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• Proposes an improved YOLOv5s model which combines the GIoU, Mish, and CBAM modules. • The improved algorithm can effectively detect different-size insulator defects under different environmental backgrounds. • The AP value in detecting insulator defects can be improved by 5 %. As one of the most important components on the transmission line, the insulator is prone to failure, which affects the safe operation of electrical power system. Hence, it is crucial to accurately detect the insulator defects for further maintenance in time. Recently, with the development of artificial intelligence and target detection algorithms, the insulator defect detection has received more and more attention. However, there are still existing some difficulties: insufficient samples and low detection accuracy. To improve the accuracy of insulator defect detection, this paper proposes an auto-detection method based on an improved lightweight YOLOv5s model. First, this paper introduces the basic network frame of YOLOv5s and proposes an improved algorithm by utilizing the GIoU loss function, Mish activation function, and CBAM module. Then, performs data enhancement in the insulator dataset to enhance the robustness of the model. Finally, trains and tests the improved YOLOv5s model, and compares it with traditional target detection algorithms. Compared with traditional target detection algorithms, the AP value of the proposed algorithm in detecting insulator defects can be improved by 5 %. The results demonstrate the improved algorithm proposed in this paper can effectively identify and position the insulator defects. [ABSTRACT FROM AUTHOR]

In this paper, an improved Reinforcement Learning (RL) based approach for adaptive Virtual Synchronous Generator (VSG) control of grid-forming inverters is proposed. High penetration of inverter-based resources causes recurrent frequency stabilization issues. For this matter, a novel model-free Actor–Critic policy optimization technique is proposed to improve frequency transients metrics such as frequency nadir and Rate of Change of Frequency (RoCoF). Stability analysis of the VSG controlled system is conducted through small signal modeling to determine the stability margins of both the virtual inertia parameter J and damping coefficient D p. The control problem is formulated in RL terms using a new technique for state, action and reward construction that improves the learning process of the agents. The proposed approach's efficiency is tested for three RL algorithms, namely, Deep Deterministic Policy Gradient (DDPG), Soft Actor–Critic (SAC), and Twin-Delayed DDPG (TD3) with special attention given to the latter. Various performance metrics such as training time and maximum cumulative episodic reward are used to compare the three algorithms. The resulting agent based VSG adaptive controllers are simulated and then compared for power quality and frequency stabilization capabilities. Finally, a comparison between non-adaptive VSG and TD3 based VSG is presented to conclude on the efficiency improvements achieved by the proposed approach. • Conventional VSG Controllers necessitate recurrent parameter adjustments. • Adaptive VSG parameter adjustment is mandatory during power disturbance events. • Model-free RL-based Adaptive VSG Controllers provide more frequency stabilization. • The TD3 Algorithm is better than DDPG and SAC for Virtual Inertia Optimization. • RL Based Adaptive VSG Methods can be improved by using a novel state formulation. [ABSTRACT FROM AUTHOR]

In this paper, a single-layer sequential neural network (SNN) control algorithm has been proposed for managing the power quality (PQ) in the double-stage three-phase grid-integrated solar photovoltaic (SPV) system. The proposed algorithm efficiently extracts the active and reactive fundamental components of the load current, with a higher convergence rate. The extracted reference currents are matched with the sensed source currents to generate gating pulses for the voltage source converter (VSC). To handle power quality issues in distribution networks such as harmonic imbalances, voltage fluctuations (sags/swells), and the need for active and reactive power compensation, the VSC is controlled very precisely. The control algorithm consists of two-stage processes. In the initial stage, the incremental conductance (INC) based DC-DC converter has been incorporated to extract the peak power from the SPV system. In the later stage SNN-based algorithm is used to control the VSC. A 100 KW solar PV system connected to the utility grid has been designed by using a three-leg VSC in the MATLAB/Simulink environment. The system performance has been evaluated by comparing it to existing techniques. The simulation results comfortably meet the requirements of the IEEE-519–2014 and IEEE 1547–2003 standards for utility grid connection. [ABSTRACT FROM AUTHOR]

• In this paper, the optimized GWO-MCSVM assessment model is constructed step by step, and the nonlinear convergence factor is used to replace the conventional convergence factor in the Grey Wolf algorithm and the thought of parameter initialization by tent chaotic mapping, which makes it more suitable for the data analysis of transformers. The improved GWO-MCSVM model ensures the rapidity and reliability of assessment. • The initialization of model parameters based on Tent chaotic map completes the preprocessing of model input data, determines the initial parameter selection of GWO parameter optimization process, and improves the optimization speed of the algorithm. • The parameters of GWO-MCSVM model are optimized through training samples of transformer operation parameters in practical projects, and the GWO-MCSVM model is tested through groups of test samples. Compared with the existing GA-SVM model and PSO-SVM model, it is verified that the model has high accuracy (accuracy rate is more than 90%) in transformer condition assessment, is superior to the existing assessment model, and has bright scalability. The continuous and reliable operation of the transformer is the basis to ensure the normal operation of the power system. Relevant departments collect multi-dimensional and multi-source heterogeneous parameter data during the operation, maintenance and repair of transformers. The effective information contained in the parameter data can directly reflect the current operating status of the transformer. On the basis of support vector machine and grey wolf algorithm, an improved GWO-MCSVM algorithm based on nonlinear convergence factor and Tent chaotic mapping is proposed. The algorithm parameters are optimized through training samples, and the results are evaluated and verified in the algorithm itself, so as to improve the accuracy of the status assessment results. Finally, the accuracy of assessment results of the algorithm proposed in this paper, existing genetic algorithms and particle swarm optimization algorithms are compared by evaluating multiple sets of measured samples. By comparison, the effectiveness of the algorithm proposed in this paper for transformer condition assessment has been verified. [ABSTRACT FROM AUTHOR]

In this paper, a multi-operator differential evolution algorithm (MODE) is proposed to solve the Optimal Power Flow problem, called MODE-OPF. The MODE-OPF utilizes the strengths of more than one differential evolution operator in a single algorithmic framework. Additionally, an adaptive method is proposed to update the number of solutions evolved by each DE operator based on both the diversity of the population and the quality of solutions. This adaptive method has the ability to maintain diversity at the early stages of the optimization process and boost convergence at the later ones. The performance of the proposed MODE-OPF is tested by solving OPF problems for both small and large IEEE bus systems (i.e., IEEE-30 and IEEE-118) while considering intermittent solar and wind power generation. To prove the suitability of this proposed algorithm, its performance has been compared against several state-of-the-art optimization algorithms, where MODE-OPF outperforms other algorithms in all experimental results thereby improving a network's performance with lower cost. MODE-OPF decreases the total generation cost up to 24.08%, the real power loss up to 6.80% and the total generation cost with emission up to 8.56%. • Development of an adaptive method (AM) for optimizing diversity and solution quality. • Innovative constraint handling approach, progressively adding constraints for improved performance. • Incorporation of intermittent renewable energy models for realistic problem solving. • Extensive validation on IEEE 30-bus and IEEE 118-bus networks, outperforming state-of-the-art algorithms in cost, loss, and environmental impact reduction. [ABSTRACT FROM AUTHOR]

