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The use of power converters to regulate voltage and power in electrical power systems has been attracting attention due to the increasing number of research and applications on renewable energy. The integration of these switched devices may cause instability and undesired oscillations depending on the operation conditions, such as when they feed constant power loads (CPLs). Therefore, this paper proposes an analysis of the effect of the power regulation in a multi-stage converter system made by buck-buck cascaded converters, in which the first converter operates as a voltage regulator and the second operates as a power regulator. To support that analysis, the region of attraction (ROA) is estimated based on convex optimization with linear matrix inequalities (LMIs) constraints considering the effect of the power variation and the voltage regulator dynamics. These regions are validated through tests in a simulated environment, showing that the trajectories initiated within those regions remain confined in those despite the CPL power variation disturbance. Finally, a case study for the experimental environment is presented. The power variation test is carried out and shows the efficacy of the stability analysis approach ratifying the simulation results. • In this paper, an LMI-based stability analysis for the microgrid operation point is presented considering the CPL effects. • The region of attraction (ROA) of a microgrid with CPL is estimated to ensure the operational stability conditions. • Analysis of the impact of the voltage regulation speed on the stability of the microgrid with a CPL whose dynamics are previously known. [ABSTRACT FROM AUTHOR]

• Challenges that mass amounts of electric vehicles (EVs) impose to power system operations. • Opportunities of intelligently managing the flexibility of smart charging of EVs are discussed. • Hybrid DERMS concept is proposed as a key tool for safe integration and proper management of emerging distribution grids with high amounts of EVs. • A real-life case study of integrating two large-scale EV charging stations into an existing feeder is presented. Global initiatives are actively progressing to integrate large numbers of electric vehicles (EVs) as part of efforts to electrify and decarbonize the transportation sector. This approach plays a crucial role in addressing global greenhouse emissions and pollution problems. However, mass integration of EVs imposes unprecedented challenges to electrical power systems, especially to their distribution grids. These challenges range from planning issues, where the traditional panning procedures are not adequate for integration of EVs and their charging stations, to operational challenges, where a huge number of dispersed EVs can cause peak load increase, voltage violations, congestions, feeder overloads, etc. Hence, despite the significant importance of maximizing the deployment of EVs, their stochastic integration can give rise to critical challenges in electric power systems, thereby impeding their subsequent expansion. Therefore, in order to properly integrate mass amounts of EVs, without causing technical violations in the electrical power system, intelligent software tools are required, to aid distribution system operators and engineers in the transition to a new era of electrified transportation. In this paper, we argue that novel software solutions called Distributed Energy Resource Management Systems (DERMSs) are a key solution for enabling a safe integration of mass amounts of EVs into emerging distribution grids. Specifically, we introduce a novel Hybrid DERMS framework, as an integration of multiple hierarchical levels of DER management solutions, and propose this solution as a suitable instrument for distribution system operators and grid engineers to safely integrate and manage high volumes of EVs within the grid infrastructure. The hypothesis is validated through a real-life use case for integration and management of high amounts of EVs into an existing distribution grid, using an industrial DERMS solution. Specifically, an in-depth analysis of adding two large charging stations, boasting capacities of 5 MW each, has been performed through all stages of integration, from the planning stage, up to using their flexible output to manage technical constraint violations in real time. The influence of these EV charging stations on both the feeder where they are planned to be integrated, as well as on the entire supply substation, have been analyzed in detail. The resultant findings, especially on successfully managing overloads, peak load increases, as well as voltage violations through intelligent use of aggregated EVs through DERMS, have proven to be notably encouraging, further substantiating the paper's hypothesis. [ABSTRACT FROM AUTHOR]

Electrical power distribution systems are experiencing a deep penetration of renewable energy integration, which is reversing the power flow during some periods and modifying their conventional operation. In this context, the curtailment of renewable distributed generation is needed to consider the electrical limitations of transformers and lines, mainly voltage deviations and power overloads. Multiport converters with energy storage stand as a potential solution for enhancing power flow operation in the distribution system and minimising renewable generation curtailments. This paper presents an optimisation-based methodology to size multiport power converters and a techno-economic comparison to other conventional approaches. The optimisation includes energy storage components and AC power flow constraints. Moreover, specific days are considered to reduce computational requirements. This methodology is evaluated in a case study based on a medium voltage benchmark network from CIGRE to identify the best scenarios where multiport converters can be considered as a potential solution. Results conclude that the multiport converter provides clear advantages and is economically viable specially in scenarios with unbalanced distributed generation in the feeders, where their rated power is around 25 MVA, or if batteries are initially installed in the feeders. [Display omitted] • Optimisation-based methodology to size a multiport converter. • Multiport converter comparison with other solutions to reduce renewable curtailment. • Multiport converter can reduce curtailment the same or more than battery solutions. • High renewable penetration scenarios are feasible to install a multiport converter. [ABSTRACT FROM AUTHOR]

