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In this paper, a set of conditions for defining output functions is derived such that a system can become passive by static state feedback. A key feature of the proposed set of conditions is that several output functions that satisfy these conditions can be defined without any transformation into a normal form or any need of linearisation of the system. In essence, this paper introduces a new connection between the Lyapunov stability concept and minimum phase property which is indeed a necessary condition of feedback passivity. [ABSTRACT FROM AUTHOR]

This paper presents a methodology and set of validation criteria for the systematic creation of synthetic power system test cases. The synthesized grids do not correspond to any real grid and are, thus, free from confidentiality requirements. The cases are built to match statistical characteristics found in actual power grids. First, substations are geographically placed on a selected territory, synthesized from public information about the underlying population and generation plants. A clustering technique is employed, which ensures the synthetic substations meet realistic proportions of load and generation, among other constraints. Next, a network of transmission lines is added. This paper describes several structural statistics to be used in characterizing real power system networks, including connectivity, Delaunay triangulation overlap, dc power flow analysis, and line intersection rate. The paper presents a methodology to generate synthetic line topologies with realistic parameters that satisfy these criteria. Then, the test cases can be augmented with additional complexities to build large, realistic cases. The methodology is illustrated in building a 2000 bus public test case that meets the criteria specified. [ABSTRACT FROM AUTHOR]

Optimal power flow (OPF) programs must be able to provide sound operating points for power systems under different conditions while meeting a large number of constraints. These constraints, however, either due to the operating conditions at hand or by construction, can have linearly dependent gradients, thus defining ill-behaved feasible sets. This paper analyzes the use of an alternative set of optimality conditions, derived from the Fritz-John (FJ) conditions, to represent OPF solutions in such critical cases. Results are presented for realistic test systems. [ABSTRACT FROM PUBLISHER]

This paper presents a new method for studying electromechanical transients in power systems using three phase, combined transmission and distribution models (hybrid models). The methodology models individual phases of an electric network and associated unbalance in load and generation. Therefore, the impacts of load unbalance, single phase distributed generation and line impedance unbalance on electromechanical transients can be studied without using electromagnetic transient simulation (EMTP) programs. The implementation of this methodology in software is called the Three Phase Dynamics Analyzer (TPDA). Case studies included in the paper demonstrate the accuracy of TPDA and its ability to simulate electromechanical transients in hybrid models. TPDA has the potential for providing electric utilities and power system planners with more accurate assessment of system stability than traditional dynamic simulation software that assume balanced network topology. [ABSTRACT FROM PUBLISHER]

This paper presents a general framework for the doubly fed induction generator connected to a complex power system in order to facilitate the dynamic estimation of its states using noisy PMU measurements. State estimation considering the whole power system with the occurrence of electric faults is performed using the Unscented Kalman Filter (UKF) with a bad data detection scheme. Such a state estimation scheme for a DFIG is important because not all dynamic states of a DFIG are easily measurable. Furthermore, the proposed state estimation technique is decentralized and the network topology of the entire power system is taken into consideration in the estimation process. In order to enhance the error tolerance and self-correction of the power system, bad data detection technique is implemented. A performance comparison with Extended Kalman Filter (EKF) is also discussed. [ABSTRACT FROM PUBLISHER]

The multiarea Thévenin equivalent (MATE) solution framework is used in this work to combine several subsystems, which are solved using different multiple and non-multiple time-step sizes. In the proposed asynchronous MATE-multirate (A-MATE-multirate) solution, each subsystem is solved with the integration step size that is most adequate for its own internal time constants. This paper relaxes the requirement of previous multirate techniques, in which the solution time-steps of different systems must be multiples or submultiples of each other. To this end, this paper introduces the concept of asynchronous updating, in which each subsystem is updated according to its own internal clock. This updating process is performed in a closed-form solution, with external subsystems represented by their interpolated Thévenin equivalents. Interpolation with future values without using extrapolation is possible in the electromagnetic transients program solution because the history source for future time-steps is calculated at previous time-steps. The exchange of information between subsystems is conditioned using filters to avoid numerical problems during the decimation of the fast subsystems and the interpolation of the slow subsystems. The effectiveness of the proposed methodology is verified with examples using multiple and non-multiple time-step sizes. [ABSTRACT FROM AUTHOR]

Synthetic power systems that imitate functional and statistical characteristics of the actual grid have been developed to promote researchers’ access to public system models. Developing time series to represent different operating conditions of these synthetic systems will expand the potential of synthetic power systems applications. This paper proposes a methodology to create synthetic time series of bus-level load using publicly available data. Comprehensive validation metrics are provided to assure that the quality of synthetic time series data is sufficiently realistic. This paper also includes an example application in which the methodology is used to construct load scenarios for a 10,000-bus synthetic case. [ABSTRACT FROM AUTHOR]