• Simplicity of principle improves computational efficiency. • Methods to effectively assess reliability. • Incorporate engineering realities to ensure accuracy. With the rise of large-scale energy DC transmission system, more and more projects use UHVDC transmission system for long-distance and large-capacity power transmission, in which the converter station is the core of the whole UHV DC transmission system. In this paper, a reliability assessment method based on improved Dijkstra's algorithm is proposed for the main wiring system of the converter station of the UHVDC transmission system and for the components in the main wiring. In order to fully consider the different states of components in actual operation, a four-state model is adopted in the study. The model improves the accuracy of the model by comprehensively considering the component's state characteristics, switching sequence, operation mode and other factors. Based on the state model of the components, the main wiring system is calculated in accordance with the theory of complex distribution networks in order to reduce the computational complexity. Finally, the main wiring system of the double 12-pulse converter station is traversed through the minimum paths based on the improved Dijkstra search method, and the reliability indexes of the obtained minimum paths are calculated according to the theory of the minimum path cut set. A typical bipolar dual 12-pulse series connection is used to verify the validity of the method, and some guidance is given for practical engineering. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Multi-source multi-area interconnected power systems with physical constraints are analyzed in deregulated scenario. • Mathematical description of AC and HVDC tie links with INEC strategy is analyzed for frequency regulation. • A novel cascaded structure of 2-DOF-PI-FOPDN is proposed successfully. • A new Volleyball Premier League (VPL) algorithm is maidenly applied for the proposed AGC controller. • The output response of the VPL algorithm based 2-DOF-PI-FOPDN controller is compared with published literature on the same platform. Abstract This paper deals with the Automatic Generation Control (AGC) strategy for multi-source interconnected power system in deregulated environment. Physical constraints like Generation Rate Constraints (GRC), Governor Dead Band (GDB) and Boiler Dynamics (BD) are incorporated in the system for the realistic approach. In this paper, an accurate model of HVDC tie-link is considered for the proposed AGC mechanism. Inertia Emulation based Control (INEC) technique is adopted to utilize the stored energy of HVDC tie-link of the interconnected power system. Distributed Generation (DG) system is also considered in the proposed AGC structure. The DG system comprises of Solar Photovoltaic (SPV), Wind Turbine System (WTS), Diesel Engine Generator (DEG), Aqua Electrolyzer (AE) and Fuel Cell (FC). Finally, a novel application of Volleyball Premier League (VPL) algorithm has been introduced to obtain the optimized gains of the proposed controller. The proposed controller includes the cascade structure of 2-Degree of Freedom Proportional-Integral controller and Fractional Order Proportional-Derivative controller with filter (2-DOF-PI-FOPDN). The robustness and effectiveness of VPL algorithm based proposed controller has been tested by comparing with the published literatures on same platform. [ABSTRACT FROM AUTHOR]

Highlights • A one-ended method is proposed to increase the fault location accuracy by determining remote end fault current. • The method is developed using covariance based formulation to increase robustness against the load variations in the network. • Using this method, fault location algorithm can be adapted to any network topology changes. Abstract Fault location algorithms encounter error because of disregarding the fault current injected from remote end bus. In this paper, a one-ended method is proposed for determination of remote end fault current, in order to increase the accuracy of the fault location algorithm. This method is based on measuring the pre-fault voltage and current phasors from one side of the line without the need to employ communication link and data synchronization. Then a new formulation is applied to estimate Thevenin impedance from remote side of the line. The obtained equivalent impedance can be used to calculate accurate fault location. Using this method, fault location algorithm can be adapted to any network topology changes. For avoiding the effect of the other load variations on the estimation of remote end impedance, a new covariance based formulation is used. To clarify the effectiveness of the proposed method, it is applied on two sample test networks and the results are compared with three other methods. The simulation results show that the presented method in this paper is adaptive enough to the network topology changes and is robust against the network side load variations. [ABSTRACT FROM AUTHOR]

The paper presents a hybrid co-simulator comprising EMT and dynamic phasor-based simulators. The EMT simulator models portion(s) of the network wherein fast transients are prevalent and detailed modeling is necessary. The dynamic phasor solver models the rest of the network using extended-frequency Fourier components. Specialized algorithms are developed and presented to accurately map instantaneous EMT and counterpart dynamic phasor samples. Interfacing requirements for co-simulation using different time-steps in the two solvers are also discussed along with implications on accuracy and numerical stability. The paper demonstrates the developed co-simulation algorithm using an example of the IEEE three-phase 118-bus network in which a wind farm is included. The wind farm and the network in its vicinity are modeled in the PSCAD/EMTDC electromagnetic transient simulator, and are interfaced to the rest of the system modeled in a dynamic phasor-based solver. The paper demonstrates the accuracy of the proposed co-simulation for a range of time-step ratios of the two solvers, and also reports the substantial computational time savings obtained using the hybrid simulator. [ABSTRACT FROM AUTHOR]

This paper introduces the first application of feature extraction and machine learning to electromagnetic interference (EMI) signals for discharge sources classification in high voltage power generating plants. This work presents an investigation on signals that represent different discharge sources, which are measured using EMI techniques from operating electrical machines within power plant. The analysis involves time–frequency image calculation of EMI signals using general linear chirplet analysis (GLCT) which reveals both time and frequency varying characteristics. Histograms of uniform local binary patterns (LBP) are implemented as a feature reduction and extraction technique for the classification of discharge sources using multi-class support vector machine (MCSVM). The novelty that this paper introduces is the combination of GLCT and LBP applications to develop a new feature extraction algorithm applied to EMI signals classification. The proposed algorithm is demonstrated to be successful with excellent classification accuracy being achieved. For the first time, this work transfers expert's knowledge on EMI faults to an intelligent system which could potentially be exploited to develop an automatic condition monitoring system. [ABSTRACT FROM AUTHOR]

Various impedance-based fault location algorithms have been presented in the related studies. The algorithms need some phasor data of the power system provided by phasor measurement units (PMUs), implying the necessity of PMU placement to attain fault location observability. This paper develops fault location observability rules associated with some important impedance-based fault location algorithms based on known state observability theories. The algorithms include two-ends measurements, one-end measurements, one bus space, only synchronized voltage measurements, and wide-area measurements. The developed rules are used to obtain an index that indicates the number of transmission lines that fault location on them is not possible. The index forms a main constraint or a part of the objective function for the defined PMU placement problem to determine the optimal placement of PMUs for state estimation observability and fault location observability. The proposed rules and optimization problem are applied to IEEE 14, 30, 39, and 57 buses test networks to study different scenarios. • New fault location observability rules for impedance-based fault location algorithms. • Accurately modeling the effect of ZI buses for fault location observability analysis. • New generalized OPP problem for joint state and fault location observability. • Provides 60% less PMU for fault location observability than the existing literature. • Examining critical buses in fault location observability. [ABSTRACT FROM AUTHOR]

• The algorithm uses the angle change between the input signals as a criterion for fault detection. • The instantaneous values of the voltages measured at the beginning of the line and the calculated instantaneous values of the auxiliary voltages are used as input signals. • The obtained results demonstrate the good properties of the presented algorithm. Conventional distance protection methods usually require additional filtering of the input signals to remove the influence of the DC component and the distortion of sinusoidal signals. The paper shows an algorithm that does not require additional filtering of the input signals. The proposed algorithm uses measured voltages at the beginning of the line and auxiliary voltages as input signals. The auxiliary voltages were calculated from measured currents and voltages at the beginning of the line and known line parameters. The algorithm compares the instantaneous values of the measured and calculated auxiliary voltages and detects a fault on the line based on the change in the phase angle of the voltage. Testing of the presented algorithm was performed with signals obtained from computer simulations of line faults and recordings of faults from protection devices from the real network. The obtained results confirmed that the algorithm represents fast and sensitive protection of transmission lines. [ABSTRACT FROM AUTHOR]

