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Summary: The continuous increase of the distributed energy resources (DERs) penetration levels leads to voltage stability problems in the distribution system. One of the approaches for the mentioned emerging challenge is the proper placement of automatic voltage regulators (AVRs). This paper investigates the optimal placement and sizing of AVRs in a distribution network by presenting a new modification of the teaching‐learning‐based optimization (TLBO) algorithm. The objective functions consist of minimizing the distribution system voltage deviation, energy generation cost, and electrical losses. The modification improves the convergence velocity and accuracy of the TLBO algorithm using the combination of mutation technique and quasi‐opposition‐based‐learning concept. This paper compares the performance of the proposed algorithm with other famous evolutionary algorithms. The test distribution system contains installed DERs that work more efficiently after the placement of AVRs based on the mentioned objective functions by the proposed optimization algorithm. The simulation results display the best optimization algorithms for AVRs placement with a significant level of less than 0.10 (ie, probability‐value). The proposed multiobjective optimization algorithm's considerable merit is the accuracy and convergence velocity in solving this specific optimization problem. [ABSTRACT FROM AUTHOR]

Summary The power grid constructed with electric power router (EPR) will have the ability of flexibly controlling the voltage and power flow on each line of the grid, which will be helpful to maximize the integration of the renewable distributed generation to the grid. Most of the current methods for transmitting energy depend on storage unit or large scale calculation, which are relatively difficult. To avoid these disadvantages, this paper proposed a two‐step routing strategy based on the improved shortest path method for DC power grid with EPRs. The improved shortest path method combines Shortest Path Faster Algorithm (SPFA) with depth first search (DFS) algorithm, which could handle the negative weights and the negative cycle issue in the graph of the power flow paths. The increase of the transmission line power loss and the EPR's power loss are taken as the weight for the path search method to evaluate the cost of the path. Applying the proposed method to each power demand and supply finally helps to obtain the current distribution of the whole grid. By analysis of typical scenarios, compared with the power flow distribution of traditional DC power grid, the one produced by the proposed strategy could improve the power transmission capability as well as reduce the maximum voltage drop in the network. Besides, this strategy introduces less power loss, than many other ways do, in power routing. The effectiveness of the rioting strategy is related to the configuration of the network. [ABSTRACT FROM AUTHOR]

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

Fast and accurate fault location methods will accelerate power system restoration process and then cause improvement on availability and reliability indices. Presenting a modified scheme in order to improve accuracy of impedance-based fault location method in electric power distribution systems (EPDS) equipped with distributed generation (DG) units is the main goal of this paper. To achieve this goal, an iterative algorithm is introduced to compensate load variations. Also, a method is presented based on forward/backward sweep load flow to consider loss in all laterals of EPDS. Then, fault location will be determined by using a comprehensive method that extracts a fifth-order algebraic equation for each type of fault. This method will be modified to consider the presence of DGs in EPDS. In this paper, all the specific characteristics of real distribution systems such as unbalanced nature of network and loads, different types of loads, presence of multi-phase laterals, and capacitive effects of distribution lines are taken into account. The proposed scheme uses only 1 measurement unit at the main substation and 1 measurement unit at the DG bus. In this paper, modified IEEE 34 node test system is simulated by using PSCAD/EMTDC software, and it is used as a test system to evaluate the performance of the proposed method. Different scenarios such as the effect of fault distance, fault type, different fault resistances, and measurement unit errors are evaluated. The results indicate usefulness and precision of the proposed scheme. [ABSTRACT FROM AUTHOR]