Nowadays, with the increasingly prominent contradiction between environment and development, renewable energy technology has received extensive attention. However, due to natural fluctuation, there are many challenges in safety and stationarity in an electric power system with a large-scale portion of renewable energy. Meanwhile, the conventional electric power system in which the power supply follows the load change paradigm is gradually broken. Thanks to advanced information and communication technology, energy storage technology, and automatic control technology, the power supply, grid, load, and energy storage interactive electric power system regulation paradigm came into being. A virtual power plant (VPP) is a concrete realization of this regulation paradigm. In this paper, based on the characteristics of VPP service requirements, we propose a data-driven method to estimate and predict the network latency. First, we investigate and summarize the characteristics of a VPP participating in various auxiliary services and their demand for communication networks. Second, the practical implementation of a VPP network architecture, which combines the local network and the backhaul network, is presented based on a secure access gateway and VPP monitoring and scheduling platform for flexible resource aggregation and regulation. Then, based on a delay probe, a network latency acquisition method is proposed for a public backhaul network. Finally, a data-driven network latency processing method is proposed to support the VPP's participation in different communication requirements of auxiliary services. [ABSTRACT FROM AUTHOR]

With the promotion of carbon peaking and carbon neutrality goals and the construction of renewable-dominated electric power systems, renewable energy will become the main power source of power systems in China. Therefore, ensuring frequency stability and system security will emerge as pivotal challenges in the future development process. Created by combining a Li-ion battery and a supercapacitor, a hybrid energy storage system (HESS), which possesses robust power regulation capabilities and rapid response capabilities, holds promise for supporting the frequency stability of power systems. In this context, the assessment of the economic viability of HESSs providing multitype frequency response services becomes a critical factor in their deployment and promotion. In this paper, an economic analysis approach for a Li-ion battery–supercapacitor HESS towards a multitype frequency response is presented. First, a multitype frequency response-oriented operational mode for the HESS is designed, outlining the roles and functions of the Li-ion battery and the supercapacitor in delivering distinct services. Moreover, building upon the analysis of the power trajectory of Li-ion batteries, a lifetime model for the HESS is proposed based on the rain-flow counting method. Furthermore, considering the competitive landscape for the HESS in the frequency regulation ancillary service market, a full lifecycle economic assessment model is proposed. Finally, case studies on actual power system frequency data and PJM market data are performed to verify the effectiveness of the proposed method, and the simulation results confirm that the HESS exhibits robust performance and a competitive advantage in providing multitype frequency response services. Additionally, it demonstrates commendable economic benefits, establishing its potential as a valuable contributor to frequency response services. [ABSTRACT FROM AUTHOR]

In a modern and technological world that has a great demand for energy, a versatile energy market, and a renewed electric infrastructure capable of expanding the electric power system under the premise of universal access to electricity, that seeks to minimize the effects of climate change, and that requires an improvement in its reliability, security, and resilience, microgrids are born as one of the systems that have the potential to supply each of these requirements in order to guarantee an adequate decarbonization, decentralization, digitalization, diversification, and democratization of the future grid. However, the integration of microgrids into the electric power system will generate impacts that are currently under study. This paper identifies and analyzes the technical impacts in the electric power system due to the implementation of microgrids, based on what has been recognized in the literature, so that those who have purposes of installation, creation, innovation, and research of microgrids, such as grid operators, technology providers, companies, and researchers, can establish criteria and indicators through which the feasibility of projects involving microgrids can be determined. The concept, importance, and characteristics of microgrids are given, along with a technical justification of the impacts. In addition, technical impacts on some study cases of real microgrids around the globe are identified. Finally, an analysis of the identified technical impacts is offered, and conclusions are drawn. [ABSTRACT FROM AUTHOR]

Reactive power management (RPM) in electric power systems is usually based on a rule‐based control derived from the transmission system operator's (TSO) experience. This approach faces challenges as the number of decisions and the complexity of the system operation is increasing. With the increasing generation from renewables and the evolution of electricity markets, the available resources must be optimally utilized. This paper compares the optimization‐based approach (OBA) and the experience‐based expert approach (EBA) for RPM. The OBA is based on security‐constrained optimization with minimum redispatch cost as the objective function for a reference contingency. In contrast, the EBA's actions are based on the system operator's experience. Comparison is made in terms of the generator redispatch cost, active and reactive power redispatch volume, active power losses, nodal voltages, and the number of actions to ensure secure operation. The analysis using a reduced model of an actual transmission system shows that OBA is more beneficial than EBA, with up to 22% and 42% reduction in redispatch cost and volume, respectively. Moreover, the control decisions from both approaches are seen to be similar. This study aims to show the usefulness of the OBA and motivate TSOs to move towards optimization‐based reactive power management. [ABSTRACT FROM AUTHOR]

