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An accurate model of electric arc furnaces (EAFs) is required to analyse their impact on the system's power quality. One of the well‐known approaches to model EAF is using the power balance equation. This model has two terms, each one has a coefficient named the model parameter. Also, both terms are powered to values, which are called model orders. So, the model includes two model parameters and two model orders. Model orders highly affect the modelling precision. The optimum model orders have not been obtained yet in previous studies. Here, based on many actual records from EAFs, the best model orders for refining, melting, and scrapping stages are attained. Unlike the original power balance equation which has constant model parameters, the first proposed model uses the attained optimal model orders with the time‐varying model parameters. In the second proposed model, the model orders are also considered time‐varying. Model parameters, which are updated every 10 ms, are obtained using autoregressive moving average (ARMA) models. The correctness of the models is assessed by calculating some important electric quantities using the actual data and the proposed models. Finally, the time‐varying parameters are generated using two MATLAB codes. [ABSTRACT FROM AUTHOR]

Optimal coordination of the protection devices (PDs) is performed here simultaneous with optimal allocation of them and the DGs. The PDs are a set of directional overcurrent relays (DOCRs) and voltage relays, each with its own fast switch (FS). In previous optimal DG placement studies the coordination of the PDs has been considered as a constraint. So, it was not possible to optimal coordination of the PDs simultaneously. In the present study, the coordination between the PDs is considered in calculating the value of the energy not supplied (ENS) that is a part of an overall cost function. The cost function considered here includes cost of purchase, installation, and maintenance of the DGs and the PDs, cost of the energy losses, cost of the ENS, cost of the purchased energy from the main grid and the DGs, and the penalty cost for emitting environmental pollutants. Here, output of the renewable DGs and the network loads during the year, in a 96‐h model, has been considered as variable. To solve the desired optimization problem, an algorithm based on evolutionary algorithms such as genetic algorithm (GA) is proposed. Finally, various cases have been simulated by considering a standard 33‐bus radial network. [ABSTRACT FROM AUTHOR]

The algorithms of the present generation of practical differential relays are based on two methods. The first method is based on the ratio of the harmonic content of the differential current, and the second one is based on the length of the time interval between the zero‐crossing points of the differential current, called the gap‐detection method. However, these methods suffer from the installation of the fault current limiters (FCLs) in the power system and current transformer (CT) saturation phenomenon. This paper deals with a simple practical method for differential relays to secure their performance. In the suggested method, a classifying algorithm is used to categorize the input signal of the relay and then the best method of the present generation of differential relays is employed. By this simple decision, the method takes the advantage of harmonic‐based and gap‐detection methods, while avoiding their drawbacks. To prove the robustness of the suggested method, a test bench with a resistive solid‐state fault current limiter (SSFCL) is implemented and examined in different situations. The results validate the consistency and the accuracy of the modified technique not only in the absence and the presence of the FCL but in the case of CT saturation. [ABSTRACT FROM AUTHOR]

Electric arc furnace (EAF) is one of the most disturbing loads in the power system as it is highly time‐varying and nonlinear. In this paper, new models based on the instantaneous EAF voltage and current, recorded from EAFs in Mobarakeh steel company in Isfahan/Iran are proposed. The focus of this paper is on developing efficient models based on the Schwarz model where three modified types are proposed. The original Schwarz model has four constant parameters. Unlike the original Schwarz model which uses invariant parameters, the time‐varying nature of the arc's parameters is considered in the proposed models. The first modified model has two constant model orders and two time‐varying coefficients. Additionally, to further enhance the model's accuracy, in the second modified model, six parameters include three constant model orders, and three time‐varying coefficients exist. The third model uses all the original model's parameters as time‐series parameters. The parameters of the time‐varying model are derived using autoregressive moving average (ARMA) models. The accuracy of the proposed model is evaluated by calculating the active power, harmonics, instantaneous flicker, and short‐term flicker. Finally, three MATLAB codes are provided to generate the model parameters time series. [ABSTRACT FROM AUTHOR]