• The study investigates shipboard power systems and distortion evaluation in "EXPERT 3." • The study analyzes distortions in converter-based propulsion systems with variable-frequency drives. • The study confirms MATLAB model accuracy at ship synchronous generators. • The paper introduces a resonance-based compensating device, validated experimentally. • The research investigates methods for managing high-frequency disturbances. This research addresses electromagnetic compatibility and power quality (EMC and PQ) challenges in shipboard electric power systems (SEPS) with dynamic positioning (DP) capabilities, focusing on the self-propelled floating crane (SPFC) "EXPERT 3." Our goal is to enhance methodologies for evaluating power quality indicators (PQI) related to voltage and current waveform distortions, specifically in converter-based propulsion complexes (CBPCs) featuring variable-frequency regulated asynchronous drives (VFDs). We investigate harmonic current and voltage distortions, reactive power generation, and power factor (PF) in SEPS "EXPERT 3″ during the operation of VFDs with conventional semiconductor power converters (SPCs). A refined MATLAB model considers equipment and cable network parameters, validating distortion indicators at ship synchronous generators (SGs). PQI compliance with international maritime standards is verified at the point of common coupling (PCC) for various VFD configurations with pulse width modulated (PWM) SPCs and filter-compensating devices (FCDs). We propose an improved controlled FCD (CFCD) incorporating a resonance filter (RF) and a controllable reactor compensator (CRC). CFCD efficiency in various VFD configurations is experimentally validated. We analyze harmonic distortions of voltage and current, including high-frequency (HF) commutations in VFDs with input thyristor-based rectifiers (TBRs), considering parasitic "phase-hull" capacitances of cable line segments (CLS). Our study examines harmonics in CBPC-based SEPS in two sub-frequency ranges: low-frequency (LF) − 0 to 2 kHz and high-frequency (HF) − 2 kHz to 500 kHz.© 2017 Elsevier Inc. All rights reserved. [ABSTRACT FROM AUTHOR]

• In the context of the Deep Convolutional Neural Networks (CNNs), there are developed and evaluated six novel CNN models for short-term prediction of multi-energy vectors of a novel integrated energy system consisting of three different electric, heat and gas networks and a total of 39 interconnected buildings. • The novel prediction CNN models can be classified function of the type and the number of input and output variables, and type of learning (centralized or distributed). • High correlations between the next and the previous 24 hours building power consumptions are envisaged, and higher correlations than the ones calculated with regard to the weather temperature data (°C) or the solar radiance. • The numerical results obtained for the testing datasets and evaluated in terms of Signal-to-Noise Ratio (SNR) and Normalized Root Mean Square Error (NRMSE), show that the single input variable/single output variable CNN models (CNN_1 and CNN_3), which input/output variables are corresponding to each building and each type of energy consumption, predict the best in comparison to the other models. • For the novel integrated energy system comprising the three distinct networks (electric, heat and gas), it is shown that as the input data is more non-linear and scarce, then it becomes more difficult to predict, and this is to be expected also for any other single or integrated energy system. Forecasting power consumptions of integrated electrical, heat and gas network systems is essential in order to operate more efficiently the multi-energy network system. Multi-energy systems are increasingly seen as a key component of future energy systems, and a valuable source of flexibility, which can significantly contribute to a cleaner and more sustainable integrated energy system. Therefore, there is a stringent need for developing novel and performant models for forecasting multi-energy demands of integrated energy systems, which to account for the different types of interacting energy vectors and of the coupling between them. Previous efforts in demand forecasting focused only on electrical power consumptions or, more recently, on the single heat or gas power consumptions. Therefore, in order to address the multi-energy demand forecasting problem, in this paper six novel prediction models based on Convolutional Neural Networks (CNNs) are developed, for either individual or joint prediction of multi-energy power consumptions: the single input/single output variable CNN model with determining the optimum number of epochs (CNN_1), the multiple input/single output variable CNN model (CNN_2), the single input/single output CNN model with training/validation/testing datasets (CNN_3), the joint prediction CNN model (CNN_4), the multiple-building input/output CNN model (CNN_5) and the federated learning CNN model (CNN_6). All six models are applied in a comprehensive manner on a novel integrated electrical, heat and gas network system, which only recently has started to be used for forecasting. The forecast horizon is short-term (i.e. next half an hour) and all the prediction results are evaluated in terms of the Signal to Noise Ratio (SNR) and the Normalized Root Mean Square Error (NRMSE), while the Mean Absolute Percentage Error (MAPE) is used for comparison purposes with other existent results from literature. The numerical results show that the single input/single output variable CNN model with training/validation/testing datasets (CNN_3) is able to equal the performances of the single input/single output variable CNN model with determining the optimum number of epochs (CNN_1), and to outperform the other four prediction models. The prediction accuracy of the multi-energy networks loads is shown to significantly depend on the level of non-linearity and scarcity existent in the input training dataset(s). Furthermore, this extensive multi-model study reveals that the characteristics (i.e. connections between the different networks, correlations between the different energy vectors) of the considered integrated energy system need to be explored when designing the CNNs prediction models. [ABSTRACT FROM AUTHOR]