Analysis of recent blackouts over the past decade has indicated overloads as being responsible for initiation and development of most large area failures. The overload occurrences have also been found to correspond especially with the overcurrent and distance protection, often causing their overfunction under allowable power system operating conditions. It is highly desired to improve the operation of protection relays for the sake of avoiding future blackout occurrences or at least lowering their scale. One of the possibilities to do so is an application of the Dynamic Line Rating algorithms into the standard overcurrent relay with the hope of ensuring safe relay behavior during overloads. The Dynamic Line Rating is usually proposed to be used for increasing the line transfer capacity by monitoring of the overhead conductors temperature and weather conditions. It is clear that one must also take into account the impact of DLR-operated line on the existing protection devices. It is required to adapt their decision-making algorithms to the new conditions, while satisfying arbitrarily established protection principles. This paper presents firstly chosen recent decade blackouts, highlighting the main causes of their formation and development process. Applicable solutions for overcurrent relay improvement are then proposed, which is followed by analyses of the new relay algorithms’ operation during allowable overloads and faults. The enhanced overcurrent relay solution introduced in this paper proved to be an efficient technique also for blackout prevention. [ABSTRACT FROM AUTHOR]

Power systems are operated in a deterministic way. However, the increase in uncertainties (caused by measurement and communication errors or the absence of complete knowledge of the measured quantity) requires algorithms capable of assessing randomness in real-time monitoring and operation of energy management systems. Among them, state estimation is a fundamental element that provides complete and reliable information about the current network state. This paper offers a review of non-deterministic algorithms, used to assess the randomness caused by the uncertainties in power system state estimation. Depending on the uncertainty modeling method, different static and dynamic non-deterministic state estimation algorithms for transmission and distribution systems are reviewed. Also, four of the most relevant algorithms are implemented and results are compared for distribution networks. The relevance of such models, as well as their motivation, are addressed. • This paper offers a review of methods employed for power system uncertainty modeling. • Review of state estimation algorithms based on uncertainty modeling methods. • Non-deterministic state estimation algorithms in transmission and distribution grids. • Non-deterministic state estimators in low voltage networks have been implemented. • Future research lines on non-deterministic state estimation are proposed. [ABSTRACT FROM AUTHOR]

• Discrimination between power swing and faults even during power swing. • A high-speed algorithm based on the DWT is achieved using a fast mother wavelet. • The noise effect is considered in the introduced algorithm. • Symmetrical and asymmetrical faults are detected in a cycle or less. • Reduction of the computational complexity allows the use of low cost microprocessors. Distance relay should be blocked during a power swing, but it should operate reliably when any fault occurs even during a power swing. Therefore, this paper introduces a high-speed algorithm based on wavelet transform (WT) to discriminate between a power swing and symmetrical/asymmetrical faults. The algorithm uses a fast mother wavelet, with a 3-coefficient high-pass filter, to decompose the voltage and current signals into their corresponding frequency levels. In this regard, two distinct levels are chosen. The first level of the voltage signal and the eighth level of the current signal are chosen to detect a fault and a power swing, respectively. Depending on the percentage change in the spectral energy of these discriminative signals, the distance relay can discriminate between a power swing and any fault that may occur during a power swing. To evaluate the performance of the introduced algorithm, several faults, including high resistance faults, and power swings cases are simulated on a typical extra high voltage transmission system using MATLAB environment. The simulation results show that the introduced algorithm has a high speed and an efficient performance, even if the signals are noised; where a power swing is detected in a suitable time and faults are detected in a cycle or less. [ABSTRACT FROM AUTHOR]

• An improved metaheuristic algorithm named the Elite Marine Predators Algorithm (EMPA) is designed. • The proposed algorithm is used to solve the directional overcurrent relay coordination problem. • The EMPA algorithm is used to find the optimal relays settings and operating times in four different power systems (3-bus, 8-bus, 9-bus and 15-bus). • The results using EMPA algorithm were compared against those of well-regarded and recent published algorithms and proved to have superior performance. The integration of renewable energy sources in the distribution network (DN) has had a significant influence by reducing power loss and enhancing network dependability. Aside from that, the protection system has met coordination issues as a result of bidirectional power flow and variations in fault levels. Therefore, an optimal coordination strategy is required to deal with relays coordination problem. The coordination problem of the directional overcurrent relays (DOCRs) is a restricted optimization issue that involves determining appropriate time dial settings (TDS) and plug setting (PS) to reduce relays operating time. Currently, a various nontraditional optimization strategies have been presented to overcome this challenge. In this paper, a modified version of the marine predators algorithm (MPA) referred to as Elite marine predator (EMPA) is developed for the optimal coordination of DOCRs. Therefore, the EMPA method is used to find out the optimal settings for the DOCRs problem. The suggested algorithm's performance is evaluated using standard test systems, including 3-bus, 8-bus, 9-bus, and 15-bus. The findings are compared with the traditional MPA and with other recent optimization methods presented in the literature to prove the efficiency and superiority of the proposed EMPA in reducing relay operation time for optimal DOCRs coordination. [ABSTRACT FROM AUTHOR]

This paper investigated a multi-variable power quality disturbance identification algorithm (MPQDIA) applying the Stockwell transform (ST), Hilbert transform (HT) and rule based decision tree (RBDT). Voltage waveform with associated power quality disturbances (PQDs) are realized by the mathematical formulation in compliance with standard IEEE-1159. These voltage signals with PQDs are processed applying the ST and HT for computing the index for power quality identification (IPI) and index for power quality location (IPL). IPI and IPL plots effectively identify and locate the PQDs of simple nature and multiple nature. Four features are extracted from data sets of IPI and IPL. These features are considered as input for the RBDT to classify the PQDs. MPQDIA is effectively tested for identification, to locate and to classify the total 21 PQDs of simple as well as multiple natures. Performance of MPQDIA is analysed in terms of rightly and wrongly categorized PQDs in noise free environment and considering noise of 20 dB SNR (signal to noise ratio) level. Efficiency of MPQDIA is compared with the ST and RBDT based algorithm, WT based fast Kurtogram and decision tree powered algorithm, and ST and RBDT powered method in terms of classification accuracy, noise level for which performance is not affected, effectiveness to detect the simple nature and multiple nature PQDs. It is established that MPQDIA effectively recognizes the PQDs on a real time power system network. Study is performed with the help of MATLAB software. • Multivariable PQ identification algorithm (MPQDIA) using ST, HT and RBDT designed. • Index for PQ identification (IPI) and location (IPL) are designed. • Features computed from IPI and IPL are used by RBDT to classify PQDs. • MPQDIA effectively identify, locate and classify PQDs of simple and complex nature. • MPQDIA has better performance with existing methods and recognizes PQD in real time. [ABSTRACT FROM AUTHOR]

• The new proposed algorithm operates upon a proper switching amongst conventional MPPT algorithms, namely perturb and observe (P&O) and incremental conductance (IC) algorithms. • Two coordination schemes are proposed for this algorithm the to prioritise the improvement of different performance aspects over others. • The impact of the proposed algorithm according to the 2 coordination schemes is evaluated and compared with the impact of conventional MPPT algorithms according to the trackability of power, the impact on DC voltage and on the AC grid side. In this paper, a new coordinated maximum power point tracking (MPPT) algorithm has been developed for a grid-tied PV system, whose inverter follows a V DC I Q control scheme. The control objectives of this system are shared between 2 converters: a DC boost converter which performs MPPT of the PV plant, and an inverter which is responsible for DC voltage setpoint control, specific reactive current injection under request and reduced harmonic content of AC grid currents. The proposed algorithm operates upon a proper switching amongst conventional MPPT algorithms, namely perturb and observe (P&O) and incremental conductance (IC) algorithms, to take advantage of the best characteristics of each MPPT method with a different step size and considering the influence of the inverter control constants. Two coordination schemes are proposed for this algorithm to prioritise the improvement of different performance aspects over others. The impact of the proposed algorithm according to the 2 coordination schemes is evaluated and compared with the impact of conventional MPPT algorithms according to the trackability of power, the impact on DC voltage and on the AC grid side. The results are analysed by simulations conducted in MATLAB-Simulink. [ABSTRACT FROM AUTHOR]