Since the penetration level of the inverter‐based distributed generations (IBDGs) into microgrids (MGs) is increasing, the protection issues of such networks have become more challenging. The present work aims to design a protection framework for fault detection and classification in IBDG dominated MGs. In the proposed approach, the current waveforms measured from one end of the protected lines are processed using superimposed components. Then, the faults are identified using the Euclidean distance concept. A Pearson correlation coefficient‐based approach is also developed to characterize the faulty phases in the proposed fault classification unit. Furthermore, an auxiliary index is defined to discriminate load change conditions from the faults. In addition to being simple and efficient, the proposed technique is highly capable of functioning in different MG operating modes and configurations without changing its settings. Also, it demonstrates robust performance against IBDG impacts, noises, and stimulating fault scenarios. To assess the scheme proficiency, a modified IEEE 15‐bus system with highly penetrated IBDGs is simulated. The results confirm the quickness and high accuracy of the proposed technique. Moreover, the method is validated in an experimental laboratory test bench. Finally, the superiority of the method is confirmed by a comparative study with other recent methods. [ABSTRACT FROM AUTHOR]

Accurate modelling of the Electric arc furnace (EAF) is necessary to study its impact on the power systems. Here, a new model for the EAF is presented in which both non‐linearity and time‐varying characteristics are taken into account. The model consists of seven parallel current sources which represent the fundamental and harmonic currents. Magnitude and phase of the fundamental harmonic and magnitude of the second to seventh harmonics are considered as time‐varying which are updated every 0.01 s. To do so, the actual data recorded from eight EAFs in the Mobarakeh steel company (MSC), Isfahan, Iran are used. Autoregressive moving average (ARMA) models are employed to derive the parameters of the time‐varying model. Also, different orders and coefficients of the ARMA model are considered at each run of the model, which enables the proposed model to predict the non‐stationary and stochastic behaviours of the EAF over long‐time periods. It is shown that the proposed combined time‐varying‐harmonic model can even model the generated inter‐harmonics. To evaluate the accuracy of the proposed model, the derived power spectral density (PSD) of the EAF time‐varying parameters, the instantaneous flicker, and short‐term flicker by the proposed model are compared with the actual recorded data. [ABSTRACT FROM AUTHOR]

Expansion of cogeneration technologies, such as combined heat and power units, has boosted the growth of multi-carrier energy systems. A two-step method is presented to enable residential demand response (DR) programmes in the multi- carrier energy systems. In the first step, the energy management system at each home solves an optimisation problem to achieve the desired energy cost and demand schedule for the customer according to received price signals. In the second step, the system operator revises the demand scheduling by running another optimisation problem to minimise the total electrical losses, subject to the operational characteristics of electrical and natural gas systems. In order to persuade customers to participate in the DR programmes, it is guaranteed that the resulted cost of the second step is not more than the desired cost of the customer in the first step. Results of applying the proposed method, incorporating different penetration levels of customer participation in a time-of-use programme is studied in a test energy system. Simulation results verify the effectiveness of proposed method in minimising the total electrical losses, improving the operational characteristics of the energy system as well as providing customers' utilities. [ABSTRACT FROM AUTHOR]

In power grids, directional relays are used in situations that direction of fault current is not fixed. Distribution networks including distributed generation (DG) resources and transmission networks are some of these situations. Directional relays as key elements of distance and over current relays provide selectivity for these protections to improve their performance and power systems stability. In this study, a directional algorithm is proposed, which is able to discriminate fault direction just by sign of imaginary part of post-fault current phasor. To evaluate the algorithm, plenty of simulations and experiments are carried out in different fault conditions. Moreover, impact of power flow direction at normal operation of the power system is considered in the evaluation of the algorithm. Also, its performance is compared with some other directional algorithms. The results confirm that the proposed algorithm is able to detect fault direction with high degree of accuracy. Moreover, simplicity of the algorithm represents its competence for practical implementation in transmission and distribution networks. [ABSTRACT FROM AUTHOR]

The output active and reactive powers of wind farms are highly time-varying even in extremely short time periods which cause flicker. In many wind farms static VAr compensators (SVCs) are employed to mitigate this flicker. In this study it is shown that reactive power variations of wind farms are even faster than those which can be fully compensated by SVC. This inability of SVCs comes from the delays in the reactive power measurement and thyristor ignition circuit. To overcome this limitation, the reactive power of a wind farm is predicted for a half cycle (10 ms) ahead. Large numbers of data were recorded from the Manjil wind farm in different weather conditions. Auto regressive moving average (ARMA) models were used for the prediction, and model adequacy checking was employed to determine the best ARMA model order. To evaluate the performance of proposed method, with a novel procedure the wind farm is simulated using the actual recorded data. The instantaneous flicker sensation and short term flicker were calculated and compared for three cases; without SVC, using SVC with the traditional control method, and using SVC with the proposed prediction method. The results confirm the superiority of the proposed technique. [ABSTRACT FROM AUTHOR]