• Compared with the traditional flexible interconnection method, the EDC-DN power supply architecture proposed in this paper does not simply use MTDC to achieve feeder interconnection but first optimizes and adds dynamic reactive power compensation devices based on voltage source converters in the context of a high percentage of DG access to the grid, and then the dynamic reactive power compensation equipment between different feeders is interconnected on the DC side by adding additional lines, thus weakening the voltage fluctuation of the grid when DG is connected while achieving closed-loop flexible interconnection between multiple feeders. This can achieve closed-loop flexible interconnection between multiple feeders while weakening the voltage fluctuation of the grid when DG is connected, provide a flexible active power adjustment path for high proportional DG access to DN, and realize power mutual aid between different feeders and network-level bearing of DG. • For the issue of power supply recovery after EDC-DN fault, a comprehensive analysis was conducted on the impact of different fault locations on the power supply recovery process. The collaborative plan between EDC and DAS was first proposed, clarifying the information interaction content between the distribution network automation central station, feeder sub-station, and EDC sub-station during the power supply recovery process. An EDC-DN two-stage power supply restoration architecture considering EDC continuous regulation, combinatorial optimization of interconnection switch and sectionalizing switch is proposed and designed, which fills the technical gap in the integration of EDC and DAS systems. • This paper demonstrates the real-time dynamics of EDC in the EDC-DN power supply restoration process through simulation. The restoration process includes a fast restoration phase based on EDC continuous regulation of power supply, a non-fault section transfer process based on mechanical switch action, and an economically optimal operation phase using an optimal combination of switches to reconfigure the distribution network topology. The current power supply restoration strategy of SOP focuses on the final restoration state of EDC continuous regulation and switch combination rather than on the whole process of power supply restoration. This paper considers the real-time dynamics of the entire EDC-DN power supply restoration process. It fills the technical gap in the current SOP power supply restoration without considering the intermediate process. The flexible interconnection device (FID) enables multiple distribution feeders in closed-loop mode to support a higher proportion of distributed generation (DG) and large-scale new loads connected to the distribution network (DN). Moreover, the closed-loop operation mode based on FIDs provides an effective technology roadmap for high-quality and highly reliable power users, especially the quick restoration of power supply after the failure of DN. This paper proposes a new supply shape in which the multi-terminal DC links are flexibly embedded in the AC DN (EDC-DN) to realize closed-loop operation, achieving lower investment costs than the existing mode that replaces tie switches with soft open points (SOPs). Meanwhile, a two-stage power supply quick recovery control technology is proposed for the EDC-DN, including the fast power supply recovery stage based on EDC and the optimizing restoration stage based on network reconfiguration. Firstly, the role of EDC in the process of power supply restoration of three different faults on AC feeder is analyzed. Secondly, a detailed power supply recovery process is proposed, which is based on a distribution automation system (DAS) and the real-time control capability of EDC. Thirdly, the power supply restoration second stage is implemented, which is based on network reconfiguration with switch combination and EDC continuous variable optimization. Finally, a 58-node DN with an EDC system was constructed using PSCAD/MTDC simulation software to verify the effectiveness of the two-stage strategy for EDC-DN power restoration. © 2017 Elsevier Inc. All rights reserved. [ABSTRACT FROM AUTHOR]

Superconducting fault current limiters (SFCLs) offer an efficient means of limiting fault currents and supporting system reliability. However, they weaken the fault characteristics and reduce the sensitivity of traditional relay protection. The seamless integration of SFCLs with protective relays remains a complex and under-explored area, impeding their widespread industrial adoption. In parallel, current differential protective (CDP) relays are almost the primary protection for all high-voltage electrical equipment and are the cornerstone of global power system security. This paper fills a critical knowledge gap by researching the intricate interaction between resistive superconducting fault current limiters (R-SFCLs) and current differential protective relays. Our investigation commences with a comprehensive mathematical analysis, while researching the influence of R-SFCLs on CDP operation. Subsequently, we conduct a series of comparative experiments using the Matlab Simulink software platform. These tests evaluate the sensitivity, dependability, and security of CDPs in scenarios with and without R-SFCLs. The simulation results not only confirm the accuracy of our analytical framework but also shed light on the multifaceted relationship between R-SFCLs and CDPs. This research contributes to a deeper understanding of how R-SFCLs can be effectively integrated into power systems, offering a roadmap for enhancing grid protection. • Innovative Integration and Mathematical Analysis: This study presents a comprehensive exploration and rigorous mathematical analysis of the challenges in integrating Resistive Superconducting Fault Current Limiters (R-SFCLs) with current differential protective relays (CDPs) in power systems. It revealed the relationship between these components, providing a theoretical foundation for their integration. • Simulink Experiments and Validation of Framework: Extensive comparative experiments conducted using Matlab Simulink offer practical insights into the behavior of R-SFCLs and CDPs under various fault scenarios. The simulation results validate the accuracy of the analytical framework, confirming its effectiveness in addressing key challenges such as fault current limitation and relay sensitivity improvement. • Practical Implications and Contribution to Grid Protection: The study offers practical recommendations for effectively incorporating R-SFCLs into power systems, enhancing grid protection without compromising the reliability and sensitivity of protective relays. It contributes to the field of electrical power and energy systems, providing insights with the potential to influence industrial practices and enhance grid resilience. [ABSTRACT FROM AUTHOR]

