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This paper presents the optimal scheduling of active distribution network (ADN) with linear and non‐linear loads in the presence of an integrated unit of electric spring and electric vehicle parking lot (IUEE). The proposed scheme is formulated in the form of three‐objective optimization, which minimizes the expected operating cost of the ADN, voltage deviation function (VDF), and the total harmonic distortion (THD) of the voltage in separate objective functions. Constraints include harmonic power flow (HPA) equations, operation and power quality limits, and operation model of the IUEE. This scheme has uncertainties of load, energy price, and energy demand of EVs, which are modelled here using stochastic programming. Next, the sum of the weighted functions method as a subset of the Pareto optimization technique is adopted to extract the integrated single‐objective problem. Then, Sine‐Cosine Combined Algorithm (SCA) and Gray Wolf Optimization (GWO) are used to achieve an optimal solution. In the end, by examining the numerical results obtained from the implementation of the proposed scheme on a 69‐bus ADN, the capability of the design in enhancing the economic situation, operation, and power quality of the ADN compared to network power flow studies obtained by optimal scheduling of the IUEE is confirmed. [ABSTRACT FROM AUTHOR]

Power management in microgrids is a major challenge due to its low total inertia and capacity. The lower the microgrid generation capacity is, the higher the share of each generation unit in total power will be, and the higher the frequency deviation in less time will be when an outage occurs. So, preventive actions can be more reasonable and affordable than corrective actions for microgrid power and frequency control. In this regard, a new primary frequency response-constrained unit commitment model is presented here to prevent excessive frequency deviations by more commitment of higher inertia power plants and more contribution of renewable energy resources or energy storage systems' fast inertia response. To have a mixed-integer linear programming model, the primary frequency response constraints are linearized. The model is solved by the combination of two commercial solvers named MOSEK and YALMIP in the MATLAB 2018 environment. The proposed model is examined on a real isolated microgrid (an island). The results show that by activating the primary frequency support of distributed energy resources, the power can be managed with lower costs because there will be less need to start up fast (and expensive) gas turbine generation units. In addition, although comparing the model with others shows the more expensive management procedure, better frequency stability is obtained in contingencies. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive characteristic for eliminating the adverse effects of fault resistance and static synchronous compensator (STATCOM) on the performance of distance relays in transmission line and collector lines of doubly‐fed induction generator (DFIG)‐based wind farms in the case of single‐phase‐to‐ground resistive faults. The proposed method improves the performance in distance relaying and maintains the coordination between relay pairs in the transmission line and wind farm collector lines. In this method, an adaptive coefficient that can modify the zone settings of conventional distance relays is added to their characteristic to improve the accuracy and coordination under the mentioned conditions. Using analytical relationships and numerical results from simulations in Matlab/Simulink environment, the efficiency of the proposed method is confirmed. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT)-based energy management systems (EMSs) are considered a new technology in which consumers can manage their electricity payments according to their preferences, such as reducing costs or increasing satisfaction. Each consumer has its own program for communicating with a central control unit. In addition, the central control unit that is responsible for energy pricing can access consumer information and network performance status through the IoT infrastructure. Therefore, technical analysis can be performed using big data to determine the optimal price in order to make a compromise between the buyer and the goals of the distribution system operators. This paper presents a model to accurately assess the impact of pricing on the behavior of IoT-based energy systems. Then, according to the load specifications of each item and the technical limitations of the distribution network, the best time to use pricing is determined. The results show that the higher the price variance, the more discomfort the consumer and the lower the daily payment. Therefore, in this paper, the main goal of energy management is to minimize the total weight of the costs paid and their discomfort level. The paper could facilitate further penetration of IoT-based EMSs into smart grids. The study was performed on an IEEE standard 33-bus network. Optimization was implemented using YALMIP and MOSEK toolboxes. Therefore, it can be concluded that IoT technology allows consumers to enjoy the benefits of the network and makes optimal consumption management possible. [ABSTRACT FROM AUTHOR]