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Factors such as persistent demand growth, expansion project delays, and the rising adoption of renewable energy sources highlight the importance of operating power systems within safe operational margins. The optimal reactive power dispatch (ORPD) seeks to find operating points that allow greater flexibility in reactive power reserves, thus ensuring the safe operation of power systems. The main contribution of this paper is a multi-area and multi-period ORPD (MA-MP-ORPD) model, which seeks the minimization of the voltage deviation in pilot nodes, the reactive power deviation of shunt elements, and the total reactive power generated, all taking into account the operational constraints for each area. The MA-MP-ORPD was implemented in the Python programming language using the Pyomo library; furthermore, the BONMIN solver was employed to solve this mixed-integer nonlinear programming problem. The problem was formulated from the standpoint of the system operator; therefore, it minimizes the variations of critical variables from the desired operative values; furthermore, the number of maneuvers of the reactive compensation elements was also minimized to preserve their lifetimes. The results obtained on IEEE test systems of 39 and 57 buses validated its applicability and effectiveness. The proposed approach allowed obtaining increases in the reactive power reserves of up to 59% and 62% for the 39- and 57-bus test systems, respectively, while ensuring acceptable operation values of the critical variables. [ABSTRACT FROM AUTHOR]

The unprecedented transformation of contemporary power systems, mainly evidenced by the high penetration of renewable energy generation and the shift from passive to active, bi-directional smart grids, has put an extraordinary burden on power system operation and control. The uncertainties created by the two aforementioned factors greatly propel the necessity of more accurate and robust system monitoring. Concurrently, an ever-increasing amount of electronics-based power generation makes frequency stability a major challenge to power system operation and control due to the vastly diminishing system inertia. As a crucial part of system control, frequency monitoring is utilized to identify potential stability issues and eventually prevent cascading power outages and blackouts. This paper proposes a dynamic state estimation (DSE) methodology that employs deep learning (DL) techniques based on feed-forward artificial neural networks (ANN) to accurately predict power system disturbances in terms of frequency disturbance events (FDE) caused by line outages, load/generation tripping events, and various types of faults. The proposed methodology was tested on a test grid model with high penetration of renewable generation, using an open-source data generator. It was concluded that DL-based DSE can be successfully utilized in the FDE detection process to improve frequency monitoring and control, and to maintain optimal performance, stability, and security of power systems. [ABSTRACT FROM AUTHOR]

The ankle exoskeleton is an auxiliary device designed to restore human independence. This paper proposes the development and initial testing of a passive ankle exoskeleton designed for movements with dorsal and plantar flexion. The device also includes a new mechanism design with four electric linear actuators, and the shank platform and the foot platform are connected to the ball by a swivel joint. Mechanical tests demonstrate the ability of the prototype to function adequately in the natural range of the ankle joint. Preliminary results show that the exoskeleton can reduce the activation of the calf muscles on the limb on which the device is installed. In the investigation of a passive ankle joint exoskeleton designed for movements with dorsal and plantar flexion, numerical test results can be highlighted by focusing on parameters such as speed, acceleration, and translation moment. These measurements provide valuable information about the performance and effectiveness of the exoskeleton. By focusing on these numerical test results, it is possible to obtain an idea of the performance of the exoskeleton, understand its impact on the movements of the ankle joint, and make informed decisions for further improvements or optimization of the design. [ABSTRACT FROM AUTHOR]

The electric power system is undergoing a significant transformation driven by advances in digital technologies. This article provides a comprehensive and detailed analysis of recent advances and the future outlook of electric power systems, with a particular emphasis on the impacts of digital transformation. By conducting a thorough examination of over 150 up-to-date research papers, the study highlights the key developments shaping the future of the field, such as the integration of renewable energy, distributed generation, microgrids, and smart grids. The analysis includes comparison tables and SWOT analysis for each technology, offering insights into their strengths, weaknesses, opportunities, and threats. The study also provides a historical and conceptual overview of digital transformation in electric power systems, exploring recent digital technologies such as cloud computing, the Internet of Things, blockchain, digital twins, and their impact on the electric power system. The article concludes by addressing the barriers and challenges in this transformation. Overall, this research offers a comprehensive and up-to-date analysis of the current state and future outlook of electric power systems, providing valuable insights for researchers, practitioners, and policymakers. [ABSTRACT FROM AUTHOR]

Based on a case study, two main problems were addressed: the data analysis of temperature sensors and current. 36433506 4 Govind K.R.A., Mahapatra S. Frequency Domain Specifications Based Robust Decentralized PI/PID Control Algorithm for Benchmark Variable-Area Coupled Tank Systems. The adaptive improved sliding mode controller is designed and used to construct an optimization model of the supply chain system under unexpected events. [Extracted from the article]

