Biblio

In this paper, a new model-free adaptive sliding mode load frequency control (LFC) scheme is designed for inter-connected power systems, where modeling is difficult and suffers from load change disturbances and denial of service (DoS) attacks. The proposed algorithm only uses real-time I/O data of the power system to achieve a high control performance. Firstly, the dynamic linearization strategy is used to build a data-based model of the power system, and intermittent DoS attacks are modeled by limiting their duration and frequency. Secondly, the model-free adaptive sliding mode control (MFASMC) scheme is designed based on optimization theory and sliding mode reaching law, and its stability is analyzed. Finally, the three-area interconnected power system was selected to test the presented MFASMC scheme. Simulation data shows the effectiveness of the LFC algorithm in this paper.

The paper presents the design of fuzzy logic controller based unified power flow controller (UPFC) to improve power system security performance during steady state as well as fault conditions. Fuzzy interference has been design with two inputs Vref and Vm for the shunt voltage source Converter and two inputs for Series Id, Idref, Iq, Iqref at the series voltage source converter location. The coordination of shunt and series VSC has been achieved by using fuzzy logic controller (FLC). The comparative performance of PI based UPFC and fuzzy based UPFC under abnormal condition has been validated in MATLB domain. The combination of fuzzy with a UPFC is tested on multi machine system in MATLAB domain. The results shows that the power system security enhancement as well as oscillations damping.

This contribution provides the implementation of a digital twin-based assistance system to be used in future control rooms. By applying parameter estimation methods, the dynamic model in the digital twin is an accurate representation of the physical system. Therefore, a dynamic security assessment (DSA) that is highly dependent on a correctly parameterized dynamic model, can give more reliable information to a system operator in the control room. The assistance system is studied on the Cigré TB 536 benchmark system with an obscured set of machine parameters. Through the proposed parameter estimation approach the original parameters could be estimated, changing, and increasing the statement of the DSA in regard to imminent instabilities.

Power system security assessment is a major issue among the fundamental functions needed for the proper power systems operation. In order to perform the security evaluation, the contingency analysis is a key component. However, the dynamic evolution of power systems during the past decades led to the necessity of novel techniques to facilitate this task. In this paper, power systems security is defined based on the N-l contingency analysis. An artificial neural network approach is proposed to ensure the fast evaluation of power systems security. In this regard, the IEEE 14 bus transmission system is used to verify the performance of the proposed model, the results showing high efficiency subject to multiple evaluation metrics.

To ensure dynamic and transient angle and load stability in order to maintain the power system security is a major task of the power Engineer. FACTS Controllers are most effective devices to ensure system security by enhancing the stability margins with reactive power support all over the power system network. The major shunt compensation devices of FACTS are SVC and STATCOM. This article dispenses the modelling and simulation of both the shunt devices viz. Oneis the Static Synchronous Compensator (STATCOM) and the other is Static Var Compensator (SVC). The small signal models of these devices have been derived from the first principles and obtained the transfer function models of weak and strong power systems. The weak power system has the Short Circuit Ratio (SCR) is about less than 3 and that of the strong power system has the SCR of more than 5. The performance of the both weak and strong power systems has been evaluated with time and frequency responses. The dynamic response is obtained with the exact models for both weak and strong systems, subsequently the root locus plots as well as bode plots have been obtained with MATLAB Programs and evaluated the performance of these devices and comparison is made. The Stability margins of both the systems with SVC and STATCOM have been obtained from the bode plots. The dynamic behaviour of the both kinds of power systems have been assessed with time responses of SVC and STATCOM models. All of these results viz. dynamic response, root locus and bode plots proves the superiority of the STATCOM over SVC with indices, viz. peak overshoot, settling time, gain margin and phase margins. The dynamic, steady state performance indices obtained from time response and bode plots proves the superior performance of STATCOM.

Transient stability accidents induced by converter-based resources have been emerging frequently around the world. In this paper, the transient stability of the grid-tied voltage source converter (VSC) system is studied through estimating the basin of attraction (BOA) based on the hyperplane or hypersurface method. Meanwhile, fault critical clearing times are estimated, based on the approximated BOA and numerical fault trajectory. Further, the dynamic security region (DSR), an important index in traditional power systems, is extended to power-electronics-dominated power systems in this paper. The DSR of VSC is defined in the space composed of active current references. Based on the estimated BOA, the single-VSC-infinite-bus system is taken as an example and its DSR is evaluated. Finally, all these analytical results are well verified by several numerical simulations in MATLAB/Simulink.