An accurate inter‐circuit fault location algorithm for double‐circuit transmission lines compensated by a generalized unified power flow controller based on phasor analysis is presented. The proposed algorithm utilizes synchronous currents and voltages of the buses on both sides of the line to accurately calculate the fault location. Using the equations of sequence component circuits, the algorithm calculates voltage and current of the fault point on both circuits. Then, using boundary conditions equations for 98 types of inter‐circuit fault on the double‐circuit transmission lines, the accurate location of the fault is obtained. The number of boundary conditions equations varies depending on the type of faulty phases of the two circuits and the number of unknowns in the current and voltage equations of the fault point. The calculation of these boundary equations are also described. The results presented in the simulation section verify the validity and accurate performance of the proposed algorithm under different fault conditions. [ABSTRACT FROM AUTHOR]

Network reconfiguration (NR) has undergone new changes to adapt to smart grid evolution. Internet of things (IoT) has found its way to smart grids especially in the distribution systems. Demand‐side management can be more efficient in the presence of IoT. IoT‐based energy management systems can have bidirectional communication with smart grids and decide according to their preferences, time‐of‐use (TOU) pricing, and their flexible devices. Therefore, customers would consume electricity more interactively. Consequently, the total load profile will be changed and a new NR approach must be adopted to meet load demands. So, the selection of critical switches must be modified to achieve the most effective network resource utilisation. For this purpose, a mixed‐integer linear programming model for feeder reconfiguration is presented considering the customers' behaviours in the IoT environment. At first, the customer manner is investigated at different prices and preferences. Then the total load profile is calculated considering the normal distribution of uncertain customer preference factors. Finally, the identification of critical switches is obtained using the proposed method. The optimisation is done in YALMIP and MOSEK toolboxes. Results show the effectiveness of the proposed method to efficient utilisation of IoT potentials and renewable energy benefits. [ABSTRACT FROM AUTHOR]

In this paper, a bi‐level power management strategy is presented for an active distribution network (ADN) in the presence of virtual power plant (VPP). In the proposed strategy, VPP contains renewable energy source (RES), energy storage system (ESS) and electric vehicles (EVs) parking lot coordinated with VPP operator (VPPO), and there is a coordinated framework between VPPO and distribution system operator. The proposed power management strategy (PMS) is considered in the context of the bi‐level optimization problem. In the first level, the optimal harmonic power flow formulation of the ADN is considered by minimizing the summation of energy cost, voltage deviation function and voltage THD% as a normalized objective function. In the second level, the VPP is modeled according to the framework of day‐ahead energy and ancillary services markets. In the next step, the linear format of the proposed non‐linear original problem is obtained with an optimal solution and low calculation burden. Also, the Karush‐Kuhn‐Tucker condition is used to convert the proposed bi‐level PMS approach to a single‐level model, and the scenariobased stochastic programming models the uncertainty of load, energy price, RES power, and EVs demand. Finally, the proposed strategy is applied on the 33‐bus distribution network using GAMS software. [ABSTRACT FROM AUTHOR]

In this study, on the basis of a new agent‐based situational awareness platform, the amount of severity in closeness to voltage instability occurrence is determined. In the proposed platform (with the aid of the agents of the disturbance detection unit that are responsible for perception of environmental events and understanding the current situation and the agents of the early enough instability prediction unit that predicts instability occurrence), the novelty is in creating the agents of clustering units that are responsible for prediction of the future status, i.e. severity in closeness to voltage instability occurrence through determining the severity class. This clustering unit maps the reactive power‐based features obtained from unconstrained power flow analyses, to the instability time; without any need of post‐disturbance data, i.e. the method belongs to just‐after‐disturbance algorithms. Then, it estimates the severity of the closeness to instability for any test scenario according to its membership degree related to the pre‐defined severity clusters. The simulation results show acceptable overall accuracy (up to 99%) in performing early warning task for operators of power systems. [ABSTRACT FROM AUTHOR]