The global trends toward increasing clean and sustainable power generation have brought significant changes and developments in electrical distribution networks. The existing passive networks are being restructured to facilitate renewable distributed generations to ensure high degree of reliability of power supply to customers. A distribution system reliability assessment (DSRA) is crucial to analyze the risk and cost associated with power interruptions and take necessary preventive and corrective actions. This paper presents an approach to DSRA and carries out a comprehensive reliability assessment of an active distribution network (ADN) connected with solar, wind, and tidal energy sources. A multi‐state reliability model is developed, combining the Markov and well‐being frameworks to determine the reliability of a network energized by multiple renewable energy sources (RESs). The load point reliability and worth‐oriented indices, namely SAIDI, SAIFI, CAIDI, AENS, EENS, ECOST and IEAR, are evaluated to analyze the impacts of the three RESs on the reliability of the ADN. The paper also proposes two new metrics to estimate the benefits of adding RESs from the reliability worth and cost perspectives. The analyses have been carried out on the Roy Billinton Test System. The results show that the maximum reliability worth and cost benefits can be extracted from a combined operation of multiple RESs. A combination of solar‐wind‐tidal energy sources, therefore, can be an effective solution for countries having long coastlines to fulfill not only the sustainable energy goals but also to improve the grid's reliability and reduce the monetary losses incurred due to customer interruptions. [ABSTRACT FROM AUTHOR]

Summary: In an active distribution network (ADN), the optimal micro‐PMU (μPMU) placement problem (OμPP) determines the location set with the minimal number of μPMUs that make the system observable. However, most approaches that solve OμPP provide a single location set limiting electrical power monitoring planning flexibility. Therefore, this paper presents an approach based on nonlinear programming (NLP) for solving the OμPP. The objective of the approach is to provide multiple location sets for OμPP that provide flexibility to electrical power monitoring planning. New constraints of the presence of distributed generations (DGs), zero injection buses (ZIBs), and communication line unavailability are taken into account for OμPP formulation. The proposed approach is implemented on the IEEE 69 distribution feeder, Indian‐85 distribution feeder, and IEEE 123 distribution feeder. The results show that the proposed approach successfully provides multiple location sets with a minimal number of μPMUs. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a multi‐objective coyote optimization algorithm (MOCOA) is proposed for techno‐economic benefits of simultaneous placement of fault current limiters (FCLs) and distributed generation (DGs) units in distribution grids. The proposed MOCOA is employed for mitigating the loss of power in distribution lines, minimizing the fault current levels, minimizing the economic costs of FCL size, enhancing the total voltage stability index, and reducing the total voltage deviation. The MOCOA is enhanced by emerging the concept of pareto‐optimal dominance to store the distinguished solutions in each generation. Finally, TOPSIS, a technique is implemented to find the compromise solution to fulfill the operator requirements. Applications are carried out in three distribution systems. The simulation results show the great effectiveness of the proposed MOCOA in acquiring several alternatives with appropriate technical improvements in power losses, voltage stability, fault level reduction, and economical FCL size. [ABSTRACT FROM AUTHOR]

Summary: This paper proposes a novel control scheme for unified power quality conditioner (UPQC) to minimize voltage sag, swell, and total harmonic distortion (THD) in a distribution grid integrated with distributed generation (DG). UPQC is a power electronics module that can provide, both, series and shunt compensation simultaneously in a distribution system. The whole characteristic of UPQC is dependent on the embedded control algorithms, which are used for generating a reference signal. This work focuses on synchrosqueezing wavelet transform (SWT) based identification, detection, and control of power quality (PQ) events. SWT is a time‐frequency analysis method that analyzes multicomponent signals with oscillating modes. In this paper, first, SWT is used for the detection and identification of various kinds of PQ issues in the DG integrated grid. The SWT based identification scheme provides better resolution and increases the readability of time‐frequency representation. This work further explores to control the PQ issues through UPQC's enhanced compensation capabilities which utilize artificial neural network (ANN) with SWT based shunt controller. The effectiveness of the proposed method is validated through MATLAB/ SIMULINK simulations and is seen that ANN with SWT based controller is better performed in comparison to ANN based controller, in terms of accuracy, and also with respect to THD. Performance analysis of UPQC is carried out with ANN based controller as well as ANN with SWT based controller, under different voltage and current disturbances, in time and frequency domain. [ABSTRACT FROM AUTHOR]