In power grids, directional relays are used in situations that direction of fault current is not fixed. Distribution networks including distributed generation (DG) resources and transmission networks are some of these situations. Directional relays as key elements of distance and over current relays provide selectivity for these protections to improve their performance and power systems stability. In this study, a directional algorithm is proposed, which is able to discriminate fault direction just by sign of imaginary part of post‐fault current phasor. To evaluate the algorithm, plenty of simulations and experiments are carried out in different fault conditions. Moreover, impact of power flow direction at normal operation of the power system is considered in the evaluation of the algorithm. Also, its performance is compared with some other directional algorithms. The results confirm that the proposed algorithm is able to detect fault direction with high degree of accuracy. Moreover, simplicity of the algorithm represents its competence for practical implementation in transmission and distribution networks. [ABSTRACT FROM AUTHOR]

There are many different techniques for discrimination between inrush current and internal faults. However, due to their inherent limitations, the methods have not reached a practical level yet, and the conventional methods are still widely employed in practice despite of their well‐known shortcomings. Current transformer saturation and large inrush currents are the most reported cause of the discrimination algorithms mal‐operation. This paper deals with an efficient approach to discriminate internal faults from switching conditions in the power transformers which can solve these problems. The proposed method is based on utilising the feature of the non‐saturation zone. The performance of the proposed method is tested using the simulations data besides to data collected from a prototype laboratory three‐phase power transformer. Also, the proposed method is evaluated and compared with some well‐known discrimination schemes including conventional and some new presented schemes by the same simulation and experimental data sets. The results validate the consistency and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

Electric arc furnace (EAF) is one of the largest loads in the power systems. Unfortunately, it is highly non‐linear and time varying which causes power quality problems such as harmonics and flicker. Therefore, having an accurate EAF model is necessary. Cassie model is one of the most utilised EAF models in the related fields. However, actual data from electrical system of Mobarakeh Steel Company in Isfahan/Iran show that this model is unable to take into account some important quantities such as the active power and harmonics. Hence, as the first step in this study, different Cassie–Mayr model variants (include the Cassie model) are investigated and the best variant is attained. A novel procedure using large number of recorded actual data is utilised for the models assessment. In the second step, two generalised types of the original Cassie–Mayr model are proposed. Both the generalised types are more accurate than the best‐selected Cassie–Mayr variant. All the proposed models have time‐varying parameters. Their time‐varying nature is studied and by analysing the time series, the proper auto regressive moving average models are attained for every parameter. [ABSTRACT FROM AUTHOR]

Differential relays are the main protection for power transformers including transmission and industrial transformers. Protection against internal fault is generally relegated to these relays. The most probable internal fault of the industrial transformer is phase to ground type. To limit the fault current in this condition, a limiter resistor is utilised in the transformer. However, it has considerable impact on sensitivity of the differential and restricted earth fault (REF) protections. In this study, an effective approach is proposed to improve the differential and REF protections sensitivity of the industrial transformers. The proposed technique not only realises the fault current limitation function, but preserves sensitivity of the protections. In this method, a developed fault current limiter is utilised in the transformer neutral instead of the neutral grounding resistor. The performance of the proposed technique is evaluated by some simulations and experiments. The results confirm the high capability of the proposed technique in different conditions. [ABSTRACT FROM AUTHOR]