In this study, a simple, fast, and adaptive network reduction procedure is presented for long‐term voltage stability analyses, to speed up the simulation time. The proposed procedure consists of two parts including disturbance detection based on data from synchronised measurement devices; and the rest, up to the final estimated values, based on simulations and calculations. In turn, simulations and calculations result in an adaptive dynamic‐oriented determination of external sub‐network (according to the disturbance occurred) and substituting an appropriate equivalent for that subsystem. The external subsystem is determined without any need to measure post‐disturbance data, while the detection criteria are calculated by simulations at 0.8 s after disturbance occurrence. The results have shown considerable reduction in the simulation time while providing acceptable accuracy in delivering the time of voltage instability occurrences, especially when applying the proposed error compensation procedure. [ABSTRACT FROM AUTHOR]

This paper deals with a control design based on amplitude adaptive notch filter (AANF) for a four-leg distributed static compensator (DSTATCOM) in a three-phase four-wire distribution grid to overcome current-related problems of power quality. Extracted reference currents of DSTATCOM are obtained using AANF because of its simple structure, exact measuring of frequency and amplitude, suitable estimation of the desired signal, and capability of tracking the changes of the input signal amplitude. To improve the dynamic performance of DSTATCOM, two fuzzy logic controllers are utilized to regulate DC link voltage and the voltage of point of common coupling (PCC). Furthermore, an adaptive hysteresis band current controller is applied for generating the gate pulses of IGBT switches. The proposed control scheme is robust to power system oscillations, especially when the main voltage suffers from disturbances and unbalancing. Different surveys are performed to study the efficacy of the proposed method, and results are verified through the simulation results in MATLAB/Simulink environment. [ABSTRACT FROM AUTHOR]

In this study, the proposed algorithm is a help for utilities to find out when voltage instability will happen, as soon as they realise that a disturbance may/will result in voltage instability. In this regard, the data gathered, on‐line, by a wide area monitoring system (WAMS) is supposed to be processed in an energy management system, where, finally, voltage instability inception time will be determined. The proposed algorithm employs k‐nearest neighbour algorithm as an instance‐based learning algorithm. This estimation uses only pre‐disturbance information and exact disturbance data, so it is fast enough for real‐time applications. A comprehensive investigation of the input features has resulted in introducing the most appropriate feature set and the most effective search procedure in estimating the instability time. The simulation results show an acceptable accuracy in estimation of voltage instability time. [ABSTRACT FROM AUTHOR]

An ultra‐high‐speed, accurate and reliable algorithm is proposed in this study for the identification and faulted phases selection of inter‐circuit faults. For this purpose, modal components of current samples just before they arrive to the relay location are extracted. Teager energy operator is used here for the extraction of current travelling waves (TWs). The amplitude of the TWs in different modal components and their ratios in similar modal components are used for the inter‐circuit fault identification and finding the faulted phases. Test signals are simulated in PSCAD/EMTDC software and the algorithm is implemented in MATLAB. Results show that the proposed algorithm is a really ultra‐high‐speed algorithm which can be reliably used for the identification and classification of the inter‐circuit faults. [ABSTRACT FROM AUTHOR]

Considering the advantages of DC microgrids, the extension of the conventional AC distribution grid can be implemented using a DC microgrid. This justifies the realization of a hybrid AC/DC microgrid. In the present study, a new global solution is presented to improve the power quality and to fully compensate the reactive power of an AC microgrid using DC bus capacity while introducing a new design for a hybrid AC/DC microgrid. In the new design, back- to-back connections of two series and parallel converters, as well as the presentation of new controllers and simultaneous utilization of an earthing switch, are proposed. The proposed method guarantees the quality of the delivered voltage to consumers and the drawn current from the network according to the IEEE-519 and IEEE-1159 standards under different power quality problems (e.g., interruptions, sags, harmonics, and any variation in voltage/current signals from pure sinusoidal). Through the proposed design of the new hybrid AC/DC microgrid, as a new feature, the operation of the network in islanded mode can be achieved in accordance with power quality standards even in the worst load quality conditions. It should be noted that in common hybrid microgrids in islanded mode, the delivered voltage quality is proportional to the quality of the consumer's load current. Another possibility of the proposed design is the instantaneous VAR compensation of nonlinear and induction loads of consumers to keep the power factor of the distribution transformer close to unit value. Simulation results indicate that there are acceptable levels of compensation for different types of power quality problems. Total harmonic distortions and total demand distortions are below 3% in both the grid-connected and isolated modes of the hybrid AC/DC microgrid. [ABSTRACT FROM AUTHOR]

