Cyber-physical Power System Research Articles

Design and Implementation of a Fully Controllable Cyber-Physical System for Testing Energy Storage Systems

Cyber-physical power systems integrate the various devices, which provide ancillary system services. In this paper, the design and implementation of a fully controllable cyber-physical system are presented. This system simulates the behavior of the real power systems and additionally assures controllable repeatable testing conditions, enabling investigations of energy storage systems. Ancillary system services provided by energy storages are especially crucial in the context of renewable energy sources and electromobility sector development. Credible tests of control strategies, realizing system services, require controllability of test parameters. Such investigations are impossible in a real power system, due to its inherent variability. The novel approach presented in this paper enables the management of power system resources supplied by various producers and ensures flexibility in the realization of assumed scenarios of power system operation. Such an controllable cyber-physical power system constitutes a suitable environment for tests of the effectiveness of ancillary services provided by energy storage systems because the system is independent of inherent variability of the real power system and enables flexible realization of the control algorithms developed for all of the system components (power source, loads, and energy storages). The voltage profile improvement in low-voltage grids has been shown in a case study confirming the applicability of the proposed approach.

Source-Load Coordinated Reserve Allocation Strategy Considering Cyber-Attack Risks

With the developing cyber physical power systems and emerging threat of cyber-attacks, the traditional power services are faced with higher risks of being compromised, as vulnerabilities in cyber infrastructure can be exploited to cause physical damage. Therefore, adjustments need to be made in current control scheme design methods to mitigate the impact of potential attacks on service quality. In this paper, focusing on the service of coordinated source-load participation in primary frequency regulation, a vulnerability analysis is performed with modelling the attack intrusion process, and the risk assessment of the service is made by further modelling the attack impacts on the service’s physical effects. On that basis, the traditional coordinated reserve allocation optimization model is modified and the allocation scheme is corrected according to the cyber-attack impacts. The proposed correction methods are validated through a case study, showing effectiveness in defending against the cyber-attack impacts.

Privacy-preserving big data analytics for cyber-physical systems

Cyber-physical systems (CPS) generate big data collected from combining physical and digital entities, but the challenge of CPS privacy-preservation demands further research to protect CPS sensitive information from unauthorized access. Data mining, perturbation, transformation and encryption are techniques extensively used to preserve private information from disclosure whilst still providing insight, but these are limited in their effectiveness in still allowing high-level analysis. This paper studies the role of big data component analysis for protecting sensitive information from illegal access. The independent component analysis (ICA) technique is applied to transform raw CPS information into a new shape whilst preserving its data utility. The mechanism is evaluated using the power CPS dataset, and the results reveal that the technique is more effective than four other privacy-preservation techniques, obtaining a higher level of privacy protection. In addition, the data utility is tested using three machine learning algorithms to estimate their capability of identifying normal and attack patterns before and after transformation.

Applications of matrix perturbation theory to delayed cyber-physical power system

In this paper, the matrix perturbation theory is introduced to delayed cyber-physical power system (DCPPS) for analyzing the variations of eigenvalues and eigenvectors when small changes are imposed on system parameters and time delays. On one hand, a perturbation-based eigenvalue tracking method is presented to reliably track the targeted interarea oscillation modes so that wide-area damping controllers (WADCs) can be optimally designed to damp them. On the other hand, key factors affecting the accuracy of the solution operator discretization (SOD)-based eigenvalue computation methods for DCPPS are identified by matrix perturbation analysis, which provide a guidance for selecting suitable parameters to precondition the DCPPS. The study results on the 16-generator 68-bus test system validate the effectiveness of the two applications of matrix perturbation theory.

Distributed Finite-Step Iterative Algorithm for Economic Dispatch of Generation

By combining the Newton–Raphson method, the graph discovery algorithm, and the finite-time consensus algorithm, a novel iterative algorithm is proposed in this paper to solve the economic dispatch problem of modern cyber-physical power systems. Fully distributed implementation and finite-time convergence properties distinguish our algorithm from the existing iterative algorithms. Several numerical examples are applied to illustrate our design procedure and validate our proposed algorithm.

Market‐based generator cost functions for power system test cases

Post-restructuring, generators are dispatched using cleared offers in the day-ahead market in the cyber-physical power system. This study proposes a novel method to design generator cost functions to emulate existing market costs for power system test cases. Cost functions on existing test cases are based on fuel costs, which do not represent organised markets. In such markets, the marginal cost of energy is determined by generator offers , not fuel costs. In this work, the authors classify real market generator offers from an independent system operator organised electricity market into generator types . Generator offers are used to develop market-based generator cost functions for use in power system test cases to emulate electricity market behaviour. The proposed method is illustrated using PJM data on eight standard power system test cases from a six bus 240 MW generation case to 2000 buses with 95,000 MW of generation. The marginal price of the proposed market-based generator costs shows on average 280% improvement in accuracy of simulating the day-ahead PJM marginal energy price over existing fuel-cost-based test cases from 2014 to 2016. By using the new market-based generator cost functions, power system simulation studies will better represent actual economic impacts.