A simple technique is proposed in this study, aimed at the islanding detection of an inverter-based distributed generation (DG). The main advantage of the proposed technique is its reliance on a simple approach for islanding detection with negligible non-detection zone and keeping the unchanged output power quality. This work attempts to detect islanding conditions through computing the rate of change of voltage phase angle (ROCOVPA) of the point of common coupling by phase-locked loop (PLL) in inverter controllers. Because almost all inverter systems are equipped with the PLL, its implementation for inverter-interfaced DGs is simple and economical. Simulation results show that the durability energy of ROCOVPA is different for islanding and non-islanding conditions. In fact, in non-islanding condition the energy of ROCOVPA reduces to a negligible value after a certain time, but in islanding conditions it has considerable variation. The proposed method is evaluated using the conditions dictated by the IEEE 1547 and UL 1741 standards. The simulation results are presented to highlight the effectiveness of the proposed technique. In addition, the proposed method is compared with several passive and intelligent methods and it is confirmed that the proposed method has better performance and more accuracy. [ABSTRACT FROM AUTHOR]

A simple technique is proposed in this study, aimed at the islanding detection of an inverter‐based distributed generation (DG). The main advantage of the proposed technique is its reliance on a simple approach for islanding detection with negligible non‐detection zone and keeping the unchanged output power quality. This work attempts to detect islanding conditions through computing the rate of change of voltage phase angle (ROCOVPA) of the point of common coupling by phase‐locked loop (PLL) in inverter controllers. Because almost all inverter systems are equipped with the PLL, its implementation for inverter‐interfaced DGs is simple and economical. Simulation results show that the durability energy of ROCOVPA is different for islanding and non‐islanding conditions. In fact, in non‐islanding condition the energy of ROCOVPA reduces to a negligible value after a certain time, but in islanding conditions it has considerable variation. The proposed method is evaluated using the conditions dictated by the IEEE 1547 and UL 1741 standards. The simulation results are presented to highlight the effectiveness of the proposed technique. In addition, the proposed method is compared with several passive and intelligent methods and it is confirmed that the proposed method has better performance and more accuracy. [ABSTRACT FROM AUTHOR]

This study represents four new methods for fault zone detection in series‐compensated lines and compares them with each other and with some previous methods. Among the proposed methods, two methods are based on direct current component of voltages and currents, and operate using both line ends data. The third method uses only one end data and is based on the analysis of instantaneous current behaviour. The fourth method also uses one line end data and acts on the basis of instantaneous power waveform behaviour. The proposed methods, besides the three well‐known previous methods, are evaluated using a large number of simulated cases by power system computer‐aided design. The results verify the validation of the proposed methods. [ABSTRACT FROM AUTHOR]

The time varying nature of electric arc furnace (EAF) gives rise to voltage fluctuations, which produces the effect known as flicker. Employing reactive power compensation devices such as static VAr compensator (SVC) is one of the main approaches to mitigate this phenomenon. By utilising prediction methods to forecast EAFs reactive power consumption for a half‐cycle ahead, performance of SVC can be enhanced substantially. This study proposes a rolling Grey model and a Grey–Markov method to predict the actual reactive power of Mobarakeh Steel Company, Isfahan/Iran. To investigate the efficiency of the proposed methods the results are compared with the results of EAFs reactive power compensation when no prediction method is employed. Furthermore, autoregressive moving average (ARMA) models with updating coefficients, which are studied in the literature are used to predict EAF reactive power. Various methods for updating ARMA coefficients including normalised least mean square, recursive least square method and an online genetic algorithm are used. By comparing the indices which are defined using the concept of flicker frequency and power spectral density, the superiority of Grey–Markov and rolling Grey model over the aforementioned prediction methods is investigated. [ABSTRACT FROM AUTHOR]

Under frequency load shedding (UFLS) scheme has been widely implemented as a safety net to prevent system collapse following major disturbances which results in large mismatch between load and generation. However, voltage related issues post activation of UFLS stages are also vital concerns in preserving system stability and should be properly analysed. Fixed and switched shunt capacitors that are in service during normal operation for maintaining system voltage and dynamic MVAR reserve can generate surplus reactive power post operation of UFLS relays which may result in over voltage issues, generator under excitation and some undesirable conditions such as transformer saturation, ferro‐resonance etc. This study addresses the need for coordinated under frequency load and capacitor shedding and its implementation approach to effectively preserve system stability following small and large disturbances. To confirm the feasibility of the approach, the proposed method has been used to design coordinated UFLS and under frequency capacitor shedding (UFCS) schemes for a real and actual power network. In addition, the proposed coordinated UFLS and UFCS scheme has been combined with automatic switching of shunt reactors to optimise the performance of the scheme. [ABSTRACT FROM AUTHOR]