The high current carrying capacity of the power electronics based switches has gained much popularity to the VSC-based HVDC system. The challenge faced by the protection schemes is to identify and isolate the relevant fault within 5 to 6 ms. Moreover, the relay algorithm will not activate the circuit breaker to operate during other disturbances including external and non relevant internal faults. The Discrete Wavelet Transform (DWT) and Support Vector Machine (SVM) classifiers are used in this paper to formulate a protection method. Different types of faults are simulated on the using PSCAD/EMTDC software. Depending upon the relevant frequency components accompanied by the DC link voltage and current during fault, nine relevant features are judiciously selected. The acquired features are then used to train and test SVM for fault identification and classification. The proposed solution does not rely on communication as it only takes information from one end. Furthermore, the approach effectively distinguishes internal faults, external faults, and non-fault disturbances in a multi-terminal VSC-HVDC system. This method is capable of classifying faults in both fault-resistant and noisy situations. The extensive execution time study demonstrated that the proposed method is fast and computationally less expensive fault detection and classification technique. • The DC voltage and current are analysed to obtain the SVM-classifier features. • Method distinguishes internal faults, external faults, and non-fault disturbances. • Method is capable of classifying faults in both fault-resistant and noisy situations. • Execution time within 6ms proved the method is a computationally less expensive. [ABSTRACT FROM AUTHOR]

• The proposed method adopts K-means, FFT, and coefficient of kurtosis to improve the signal preprocessing ability of SGMD, which makes different types of disturbance features easy to be extracted. • It adopts an optimization algorithm to optimize the feature extraction of multiple methods and the disturbance identification of ELM, which improves the accuracy of feature extraction and disturbance identification. • It adopts tent chaotic mapping and adaptive parameters to further improve the optimization performance of MPA. Power quality is the quality of electrical energy in the power system. And the power quality disturbances (PQDs) in the power system lead to severe consequences for the equipment's life and the operator's safety. The accurate disturbance identification is a crucial prerequisite to managing power quality. Currently, the identification accuracy of PQDs needs to be improved, especially in high-intensity noise environments. In this paper, a novel power quality identification method based on adaptive symplectic geometric mode decomposition (ASGMD) and tent chaotic map and adaptive parameter method improved marine predators algorithm (IMPA) optimization is proposed. Firstly, the PQDs are pre-processed by adaptive symplectic geometric mode decomposition with K-means, fast Fourier transform, coefficient of kurtosis, and wavelet thresholding to reduce the noise component. Secondly, twenty-three PQDs features of the wavelet transform, fast Fourier transform, and mathematical statistics are optimally selected by IMPA to improve the identification accuracy and efficiency. Finally, the PQDs with selected features are recognized by the extreme learning machine with optimized weights and biases. IMPA improves the uniformity of the initial population distribution and the optimization process of three iterative phases, thus promoting the search accuracy of the optimal features, input weights, and biases. The proposed method has more accurate identification accuracy and fast identification speed by simulating different noise intensity environments than other methods. Remarkably, the identification accuracy reaches 91% in high-intensity noise environments of 10dB This method has practical significance for PQDs identification of large areas, long periods, and high noise-resistant. [ABSTRACT FROM AUTHOR]

• The operation characteristics of household appliances masks the arc fault characteristics. • Arc fault location affects the performance of arc fault detection features. • The adaptive algorithm can effectively extract arc fault detection features and help accurately detect multi-branch arc faults. • Leaf-wise strategy can simplify the algorithm structure and improve efficiency. The operation characteristics of household appliances would interfere with the arc fault detection. Especially in the case of the multi-branch circuit, the arc fault information is mixed with the operation characteristics of various loads, which makes the traditional arc fault detection algorithm invalid. In this paper, arc fault signals are acquired from the designed multi-branch experimental platform composed of masking loads according to IEC 62606. By adding the adaptive noise, ICEEMDAN algorithm is found to be suitable to extract more sufficient arc fault information. By selecting the IMF and constructing its variance, the detection variables are constructed to distinguish the arc fault from the normal state. Compared with wavelet transform, the ability to extract arc fault information is improved by 8.47 times on average. In order to simplify the algorithm structure, the Boruta and LightGBM algorithm are used to reduce the feature dimension and improve the algorithm efficiency. Based on the well-trained LightGBM model, the arc fault detection algorithm is finally proposed, which could detect multi-branch arc faults accurately and fast. It is proved to have the higher detection accuracy of 97.06% and the lower detection time of no more than 300 ms on the Raspberry pi platform. [Display omitted] [ABSTRACT FROM AUTHOR]

Non-technical losses (NTL) identification has been paramount in the last years. However, it is not straightforward to obtain labelled datasets to perform a supervised NTL recognition task. In this paper, the optimum-path forest (OPF) clustering algorithm has been employed to identify irregular and regular profiles of commercial and industrial consumers obtained from a Brazilian electrical power company. Additionally, a model for the problem of NTL recognition as an anomaly detection task has been proposed when there are little or no information about irregular consumers. For such purpose, two new approaches based on the OPF framework have been introduced and compared against the well-known k -means, Gaussian mixture model, Birch, affinity propagation and one-class support vector machines. The experimental results have shown the robustness of OPF for both unsupervised NTL recognition and anomaly detection problems. In short, the main contributions of this paper are fourfold: (i) to employ unsupervised OPF for non-technical losses detection, (ii) to model the problem of NTL as being an anomaly detection task, (iii) to employ unsupervised OPF to estimate the parameters of the Gaussian distributions, and (iv) to present an anomaly detection approach based on unsupervised optimum-path forest. [ABSTRACT FROM AUTHOR]

This paper presents an algorithm for fault-location for series-compensated transmission lines based on phase components and on an heuristic method. The proposed algorithm uses voltages and currents measurements provided by intelligent electronic devices installed at both line ends to calculate the voltages at the fault point and to determine the exact fault location. The paper also presents a detailed mathematical model of the series compensation, which is capable of representing its behavior accurately, improving the algorithm's response. The authors implemented a series-compensated double-circuit transmission line using the Alternative Transients Program, in order to evaluate the performance of the proposed algorithm. The results indicate that it presents a high level of accuracy. [ABSTRACT FROM AUTHOR]

Power system operators are increasingly looking toward distributed optimization to address various challenges facing electric power systems. To assess their capabilities in environments with nonideal communications, this paper investigates the impacts of data quality on the performance of distributed optimization algorithms. Specifically, this paper compares the performance of the Alternating Direction Method of Multipliers (ADMM), Analytical Target Cascading (ATC), and Auxiliary Problem Principle (APP) algorithms in the context of DC Optimal Power Flow (DC OPF) problems. Using several test systems, this paper characterizes the performance of these algorithms in terms of their convergence rates and solution quality under three data quality nonidealities: (1) additive Gaussian noise, (2) bad data (large error), and (3) intermittent communication failure. • Parameter tunning plays a crucial role in the distributed algorithms' convergence rate. • Distributed OPF with nonideal communications may converge to suboptimal solutions. • Bad data severely impacts the quality of the distributed algorithms' solutions. [ABSTRACT FROM AUTHOR]