Summary: Identifying maximum penetration level (MPL) of Solar Photo‐Voltaic Generation (SPVG) in the distribution system is crucial for system planners and network operators to keep the system parameters within the acceptable limits. This paper provides a systematic and extensive procedure for evaluation of MPL of SPVG and its enhancement methods in distribution systems. More importantly, it illustrates a novel algorithm for affixing the penetration cap of Solar PV. The methodology initially derives a new stability index for locating SPVGs in the system, including both active and reactive power support from SPVGs. The study shows the utility of redefining MPL of SPVGs by considering the reactive power injection through solar inverters also. Deviating from the practice of considering the conventional constraints of voltage rise and maximum loading for MPL estimation, the paper considers loss minimization as the major constraint. The algorithm has potential to identify distributed integration scenario of SPVGs compared to the limited number of placements in the extant algorithms. This paper provides a novel algorithm to evaluate of maximum penetration level (MPL) of solar photo voltaic generation (SPVG) and its enhancement methods in distribution systems. The utility of redefining the MPL of SPVG by considering the reactive power injection through solar inverter is illustrated. The algorithm has distinct advantages over the extant algorithms in identifying a distributed integration scenario. [ABSTRACT FROM AUTHOR]

Summary: The development of power systems and the move to smart grid have increased the need for new technologies. In this regard, solid‐state transformers have been proposed as a suitable alternative to conventional transformers. Solid‐state transformers are among the equipment based on power electronic converters that in addition to better performance than conventional transformers provide a variety of other services. In this article, the concept and types of solid‐state transformer topologies and configurations and their applications, especially in smart grid, are investigated. Studies show that the various characteristics of solid‐state transformers have led to much consideration as potential transformers in smart grid applications, the integration of distributed generation sources, modern traction systems, and so on. [ABSTRACT FROM AUTHOR]

Summary: Reconfiguration is one of the most important functions in the distribution network's automation system. Reconfiguration is formulated as an optimization problem with a large number of scenarios, which demands high central processing unit time to check all of them. Therefore, it is necessary to utilize a high‐efficiency optimization method. In this paper, the minimization of active power losses, total voltage deviations of buses, and maximization of system loading margin are integrated as three objective functions of the proposed reconfiguration model. Also, to improve the voltage profile, reduce power losses, and increase system loading margin, shunt capacitors (SCs) and distributed generations (DGs) are located. Seasonal daily load curves are applied to better simulate networks' real conditions. This paper uses the nondominated sorting genetic algorithm II, which generates a set of nondominated solutions. This set includes a wide range of solutions with different weighting coefficients. The multicriteria decision‐making (MCDM) algorithm, as a powerful and flexible decision‐making tool, is utilized to select the best solution based on tuning parameters. Also, it is assumed that DGs are wind farms, thus the uncertainty of DGs' power output is taken into the account, and the three‐point estimate method (3PEM) is utilized to reduce the number of subscenarios generated by 3PEM. Finally, the subscenario aggregation method is utilized to extract the value of objective functions in subscenarios. The developed model determines the optimal location of SCs and DGs in conjunction with the optimal network reconfiguration. The proposed method is implemented on the typical 33 and 69 bus radial distribution systems. [ABSTRACT FROM AUTHOR]

Summary: This paper aims to advance the recently progressing research on solid‐state transformers (SST) and examines the impact of uncertainty on load demand and distributed generation (DG) units while integrating SST into an active distribution network (ADN) in the presence of battery backed solar photovoltaic (BBSPV) and wind generation. The uncertainty related to solar irradiance, wind speeds, and load demands is modeled through kernel density estimation (KDE), generalized extreme value (GEV) distribution, and Gaussian distribution summed with the maximum likelihood estimation (MLE) approach respectively. The K‐medoid clustering procedure is utilized to group the load demand into multiple load levels, which helps in the intelligent scheduling of charging and discharging of battery energy storage systems (BESS). The distribution network planning process manages two conflicting criterion functions of real power loss (RPL) reduction and sum of square deviations of the expected voltage values, which are optimized utilizing the non‐dominated sorting genetic algorithm (NSGA‐II). The probabilistic power flow uses the direct load flow procedure utilizing bus injection to branch current (BIBC) matrix along with the forward sweep method to investigate each run of Monte Carlo simulation (MCS). Multiple case studies have been conducted on the IEEE 33 bus radial distribution network (RDN). The outcomes demonstrate the potential benefits of RPL reduction and voltage profile improvement (VPI) with increasing penetration levels of SST. [ABSTRACT FROM AUTHOR]