Eigen-Analysis of Large Delayed Cyber-Physical Power System by Time Integration-Based Solution Operator Discretization Methods

In this paper, solution operator discretization methods with linear multistep and implicit Runge–Kutta (SOD-LMS/IRK) are presented for efficient eigen-analysis of large delayed cyber-physical power system (DCPPS). First, the time integration-based discretization generates highly structured approximate matrices to the solution operator. Exploitation of the structure ensures low computational burden and high efficiency in solving the matrix-inversion-vector product involved in eigenvalue computation. Second, the implicitly restarted Arnoldi algorithm is employed to compute critical eigenvalue from the solution operator's discretized matrices. SOD-LMS/IRK are endowed with scalability in analyzing very large DCPPS by fully utilizing the inherent sparsity in the augmented system state matrices. The main contribution of the presented SOD-LMS/IRK is the improved efficiency and scalability of existing SOD-PS (pseudo-spectral collocation) and SOD-LMS/IRK. Numerical results on the 16-generator 68-bus test system, a 516-bus, and a 33028-bus real-life large transmission systems validate the effectiveness of the proposed SOD-LMS/IRK.

Swarm‐based automation of electrical power distribution and transmission system support

The increasing amount of distributed energy resources installed in distribution systems imposes new challenges on the operation and control of both distribution and transmission systems. At the same time, most distributed energy resources have the potential to support grid operation, e.g. as reactive power suppliers. To exploit these capabilities, a flexible and scalable control approach capable of dealing with large numbers of heterogeneous components is required. Many approaches are either distribution or transmission oriented and neglect the interests or constraints of the other side. Furthermore, the drawbacks of classical centralised control are often ignored. This study presents SwarmGrid-X, an agent-based control concept that considers the structure, demands and capabilities of components in the distribution system and the power requirements of the transmission system at the point of common coupling. Agents control components autonomously and determine control decisions in a decentralised way. They cooperate in swarms to achieve a common system goal while information and power flow are kept as local as possible. The cooperative nature of SwarmGrid-X transforms the distribution system into a cyber-physical power system. This study explains how SwarmGrid-X enables cyber-physical interactions of components to automate electrical power distribution and support the transmission system.

Self-organized cyber physical power system blockchain architecture and protocol

The state parameters of electrical equipment and power system control parameters are the key data to realize the precise control and cooperative autonomy of a cyber physical power system. The trustworthiness of the data is the primary condition to guarantee the electric power system’s safe and reliable operation. In the traditional centralized data acquisition and management architecture, the security and trustworthiness completely depend on the central main server. A small mistake in the main server will result in data loss, which is irreversible and fatal. Blockchain technique combines the dispersed data with mutual backup and retrieval mechanism, which guarantees that the data cannot be tampered with and forged privately. Based on the blockchain technology, this article proposes a novel data trustworthy acquisition model with high credibility, applied to a self-organized cyber physical power system. In order to overcome the long time-consuming process of building traditional blockchains, a new on-demand data transmission routing algorithm with M/M/1/k queuing model is proposed in this article. Different scales of IEEE standard bus systems are employed as experimental examples to evaluate the algorithm’s performance. The results show that the proposed algorithm can effectively shorten the time consumption of blockchain construction and realize the data trustworthiness of cyber physical power system.

Reliability Assessment of Distribution System Considering Cyber-Induced Dependent Failures in Substation

With the increasing dependencies on Information and Communication Technologies (ICTs), the smart distribution system has similar characteristics to Cyber-Physical System (CPS) and is seen as the so-called “cyber-physical power system” (CPPS). However, the impact of upstream substation is becoming one of the main factors impacting on distribution reliability. To avoid the too optimistic conclusion, the Cyber-Induced Dependent Failures (CDFs) of upstream substation are important to be considered. Thus the cyber security risk brought by both the malfunction of ICT components and the cyber-attack should be taken into account. This paper provided a methodology to incorporate both the two sides of CDFs in upstream substation into cyber-enabled distribution system reliability assessment. In the sequential Monte Carlo simulation (MCS), the game process between attackers and defenders can be modelled as the semi-Markov Chain (SMP), and indices are calculated by the minimal path method. The effects of CDFs are quantified and converted onto the joint feeders, based on the Breadth-First-Search (BFS), as well. Some conclusions for the distribution and substation automation planning have been made and verified by the cyber-extended Roy Billinton Test System (RBTS).