• A new methodology to increase power factor for multiple EVs charging. • A Simulink model validate by experimental measurements. • Real time algorithm able to mitigate the power factor decay at the point of delivery. The paper suggests a new methodology to increase the PF of a hub for EV charging. A smart management of the EV charging sessions allows to impose the stand-by operation of a vehicle based on the local PF value at EV charging points. Current harmonics are taken into account to ensure an effective improvement of the hub power quality. The case study of this paper consists of a hub for EV charging with a dedicated MV/LV substation, enriched by an experimental dataset containing measurements of 13 EVs during charging in terms of active and reactive power profiles, current harmonics, PF trends. The model is developed in Simulink environment and the proposed algorithm is implemented in a MATLAB script. The results highlight that in case of multiple EV charging sessions, the algorithm is able to maintain the hub PF value greater than the acceptable PF threshold limit. This scenario is expectable in real conditions, e.g. EV hubs near shopping centres or in cities with high population density. [ABSTRACT FROM AUTHOR]

• This paper illustrates an innovative signal processing method based on the concept of the 2nd SOD transform. • The 2nd SOD signals-based innovative method presents distance protection for the bipolar HVDC transmission line. • The paper succeeded in the challenges like power swing situations, noise interference, high impedance faults, and remote end faults with high accuracy, reliability, and stability and without delay in protection startup for all fault types (the single pole-to-ground faults and pole-to-pole faults) during ultra-high-speed. • The paper presents new employment for the 2nd order of the SOD tool to capture transient component characteristics of both terminals of the DC-TL, calculate the fault distance, and identify the faulted pole. • Also, it presents novel employment of external disturbances to estimate the fault location. This employment protects the proposed technique from the errors resulting from the mistakes in knowing the transmission line parameters data. • The proposed algorithm is valid for both single-pole and two-pole operation modes. • Also, it suggested an amplification process to magnify the stability margin between normal and abnormal operations. • And, it verifies the decision by employing more than information. In addition to the distributed capacitance does not affect the proposed technique. It is a vital challenge to perfectly and reliably position high impedance faults and remote end faults in high-voltage direct current (HVDC) transmission lines. Also, distance protection systems are very vulnerable to maloperation under power swing situations and noise interference. These challenges are essential for system stability. This paper succeeded in these challenges with high accuracy, reliability, and stability and without delay in protection startup for single pole-to-ground faults and pole-to-pole faults during ultra-high-speed. The paper presents new employment for the 2nd order of the sequential overlapping difference (SOD) tool to capture transient component characteristics of both terminals of the DC-TL, calculate the fault distance, and identify the faulted pole. Also, it presents novel employment of external disturbances to estimate the fault location. This employment protects the proposed technique from the errors resulting from the mistakes in knowing the transmission line parameters data. The paper studies a bipolar-HVDC-TL system established in (ATP/EMTP). Besides, the proposed algorithm is valid for both single-pole and two-pole operation modes. Also, it suggested an amplification process to magnify the stability margin between normal and abnormal operations. And, it verifies the decision by employing more than information. In addition, the distributed capacitance does not affect it. [ABSTRACT FROM AUTHOR]

• A novel algorithm for 2-terminal transmission line fault location is proposed. • Phase Angle Jump Checking method is proposed. • This method is not affected by fault type and has good universality. • This method is immune to transition resistance. • The fault location accuracy of this method is high. The low precision and instability of fault location results of power system transmission lines is a major problem that affects the safe operation of power systems, which needs to be solved more effectively. With the increasing coverage of the synchronic Phasor Measurement Unit (PMU) in power systems, it has laid a good foundation for the research and application of high-precision fault location method based on 2-termnal synchronous measurement of phasor. Based on this, a new high-precision fault location algorithm integrating voltage phasor feature and phase-angle jump checking is proposed in this paper. Firstly, the synchronous fundamental positive sequence voltage and current phasors of the fault line are extracted; and then all the roots(including real and virtual roots) are calculated by using the condition that the fundamental positive sequence voltage phasor at the fault point is equal; finally the unique real root represents the actual fault point can be determined by using the feature that the check function of phase-angle will step-jump when crossing the fault point from left to right, and then the purpose of high precision fault location is realized. This algorithm has the characteristics of strong versatility, high precision and immunity to transition resistance. The results of simulation and example show the feasibility and effectiveness of the fault location algorithm the fault location algorithm proposed in this paper. [ABSTRACT FROM AUTHOR]

• This paper establishes a multi-objective optimization model for the dynamic reconfiguration of the distribution network. • Aiming at the time-varying load, considering the switching constraints, a dynamic optimal period division function and optimal function threshold are proposed. • An improved SMA is proposed, called MFSMA. It is used to solve the dynamic reconfiguration of distribution network problem for the first time. This paper suggests a multi-period dynamic reconfiguration method for the distribution network. The reconfiguration period is preliminarily divided based on the load monotonicity and amplitude change with taking the length of the actual load as the reconfiguration time section. A multi-objective dynamic reconfiguration is modeled based on the time-varying load distribution network considering network active power loss, static voltage stability, and load balance. The optimal period partition function is dynamically adjusted by the time-division method under the constraint of switching actions. The paper also proposes a multi-group flight slime mould algorithm (MFSMA) by applying a multi-group optimization strategy and adaptive Levy flight for the dynamic distribution network reconfiguration problem. Through experiments on IEEE-33 and IEEE-118 bus distribution networks, the experimental results show that the MFSMA for the multi-period dynamic reconfiguration effectively simulates the actual reconfiguration of the distribution network and provides a new scheme for the economic, stable, and safe operation of the distribution network. [ABSTRACT FROM AUTHOR]

Highlights • We used faulty phase reactive power to identify a transient fault. • Instantaneous power algorithm was used to calculate faulty phase reactive power. • We provided TFI methods for transmission lines based on the RPVR. • We provided TFI methods for transmission lines based on LPC and HPC ratios. • The proposed ASPAR scheme can be used on wind power outgoing lines. Abstract This paper proposes two anti-interference adaptive single-phase auto-reclosing (ASPAR) schemes for transmission lines with shunt reactors. This approach is based on faulty phase reactive power characteristics. Instantaneous power algorithm (IPA) is used to calculate the reactive power using voltage and current measurements at only one end of the transmission line. After fault extinction, faulty phase reactive power magnitude rapidly rises and can be divided into five frequency components, hence, magnitude and frequency components ratio are used to identify fault extinction time. Integral processes are included in IPA, for this reason, the proposed ASPAR schemes possess anti-interference capability, and it can be used on wind power outgoing lines with multiple kind of interference often. The proposed approach considers various transmission lines interferences: rapid transmit power fluctuation and external lightning strike. Influences of high frequency disturbance and wind power plants low voltage ride through (LVRT) process were also taken into account. The proposed ASPAR schemes is extensively investigated on a typical wind power outgoing line, Hami, Xinjiang, China via the simulation platform PSCAD/EMTDC 4.5.0.0. Different cases are studied considering rapid transmit power fluctuation and external lightning strike. The simulation results ensure the validity and feasibility of the proposed ASPAR schemes on transmission lines with and without much interference. Besides, the robustness of the proposed ASPAR schemes against varied fault location and transition resistance is also verified. [ABSTRACT FROM AUTHOR]