Summary: The distributed generation (DG) units are used more in the electrical networks to reduce the energy demand along with reducing the system losses and increasing the voltage profile of the load points. This paper presents an unintentional islanding detection, reliability enhancement, and power loss minimization of the restored system after an islanding event. The detection of islanding is performed by passive detection method of simultaneous measurement of voltage and frequency (vf)‐based technique. The reliability of the system is increased along with the power loss minimization through reconfiguration by Particle Swarm Optimization (PSO) technique. The network reconfiguration is performed by identifying the most vulnerable buses, and reliability indices of the system are evaluated after the islanding event. The reliability indices act as a marker for validating the proposed reconfiguration strategy. The proposed method for islanding detection, reliability enhancement, and power loss minimization is compared with the existing methods available in the literature. The proposed method is tested on two different radial distribution system such as IEEE‐69 and 118 bus systems, and the results obtained after the validation are promising. [ABSTRACT FROM AUTHOR]

A MicroGrid (MG) can be operated in two main situations: grid-connected mode and autonomous mode. Power electronics (PE) are required to interface the DG units with the MG. This paper presents an optimal operating strategy and cost minimization scheme for an electronically weak-coupled MG. The major objective of the paper is to minimize the overall cost considering both the power system and the power electronics constraints in the two modes of operation. The paper presents steady-state models of power electronic converter/inverter systems for coupling distributed generation (DG) units to the grid based on Newton-Raphson method. A Matlab program is developed to represent the proposed algorithm. The program is tested in various network conditions and verified by applying it to an MG with three different DG units. The main contribution of the study is to ensure that the converter constraints are satisfied for both types using DC/AC inverter and AC/AC matrix converter. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: Higher load growth in the distribution system and its consequences on higher voltage deviation, feeders overloading, and distribution system loss increase have a bad effect on system quality. Global warming and the dwindling supply of fossil fuels also make it imperative to search for more effective alternatives that guarantee appropriate operating level of power losses and voltage profile at different points of the distribution networks. Capacitor banks (CBs), renewable distributed generators (DGs), and automatic voltage regulators (AVRs) can be considered the most suitable enhancement devices for distribution systems that reduce both pollution and power losses, improving the voltage profile, ..., etc, if they are optimally sized and sited. The objective of this paper is to investigate the optimal placement of each of the 3 mentioned solutions (CBs, DGs, and AVRs) on a part of real Egyptian distribution system. This system is an old, long, weak, and heavily loaded distribution system with high power losses (about 29% of system loading) and poor voltage regulation (about 30%). Each introduced solution has been evaluated according to power loss minimization and investment cost minimization. A new modification to the backward‐forward power flow method for radial distribution system embedded AVRs has been proposed, which facilitates the placement procedure of AVRs and reduces computation time as compared to other methods. In this paper, an optimal placement of the combined CBs, DGs, and AVRs has also been introduced based on integrated particle swarm optimization technique and rough set theory. The proposed approach aims to minimize the problem complexity and reduce the storage capacity required for the optimization problem. [ABSTRACT FROM AUTHOR]

With increasing annual energy demand and significant growth in the use of distributed generation (DG), distribution companies are exploring ways to improve the technical specifications of the distribution networks such as power losses, customer interruption costs, and voltage stability and on the other hand to increase the penetration level of DGs. In this paper, a multi-objective optimization model is proposed for distribution network reconfiguration (DNR) to decrease the total costs of energy losses and energy not supplied (ENS) and increase the voltage stability and DG penetration level. Seasonal hourly load curves are applied, and best configuration is determined for each loading condition. Uncertainties regarding the load variations and volatile power production of wind turbine are modeled using a 2-point estimate method, and a benefit-cost analysis is used to assess the effects of depreciation cost in DNR problem. The proposed model is applied on 2 typical test systems. [ABSTRACT FROM AUTHOR]