With the intelligent development of power system, due to the double-layer structure of smart grid and the characteristics of failure propagation across layers, the attack path also changes significantly: from single-layer to multi-layer and from static to dynamic. In response to the shortcomings of the single-layer attack path of traditional attack path identification methods, this paper proposes the idea of cross-layer attack, which integrates the threat propagation mechanism of the information layer and the failure propagation mechanism of the physical layer to establish a forward-backward bi-directional detection model. The model is mainly used to predict possible cross-layer attack paths and evaluate their path generation probabilities to provide theoretical guidance and technical support for defenders. The experimental results show that the method proposed in this paper can well identify the dynamic cross-layer attacks in the smart grid.

This paper presents a study on the "Dynamic Load Altering Attacks" (D-LAAs), their effects on the dynamics of a transmission network, and provides a robust control protection scheme, based on polytopic uncertainties, invariance theory, Lyapunov arguments and graph theory. The proposed algorithm returns an optimal Energy Storage Systems (ESSs) placement, that minimizes the number of ESSs placed in the network, together with the associated control law that can robustly stabilize against D-LAAs. The paper provides a contextualization of the problem and a modelling approach for power networks subject to D-LAAs, suitable for the designed robust control protection scheme. The paper also proposes a reference scenario for the study of the dynamics of the control actions and their effects in different cases. The approach is evaluated by numerical simulations on large networks.

Power system robustness against high-impact low probability events is becoming a major concern. To depict distinct phases of a system response during these disturbances, an irregular polygon model is derived from the conventional trapezoid model and the model is analytically investigated for transmission system performance, based on which resiliency metrics are developed for the same. Furthermore, the system resiliency to windstorms is evaluated on the IEEE reliability test system (RTS) by performing steady-state and dynamic security assessment incorporating protection modelling and corrective action schemes using the Power System Simulator for Engineering (PSS®E) software. Based on the results of steady-state and dynamic analysis, modified resiliency metrics are quantified. Finally, this paper quantifies the interdependency of operational and infrastructure resiliency as they cannot be considered discrete characteristics of the system.

Smart grid is a new generation of grid that inte-grates traditional grid and grid information system, and infor-mation security of smart grid is an extremely important part of the whole grid. The research of trusted computing technology provides new ideas to protect the information security of the power grid. To address the problem of large deviations in the calculation of credible dynamic thresholds due to the existence of characteristics such as self-similarity and traffic bursts in smart grid information collection, a traffic prediction model based on ARMA and Poisson process is proposed. And the Hurst coefficient is determined more accurately using R/S analysis, which finally improves the efficiency and accuracy of the trusted dynamic threshold calculation.

The increasing demand for the interconnected IoT based smart grid is facing threats from cyber-attacks due to inherent vulnerability in the smart grid network. There is a pressing need to evaluate and model these vulnerabilities in the network to avoid cascading failures in power systems. In this paper, we propose and evaluate a vulnerability assessment framework based on attack probability for the protection and security of a smart grid. Several factors were taken into consideration such as the probability of attack, propagation of attack from a parent node to child nodes, effectiveness of basic metering system, Kalman estimation and Advanced Metering Infrastructure (AMI). The IEEE-300 bus smart grid was simulated using MATPOWER to study the effectiveness of the proposed framework by injecting false data injection attacks (FDIA); and studying their propagation. Our results show that the use of severity assessment standards such as Common Vulnerability Scoring System (CVSS), AMI measurements and Kalman estimates were very effective for evaluating the vulnerability assessment of smart grid in the presence of FDIA attack scenarios.

With the rapid development of power Internet of Things (IoT), the ubiquitous edge agents are frequently exposed in a risky environment, where the white-box attacker could steal all the internal information by full observation of dynamic execution of the cryptographic software. In this situation, a new table-based white-box cryptography implementation of SM4 algorithm is proposed to prevent the attacker from extracting the secret key, which hides the encryption and decryption process in obfuscated lookup tables. Aiming to improve the diversity and ambiguity of the lookup tables as well as resist different types of white-box attacks, the random bijective nonlinear mappings are applied as scrambling encodings of the lookup tables. Moreover, in order to make our implementation more practical in the resource-constrained edge IoT agent, elaborate design is proposed to make some tables reusability, leading to less memory occupation while guaranteeing the security. The validity and security of the proposed implementation will be illustrated through several evaluation indicators.

In order to protect the safety of power grid, improve the early warning precision of false data injection. This paper presents a dynamic detection model for false data injection attacks. Based on the characteristics of APT attacks, a model of attack characteristics for trusted regions is constructed. In order to realize the accurate state estimation, unscented Kalman filtering algorithm is used to estimate the state of nonlinear power system and realize dynamic attack detection. Experimental results show that the precision of this method is higher than 90%, which verifies the effectiveness of this paper in attack detection.