State feedback control aware stochastic transmitting latency in cyber-physical power system

Distributed sensor networks with a great number of sensors realize information gathering, transmitting, and controlling, which will greatly improve the reliability and efficiency of industrial infrastructure systems, such as cyber-physical power system. Cyber-physical power system is one of the heuristic systems tightly coupled by a continuous-time electrical power system and a discrete-time information system. The transmitting latency, packets disorder, or loss will fail system convergence, even unstable under disturbance. This article studies the effect of long latency on cyber-physical power system frequency stability based on network control theory and establishes a heuristic model to express the continuous-time distributed generation system and the discrete-time distributed sensor network. A new state feedback controller is designed based on the stochastic optimal control theory to solve the micro-grid’s frequency stability problem with stochastic latency disturbance. Finally, we have conducted an extensive evaluation study using a real distributed generation micro-grid system. The simulation results show that the new controller reduces the influence of distributed sensor networks transmitting latency on the frequency stability, and the frequency dynamic process in the distributed generation micro-grid has smaller overshoot and obtains faster dynamic response speed.

Set-theoretic detection of data corruption attacks on cyber physical power systems

This paper addresses a set-theoretic method for the detection of data corruption cyber-attacks on the load frequency control loop of a networked power system. The system consists of several interconnected control areas forming a power grid. Based on the overall discrete-time network dynamics, a convex and compact polyhedral robust invariant set is extracted and is used as a set-induced anomaly detector. If the state vector exits the invariant set, then an alarm will be activated, and the potential threat is considered disclosed. The attack scenario used to assess the efficiency of the proposed anomaly detector concerns corrupted frequency sensor measurements transmitted to the automatic generation control unit of a compromised control area. Simulation studies highlight the ability of a set-theoretic approach to disclose persistent and intermittent attack patterns even when they occur at the same time with changes in the power load demand.

A Simplified Co-Simulation Model for Investigating Impacts of Cyber-Contingency on Power System Operations

In cyber-physical power systems, a contingency in the cyber may hamper secure operations of the physical system by changing the information flows. In order to investigate the degree to which a cyber-contingency affects power system operations, we first categorize the potential impacts on the information flow respecting the end-to-end information features in terms of delayed, disordered, dropped, and distorted data. A simplified co-simulation model is then put forth for analyzing the interdependencies between energy and information flows, and obtaining the quantitative relation between information features and power system operations. As the operational characteristics of a cyber system can be entirely captured by all end-to-end information flows, our developed model is hence termed as the information flow based co-simulation model. The information flow based model features in low complexity and covering potential cyber contingencies. Moreover, the quantitative relation can provide requirements for the planning and operation of cyber systems. To illustrate the effectiveness and advantages of the proposed model, a comparison with the commercial communication simulation software OPNET is made. Finally, a wide-area damping control application is taken as an example to demonstrate physical impacts of various cyber-contingencies.

Modeling cascading failures and mitigation strategies in PMU based cyber-physical power systems

This paper presents a model of cascading failures in cyber-physical power systems (CPPSs) based on an improved percolation theory, and then proposes failure mitigation strategies. In this model, the dynamic development of cascading failures is divided into several iteration stages. The power flow in the power grid, along with the data transmission and delay in the cyber layer, is considered in the improved percolation theory. The interaction mechanism between two layers is interpreted as the observability and controllability analysis and data update analysis influencing the node state transformation and security command execution. The resilience indices of the failures reflect the influence of cascading failures on both topological integrity and operational state. The efficacy of the proposed mitigation strategies is validated, including strategies to convert some cyber layer nodes into autonomous nodes and embed unified power flow controller (UPFC) into the physical layer. The results obtained from simulations of cascading failures in a CPPS with increasing initial failure sizes are compared for various scenarios. Dynamic cascading failures can be separated into rapid and slow processes. The interdependencies and gap between the observable and controllable parts of the physical layer with the actual physical network are two fundamental reasons for first-order transition failures. Due to the complexity of the coupled topological and operational relations between the two layers, mitigation strategies should be simultaneously applied in both layers.

A Frequency Control Model for Cyber Physical Power System Considering Demand Response Strategy

Due to the increase of power transmission capacity, once an active power vacancy happens, power systems will face a serious frequency instability problem. With the development of communication technology in cyber physical power system (CPPS), demand response (DR) resources can take the initiative to reduce electricity utilization in order to tackle the system under-frequency challenge. This paper presented a frequency control model for CPPS considering DR strategy to rapidly forecast the effects of DR sources participating in frequency control. The model was verified through a case study as well.

