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Nowadays, the power system is evolving into a complex cyber physical system with the closely merged physical system, information system, and communication network. It is critical to understand the connections between the power and cyber systems, and the potential impact of cyber vulnerability. In this study, a flexible hardware-in-the-loop (HIL) testbed is proposed for studying the cyber physical power system. By using the flexible interface, various co-simulation systems for different purposes are generated. Based on this testbed, three sample co-simulators are built as proofs. First, a HIL power and communication co-simulator with non-real-time synchronisation mechanism is introduced, and a case of false data injection attack on automation voltage control is studied. Then, a real-time power and communication HIL co-simulator is introduced, and a case considering the impact of communication bit error on the stability control system is simulated to demonstrate the performance of stability control equipment. Finally, another co-simulator for simulating the actual cyber-attack on the stability control system is introduced, and a case of a man-in-the-middle attack on the data link is simulated to demonstrate the impact of cyber-attack on the stability control system.

The ability to control tens of thousands of residential electricity customers in a coordinated manner has the potential to enact system-wide electric load changes, such as reduce congestion and peak demand, among other benefits. To quantify the potential benefits of demand-side management and other power system simulation studies (e.g. home energy management, large-scale residential demand response), synthetic load datasets that accurately characterise the system load are required. This study designs a combined top-down and bottom-up approach for modelling individual residential customers and their individual electric assets, each possessing their own characteristics, using time-varying queueing models. The aggregation of all customer loads created by the queueing models represents a known city-sized load curve to be used in simulation studies. The three presented residential queueing load models use only publicly available data. An open-source Python tool to allow researchers to generate residential load data for their studies is also provided. The simulation results presented consider the ComEd region (utility company from Chicago, IL) and demonstrate the characteristics of the three proposed residential queueing load models, the impact of the choice of model parameters, and scalability performance of the Python tool.

Offers an overview of state of the art passive macromodeling techniques with an emphasis on black-box approaches This book offers coverage of developments in linear macromodeling, with a focus on effective, proven methods. After starting with a definition of the fundamental properties that must characterize models of physical systems, the authors discuss several prominent passive macromodeling algorithms for lumped and distributed systems and compare them under accuracy, efficiency, and robustness standpoints. The book includes chapters with standard background material (such as linear time-invariant circuits and systems, basic discretization of field equations, state-space systems), as well as appendices collecting basic facts from linear algebra, optimization templates, and signals and transforms. The text also covers more technical and advanced topics, intended for the specialist, which may be skipped at first reading. * Provides coverage of black-box passive macromodeling, an approach developed by the authors * Elaborates on main concepts and results in a mathematically precise way using easy-to-understand language * Illustrates macromodeling concepts through dedicated examples * Includes a comprehensive set of end-of-chapter problems and exercises Passive Macromodeling: Theory and Applications serves as a reference for senior or graduate level courses in electrical engineering programs, and to engineers in the fields of numerical modeling, simulation, design, and optimization of electrical/electronic systems. Stefano Grivet-Talocia, PhD, is an Associate Professor of Circuit Theory at the Politecnico di Torino in Turin, Italy, and President of IdemWorks. Dr. Grivet-Talocia is author of over 150 technical papers published in international journals and conference proceedings. He invented several algorithms in the area of passive macromodeling, making them available through IdemWorks. Bjørn Gustavsen, PhD, is a Chief Research Scientist in Energy Systems at SINTEF Energy Research in Trondheim, Norway. More than ten years ago, Dr. Gustavsen developed the original version of the vector fitting method with Prof. Semlyen at the University of Toronto. The vector fitting method is one of the most widespread approaches for model extraction. Dr. Gustavsen is also an IEEE fellow.

Maximum Power Point Tracking (MPPT) methods are used in photovoltaic (PV) systems to continually maximize the PV array output power, which strongly depends on both solar radiation and cell temperature. The PV power oscillations around the maximum power point (MPP) resulting from the conventional methods and complexity of the non-conventional ones are convincing reasons to look for novel MPPT methods. This paper deals with simple Genetic Algorithms (GAs) based MPPT method in order to improve the convergence, rapidity, and accuracy of the PV system. The proposed method can also efficiently track the global MPP, which is very useful for partial shading. At first, a review of the algorithm is given, followed with many test examples; then, a comparison by means Matlab/Simulink© (R2009b) is conducted between the proposed MPPT and, the popular Perturb and Observe (PO) and Incremental Conductance (IC) techniques. The results show clearly the superiority of the proposed controller. Indeed, with the proposed algorithm, oscillations around the MPP are dramatically minimized, a better stability is observed and increase in the output power efficiency is obtained. All these results are experimentally validated by a test bench developed at LIAS laboratory (Poitiers University, Poitiers, France) using real PV panels and a PV emulator which allows one to define a profile insolation model. In addition, the proposed method permits one to perform the test of linearity between the optimal current I mp (current at maximum power) and the short-circuit current I sc , and between the optimal voltage V mp and open-circuit voltage V oc , so the current and voltage factors can be easily obtained with our algorithm.

With the increasing occurrence of extreme weather events, the short circuit and line-breaking faults in transmission lines caused by line galloping have been threatening the security operation of power systems. These faults are also hard to be simulated with current simulation tools. A numerical simulation approach of power systems is presented to simulate the clustered, cascading faults of long-timescale caused by line-galloping events. A simulation framework is constructed in which large numbers of fault scenarios are simulated to reflect the randomness of line galloping. The interaction mechanism between power system operation states and line galloping processes is revealed and simulated by the solution of differences of timescales and parameters. Based on Power System Simulator/Engineering (PSS/E), an extended software package for line galloping simulation is developed with Python, which extends the functionalities of the PSS/E in power system simulation. An example is given to demonstrate the feasibility of the proposed simulation method.