The load margin due to voltage instability and small-signal instability can be a valuable measure for the operator of the power system to ensure a continuous and safe supply of electricity. However, if this load margin was calculated without considering system operating requirements, then this margin may not be adequate. This article proposes an algorithm capable of providing the power system load margin considering the requirements of voltage stability, small-signal stability, and operational requirements, as limits of reactive power generation of synchronous generators in dynamic security assessment. Case studies were conducted in the 107-bus reduced order Brazilian system considering a list of contingencies and directions of load growth.

With the construction of power information network, the power grid has built a security protection system based on boundary protection. However, with the continuous advancement of the construction of the power Internet of Things, a large number of power Internet of Things terminals need to connect to the power information network through the public network, which have an impact on the existing security protection system of the power grid. This article analyzes the characteristics of the border protection model commonly used in network security protection. Aiming at the lack of security protection capabilities of this model, a zero-trust security architecture-based power Internet of Things network security protection model is proposed. Finally, this article analyzes and studies the application of zero trust in the power Internet of Things.

The widely adopted dynamic line rating (DLR) mechanism can improve the operation efficiency for industrial and commercial power systems. However, the predicted environmental parameters used in DLR bring great uncertainty to transmission line capacity estimation and may introduce system security risk if over-optimistic estimation is adopted in the operation process, which could affect the electrical safety of industrial and commercial power systems in multiple cases. Therefore, it becomes necessary to establish a system operation security assessment model to reduce the risk and provide operational guidance to enhance electrical safety. This paper aims to solve the electrical safety problems caused by the transmission line under DLR mechanism. An operation security assessment method of transmission lines considering DLR uncertainty is proposed to visualize the safety margin under the given operation strategy and optimally setting transmission line capacity while taking system safety into account. With the help of robust optimization (RO) techniques, the uncertainty is characterized and a risk-averse transmission line rating guidance can be established to determine the safety margin of line capacity for system operation. In this way, the operational security for industrial and commercial power systems can be enhanced by reducing the unsafe conditions while the operational efficiency benefit provided by DLR mechanism still exist.

This work introduces methods that unlock a series of applications for decision trees and neural networks in power system optimization. Capturing constraints that were impossible to capture before in a scalable way, we use decision trees (or neural networks) to extract an accurate representation of the non-convex feasible region which is characterized by both algebraic and differential equations. Applying an exact transformation, we convert the information encoded in the decision trees and the neural networks to linear decision rules that we incorporate as conditional constraints in an optimization problem (MILP or MISOCP). Our approach introduces a framework to unify security considerations with electricity market operations, capturing not only steady-state but also dynamic stability constraints in power system optimization, and has the potential to eliminate redispatching costs, leading to savings of millions of euros per year.

Dynamic security assessment (DSA) is to ensure the power system being operated under a secure condition that can withstand potential contingencies. DSA normally proceeds periodically on a 5 to 15 minutes basis, where the system security condition over a complete time interval is merely determined upon the system snapshot captured at the beginning of the interval. With high wind power penetration, the minute-to-minute variations of wind power can lead to more volatile power system states within a single DSA time interval. This paper investigates the intra-interval variation (IIV) phenomenon in power system online DSA and analyze whether the IIV problem is deserved attention in future DSA research and applications. An IIV-contaminated testing environment based on hierarchical Monte-Carlo simulation is developed to evaluate the practical IIV impacts on power system security and DSA performance. The testing results show increase in system insecurity risk and significant degradation in DSA accuracy in presence of IIV. This result draws attention to the IIV phenomenon in DSA of wind-energy power systems and calls for more robust DSA approach to mitigate the IIV impacts.

Considering the influence of load, This paper proposes a robust analysis method of cyber-physical power system based on the evolution of adjacency matrix. This method uses the load matrix to detect whether the system has overload failure, utilizes the reachable matrix to detect whether the system has unconnected failure, and uses the dependency matrix to reveal the cascading failure mechanism in the system. Finally, analyze the robustness of the cyber-physical power system. The IEEE30 standard node system is taken as an example for simulation experiment, and introduced the connectivity index and the load loss ratio as evaluation indexes. The robustness of the system is evaluated and analyzed by comparing the variation curves of connectivity index and load loss ratio under different tolerance coefficients. The results show that the proposed method is feasible, reduces the complexity of graph-based attack methods, and easy to research and analyze.