Highlights • A three-phase phase-locked loop algorithm is introduced. • Inherent immunity to subharmonics and interharmonics is achieved. • An adaptive filter is employed to improve disturbance rejection. • A proper comparison with similar approaches is presented. Abstract This paper introduces a synchronization algorithm for the detection of the fundamental positive-sequence component in three-phase systems. The structure is based on the correlation of the input signal with a complex signal generated from the association of an adaptive filter and a phase-locked loop (PLL) method previously presented in literature. Good disturbance rejection is then achieved, in particular to interharmonics and subharmonics. Simulation and experimental results are presented and discussed in order to demonstrate the performance of the proposed solution when compared with that regarding dual second-order generalized integrator frequency locked loop (DSOGI-FLL), which is often considered to present good disturbance rejection. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • We proposed and test a DSE based algorithm to detect traveling waves in transmission lines. • Performance was validated with transient simulations and playback testing using Bergeron and frequency dependent parameter models. • The method was compared to legacy protections with TWs differentiator smoother and impedance based relays. • The method showed a successful performance with different sampling rates (lower sampling rates) which is one of the main contributions. • The method was also assessed with different types of fault with the EMTP case study and a real Colombian overhead transmission line. Abstract A dynamic state estimation (DSE) approach is proposed to improve the accuracy to identify the front-wave arrival times of a two-terminal traveling wave protection scheme for a transmission line with low sampling rates. The solution is implemented as an offline method aiming to use existing infrastructure measurements. The work presents the principles of traveling wave (TW) theory and legacy protection schemes with this methodology. The proposed method requires GPS synchronized measurements at both ends of the line and a high fidelity model of the protected line. The paper presents comparisons between the differentiator smoother for arrival time identification, traditional impedance based fault location using 1 or 2 terminals and the proposed DSE-TW. The performance is also assessed with the Bergeron model and the frequency dependent parameter model of the transmission line. Numerical simulations and laboratory tests demonstrate that the method can correctly identify the front-wave arrival time at each end with better accuracy and different sampling rates. This work illustrates the advantages of DSE-TW such as high accuracy of arrival time identification, the minimum error of fault location and better performance with different (lower) sampling rates. [ABSTRACT FROM AUTHOR]

Highlights • Two incidence matrices are proposed for complete modeling of distribution systems. • A review of various distributed generations is provided in power flow studies. • An efficient power flow algorithm for distribution systems is proposed. • Constant power-voltage buses are handled by a new in-program sensitivity matrix. • Accuracy, performance, and robustness of the model are validated by simulations. Abstract Real-time operation, analysis and control of active distribution systems (DSs) mainly rely on accurate power flow (PF) results. Almost all decisions are made considering PF calculations. On the other hand, efficiency of PF algorithm should be updated to comply with new smart grid paradigms which affect traditional management methods of DSs. A new graph theory based PF algorithm is proposed in this paper for active electrical DSs including various distributed generation (DG) models, three phase equipment and meshed topologies. At first, two incidence matrices are proposed for modeling of DSs. These matrices could successfully handle meshed topologies and unbalanced networks. They could also be modified to consider various three phase equipment such as transformers and voltage regulators. Moreover, a comprehensive study of various modeling methods of DGs in PF studies is presented. In order to handle DG models, a new sensitivity matrix is proposed for in-algorithm calculation of reactive power injection of PV buses. Since, the proposed incidence matrices provide a decoupled model of the network, any topology and characteristic change could be simply applied in this PF algorithm. The proposed PF algorithm was tested in several simulations in various test systems. The results of accuracy test, performance test, and robustness test show capability of the proposed PF algorithm for handling various situations in different PF calculations. [ABSTRACT FROM AUTHOR]

Highlights • A wave polarity coefficient is defined to detect the fault line. • A single-end fault location method using time difference of arrival is proposed. • WTE-MM algorithm is presented to detect wave front with noises. • PSCAD/EMTDC simulations demonstrate the advantages of the proposed method. Abstract Due to complex reflection and refraction at line terminals, traditional single-end traveling wave (TW) fault location (FL) cannot be directly applied to transmission lines connecting with short branches. This paper presents an improved single-end TW FL method for this special case. Three TW recorders are required to be mounted at local, middle and remote terminals of the transmission line but accurate synchronous sampling is not required. In the proposed method, combined with the defined polarity coefficients of current TW wave fronts (WFs), the absolute difference of the time differences of arrival (TDOAs) of the modulus TWs at both terminals is firstly utilized to determine whether the fault occurs in the transmission line. If the fault is detected in the transmission line, the fault line section can be then determined by the ratio of the TDOAs of the modulus TWs recorded at both terminals. Finally, the TDOAs of the first two WFs at the three TW recorders are calculated and compared with the theoretical ones to determine the source of the second WF. The corresponding single-end accurate FL formula is selected to pinpoint the fault. A simulation model of a transmission line connecting with short branches is constructed by PSCAD/EMTDC. Various faults are simulated to verify the proposed FL method. The calculation results demonstrate that the method is not affected by FLs, impedances, inception angles, noises and longer lines to a certain extent. [ABSTRACT FROM AUTHOR]

Highlights • A temperature-dependent power flow algorithm is developed. • Longitudinal variations in weather conditions are incorporated. • It enables determination of the transmission system loadability. • Both thermal and voltage stability limits are considered. • Quantifiable differences in power transfer capabilities are noted. Abstract The paper presents an approach to determine the maximum power transfer capabilities of electric transmission systems by coupling dynamic line ratings with temperature-dependent line modeling. This approach avoids using a set of predefined, conservative weather conditions often assumed uniform along lines. Specifically, a temperature-dependent power flow algorithm was been developed to account for weather conditions, their effects on conductor temperature, line parameters and line models. Moreover, coupling temperature-dependent line model structures within the temperature-dependent power flow, captures longitudinal variations in weather conditions (and the subsequent non-uniform distribution of electrical parameters) into the steady-state analysis of the power system. This enables determination of the transmission system loadability in terms of both thermal and voltage stability limits. The proposed methodology is applied to the IEEE 4-bus and 39-bus systems; computational impacts and quantifiable differences in maximum power transfer capabilities determined using the proposed approach and a conventional approach are discussed. [ABSTRACT FROM AUTHOR]

Highlights • Non-iterative algorithm for computation of the prospective permissible touch voltage is presented. • Computation is reduced to linear combination of permissible touch voltage and body current. • Body impedance dependence on the permissible touch voltage is replaced by body current dependence. • Grapho-analytical estimation and piecewise cubic Hermite splines are used. • The permissible touch voltage can be computed for chosen fault duration. Abstract The prospective permissible touch voltage computation algorithm can be found in the international standards and technical specifications. By combining values of the total human body impedance and values of the permissible body current, extracted from tables and figures, the relevant permissible touch voltage as a function of the fault duration is obtained using an iterative process. In this paper, a simple and robust non-iterative algorithm for computation of the prospective permissible touch voltage according to EN 50522 for chosen fault duration is presented. In proposed algorithm, computation of the prospective permissible touch voltage is reduced to linear combination of permissible touch voltage for a current path hand to hand and permissible body current. For chosen fault duration, permissible touch voltage for a current path hand to hand and permissible body current are computed using piecewise cubic Hermite interpolation and given sampled values of these functions and sampled values of their derivatives with respect to fault duration. [ABSTRACT FROM AUTHOR]

