s performance in terms of detecting FDI attacks. We provide a sufficient condition for a specially designed MTD to detect and identify the FDI attack and a necessary condition for general MTDs to protect the state estimates from being independently modified. With the aim to reduce the number of measurements that can be manipulated by the attacker after MTD, we develop a heuristic algorithm to compute a near-optimal solution for the deployment of D-FACTS devices. Moreover, we prove that the coordinated design of consecutive perturbation schemes within an MTD cycle can improve the performance of MTD in terms of detecting FDI attacks. Finally, we conduct extensive simulations with the IEEE power system test cases to validate our findings.

Moving-Target Defense Against Cyber-Physical Attacks in Power Grids via Game Theory

This work proposes a moving target defense (MTD) strategy to detect coordinated cyber-physical attacks (CCPAs) against power grids. The main idea of the proposed approach is to invalidate the knowledge that the attackers use to mask the effects of their physical attack by actively perturbing the grid’s transmission line reactances via distributed flexible AC transmission system (D-FACTS) devices. The proposed MTD design consists of two parts. First, we identify the subset of links for D-FACTS device deployment that enables the defender to detect CCPAs against any link in the system. Then, in order to minimize the defense cost during the system’s operational time, we formulate a zero-sum game to identify the best subset of links to perturb (which will provide adequate protection) against a strategic attacker. The Nash equilibrium robust solution is computed via exponential weights, which does not require complete knowledge of the game but only the observed payoff at each iteration. Extensive simulations performed using the MATPOWER simulator on IEEE bus systems verify the effectiveness of our approach in detecting CCPAs and reducing the operator’s defense cost.

Optimal Planning and Operation of Hidden Moving Target Defense for Maximal Detection Effectiveness

Moving target defense (MTD) in the power system is a promising defense strategy to detect false data injection (FDI) attacks against state estimation using distributed flexible AC transmission system (D-FACTS) devices. A hidden MTD (HMTD) is a superior MTD method, as it is stealthy to sophisticated attackers. However, the optimal planning and operation of D-FACTS devices that ensure the MTD hiddenness and maximal detection effectiveness are challenging yet unresolved issues. In this paper, we tackle these challenges by first deriving a novel hiddenness operation condition. Then, we propose an analytical sufficient condition on the D-FACTS placement for HMTDs using a graph-theory-based topology analysis. A depth-first-search-based D-FACTS placement algorithm is proposed to guarantee the MTD hiddenness while maximizing the rank of its composite matrix, i.e., an indicator of the MTD effectiveness, and covering all necessary buses. Additionally, we propose DC- and AC-HMTD operation models to determine the setpoints of D-FACTS devices. The optimization-based DC-HMTD model overcomes the drawbacks of the existing HMTD operation. The ACOPF-based HMTD operation model minimizes the generation cost to utilize the economic benefit of D-FACTS devices. Comparative numerical results on the IEEE 14-bus and IEEE 57-bus systems show the efficacy of the proposed planning and operation approaches.

Power quality enhancement using Artificial Neural Network (ANN) based Dynamic Voltage Restorer (DVR)

The power quality, which can affect consumers and their utility, is a key concern of modern power system. The sensitive equipment is damaged by voltage harmonics, sag and swell. Therefore, as usage of sensitive equipment has been increasing, power quality is essential for reliable and secure operation of the power system in modern times. The potential distribution flexible AC transmission system (D-FACTS) device, a dynamic voltage restorer (DVR), is widely used to address problems with non-standard voltage in the distribution system. It induces voltages to preserve the voltage profile and ensures continuous load voltage. In this paper, the voltage sag and swell is compensated by DVR with an artificial neural network (ANN) controller. For the generation of reference voltage for voltage source converter (VSC) switching, and for the voltage conversion from rotating vectors to stationary frame, synchronous reference frame (SRF) theory is applied. The DVR Control Strategy and its performance is simulated using MATLAB software. It is also shown a detailed comparison of the ANN controller with the conventional Proportional Integral controller (PI), which showed ANN controller’s superior performance with less Total Harmonic Distortion (THD).