An open source software package for performing dynamic RMS simulation of small to medium-sized power systems is presented, written entirely in the Python programming language. The main objective is to facilitate fast prototyping of new wide area monitoring, control and protection applications for the future power system by enabling seamless integration with other tools available for Python in the open source community, e.g. for signal processing, artificial intelligence, communication protocols etc. The focus is thus transparency and expandability rather than computational efficiency and performance.The main purpose of this paper, besides presenting the code and some results, is to share interesting experiences with the power system community, and thus stimulate wider use and further development. Two interesting conclusions at the current stage of development are as follows:First, the simulation code is fast enough to emulate real-time simulation for small and medium-size grids with a time step of 5 ms, and allows for interactive feedback from the user during the simulation. Second, the simulation code can be uploaded to an online Python interpreter, edited, run and shared with anyone with a compatible internet browser. Based on this, we believe that the presented simulation code could be a valuable tool, both for researchers in early stages of prototyping real-time applications, and in the educational setting, for students developing intuition for concepts and phenomena through real-time interaction with a running power system model.

This paper presents some of our first experiences and findings in the ARPA-E project ReNew100, which is to develop an operator support system to enable stable operation of power system with 100% non-synchronous (NS) generation. The key to 100% NS system, as found in many recent studies, is to establish the grid frequency reference using grid-forming (GFM) inverters. In this paper, we demonstrate in Electro-Magnetic-Transient (EMT) simulations, based on Hawai'i big island system with 100% NS capacity, that a system can be operated stably with the help of GFM inverters and appropriate controller parameters for the inverters. The dynamic security optimization (DSO) is introduced for optimizing the inverter control parameters to improve stability of the system towards N-1 contingencies. DSO is verified for five critical N-1 contingencies of big island system identified by Hawaiian Electric. The simulation results show significant stability improvement from DSO. The results in this paper share some insight, and provide a promising solution for operating grid in general with high penetration or 100% of NS generation.

This paper puts forward a dynamic reduction method of renewable energy based on N-1 safety standard of power system, which is suitable for high-voltage distribution network and can reduce the abandoned amount of renewable energy to an ideal level. On the basis of AC sensitivity coefficient, the optimization method of distribution factor suitable for single line or multi-line disconnection is proposed. Finally, taking an actual high-voltage distribution network in Germany as an example, the simulation results show that the proposed method can effectively limit the line load, and can greatly reduce the line load with less RES reduction.

This paper presents a secure reinforcement learning (RL) based control method for unknown linear time-invariant cyber-physical systems (CPSs) that are subjected to compositional attacks such as eavesdropping and covert attack. We consider the attack scenario where the attacker learns about the dynamic model during the exploration phase of the learning conducted by the designer to learn a linear quadratic regulator (LQR), and thereafter, use such information to conduct a covert attack on the dynamic system, which we refer to as doubly learning-based control and attack (DLCA) framework. We propose a dynamic camouflaging based attack-resilient reinforcement learning (ARRL) algorithm which can learn the desired optimal controller for the dynamic system, and at the same time, can inject sufficient misinformation in the estimation of system dynamics by the attacker. The algorithm is accompanied by theoretical guarantees and extensive numerical experiments on a consensus multi-agent system and on a benchmark power grid model.

The correctness of security control system strategy is very important to ensure the stability of power system. Aiming at the problem that the current security control strategy verification method is not enough to match the increasingly complex large power grid, this paper proposes a cyclic verification method of security control system strategy table based on constraints and whole process dynamic simulation. Firstly, the method is improved based on the traditional security control strategy model to make the strategy model meet certain generalization ability; And on the basis of this model, the cyclic dynamic verification of the strategy table is realized based on the constraint conditions and the whole process dynamic simulation, which not only ensures the high accuracy of strategy verification for the security control strategy of complex large power grid, but also ensures that the power system is stable and controllable. Finally, based on a certain regional power system, the optimal verification of strategy table verification experiment is realized. The experimental results show that the average processing time of the proposed method is 10.32s, and it can effectively guarantee the controllability and stability of power grid.

Aiming at the problems of imperfect dynamic verification of power grid security and stability control strategy and high test cost, a reliability test method of power grid security control system based on BP neural network and dynamic group simulation is proposed. Firstly, the fault simulation results of real-time digital simulation system (RTDS) software are taken as the data source, and the dynamic test data are obtained with the help of the existing dispatching data network, wireless virtual private network, global positioning system and other communication resources; Secondly, the important test items are selected through the minimum redundancy maximum correlation algorithm, and the test items are used to form a feature set, and then the BP neural network model is used to predict the test results. Finally, the dynamic remote test platform is tested by the dynamic whole group simulation of the security and stability control system. Compared with the traditional test methods, the proposed method reduces the test cost by more than 50%. Experimental results show that the proposed method can effectively complete the reliability test of power grid security control system based on dynamic group simulation, and reduce the test cost.