Highlights • Ιncreasing need for modern pricing schemes to effectively incentivize willing users to modify their energy consumption pattern. • Current energy pricing schemes do not adequately compensate for behavioral changes. • We propose a Community aware — Real Time Pricing (CRTP) scheme to reduce system's energy cost. • We propose an Energy Community Formation Algorithm (ECFA). • The proposed scheme achieves considerable reduction in the system's energy cost and greater aggregated users' welfare. Abstract The harmonization between the variable rate of energy production in the era of massive renewable energy penetration is a major challenge in an open, competitive and resilient electricity market. As a result, there is an increasing need for modern pricing schemes, which will effectively incentivize willing users to modify their energy consumption pattern to meet this objective. Current energy pricing schemes (e.g. real time pricing) treat all users the same, and do not adequately compensate for behavioral changes, thus mitigating the behavioral change dynamics. In this paper, we propose a Community Real Time Pricing (CRTP) scheme together with an Energy Community Formation Algorithm (ECFA), where users are clustered in Virtual Energy Communities (VECs) according to: (i) their level of flexibility in modifying their Energy Consumption Curve (ECC), and (ii) their relationships in Online Social Networks (OSNs), modelling peer-pressure capabilities. We show that CRTP with ECFA can simultaneously achieve considerable reduction in the system's energy cost and greater aggregated users' welfare than with the state-of-the-art real time pricing. CRTP–ECFA adopts a truly fair pricing policy, as each user is rewarded exactly according to his/her individual contribution in reducing system costs, thus promoting the desired behavioral change. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • An original OLTC model has been introduced that benefits from the arc modeling concepts of CB. • A new arcing power-based algorithm has been introduced for condition monitoring of OLTCs. • The proposed algorithm uses the power difference between terminals of transformer to calculate the arcing power of OLTC contacts. • The proposed algorithm determines the electrical wear of OLTC's contacts for estimating the maintenance schedule of OLTC contacts. Abstract An on-load tap-changer (OLTC) regulates the output voltage level of transformer by changing the winding voltage ratio without current interruption. It is one of the most expensive and vulnerable parts of power transformers. Therefore, modeling and condition monitoring (CM) of OLTCs are important for the power system operation. This paper presents a new modeling principle for OLTCs based on the circuit breaker (CB) arc models. There is a sequence of switching events with certain timings during each operation of OLTC. These switching operations are modeled individually and a full model of OLTC operation is derived. Computer simulation studies and the measurements captured from the real-time test studies of OLTC operation verify and validate the performance of the proposed OLTC model. On the other hand, the instantaneous differential power of tap-changing transformer measured from its input and output terminals is used to calculate the arcing power and energy associated with OLTC operation. The cumulative arcing energy is a good indication of the electrical wear of OLTC contacts. Therefore, it is used to propose a novel CM algorithm for OLTCs. The proposed method considers the effects of both arcing voltage and current signals to accurately estimate the arcing energy. The results obtained from computer simulation studies demonstrate that the proposed algorithm accurately evaluates the electrical wear of OLTC contacts and determines the inspection or maintenance schedules of OLTC contacts. [ABSTRACT FROM AUTHOR]

Highlights • The dual-level control scheme can meet the frequency regulation requirement and the individual PEV charging requirements. • The consensus algorithm is applicable for distributed control areas and PEVs power coordination with limited communication: every control area/PEV only needs to exchange information among the neighboring control areas/PEVs instead of all the agents. • This method can be applied in real-time simulation. The optimal charging commands can be obtained and updated in every time step based on the current frequency deviation condition and electricity price. Abstract To coordinate plug-in electric vehicles (PEVs) to support the primary frequency control, this paper presents a dual-level consensus-based frequency control method. The upper-level control aims to minimize the frequency deviation of multi-area power system, and the lower-level control aims to minimize the frequency regulation cost and battery degradation cost for individual PEVs. The incremental cost functions are formulated based on the objectives of the dual control levels, in this case, no objective function needs to be solved, and instead, the optimal results can be achieved by reaching a consensus incremental cost among neighboring individuals. The graph theory is applied to build the communication network among neighboring control areas in upper-level control, and among neighboring PEVs in lower-level control. The consensus algorithm is applied to specify the information updating and exchange among neighboring individuals. In addition, the dynamic models of multi-area power system and PEVs are developed for controller implementation and investigation. The simulation with different case studies are conducted to validate the performance of the proposed dual-level frequency control. The simulation results show that, with limited communication, the connected PEVs can be efficiently coordinated via dual-level controller to provide primary frequency regulation service, and meanwhile meet the battery charging/discharging constraints. [ABSTRACT FROM AUTHOR]

Highlights • The modified Distributed Gradient Projection algorithm with a constant step size can handle non-strictly and convex consumer costs. • We establish a bound on the step size such that the algorithm behaves in a stable manner. • Numerical tests with the IEEE 39-bus system show that predictions are still accurate even when consumer costs are non-convex. • The algorithm is robust to model mismatch and time delays. • Its performance suffers if the dynamic response of the loads is slow. Abstract The Distributed Gradient Projection (DGP) algorithm was proposed in prior work to allow loads to provide contingency service to the grid using local noisy frequency measurements by varying their demand. Convergence of DGP was established in prior work for a decaying step size. In this paper we modify the algorithm to using a constant step size—constant step size being much more useful for practical implementation. We provide a convergence analysis of the modified algorithm, which we call DGP-C (DGP with Constant step size) and perform extensive simulations in the IEEE 39-bus test system. These studies (i) demonstrate that the DGP-C algorithm is robust to several assumptions made in the analysis and (ii) reveal which factors among the many tested (measurement noise, loads' response time, etc.) have significant effect on the algorithm's performance. [ABSTRACT FROM AUTHOR]

Highlights • A new intelligent hybrid three-stage model is proposed for simultaneous load and price forecasting. • The proposed algorithm uses wavelet and Kalman machines and Kohonen self-organizing map. • The second stage uses Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System. • The proposed algorithm was applied to Nordpool and mainland Spain power markets. Abstract Short-term load and price forecasting is an important issue in the optimal operation of restructured electric utilities. This paper presents a new intelligent hybrid three-stage model for simultaneous load and price forecasting. The proposed algorithm uses wavelet and Kalman machines for the first stage load and price forecasting. Each of the load and price data is decomposed into different frequency components, and Kalman machine is used to forecast each frequency components of load and price data. Then a Kohonen Self Organizing Map (SOM) finds similar days of load frequency components and feeds them into the second stage forecasting machine. In addition, mutual information based feature selection is used to find the relevant price data and rank them based on their relevance. The second stage uses Multi-Layer Perceptron Artificial Neural Network (MLP-ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) for forecasting of load and price frequency components, respectively. The third stage machine uses the second stage outputs and feeds them into its MLP-ANN and ANFIS machines to improve the load and price forecasting accuracy. The proposed three-stage algorithm is applied to Nordpool and mainland Spain power markets. The obtained results are compared with the recent load and price forecast algorithms, and showed that the three-stage algorithm presents a better performance for day-ahead electricity market load and price forecasting. [ABSTRACT FROM AUTHOR]

Highlights • Modelling of magnetic coupling for perfect parallelism between the power line and pipeline. • Passive loops configuration is proposed to reduce the magnetic coupling generated by HV power line. • An optimization algorithm is applied to improve the mitigation efficiency for magnetic coupling. • The performance of the passive loops is evaluated by conductive/ferromagnetic shields. • The obtained results are validated and a good correlation is reached. Abstract This paper proposes a methodology based on Faraday's electromagnetic induction law (EMF) for evaluating the induced voltage produced by high voltage power line on an aerial metallic pipeline located parallel in its immediate vicinity under normal operating condition. It also describes the procedure of the induced voltage mitigation using the passive loop technique combined with the particle swarm optimization algorithm (PSO). The presence of a pipeline in the vicinity of an overhead power line strongly disturbs the mapping of the magnetic induction produced by this power line. The mitigation efficiency is significantly improved by optimizing the position of the loop conductors, by increasing the number of loops and the use of a shielding magnetic material of high relative permeability. The obtained simulation result is compared with that obtained by the Carson's formulas. A good agreement was obtained. [ABSTRACT FROM AUTHOR]