According to IEEE std. 1547, islanding mode is 'a condition in which a portion of an Electric Power System (EPS) is energized solely by one or more local EPSs through the associated Point of Common Coupling (PCC) while that portion is electrically separated from the rest of the area EPS'. Therefore, the dynamic instability due to islanding may result in power swing and finally loss of synchronism. Hence, many studies have been done for islanding detection and disconnection of distributed generation (DG) in an EPS. But, these conventional methods eventually lead to the disconnection of the DG units. To improve DG dynamic stability, superconducting magnetic energy storage (SMES) can be used effectively, because SMES have a high-energy density and fast response. This paper proposes a new method to damp the power swing after DG islanding and to maintain synchronism conditions based on SMES. Hence, the disconnection of the DG units is not required. Also, new controllers are developed for SMES including voltage source converter (VSC), and DC-DC chopper. The controller structures of VSC and DC-DC chopper are of PI and fuzzy logic-based type, respectively. Superconducting coil charging is controlled by the DC-DC chopper. SMES sizing is performed, based on power swing equations. Hereupon, dynamic load model is considered. Performance of the proposed method is evaluated by defining 12 scenarios such as strong and weak networks with load changing simulated in PSCAD. Simulation results show that the islanded DG stabilization (IDGS) method has good performance to maintain stability margin in a weak network. [ABSTRACT FROM AUTHOR]

Summary: Renewable energy sources powered distributed generation (RES‐DG) is getting more indispensable to encounter the considerable increase in demand for electric energy owing to its techno‐economic benefits and eco‐friendly nature. An economic solution to this demand can only be obtained with the optimal placement and sizing of RES‐DGs. The optimal siting and sizing of RES‐DG, such as Photovoltaic (PV) and Wind Turbine (WT) is still a hot topic due to the uncertainties in solar irradiance (SI) and wind speed (WS). The main objective of this research paper is to develop a RES‐DG siting and sizing strategy for the discrete, nonlinear siting and sizing pattern of RES‐DGs using a novel hybrid Harris' Hawk optimizer (HHHO), considering the stochastic nature of SI and WS. The Weibull and Beta probability density functions (PDFs) are utilized for modeling the stochastic nature of WS and SI, respectively. The optimization of the multiobjective function comprises active power loss reduction, enhancement in voltage profile, and improvement in voltage stability index (VSI). Different scenarios of single and multiple RES‐DGs and capacitor banks (CB) are examined to validate the efficiency of the proposed novel HHHO based RES‐DGs siting and sizing strategy. The results show a considerable reduction in power loss, enhancement in the system voltage profile, and improvement in VSI. Evaluation of results by comparing withstate‐of‐art hybrid algorithms shows that the proposed solution using HHHO algorithm is globally optimum. [ABSTRACT FROM AUTHOR]