Decaying DC (DDC) offset current mitigation is a vital challenge in phasor current estimation since it causes malfunctioning/maloperation of measurements and protection systems. Due to the inductive nature of electric power systems, the current during fault inception cannot change immediately and it contains a transient oscillation. The oscillatory component acts similar to an exponential DC signal and its characteristics depend on the X/R ratio of the system, fault location, and fault impedance. DDC attenuates accurate phasor estimation, which is pivotal in protection systems. Therefore, the DDC must be eliminated from the fault current (FC) signal. This paper presents an overview of DDC mitigation methods by considering different groups—before the discrete Fourier transform (pre-DFT), after the discrete Fourier transform (post-DFT), the least square-based (LS-based), and other methods. Through a comprehensive review of the existing schemes, the effects of noise, harmonics, multiple DDCs (MDDCs), and off-nominal frequency (ONF) on the accuracy of DDC estimation, were recognized. A detailed discussion (along with some simulation results) are presented to address the main advantages/disadvantages of the past studies. Finally, this paper presents a few suggestions for future researchers, for researchers to investigate more implementable solutions in this field. [ABSTRACT FROM AUTHOR]

The islanded mode of operation of an electric power system (EPS) that has generation capabilities provided by conventional thermal power plants, by a pumped-storage power station, or from an interlink with a neighboring electric power system through an HVDC BtB converter is addressed in this paper. The risk for electrical power systems to fall into an islanded mode has recently grown, as it is caused not just by technical reasons but by a geopolitical situation as well. The current strains demand the close consideration of problems related to EPS operation in an islanded mode. This paper considers several. The research covers the following issues. The response of the islanded system to a sudden and spasmodic load change is analyzed in cases when the system deals with the disturbance with internal resources alone and with the help of an HVDC BtB converter's frequency control functionality. Analysis of the impact of the settings of the HVDC BtB converter on the system's response to disturbances is presented and the optimal set of parameters found. The impact of the system's extended inertia on the system's response is evaluated by using an additional unit of the pumped-storage power station in synchronous condenser mode. Transients in the system when switching a unit operating in synchronous condenser mode on and off are analyzed. The capability of the system to withstand major disturbances, such as disconnection of the pumped-storage power station's unit operating in a pump mode and disconnection of the HVDC BtB converter in emergency modes, if a situation demands, is researched. The research is carried out by numerical simulations using PSS Sincal Electricity Basic software. Updated operating parameters of the isolated power system and the LCC HVDC BtB converter, as well as frequency control automation provided by ABB, were used in the simulations. [ABSTRACT FROM AUTHOR]

This paper presents an advanced methodology for restoration of the electric power transmission system after its partial or complete failure. This load-optimized restoration is dependent on sectioning of the transmission system based on artificial neural networks. The proposed methodology and the underlying algorithm consider the transmission system operation state just before the fallout and, based on this state, calculate the power grid parameters and suggest the methodology for system restoration for each individual interconnection area. The novel methodology proposes an optimization objective function as a maximum load recovery under a set of constraints. The grid is analyzed using a large amount of data, which results in an adequate number of training data for artificial neural networks. Once the artificial neural network is trained, it provides an almost instantaneous network recovery plan scheme by defining the direct switching order. [ABSTRACT FROM AUTHOR]

Conservation through voltage reduction (CVR) aims to reduce the peak load and energy savings in electric power systems and is being deployed at various utilities. The effectiveness of the CVR program depends on the load characteristics, i.e., the sensitivity of the load to voltage variation, and voltage regulation device settings. In the current literature, there is a lack of discussion on the CVR factor calculation using different measurements, and there is a lack of method for active power loss estimation using substation measurements. This paper provides insights into CVR factor calculation based on the measurements captured at the substation and those at the load location. This paper also proposes a new method based on curve fitting and artificial neural network to estimate the active power loss using input active power, input reactive power and input voltage at the substation. The CVR comparison study conducted in this paper helps in understanding the factors affecting CVR factor and may provide guidance in CVR implementation and impact assessment. The proposed loss estimation method sheds light on the impacts of CVR in terms of load and loss reduction. The results based on simulation studies using the IEEE 13-bus and 34-bus systems are reported in this paper, noting that the proposed methods are applicable to larger systems, as long as the required measurements at the substation are available. Future research includes testing and refining the methods using large IEEE and utility distribution systems and considering the stochastic nature of the CVR factor with changing load and voltage regulator control schemes. [ABSTRACT FROM AUTHOR]