The growing penetration of renewable energy resources (RERs) and the ever-increasing implementation of information and communication technologies in smart grids necessitate the utilization of fast and safe operation methods. These schemes should be able to cope with the intermittency of uncertain RERs and fully explore the capabilities of new technologies while considering the vulnerabilities as a result of digitalization. Here, the integrity of the energy and flexibility scheduling and trading heavily depends on the security of the cyber-physical system. Local energy networks (LENs) are introduced to easily incorporate and utilize distributed energy resources, improving electrical power reliability and efficiency. This study develops a cyber-secure energy and flexibility scheduling platform for interconnected local energy networks. Hence, it introduces a novel false data detection and correction method based on the XGBoost machine learning method and investigates the performance of the proposed algorithm in the context of an interconnected local energy network and the corresponding energy and flexibility transactions. In this regard, this paper initially presents a bilevel energy and flexibility scheduling problem for interconnected local energy networks (ILENs) considering cyber-attacks (B L E F S CA ILEN), which tries to satisfy the energy and flexibility requirements of the ILEN guaranteeing a resilient decision against false data injection cyber-attacks. Within the proposed B L E F S CA ILEN a bi-level multi-objective optimization problem is defined where the operator of ILEN optimizes both energy and flexibility trading among LENs in the upper level to maximize its revenue. In the proposed structure, the operator of each LEN is situated at the lower level and tries to minimize the scheduling cost and simultaneously maximize the local flexibility index. Furthermore, in order to evaluate and improve the proposed system's cyber-security, a false data injection attack is constructed using the Gaussian probability distribution function. Herein, the scheduling of ILEN is optimized considering vulnerabilities of electricity consumption data as a consequence of cyber-attack. Finally, the novel XGBoost-assisted deviation bound-based false data detection/correction (XGBFDD) algorithm is suggested to mitigate the above-mentioned cyber-attack and attain near real-world conditions. Simulation results demonstrate that the proposed false data detection/correction strategy exhibits a maximum accuracy of 91.67 precent in mitigating the attack effects. This is because the acquired post-correction results exhibit minor deviations in comparison to the original optimization output that is calculated with the pre-attack consumption data. [ABSTRACT FROM AUTHOR]

• Proposing an new integration method that considers the relationship between simulation time-step and time constants of elementary transfer function blocks (ETFBs), including three integration modes: single-step integration, multiple-step integration, and static approximation. • Giving the implementation of static approximation for ETFBs with small time constants. • Discussing the determination of the threshold values of internal time-step for ETFBs. • Applying the proposed method to an open-source Simulation Toolkit for Electrical Power Systems (STEPS). With the development of renewable energy sources, the scale and complexity of power systems are continuously increasing, resulting in a high requirement for the efficiency of dynamic simulation. Increasing the simulation time-step is a possible measure for the fixed time-step (FTS) method to accelerate the simulation, yet also a potential cause for deteriorating the simulation accuracy. To improve the overall power system dynamic simulation speed without jeopardizing the expected accuracy, this paper proposes a novel Uneven Internal Time-Step Adjustment method based on Trapezoidal integration of elementary transfer function blocks (ETFBs). For ETFBs with different time constants, three different integration modes are defined, including single-step integration, multiple-step integration, and static approximation. Each ETFB can select an appropriate integration mode and adjust its internal time-step, automatically expanding the size of the simulation time-step. Implementation of static approximation for ETFBs with small time constants is given. Discussion on the determination of threshold values of internal time-step is provided, which mainly affect the accuracy of the system. The proposed method is applied to the open-source Simulation Toolkit for Electrical Power Systems (STEPS). Different cases are tested to obtain the maximum simulation time-step that can maintain numerical stability and validate the efficiency and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