The widespread deployment of distributed energy resources including volatile renewable generation raises the need for detailed distribution network analysis. In many cases, the vast system sizes make the joint analysis of multiple voltage levels computationally impracticable. Consequently, most studies focus on single or selected voltage levels and represent subordinate system portions by conventional static load models. Their parameters are usually identified by simplified aggregation methods that do not consider the effects of the network, i.e., network losses and spatial voltage variations. This approach involves inaccuracies and does not allow for validating compliance with the voltage and current limits inside subordinate system parts that are not explicitly represented in the model. In response to this challenge, this paper extends the static load model by including new parameters, i.e., the boundary voltage limits, and describes the associated component-based parameter identification method. Their combination paves the way for a modular power flow approach, which supports the separate investigation of different system portions without introducing considerable inaccuracies, enabling the systematic, precise, and computationally practicable power flow analysis and validation of voltage and current limit compliance in large distribution systems. The proposed concepts are applied to a synthetic distribution system to facilitate their use and showcase their usefulness.

Many large-scale processes like refineries or power generation plant are constructed using the multi-vendor system and a main co-ordinating engineering contractor. With such a methodology. the key process units are installed complete with local proprietary control systems in place. Re-assessing the so called lower level control loop design or structure is becoming less feasible or desirable. Consequently, future comp~titive gains in large-scale industrial systems will arise from the closer and optimised global integration of the process sub-units. This is one of the inherent commercial themes which motivated the research reported in this monograph. To access the efficiency and feasibility of different large-scale system designs, the traditional tool has been the global steady-state analysis and energy balance. The process industries have many such tools encapsu­ lated as proprietary design software. However, to obtain a vital and critical insight into global process operation a dynamic model and simulation is necessary. Over the last decade, the whole state of the art in system simulation has irrevocably changed. The Graphical User Interface (G UI) and icon based simulation approach is now standard with hardware platforms becoming more and more powerful. This immediately opens the way to some new and advanced large-scale dynamic simulation developments. For example, click-together blocks from standard or specialised libraries of process units are perfectly feasible now.

The increasing complexity of Cyber-Physical Energy Systems, driven by the high penetration of power electronics, advanced control, and digitalization, demands scalable, flexible real-time simulation platforms beyond traditional laboratory-based solutions. This paper investigates the feasibility of deploying open-source real-time power system simulation frameworks on cloud-based infrastructures while meeting real-time computational constraints. An open-source architecture based on DPsim and the VILLAS framework is implemented and evaluated across five computing environments using open-source tools: bare-metal, non-cloud virtual machines, private cloud Kubernetes clusters, public cloud virtual machines, and public cloud Kubernetes clusters. Each environment is carefully configured and tuned using real-time operating systems, CPU isolation, and affinity mechanisms to improve deterministic behavior. Performance and scalability are assessed through a benchmark based on replicated IEEE 9-bus systems, progressively increasing system size, and measuring simulation-timestep execution time. The results show that cloud and cloud-like infrastructures can support soft and, under controlled conditions, firm real-time simulation tasks, although achievable system scale decreases as additional abstraction layers are introduced. The study identifies practical performance limits for each infrastructure and discusses their suitability for different real-time simulation and co-simulation applications. These findings demonstrate that cloud-based real-time simulation can complement traditional digital real-time simulators, enabling scalable and cost-effective CPES experimentation.

Power system simulation is vital for designing and evaluating the performance of electrical system protection and control devices. Although several commercial simulators exist, most are expensive and not open-source code. It is essential to develop educational and research simulators that can prepare students, allow researchers to develop new methodologies, and assist system operators in making decisions. This paper aims to present a computer simulation platform called AnaDyn (dynamic analysis), a non-commercial and open-source platform. AnaDyn is an educational/research platform that allows dynamic (transient stability), quasi-steady-state simulation, modal, and power flow analysis. Short- and long-term studies of voltage, frequency, and rotor angle instability problems can be performed. The main characteristics of AnaDyn are quasi-steady-state simulation, in which the equations are not simplified; easy integration with other tools and toolboxes, since AnaDyn is developing in MATLAB; flexible modeling that allows the inclusion of new devices and controller tests. The detailed modeling of various power system devices, the description of the numerical solution method, and the interface are also presented in this work. The platform is validated by comparing a test system's results with those obtained with Brazil's most popular commercial software. The main potentials of quasi-steady-state simulation are also presented. The results indicate that AnaDyn is efficient for educational and research studies on the stability of short- and long-term electrical systems.

The dynamics of power systems is often analyzed using real-time simulators. The basic requirements of these simulators are the speed of obtaining the results and their accuracy. Known algorithms (backward Euler or trapezoidal rule) used in real-time simulations force the integration time step to be reduced to obtain the appropriate accuracy, which extends the time of obtaining the results. The acceleration of obtaining the results is achieved by using parallel calculations. The paper presents an algorithm for mathematical modeling of the dynamics of linear electrical systems, which works stably with a relatively large integration time step and with accuracy much better than other algorithms widely described in the literature. The algorithm takes into account the possibility of using parallel calculations. The proposed algorithm combines the advantages of known methods used in the analysis of electrical circuits, such as nodal analysis, multi-terminal electrical component theory, and transient states analysis methods. However, the main advantage over other algorithms is the use of the method based on average voltages in the integration step (AVIS method). The attention was focused on the presentation of the scientifically acceptable general principle offered to mathematical modeling of dynamics of linear electrical systems with parallel computations. However, the evidence of its effective application in the analysis of the dynamics of electric power and electromechanical systems was indicated in the works carried out by the team of authors from the Institute of Electrical Engineering UTP University of Science and Technology in Bydgoszcz (Poland).