In the electricity industry, load forecasting is one of the most important tasks in planning, distribution, operations management, and providing appropriate solutions for power systems. Power consumption plays an important role in the planning and optimal use of power systems. With the existing technology, it is not yet possible to store this energy in large dimensions, so accurate forecasting of consumption can play an important role in the economic use of electricity. The amount of electrical charge consumption is not constant but is complex and nonlinearly a function of several parameters. Due to the variable amount of electrical charge consumption, power companies must anticipate it in different timelines of the information needed to make decisions. In this article, a new method is presented according to the efficiency of short-term load prediction, which can be from the next few hours to a week or a few weeks. Due to the efficiency of evolutionary methods in setting the parameters of forecasting methods, in this paper, the SALP optimization algorithm is used as an algorithm with high convergence accuracy to improve the neural network of the radial base function. Therefore, in this paper, a comparison between the method of improving the neural network of the radial base function with the SALP optimization algorithm for short-term load prediction by considering meteorological factors with other combined methods of optimization algorithms is shown. The results of comparison between predictions in the proposed model (improved neural network with SALP algorithm) compared to other combined methods of load prediction, show that the proposed neural network method improves the radial base function with SALP (RBF-SSA) better. Other combined methods improve the results. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to propose a condition-based opportunistic maintenance policy considering economic dependence for a series–parallel hybrid system with a K-out-of-N redundant structure, where a single component in series is denoted as subsystem1, and K-out-of-N redundant structure is denoted as subsystem2. Design/methodology/approach: Based on the theory of Residual Useful Life (RUL), inspection points are determined, and then different maintenance actions are adopted in the purpose of minimizing the cost rate. Both perfect and imperfect maintenance actions are carried out for subsystem1. More significantly, regarding economic dependence, condition-based opportunistic maintenance is designed for the series–parallel hybrid system: preemptive maintenance for subsystem1, and both preemptive and postponed maintenance for subsystem2. Findings: The sensitivity analysis indicates that the proposed policy outperforms two classical maintenance policies, incurring the lowest total cost rate under the context of both heterogeneous and quasi-homogeneous K-out-of-N subsystems. Practical implications: This model can be applied in series–parallel systems with redundant structures that are widely used in power transmission systems in electric power plants, manufacturing systems in textile factories and sewerage systems. Considering inconvenience and high cost incurred in the inspection of hybrid systems, this model helps production managers better maintain these systems. Originality/value: In maintenance literature, much attention has been received in repairing strategies on hybrid systems with economic dependence considering preemptive maintenance. Limited work has considered postponed maintenance. However, this paper uses both condition-based preemptive and postponed maintenance on the issue of economic dependence bringing opportunities for grouping maintenance activities for a series–parallel hybrid system. [ABSTRACT FROM AUTHOR]

The penetration of renewable-based converter-interfaced generation and flexible alternating current transmission systems significantly changes properties and dynamic characteristics of modern electric power systems, which leads to the need to take measures to ensure security of their operation. These measures may consist in using the capabilities of new penetrated units or in adapting conventional means. Such adaptation consists in reconfiguration of control systems, development of new systems or approaches to settings determination, which include tuning of automatic voltage regulators with power system stabilizers of conventional synchronous generation. This paper proposes a new approach to tuning of automatic voltage regulators, based on the use of the most complete and reliable information about processes in modern power systems. This approach allows to get settings that are most adequate to practical conditions of operation as part of power systems. For this purpose, the hybrid real-time power system simulator and concept of hybrid modeling are used, and within this paper, and the hybrid modeling tools necessary for the tuning process have been developed. The result of the study is a comprehensive assessment of the reliability of the simulation results obtained using the developed tools, which allows to conclude about the possibility of their application. [ABSTRACT FROM AUTHOR]

Fair distribution of generated power has a significant impact on the performance of the power system. Many methods have been proposed for the safe and secure operation of power systems under the uncertainties of distributed generators and system load. In this paper, we present an optimal power distribution algorithm for distributed generators against uncertainties and load changes of direct-current and alternating-current transmission systems. In this optimal algorithm, considering the stable-state constraints for all uncertainties is performed. In order to establish these constraints at the lowest cost, the adaptive droop coefficients are employed to optimize the power sharing, reloading and modifying the power coefficient of each distributed generator in the power system. Simulation results show the efficiency of the proposed method to improve the performance of the system and reduce the total cost. The voltage/power deviation from reference value in the proposed method is about 1-1.5% where in the conventional droop control, it is more than 2-3%. In addition, in the same uncertainty of the load/distributed generator power in the test system, proposed method requires 20% less power redistribution compared to the conventional droop method. Also, total cost increasing (due to uncertainty increasing) in the conventional droop method is higher than the proposed method (about 10-15%) which shows the robustness of the suggested method against uncertainty changes. [ABSTRACT FROM AUTHOR]

This paper proposes a new strategy for modeling predictability uncertainty in a stochastic context for decision making within a Virtual Power Plant (VPP). Modeling variable renewable energy generation is an essential step for effective VPP planning and operation. However, it is also a challenging task due to the uncertain nature of its sources. Therefore, developing tools to effectively predict these uncertainties is essential for the optimal participation of VPPs in the electricity market. The purpose of this paper is to present a novel method to model the uncertainties associated with energy dispatching in a VPP using the Unscented Transform (UT) method. The proposed algorithm minimizes the risks associated with the VPP operation in a computationally efficient and simple manner, and can be used in real-time on a power system. The proposed framework was evaluated based on an Electric Power System (EPS) model with historical data. Case studies have been performed to demonstrate the effectiveness of the proposed framework in minimizing power demand and renewable-energy-forecasting uncertainty for a VPP. [ABSTRACT FROM AUTHOR]