• A fully decentralized P2P power market with AC modelled network constraints is proposed. • Network operational security is guaranteed under proposed P2P market mechanism. • User privacy is protected as nodal voltage variables are the only public variables shared among participants. • Extensive numerical simulations are conducted to validate proposed models and solving algorithm. The rapid growth of Distributed Energy Resources (DERs) and demand response in modern power grids calls for decentralized electricity trading mechanisms to effectively induce and coordinate responses from massive DERs and load entities. This paper proposes a fully decentralized peer-to-peer (P2P) distribution electricity trading mechanism backboned by a modified version of Alternating Direction Method of Multipliers (ADMM). Comparing with the state-of-the-art P2P electricity markets, the proposed electricity trading mechanism comprehensively incorporates power network constraints formulated by an alternating current power flow model. In the proposed method, nodal voltages are designed as the only public variables shared among participants. Privacy of each participant is thus sufficiently preserved without exposing the bid data to the others. Meanwhile, the proposed P2P method can also ensure the global optimality of social welfare in electricity transactions. Comprehensive case studies are carried out using the IEEE 33-node distribution system to demonstrate the feasibility and efficiency of proposed P2P electricity trading mechanism. The results indicate that the proposed model can efficiently integrates network constraints in the market clearing process while maintaining computational performance, ensuring stable convergence regardless of distribution system congestion. The proposed P2P electricity market can achieve global maximization of social welfare, with a relative difference of no more than 5.0% compared to the conventional centralized market. Even in worst-case scenarios, the relative difference remains within 7.32%. Meanwhile, the method accurately accounts for network losses, guaranteeing the feasibility of trading plans within the physical network. © 2017 Elsevier Inc. All rights reserved. [ABSTRACT FROM AUTHOR]

• A novel robust pitch controller to enhance the dynamic performance in WT output power/speed in the high wind speed domain. • The proposed controller is independent of the exact model parameters of WTs, easy to implement in practice. • Improving access to the rotor acceleration signal with minimizing system noise amplification. • Giving a rigorous stability demonstration for the closed-loop system. • Developing a refined HIL platform for wind energy conversion systems to validate the approach's effectiveness. The wind energy conversion system is a complex dynamic system with strong nonlinearity, perturbation, and uncertainty. In this paper, a novel optimal pitch control strategy is proposed to improve the ability to stabilize the captured wind energy, so as to realize robust operation in the high-wind-speed condition for wind turbines (WT) subject to unmodeled system disturbances and uncertainty. This control strategy combines three critical techniques: optimal pitch control law determination, disturbance compensation, and acceleration estimation. Among them, the optimal pitch control law is determined by utilizing the Hamilton-Jacobi-Bellman equation, regarding the minimization of the quadratic performance index. The total system uncertain disturbance is compensated by a designed extended state observer, making the pitch control approach almost independent of precise WT model parameters, markedly reinforcing the control system robustness. To prevent system noise amplification from direct differential means in acquiring rotor acceleration, we employ a fast-converging acceleration estimator to obtain the rotor acceleration feedback signal required by the pitch control law. System stability is proved using the Lyapunov theory. The comparative results on the developed hardware-in-the-loop test platform validate the effectiveness of the proposed solution, demonstrating that it provides superior dynamic performance in WT electrical power and speed with reduced fluctuation, overshoot, and regulation time while maintaining robustness against disturbances. [ABSTRACT FROM AUTHOR]

The renewable energy sources based distributed generation is increasingly penetrating into conventional distribution network. Aside from the technical and economical benefits, distributed generation may incapacitate the sensitivity of backup protection devices , which may face partial blindness in grid-connected, even full blindness in islanded mode of operation and during high impedance faults. This paper proposes a novel stratagem to completely plummet the blindness of backup relay by inducing the artificial fault current. A blindness severity index is developed to induce artificial fault current in a controlled manner according to blindness severity. Two methods are proposed. First, the OCR vulnerable to blindness is provided with an auxiliary current transformer, whose output is tuned in conjunction with blindness severity index and merged with main current transformer's output to modulate its secondary current responsible for sensitivity. Second, the microprocessor based relay is used and the time current characteristics is modified by augmenting a new variable named as artificial fault current factor to scale the fault current. As, the current is increased by the TCC modification and no external equipment is added here, so named as AFC. To assure that the AFC is induced only in fault event and to prevent mal-functioning of OCR during normal operation, a simple logic is designed using AND gates to fend off trip signal to circuit breaker. The proposed protection scheme is evaluated on typical distribution feeder in Tianjin, China and IEEE-34 standard test benchmark and results show that the blindness of backup PDs is dwindled in a proficient manner. • Renewable energy sources help to improve electrical power quality, continuity and economic factors. • Deep analysis of renewable energy sources impact on power system protection. • The backup protection lost coordination with primary protection due to fault current variation by renewable energy sources. • Compensation of fault current in backup protection through artificially increasing fault current it in and restoring coordination with backup protection. [ABSTRACT FROM AUTHOR]