This paper presents a new hybrid islanding detection approach for microgrids (MGs) with multiple connection points to smart grids (SGs) which is based on the probability of islanding (PoI) calculated at the SG side and sent to the central control for microgrid (CCMG). The PoI values are determined using a combination of passive, active, and communication islanding detection approaches based on the utility signals measured at the SGs sides which are processed by discrete wavelet transform using an artificial neural network (ANN). If \textPoI{\rm{ANN}} is larger than the threshold value (indicating high possibility of islanding) then a more accurate approach based on fuzzy network is used to recompute it (\textPoI{\rm{FUZZY}}) where the fuzzy parameters are determined by an adaptive neuro-fuzzy inference system. In the proposed technique, an active islanding is only performed when PoI is high and the amplitudes of the disturb signals are proportional to \textPoI{\rm{FUZZY}}. Furthermore, if the PoI is not correctly received by CCMG, two auxiliary tests will be performed in the MG side to detect islanding. These tests include an intentional passive islanding detection in a short preset time and an active islanding detection with disturb signals proportional to the calculated PoI. Detailed simulations are performed and analyzed to evaluate the performance of the proposed method. [ABSTRACT FROM AUTHOR]

Due to the limited operations of three-phase machines in open-phase fault conditions, the multiphase induction generators are now introduced in high-performance power generation systems. In the case of six-phase induction generators, the operation with opened phases is associated with torque and consequently power oscillations even in steady state conditions. Previous works have reported different methods to reduce these oscillations but they only deal with sensored control issues. Therefore, this paper deals with on-line modification of a sensorless control system applied to a squirrel cage six-phase induction generator (SC6PIG) when one to three phases of the machine are lost. Designing ten different off-line Luenberger speed observers as well as ten control systems corresponding to the different possible fault types and switching between them as a function of a detection system is proposed in this paper. Furthermore, on-line imposing of the nonzero initial conditions induces a smooth switching between the observers as well as the controllers with minimum associated transient at switching instants. The proposed strategy is tested on a wind turbine simulator driven by a permanent magnet dc motor. The experimental results in healthy and faulty modes assess the validity of the proposed strategy. [ABSTRACT FROM AUTHOR]

This study proposes an intelligent traveling‐wave (TW)‐based protection algorithm for parallel transmission lines. In the proposed algorithm, Karenbauer's phase to modal transform is applied on three phase current signals. Teager energy operator is then applied on the modal components to extract TWs. First extracted TW of each modal component along with well‐designed fuzzy systems are used for internal fault identification and fault type classification. In order to find the fault location, the time difference between the first and the second TWs and the TW propagation speed are utilised. Test signals are generated in PSCAD/EMTDC software and the algorithm is implemented in MATLAB. Results show that the proposed algorithm is an ultra‐high‐speed algorithm for the reliable protection of parallel transmission lines. [ABSTRACT FROM AUTHOR]

The cuckoo search (CS) algorithm is a simple and effective global optimization algorithm. It has been successfully applied to solve a wide range of real- world optimization problem. In this paper, a modified CS algorithm is applied to determine the feasible optimal solution of the economic load dispatch problem considering various generator constraints. In order to solve the problem of being trapped into the local optima, a new mutation scheme, inspired by the DE/current-to-gr_best/1, is incorporated in standard CS to enrich the searching behavior and solution quality and to avoid being trapped into local optimum. In order to verify the performance of our approach, the proposed approach is tested with two power system cases consisting of 3, 6, 15, and 40 thermal units with generator constraints. State-of-the-art optimization techniques are compared with simulation results obtaining proposed method to illustrate the efficiency of the proposed method and to show that the improved CS could be used as a reliable tool for solving economic load dispatch problems with generator constraints. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]