Under the background of high-energy penetration of new energy into the power grid, this paper takes the ancillary service capability of photovoltaic energy integrated into the grid as the starting point and builds a photovoltaic system reactive power service impact evaluation model on the grid energy efficiency. This is based on the multi-temporal and spatial scale operation mode, in order to study the supporting principles of photovoltaic system reactive power services on the energy efficiency of grid operation and the law of influence on system energy efficiency changes. In this way, the space for power system energy efficiency improvement and the reactive power service market value of renewable energy are explored to improve the renewable energy auxiliary services participation in the theoretical system of electric power spot market transactions. The research conclusions can provide a decision-making reference for system dynamic energy efficiency management and can assist relevant market entities to make optimal decisions in spot market transactions, and provide empirical data for improving the theory of renewable energy participation in auxiliary service market transactions. [ABSTRACT FROM AUTHOR]

This article classifies, describes, and critically compares different compensation schemes, converter topologies, control methods, and coil structures of wireless power transfer systems for electric vehicle battery charging, focusing on inductive power transfer. It outlines a path from the conception of the technology to the modern and cutting edge of the technology. First, the base principles of inductive coupling power transfer are supplied to give an appreciation for the operation and design of the systems. Then, compensation topologies and soft-switching techniques are introduced. Reimagined converter layouts that deviate from the typical power electronics topologies are introduced. Control methods are detailed alongside topologies, and the generalities of control are also included. The paper then addresses other essential aspects of wireless power transfer systems such as coil design, infrastructure, cost, and safety standards to give a broader context for the technology. Discussions and recommendations are also provided. This paper aims to explain the technology, its modern advancements, and its importance. With the need for electrification mounting and the automotive industry being at the forefront of concern, recent advances in wireless power transfer will inevitably play an essential role in the coming years to propel electric vehicles into the common mode of choice. [ABSTRACT FROM AUTHOR]

This paper develops a systematic framework for analyzing how low frequency forced oscillations propagate in electric power systems. Using this framework, the paper shows how to mathematically justify the so-called Dissipating Energy Flow (DEF) forced oscillation source location technique. The DEF's specific deficiencies are pinpointed, and its underlying energy function is analyzed via incremental passivity theory. This analysis is then used to prove that there exists no passivity transformation (i.e. quadratic energy function) which can simultaneously render all components of a lossy classical power system passive. The paper goes on to develop a simulation-free algorithm for predicting the performance of the DEF method in a generalized power system, and it analyzes the passivity of three non-classical load and generation components. The proposed propagation framework and performance algorithm are both tested and illustrated on the IEEE 39-bus New England system and the WECC 179-bus system. [ABSTRACT FROM AUTHOR]

This paper presents a review on real-time simulators and their use applied to power systems in Brazil. The review comprises most of the current research made in institutions/enterprises that own real-time simulators as well as the application trends of related technologies, considering both conferences and journals published papers. It is observed that several Brazilian universities have simulators in real-time and that the publications in journals have been increased, which shows that the learning curve of the Brazilian research institutions has led to an improvement in the quality of the publications. It is also important to emphasize that the analysis of real systems in most publications indicates a trend and a demand for studies with simulators in real time, to solve problems of companies of the electric sector. Related with works that use real systems in their simulations, several publications were generated in the context of R&D projects. This shows that real-time simulators are very relevant tools for studies on power systems of companies in the electricity sector, aligning scientific research and the provision of highly specialized services. [ABSTRACT FROM AUTHOR]

Summary: Integration of renewable energy sources into a distribution system requires adjustments and improvement of the existing relay protection systems. Application of the three‐phase reclosing in radial distribution networks often leads to the island operation of the distributed power generation, which causes the generator's disconnection from the network. The application of the upgraded single‐phase reclosing technique, which is proposed in this paper, enables a partial transfer of energy into the electric power system during the temporary fault. Thus, it contributes to the maintenance of the distributed generator transient stability during temporary faults in the distribution network. Improvement of single‐phase reclosing technique is reflected in the adaptation to eliminate various types of faults that may occur. The analyses include different operation conditions and stability requirements of distributed generators. The proposed solution is presented in the paper by example of different types of distributed generation: a small hydropower plant with a synchronous generator that is directly connected to the distribution network, and a wind power plant with double fed induction generator and photovoltaic systems. The results of the analyses are presented in the form of dynamic simulations performed by DIgSILENT PowerFactory software using IEEE 33‐bus model of distribution network. [ABSTRACT FROM AUTHOR]