• Classification of CPPS testbeds and its design processes are illustrated. • 72 types of CPPS testbeds for sustainable cybersecurity research focus is covered. • Sustainable cybersecurity assessment of CPPS testbeds are proposed. Cyber-physical power systems (CPPS) are interconnected architectures that interact with the physical power system environment by utilizing communication, control, and computing resources. Enterprise, industries, and critical infrastructure rely on CPPS. As a result of their critical importance, they are prime targets for cyberattacks aimed at disrupting their operations. CPPS are mission-critical, attacks on them can have disastrous consequences. CPPS security can be improved by utilizing testbed capabilities to replicate power system operations, discover threats, develop sustainable cybersecurity solutions, and evaluate grid operation in physical fault-induced or cyberattack scenarios. This Part-II paper reviews the CPPS testbeds in the view of the testbed type, targeted research area, CPPS domain, and communication infrastructure with the fusion of physical and cyber systems. Furthermore, this review gives an outline, framework, and application-based assessment of various industry and institutional testbeds. The design process of CPPS testbeds is reviewed first in this paper(Part-II) , followed by description of the classification of CPPS testbeds for cyberattacks and sustainable cybersecurity analysis in CPPS. A brief overview of CPPS testbeds in various academic institutions, R&D laboratories, and industries are provided and each testbed is evaluated using the eleven proposed assessment criteria. Finally, the current issues and future research directions for CPPS testbeds to develop a secure and sustainable electric power grid are discussed. The Part-I paper reviewed the major research areas in CPPS, the importance of cyberattack testbeds, and long-term cybersecurity analysis in CPPS, as well as the NIST framework for CPS, CPPS domains and research areas. [ABSTRACT FROM AUTHOR]

• A comprehensive review of consolidated works on CPPS is presented. • History of cyberattacks in energy sector and need for CPPS testbeds are provided. • NIST framework for deploying CPS in CPPSs are presented with neat illustrations. The integration of advanced Information and Communication Technologies (ICTs) in the conventional electric power grid is evolving into a Cyber-Physical Power System (CPPS). The seamless integration of control, communication, and computing operations allow CPPS to be fully monitored and controlled. Threats, vulnerabilities, and catastrophic attacks will intrude as CPPS monitoring, protection, and control functions advance. For the CPPS to operate safely, securely, and efficiently, sustainable cybersecurity solutions must be developed, and the power grid's reliability and resilience must be maintained even when exposed to unfavorable network conditions. While more distributed and renewable energy sources are connected to the grid, cybersecurity helps to ensure the supply of electricity is sustainable and of high quality. The validation of such sustainable cybersecurity analysis goes beyond the traditional power grid network analysis, which means that the test should integrate the physical and cyber system behavior and respond to the network attacks. To analyze the cybersecurity and cyberattacks in the practical CPPS, comprehensive and realistic CPPS testbeds are needed. The heterogeneous nature of the CPPS concept urges multidisciplinary testbeds with various functions and capabilities to evaluate the new cyber-attacks, vulnerabilities, and threats in CPPS. Using this CPPS testbed framework, the different types of cyber-attack can be detected, and detection algorithm can be evaluated, and helps to enhance the development of sustainable cybersecurity defenses for realistic CPPS environment with the increasingly dense integration of distributed energy resources (DERs). This Part-I paper review the CPPS testbeds in the view of the physical power system layer, sensing layer, communication layer, control layer, application layer, test platforms, and research goals with the fusion of cyber and physical systems. In addition, this review presented an overview, structure, and application-based evaluation of existing testbeds from the industry and institutions. The various research areas in CPPS are reviewed first to show the research trends on different aspects of CPPS which have gained significant attention in the past decade. The necessity of testbeds for cyberattacks and sustainable cybersecurity analysis in CPPS are then described. Finally, the NIST framework for CPS, CPPS domains, and research areas are presented. Further the Part-II paper will review the classification, overview, and assessment of CPPS testbeds. [ABSTRACT FROM AUTHOR]

• A new combination forecasting model is proposed to improve the ultra-short-term forecast accuracy of traction load. • The design concept of the combined model proved to be reasonable. • This model can get the changing trend of the predicted load in different time scales. The ultra-short-term prediction of traction load is a key aspect of electric power control in electrified railroads. In order to provide more accurate traction load prediction data for the control process, this paper designs a combined prediction method combining Discrete Wavelet Transform(DWT), Temporal Convolutional Network (TCN) and Support Vector Regression based on Particle Swarm Optimization(PSO_SVR) for the characteristics of traction load with strong random fluctuation, large jump amplitude and frequent no-load. This method will use DWT model to decompose the traction load with strong random fluctuation and difficult to predict into sub-series with single fluctuation frequency and easy to predict; then, according to the frequency difference of different series, TCN model is selected to predict medium and low frequency series. The SVR model is selected to predict the high frequency sequences. Finally, the prediction results of each sub-sequence are summed to obtain the final prediction. The combined prediction model designed in this paper is used to predict the traction load of traction power supply stations. The experimental results show that the prediction method proposed in this paper has higher prediction accuracy than the existing prediction methods in the current prediction field. [ABSTRACT FROM AUTHOR]