In this paper, a new algorithm based on harmonic signatures is proposed to detect extinction of secondary arc for single-pole auto-reclosing (SPAR). In the proposed algorithm, the TT-transform is used to highlight harmonics of healthy phase voltages. The criterion for the detection of extinction of secondary arc is harmonics amplitudes, which is calculated after the TT-transform. The algorithm is noncommunication and the threshold value is adaptive; therefore, for various transmission systems no special adjustment is needed. To evaluate the accuracy of the proposed scheme, numerous simulations under different conditions including fault location, fault inception angle and line compensation are performed, in all of which the highest reliability is achieved. [ABSTRACT FROM AUTHOR]

Fault section diagnosis (FSD) of power systems plays an important role in power system operation. In order to quickly and accurately diagnose the fault section or sections after the occurrence of an event, a novel variant of brain storm optimization (BSO) in objective space algorithm, referred to as BCBSO (binary coded BSO), is proposed in this paper. The FSD problem is transformed into a 0–1 integer programming problem. The difference between the reported alarms and the expected states of protective relays and circuit breakers is used as the objective function. In BCBSO, each population individual is directly encoded as a binary vector and thereby the transcoding process can be avoided when solving the 0–1 integer programming problem. In addition, logical operations instead of floating operations are employed for binary strings, making the evolutionary process more convenient. In order to verify the performance of BCBSO, three test systems, i.e., the typical 4-substation power system, IEEE 118-bus system, and a practical power grid in Jilin province of China with different fault scenarios including single fault and multiple faults with failed and/or malfunctioned protective devices are employed. Six popular metaheuristic methods including ABC, BBO, DE, GA, PSO, and BSO are utilized to validate the effectiveness of BCBSO. The experimental results comprehensively demonstrate the superiority of BCBSO in terms of successful rate, diagnosis error, robustness, computation efficiency, convergence speed, and statistics. In addition, the effect of population size is investigated as well. [ABSTRACT FROM AUTHOR]

Renewable energy-based multi-energy supply microgrids are expected to play an important role in smart cities. How to schedule such microgrids in grid-connected mode and dispatch power among sources inside the microgrids is a problem. Moreover, as electric vehicles are becoming more and more common, the charging of large numbers of vehicles is also a challenge for the utility grid. In this paper, we build a temporal-spatial electric vehicle charging demand model, which includes three parts: trip plans, duration of stay, and search for the shortest path based on the Dijkstra algorithm. Then, we build a grid-connected gas/electricity/heat microgrid and present a coordinated scheduling method for this microgrid. A day-ahead scheduling method is used to decide the role of the microgrid (i.e., operate as a load or as a generator from the point of view of the utility), a real-time rolling-horizon dispatching algorithm is used to respond to the forecasting errors and at the same time implement the real-time actual power exchange between the microgrid and the main grid. The problem is formulated as a mixed integer linear programming problem. The temporal-spatial electric vehicle charging demands model is simulated based on a 81-node transportation network, while the energy supply network is a combined IEEE-30, gas-20 and heat-14 network. The simulation results show the effectiveness of this coordinated scheduling method. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to detect and classify the power quality disturbance (PQD) signals based on singular spectrum analysis (SSA), curvelet transform (CT) and deep convolutional neural networks (DCNNs). SSA is a non-parametric technique, does not require any supposition to generate the observed signal, and provides an effective way to recognize weak transient PQ signal. Fast discrete curvelet transform (FDCT) is an efficient method compared to wavelet transforms. Firstly, PQD signals are decomposed using SSA and FDCT methods. Initial six and three levels decomposition of the SSA and FDCT are used as features of PQD respectively. Finally, DCNNs based classifier and multiclass support vector machines (SVMs) classifier are used for classification of single and complex PQDs. For validation of the proposed algorithm, thirty-one categories of real and synthetic PQD waveforms are considered. The proposed scheme is tested and the results are recorded. The results of proposed SSA-FDCT-DCNN (SFD) based classifier are compared to the results of multiclass SVM based and other existing methods The achieved results show that the SFD classifier is more proficient than the multiclass SVM and other present methods. In addition, the proposed SFD based classifier can be efficiently used to classify the single and complex PQ disturbances. [ABSTRACT FROM AUTHOR]

This paper presents a wavelet-alienation based protection scheme for multi-terminal transmission system. The proposed algorithm makes use of wavelet transform based approximate coefficients of three-phase voltage and current signals, obtained over a quarter cycle to detect, classify and locate various faults. Detection and classification of faults are achieved with the help of approximate coefficients based alienation coefficients of current signals, measured from all the buses of system. The approximate coefficients of voltage and current signals, obtained over a quarter cycle, are fed to artificial neural network to locate the faults precisely, from respective buses. This algorithm has been tested successfully for all the types of faults with variations in location, inception angle and fault impedance. The proposed protection scheme is generalized for N-terminal system followed by successful testing on three-terminal and five-terminal systems. [ABSTRACT FROM AUTHOR]

The spread of distributed generation systems has reinforced concerns and requirements on grid-tied power converters. The synchronization with the utility voltage vector is a major concern. In the literature, algorithms based on Phase Locked Loops are extensively presented. In spite of adequate performances under ideal and balanced grid conditions, under grid faults great inaccuracies arise. Shortcomings are overcome by advanced algorithms at the expenses of the complexity and computational cost. In this paper, grid synchronization algorithms are addressed. A solution is proposed by introducing a new post-filter stage in a Decoupled Double Synchronous Reference Frame not affecting, at the same time, the complexity of implementation, the detection time and damping of the conventional DDSRF solution. The post-filtering stage design criteria are described based on a mathematical derivation of the phase error in a conventional DDSRF algorithm under distorted grid utility. A comparison of system performances with the conventional DDSRF algorithm is carried out under distorted, balanced and unbalanced utility conditions, validating the benefits brought by the proposed solution. [ABSTRACT FROM AUTHOR]

In this paper, a novel PWM carrier synchronization method is proposed for distributed DC–DC converters in DC-Microgrids. The synchronization method is based on carrier frequency extraction from DC-bus voltage ripple. In addition, an advanced phase shift control algorithm for the synchronized carriers is implemented to reduce the DC bus voltage ripple contents. A DC-Microgrid encompassing different distributed energy resources with their DC–DC converters is modeled using Matlab\Simulink to test the proposed synchronization method and control algorithm. Then, a small power scale experimental testbed is built in order to validate the simulation results. The simulation and the experimental results demonstrated that the proposed method and algorithm are very promising to minimize DC-bus ripple contents in DC-Microgrid applications. [ABSTRACT FROM AUTHOR]

This paper presents the design of proportional integral derivative (PID) based load frequency control (LFC) scheme effectively optimized through novel combination of bacteria foraging oriented particle swarm optimization (BFO-PSO) technique for a hydro dominating energy system model. The design control are implemented for 1% load disturbance in area-1 and compared with classical PID, Pessen integral rule, some overshoot, no overshoot as well as with recently published bacteria foraging optimization algorithm (BFOA) in terms of computed gains and inverse time multiplied absolute error (ITAE). The system performance for hydro energy system is sluggish and oscillatory. Hence, the further enhancement with proposed design are observed by considering the combination of unified power flow control (UPFC) in series with the tie-line and hydrogen aqua electrolyzer units installed at terminal of area-2. The system performance of the designed control is evaluated under various system investigations considering the dead-band and generation rate constraint (GRC) non-linearity and the applications results are presented to show the superiority of the proposed work. [ABSTRACT FROM AUTHOR]