For the bidirectional wireless power transfer system of electric vehicles, the topology proposed in this paper includes a direct three-phase AC–AC matrix converter as the pre-stage main circuit, a bilateral inductor–capacitor–capacitor–inductor (LCCL) as the resonance compensation network, and a full-bridge converter as the latter stage circuit. According to the characteristics of the system topology, a new control strategy is proposed based on the de-re-coupling method. The control principle of the coordination work of the scheme is expounded, and the corresponding switch combination logic is designed. According to the three-phase voltage amplitude relationship at different stages, combined with the resonant frequency, the switch arms of the matrix converter are alternately controlled separately. The number of switching operations is reduced, the system efficiency and safety are improved, and the full range of soft switching operations of the converter is realized. The theoretical analysis of the bilateral LCCL resonance compensation network is carried out, and its constant voltage/current output characteristic and high power factor transmission characteristic are obtained. Finally, the effectiveness and feasibility of the bidirectional wireless power transfer system for electric vehicles proposed in this paper are verified by simulation analysis. [ABSTRACT FROM AUTHOR]

Renewable energy production is constantly growing worldwide, and some countries produce a relevant percentage of their daily electricity consumption through wind energy. Therefore, decision support systems that can make accurate predictions of wind-based power production are of paramount importance for the traders operating in the energy market and for the managers in charge of planning the nonrenewable energy production. In this paper, we present a decision support system that can predict electric power production, estimate a variability index for the prediction, and analyze the wind farm (WF) production characteristics. The main contribution of this paper is a novel system for long-term electric power prediction based solely on the weather forecasts; thus, it is suitable for the WFs that cannot collect or manage the real-time data acquired by the sensors. Our system is based on neural networks and on novel techniques for calibrating and thresholding the weather forecasts based on the distinctive characteristics of the WF orography. We tuned and evaluated the proposed system using the data collected from two WFs over a two-year period and achieved satisfactory results. We studied different feature sets, training strategies, and system configurations before implementing this system for a player in the energy market. This company evaluated the power production prediction performance and the impact of our system at ten different WFs under real-world conditions and achieved a significant improvement with respect to their previous approach. [ABSTRACT FROM AUTHOR]

Multi-area Combined Economic Emission Dispatch (MACEED) problem is an optimization task in power system operation for allocating the amount of generation to the committed units within the system areas. Its objective is to minimize the fuel cost and the quantity of emissions subject to the power balance, generator limits, transmission line and tie-line constraints. The solutions of the MACEED problem in the conditions of deregulation are difficult, due to the model size, nonlinearities, and the big number of interconnections, and require intensive computations in real-time. High-Performance Computing (HPC) gives possibilities for the reduction of the problem complexity and the time for calculation by the use of parallel processing techniques for running advanced application programs efficiently, reliably and quickly. These applications are considered as very new in the power system control centers because there are not available optimization methods and software based on them that can solve the MACEED problem in parallel, paying attention to the existence of the power system areas and the tie-lines between them. A decomposition-coordinating method based on Lagrange's function is developed in this paper. Investigations of the performance of the method are done using IEEE benchmark power system models. [ABSTRACT FROM AUTHOR]

This paper proposes a new method for measurement-based modeling of nonlinear loads in power systems. The proposed method includes a combination of a binary tree algorithm with nonlinear autoregressive with exogenous input (NARX) identification. This paper demonstrates that the new method performs well without any prior knowledge of the system structure. In contrast to other load modeling methods, which are typically aimed for particular studies or load types, the proposed method can be used with any load type and for any study. Accurate load modeling is particularly important for studies of industrial networks and grids. In the study described, a field data set was collected at a mine site from a large electrical rope shovel. This data set has been used to develop a model of the rope shovel based on the proposed binary tree—NARX algorithm. When compared to other known methods, such as wavelet and sigmoid networks, the proposed method has shown the fastest training time and the highest accuracy. Finally, the modeling results have been verified against another set of field measurements from an existing network and have shown a very good agreement. [ABSTRACT FROM PUBLISHER]

This paper proposes a general framework for determining the effect of communication delays on the convergence of certain distributed frequency regulation (DFR) protocols for prosumer-based energy systems, where prosumers are serving as balancing areas. DFR relies on iterative and distributed optimization algorithms to obtain an optimal feedback law for frequency regulation. But, it is, in general, hard to know beforehand how many iterations suffice to ensure stability. This paper develops a framework to determine a lower bound on the number of iterations required for two distributed optimization protocols. This allows prosumers to determine whether they can compute stabilizing control strategies within an acceptable time frame by taking communication delays into account. The efficacy of the method is demonstrated on two realistic power systems. [ABSTRACT FROM PUBLISHER]

This paper discusses some of the main issues that are generally found in protection systems of low-voltage electrical installations and presents a methodology that can be used to analyze and upgrade the existing power system protective devices in these low-voltage distribution systems. The upgrades of existing operating systems, especially low-voltage systems, always face an economic challenge where the monetary value spent on upgrades has to be justifiable against the benefit derived. If understood clearly, the benefit of upgrades to existing protective systems is larger than just making these systems safer. A gated approach for the upgrade and proper management of such systems can help in planning for future expansions, provide reliability of equipment, and decrease the overall risk for the operation of any facility. [ABSTRACT FROM AUTHOR]