• State-of-the-art of model predictive control (MPC) of microgrids is reviewed. • The first paper in a two-part series on MPC of ac and dc microgrids. • Advantages of MPC for power quality, inertia emulation, transportation electrification. • Experimental comparison of MPC versus linear control for microgrid primary level. • Emerging trends of MPC for autonomous and networked microgrids. • Demonstration of new adaptive MPC of grid-forming converters. The smart-grid has requirements of flexible automation, efficiency, reliability, resiliency and scalability. These are necessitated by the increasing penetration of power-electronics converters that interface distributed renewable energy systems which energize the fast-evolving electric power network. Microgrids (MGs) have been identified as modular grids with the potential to effectively satisfy these characteristics when enhanced with advanced control capabilities. Model predictive control (MPC) facilitates the multivariable control of power electronic systems while accommodating physical constraints without the necessity for a cascaded structure. These features result in fast control dynamic response and good performance for systems involving non-linearities. This paper is a survey of the recent advances in MPC-based converters in MGs. Schemes for the primary control of MG parameters are presented. We also present opportunities for the MPC converter control of autonomous MGs (power quality and inertia enhancement), and transportation electrification. Finally, we demonstrate MPC's capabilities through hardware-in-the-loop (HiL) results for a proposed adaptive MPC scheme for grid-forming converters. [ABSTRACT FROM AUTHOR]

The electric-gas coupling integrated energy system provides an effective way to improve the operation flexibility of IES and the consumption capacity of renewable energy resources. It is very hard to achieve due to the different characteristics between the power and gas system in aspects of control mechanism, network topology and dynamic process. To solve this problem, both a unified model of the transient energy flow and an algorithm for solving this unified model are proposed for the first time in this paper, combining the dynamic modeling of the electric-gas network and the singular perturbation theory. Moreover, in the unified model, an improved model of the gas turbine is designed for capturing the energy interactions of electric-gas networks and meeting the calculation need of multiple time scales simultaneously. Simulation results show that the transient information can be acquired under disturbances of any time by solving the unified model. • Combining the dynamic modeling and perturbation theory, a unified model is proposed. • An improved gas turbine model is proposed to analyze the interaction of networks. • Considering multi-time scale of networks, an integrated transient energy flow algorithm is proposed. [ABSTRACT FROM AUTHOR]

• A multi-microgrids source-load coordinated operation model considering demand response and multiple energy sources is proposed. • The generalized Nash bargaining method is uesd to distribute income of each microgrid, which makes the distribution plan more objective and fair. • A stochastic programming model based on CVaR is established to provide a reference plan for the trade-off between economic benefits and risk level of microgrids. Energy sharing has significant potential in improving system energy utilization, improving economic efficiency, and reducing the impact on power system. The multi-microgrids distributed coordinated operation model is proposed in this paper to provide a reference for the coordinated operation of multi-microgrids considering factors such as electric and heat demand response, multi-energy interaction and uncertainties. First of all, the system operation framework is introduced and the function of each part is analyzed. Secondly, the multi-microgrids cooperative operation model is established, and generalized Nash bargaining method is used to assign total operating cost to ensure the enthusiasm of each microgrid to participate in cooperation. Then, considering the uncertainty of wind power and load in microgrids, a stochastic programming model based on conditional value-at-risk is established. Furthermore, alternate direction multiplier method is used to solve the proposed model to protect the data privacy of each microgrid participating in cooperation. Finally, through the analysis of calculation example, it is verified that the proposed model can reduce the operating cost of each microgrid and maintain enthusiasm of each microgrid for cooperation. In addition, the convergence and accuracy of algorithm are explained, and the influence of different connection modes and the interaction limit of electric and thermal power on the operating cost of microgrids is compared. Moreover, stochastic programming model also provides a reference plan for the trade-off between economic benefits and risk level of multi-microgrids system. [ABSTRACT FROM AUTHOR]