Risk analysis and optimization for communication transmission link interruption in Smart Grid cyber-physical system

Since the communication network of the cyber-physical power system is responsible for communicating information, which guarantees the operation of the cyber-physical power system, researchers focus on the stability of the communication system. This article analyzes the risk of the communication transmission link interruption based on the network structure and characteristics of service transmission and proposes a path optimization method. First, we analyze the impact of link disruption on network structure and service, respectively, and quantify the impact as link interruption risk. According to the risk analysis, we propose an optimization method utilizing the Dijkstra’s algorithm and the genetic algorithm to reconfigure service paths, which aims to minimize time delay and realize the equilibrium of service distribution. Through a particular situation, we calculate the link interruption risk and use the optimization method to configure service path for affected service. The results show that the time delays of the optimized service paths are in the acceptable level as well as the balance index of the service distribution is decreased obviously. The simulation experiment reveals the operability of the risk analysis method and the effectiveness of the path optimization method, which provides a technical reference for risk analysis and service path configuration.

EMS communication routings’ optimisation to enhance power system security considering cyber‐physical interdependence

Energy management system (EMS) is one of the most essential categories of the advanced applications in current cyber-physical power systems. However, because of the tight coupling relationship between a power network and EMS's communication network, a physical break-line fault may be accompanied by a communication line outage, which may result in regional unobservability and uncontrollability. To maximally avoid and eliminate such operation risks, referring to current EMS's `active + standby' communication configuration scheme in China, the authors propose a dynamic routing optimisation mechanism for its standby communication routings, assigning the most reliable communication lines to the most important information. Such optimisation considers two factors: information's significance and the reliability of communication lines. By introducing cyber-physical sensitivity index and path-branch incidence matrix, both factors can be expressed numerically. In the case study, the authors optimise the standby communication routings for a power flow corrective control application under different scenarios. The results verify the effectiveness and superiority of their approach.

Cascading Failure Analysis of Cyber Physical Power System With Multiple Interdependency and Control Threshold

The traditional infrastructure in power system is undergoing a transition to the Smart Grid, in which the communication network and power grid will be integrated into a cyber-physical power system (CPPS). Although the traditional topological analysis reveals the mechanism of cascading failure between two networks, it ignores the control redundancy and standby lines from communication network to power grid. The robustness analysis in CPPS requires a more comprehensive model to analyze failure behavior in reality. Here, we propose a cascading failure model with one-to-multiple interdependency and a relevant theoretical framework to analyze CPPS cascading failure. In consideration of real CPPS, in the proposed model we introduce two robustness factors, the number of dependent links and control threshold, which can better describe the control function from communication nodes to power nodes. The remaining fraction under different initial attacking on high voltage transmission network, small world network, double star network, and the different topological combination of CPPS are analyzed. The results show that the proposed model and robustness factors can better reveal the robustness and the mechanism of two networks in cascading failure.

Security Analysis of Energy Internet With Robust Control Approaches and Defense Design

Power cyber-physical systems (PCPSs) are becoming increasingly complex and diverse, benefitting from all aspects of societal issues. A PCPS is a next-generation system that is a tight conjunction of computation, communication, control, and power systems. The integration of Internet of Things and PCPS generates a novel energy system, the Internet of Energy, which is the future of the energy system. In the same way, the connection of bulk components and the extensive communications among them has brought many insecurities, uncertainties, and security challenges. Thus, a study of the analysis and synthesis of the reliability and security of PCPS is presented in this paper. By considering the unsafe uncertainties, models are formulated for a general cyber-attack, and a double-loop architecture for security defense is designed. According to this framework, security control scenarios are obtained from the character of each kind of cyber-attack. Finally, a separately excited dc motor with uncertainty is used as an example to demonstrate the problem.

Non-smooth Optimization Based WADC Tuning in Large Delayed Cyber-Physical Power System by Interarea Mode Tracking and Gradient Sampling

This paper presents a nonsmooth optimization-based method to optimally tune wide-area damping controllers in large delayed cyber-physical power system (DCPPS). The objective is to maximize the damping ratios of the weakly damped interarea oscillation modes under multiple operating conditions. An eigenvalue-perturbation and receding-tracking method is then proposed to reliably trace the targeted interarea oscillation modes during the optimization process. The Broyden–Fletcher–Goldfarb–Shanno method combined with the gradient sampling technique is employed to efficiently solve the presented nonsmooth, nonconvex, and nonlinear eigenvalue optimization-based problem. The effectiveness of the proposed method is validated by the significantly improved damping of the interarea oscillation modes in the two-area four-machine test system and a real-life large DCPPS.