This paper is concerned with the security-constrained optimal power flow (SCOPF) problem, where each contingency corresponds to the outage of an arbitrary number of lines and generators. The problem is studied by means of a convex relaxation, named semidefinite program (SDP). The existence of a rank-1 SDP solution guarantees the recovery of a global solution of SCOPF. We prove that the rank of the SDP solution is upper bounded by the treewidth of the power network plus one, which is perceived to be small in practice. We then propose a decomposition method to reduce the computational complexity of the relaxation. In the case where the relaxation is not exact, we develop a graph-theoretic convex program to identify the problematic lines of the network and incorporate the loss over those lines into the objective as a penalization (regularization) term, leading to a penalized SDP problem. We perform several simulations on large-scale benchmark systems and verify that the global minima are at most 1% away from the feasible solutions obtained from the proposed penalized relaxation. [ABSTRACT FROM AUTHOR]

The operational availability of mining shovels is the focus of this paper. The hypothesis is that energy quality is responsible for the frequent shutdowns of the shovels. Previous engineering studies have highlighted a large presence of harmonics and reactive power in the mine loop electric system. A common solution proposed was to use a combination of active filters, larger mobile substations, shorter mining cables, and equipment location constraints. The aim of this paper is to produce a precise diagnosis of the source and nature of the energy quality issues. Mine loop electric quality monitoring, system modeling, equipment technologies, and shovel's histograms are considered. Results are measured against IEEE standards and shovel's voltage regulation susceptibility. With the diagnosis, the goal was to produce a reliable cost-effective solution. Different alternatives are crosschecked with this paper proposal. The solution presented provides energy quality well within the shovel's susceptibility and improves energy efficiency. The lower energy consumption pays the investment required and is currently under construction. [ABSTRACT FROM AUTHOR]

Recurrence quantification analysis (RQA) is a nonlinear data analysis technique that can quantify the number and duration of a dynamical system of being in nearly the same area in phase space trajectory. This paper proposes three applications of RQA to analyse power system dynamics. These are denoising of PMU data, localization of power system events, and transient stability contingency ranking of power system. All three applications have been demonstrated using a multimachine test system. [ABSTRACT FROM AUTHOR]

This paper presents an improved corrective security constrained optimal power flow (CSCOPF) for a meshed AC/DC power transmission network with voltage source converter based multi-terminal HVDC (VSC-MTDC) grids. The security constrains of N-1 contingencies for both AC and DC networks are fully considered in the CSCOPF problem. The corrective actions employed in this paper include not only the traditional long-term rescheduling control actions of the AC system, but also the short term post-contingency fast corrective control of multi-terminal VSC-HVDC. A hybrid method is developed to solve the improved CSCOPF problem and the effectiveness of the proposed method is evaluated and demonstrated in this paper by two example meshed AC/DC power systems. [ABSTRACT FROM AUTHOR]

Flexibility is a widely used term in planning process and real-time operation. The existing research on flexibility uses different techniques to study flexibility property from different aspects. While studying a property from various viewpoints increases the understanding on the subject, we need a consistent theoretical framework to consolidate the ideas generated in the field, compare and contrast results, and build on for future analysis. Based on the insights of the nature of flexibility, this paper proposes a unified framework for defining and measuring flexibility in power system. Under the proposed framework, we propose a flexibility metric which evaluates the largest variation range of uncertainty that the system can accommodate. Such a metric takes into account transmission network and system operations constraints, which are critical to assessing flexibility, but are often ignored in literature. A robust optimization technique is used to calculate the proposed metrics. While the illustrative example presented in this paper focuses on the flexibility in real-time system operation in the presence of wind and load uncertainty, this framework can generally be applicable to long-term studies such as system planning. [ABSTRACT FROM AUTHOR]

Small isolated power systems often experience generator outages, which are responsible for the activation of the under-frequency load shedding scheme with the corresponding negative impact on electricity consumers and, hence, market loss. There are three main causes of this problem: the power system's low inertia, the speed governors' low capacity, and a poor size-ratio between generator and system. The most extensive research line in this area is focused on the optimization of the load shedding scheme, which is a partial solution. Another research line is presented to solve the problem from the point of view of the system operator. This paper proposes an online method to predict and correct possible load shedding by redistributing load dispatching. This proposal uses artificial intelligence techniques, in particular neural networks, and a special-purpose power system simulator. In order to evaluate the proposal, the achieved solution is applied to a real case study: the island of Gran Canaria. This application shows the improvement that might be achieved by implementing this simple method. The method proposed in this paper is strongly recommended for regions that have suitable geographical sites as well as energy problems similar to those of the Canary Islands (see tech. rep. “Map of the Canary Islands Power Systems” by Red Electrica de Espana). [ABSTRACT FROM AUTHOR]