• A risk and traffic based routing algorithm for communication services in electric power network is proposed. • A risk balance strategy with service importance and link availability is proposed. • An efficient traffic balance scheme considering bandwidth and traffic-processing capability is established. • Both the blocking probability and service risk can be decreased simultaneously. There is a trend that traffic unbalance in electric power communication networks is becoming more and more prominent because of the increasing communication demand from the development of the energy Internet. To reduce transmission risk and improve network's reliability and throughput, it is necessary to optimize the routes of communication services with traffic and risk balance strategies. In this paper, a risk and traffic-based routing algorithm for electric power communication services is proposed. We first establish a risk balance strategy with service importance and link availability, then proposes a traffic balance scheme considering bandwidth on links and traffic-processing capability of nodes. Based on traffic characteristics and service risk, the proposed algorithm considers the traffic flow and risk value of the link synthetically and designs a corresponding routing strategy by introducing the balance factor. Numerical results obtained in a real electric power communication environment demonstrate that the algorithm can reduce both the blocking probability and the service risk simultaneously, which achieves the balance between traffic and risk and obtain the optimal performance of electric power communication network. [ABSTRACT FROM AUTHOR]

• History of cyberattacks in energy sector is presented. • Necessity of CPPS testbeds in energy sector are discussed. • A detailed overview on outlook of future CPPS testbeds are provided. • Communication, Control, Computing, and Educational point of view is covered. The Cyber-Physical Power System (CPPS) is a new type of system in which the traditional energy system is integrated into the information network with control systems, communication networks, and computational units. CPPS is the foundation of a long-term transformation of energy management that will fundamentally alter the perspective and application pattern of traditional energy research. The strong interactions between systems in a CPPS introduce new challenges in maintaining high supply security, as new factors can affect the overall security of the power system. Such factors include cybersecurity, the behaviour and constraints of neighbouring energy systems, and the dynamics of interactions between the various systems. Integrating computing, communications, and control at all levels of electrical energy generation, transmission, distribution, utilisation, and storage in CPPS increases vulnerabilities and complicates security. Security studies must reflect the characteristics of the CPPS infrastructure in actual testing environments that support the interfacing of real-world hardware devices. CPPS testbeds are effective in this context because they provide testing capabilities for evaluating the synergistic relationship between physical and virtual components in controlled environments. Security-oriented CPPS testbeds are invaluable for performing cybersecurity and cyberattack analyses, identifying system threats and vulnerabilities in various layers of CPPS, implementing intrusion detection and prevention algorithms, and evaluating the efficacy of mitigation techniques without imposing excessive economic burdens or posing safety risks. This paper provides a comprehensive review of CPPS testbeds from the standpoint of the physical power system layer, cyber system layer, and cyber-physical fusion layer. Following a brief description of the importance of testbeds for cybersecurity research in CPPS, and a brief classification of existing CPPS testbeds for cyberattacks, and cybersecurity analysis in CPPS is presented. A detailed overview of the outlook for future CPPS testbeds in terms of communication, control, computing, and educational perspective is provided. Finally, the work is concluded with future research directions for developing a secure electric power grid. [ABSTRACT FROM AUTHOR]

• Phase-shifting transformers cause under-reach for the distance protection. • Improved phase and ground protection elements are proposed. • The proposed method uses local measurements. • Tap position of the PST is the data that needs sharing with remote relays. Phase-shifting transformers (PSTs) provide an economical solution to control the power flow in the electric grids. However, the PSTs vitiate the conventional protection system applied. This paper studies the impact of the delta-hexagonal phase-shifting transformer on the performance of the distance protection relays for the transmission lines. Modified distance protection formulas are derived for both phase and ground faults. The proposed method uses the local measurements at the relay point and does not require voltage or current measurements from a remote substation. Alternatively, the tap position of the phase-shifting transformer is the data needs to be shared between substations which can be accomplished using a simple communication method. The proposed method is evaluated on a simulated transmission line using MATLAB/Simulink packages. The results show the ability of the proposed method to compensate for the PST effect on the distance protection relays. [ABSTRACT FROM AUTHOR]

• Analysis on unbalanced operation of an improved two-level converter. • Development of 2nd order harmonic suppression controller for improved two level converter. • Reduction of DC voltage and current ripples during unbalanced operation. • Simulation and hardware validation of the proposed controller architecture. An improved two-level converter (I2LC) represents a practical design trade-off between the conventional two-level converter (C2LC) and modular multilevel converter (MMC), in which the MMC like AC and DC fault responses and relative simplicity of C2LC power circuit and control are prioritized. Therefore, this paper presents theoretical analysis, which helps to develop broader understandings of the I2LC, and identification of the needed countermeasures to ensure correct operation during balanced and unbalanced grid conditions. The correctness of the findings and observations drawn from the presented analysis has been validated with the aid of scaled-down simulations and experimentations of the I2LC. Unlike the C2LC, it has been revealed that the I2LC can offer two concurrent operational objectives at system level during unbalanced AC grid conditions, such as balanced output currents and ripple-free DC link current. Further investigation conducted on the performance of the I2LC based two-terminal DC link during asymmetrical AC faults corroborates the theoretical analysis and scaled-down simulation and experimental studies. [ABSTRACT FROM AUTHOR]