Multiperiod Optimum Power Flow for Active Distribution Networks With Provisioning of Ancillary Services

Distribution networks are suffering a transformation process with the insertion of distributed energy resources, changing from a passive part of the power grid into an active system. Aiming to reduce the challenges for the distribution system operators to keep the power grid operating inside of the quality levels it is possible to propose some ancillary services. Optimum Power flow is an optimization method used to plan the distribution grid operation. Additionally, the distributed energy resources can be modeled on it and ancillary services provisioning can be considered, as proposed in this work. In this way, the objective of the present work is to formulate a Multiperiod Optimum Power Flow (MPOPF) with the insertion of distributed generation, energy storage systems, microgrids, and electric vehicles at the distribution grid. This MPOPF considers the provisioning of ancillary services by the inverters associated with the equipment connected to the main grid. In the formulation, the entire grid is modeled, considering the placement of classic equipment as a voltage regulator and capacitor banks, in addition to modern technologies as DFACTS (Distribution - Flexible AC Transmission System) and four-quadrant inverters. The MPOPF was simulated for several scenarios considering a 90-bus test feeder and a real distribution grid from Curitiba - Brazil. From the results, the MPOPF proved to be highly robust, being able to simulate the grid with all the equipment connected simultaneously, performing the optimal dispatch of active and reactive power, as well as allowing the operation of ancillary services such as voltage support, peak-shaving, and demand-side management.

Optimal Reconfiguration of Distribution Network in Presence of D-STATCOM and Photovoltaic Array using a Metaheuristic Algorithm

In this paper, grasshopper optimization algorithm (GOA) a novel meta-heuristic optimization algorithm is used to solve the network reconfiguration problem in presence of distribution static compensator (D-STATCOM) and photovoltaic (PV) arrays in a distribution system. Here, D-STATCOM acts as distribution flexible ac transmission (D-FACT) device and PV arrays as decentralized or distributed generation (DG). The main purpose of the present research includes power loss minimization and voltage profile (VP) enhancement in radial distribution systems under different loading conditions. The proposed GOA is based on swarming behavior of grasshoppers in nature. The proposed GOA is validated using the standard 33, 69 and 118 – bus test systems. The simulation results proved that the optimal network reconfiguration in presence of D-STATCOM units and PV arrays leads to significant reduction in power loss and enhancement in VP. The results obtained by the proposed GOA are compared with base value and found that the optimal network reconfiguration in presence of D-STATCOM and PV arrays is more beneficial than individual objective optimization. Also, the proposed GOA is more accurate, efficient and reliable in finding optimal solution when compared to existing modified flower pollination algorithm (MFPA), firework algorithm (FWA), fuzzy-based ant colony optimization (ACO) and genetic algorithm (GA).

Elimination of the Impact Produced by DG Units on the Voltage Profile of Distribution Networks

In this paper, an alternative strategy for real-time control of active distribution network voltage is developed, not by controlling the bus voltage as in the various centralized, decentralized, and local approaches presented in literature but rather by only eliminating the impact produced by active and reactive power of distributed generation (DG) units on the voltage of all network nodes and keeping the traditional voltage control systems dealing with the same constraints of passive systems. In literature, voltage deterioration introduced by DGs has been reported as one of the main obstacles for the interconnection of large amounts of DG units to the existing networks. In this paper, the novel control strategy is based on a sensitivity formula developed to calculate the compensation needed for additional distributed flexible AC transmission system (D-FACTS) devices to push and pull the exact reactive power and to eliminate the impact produced by DGs on the network voltage profile. The criteria of the allocation of the var devices and the required network reinforcement are developed in this paper, considering all possible topology structures, and an innovative codification method is introduced to reduce the needed computation time and communication data to actualize the sensitivity coefficients and get the proposed control approach flexible with network topology reconfiguration. The risk of the conflict of the proposed control system with the traditional voltage equipment is reduced due to the fast capability of D-FACTS devices to regulate their reactive power in finer granularity. A case study of two meshed IEEE 15-bus feeders is introduced to compare the voltage behavior with and without the presence of DG units and to evaluate the total system losses. The proposed method could be used for the interconnection of the first generation units in emerging networks, which does not yet have an active voltage control strategy, as it could be used for DG units not able to be connected to existing centralized control systems and it could also be used as the principal voltage control strategy, with the extension for several neighboring units and the preservation of the traditional voltage control systems.