The paper presents a novel detection method based on feature extraction discrete wavelet transform (DWT) combined with artificial neural network (ANN) for identification of islanding condition in distributed generation (DG) system. Islanding detection methods can be classified into two major categories as active and passive methods. The main disadvantages of the passive methods are determined threshold value and related to their large non-detection zone. The emphasis of the proposed approach is eliminating the aforementioned drawbacks. The DWT allows revealing various hidden features of the signal. The aim of this paper is to determine the best wavelet basis function in order to identify islanding occurrence with higher accuracy and lower decomposition level. The proposed approach requires the measure rate of change of frequency at the DG's terminal, and various features are extracted from DWT then these features used as input into ANN. Also, the performance of the different structures of ANN such as feed-forward neural network, radial basis function, and probabilistic neural network are compared for islanding detection purpose. The proposed method is simulated and tested in various operation conditions such as islanding conditions, motor starting, capacitor bank switching, and nonlinear load switching. The test results showed that the proposed method correctly detects the islanding operation and does not mal-operate in the other situations. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Usually, distributed generations with natural energies bring negative effects to the utility grid. Microgrid with various power sources is able to eliminate these negative effects. A frequency domain-based method is proposed in this paper for configuration and control design of power sources in a grid-connected microgrid. First, the power sources are configured based on their frequency spectrum features. After that, the frequency domain-based power follow-up control is applied to the power sources, and the power at the point of common couple (PCC) is regulated to follow up a desired power value. Detailed theoretical analysis of the frequency domain-based method for configuration and power follow-up control of power sources are presented. Finally, a microgrid in a campus with multiple power sources is designed based on the proposed configuration method and control method. Frequency domain analysis and experimental results show that the power at PCC can be regulated to a desired value, i.e. the disturbances to the grid caused by loads and renewable resources in microgrid are successfully suppressed. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In a microgrid, the islanding condition occurs when the utility circuit breaker (CB) is opened. In this case, the microgrid is disconnected from the main grid. Therefore, the islanding condition can be detected by monitoring the variables that caused the utility CB to open. In this paper, the utility CB current is measured at the grid side, and the islanding condition is detected based on a feature extracted from the measured signal before the utility CB opening. Discrete wavelet transform is used to extract the features of the measured current, and then, the artificial neural network is trained in order to detect the islanding conditions based on the extracted features. Since the disturbances of distributed generation (DG) units or fault occurrence have no effect on the measured current, the proposed method is an effective one for islanding detection in distribution networks with high penetration of DGs. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: The addition of photovoltaic (PV)‐based distributed generators introduces several challenges to power system protection and control engineers. In a multi‐source distribution network, power flow becomes bi‐directional, and conventional overcurrent and earth fault protection schemes are threatened. Addition of PV‐based distributed generation could lead to protection blinding, sympathetic tripping, and loss of coordination in conventional overcurrent protection. This paper evaluates the general concerns regarding protection in a PV‐based distributed generation network, by modeling a power system with sequence networks for different types of faults. The power system is simulated with Digsilent PowerFactory. The results show that many of the general concerns can be mitigated by using sequence components to identify faults. A method is presented to adapt conventional overcurrent protection schemes without the need for communication‐assisted protection. [ABSTRACT FROM AUTHOR]

Summary: This paper presents the design of a current reference used in an inverter‐side current controller for a grid‐connected single‐phase transformerless inverter with an Inductive‐Capacitive‐Inductive of LCL filter. The idea is to indirectly control the inverter‐side current, by directly acting on the grid‐side current. Furthermore, it can be shown that the simple proportional term guarantees damping injection. However, the design of the current reference for such a controller is a more involved process, which turns out to be even more challenging in the case where the grid voltage signal is subject to harmonic distortion. In this case, the distortion propagates into the converter through the LCL filter. Therefore, an inverter‐side current reference must be proposed to be as distorted as necessary to assure indirect tracking of the grid‐side current towards its corresponding reference, which is built as a sinusoidal with a given phase displacement to allow reactive current injection. The inverter‐side controller must then include a harmonic compensation mechanism, to assure perfect tracking of the inverter‐side current towards its distorted reference, and thus, achieve an adequate performance under harmonic distortion. Experiments are performed in a prototype to evaluate the performance of the proposed controller. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a multiobjective method for obtaining optimal size and site of distributed generation (DG), to reduce loss, and DG investment cost while improving the voltage profile in primary distribution networks. To solve the multiobjective problem, a classical technique known as global criterion method is implemented to form a novel objective function equation, which is custom‐built for a distribution system. The application of the global criterion method is explained using a DG that is capable of injecting real power, ie, unity power factor DG, and then extended to DGs capable of injecting reactive power. The method is validated for 2 distribution systems. Results show that the proposed method satisfies the individual objectives simultaneously. The proposed method is also compared with existing methods to exhibit its effectiveness. [ABSTRACT FROM AUTHOR]

This paper presents an application of the chaotic artificial bee colony (CABC) algorithm to identify the optimal location and sizing of the distributed generation (DG) units in order to improve the voltage stability margin in the radial distribution system. Artificial bee colony algorithm is an optimization algorithm based on the intelligent foraging behavior of honey bee swarm. To improve the searching ability of an artificial bee colony algorithm, chaos theory is united with artificial bee colony, called the CABC algorithm. The various impact indices are used to evaluate the multi-objective performance index aimed to identify the optimal location and sizing of combined real and reactive power-based DGs on the distribution systems. The presence of DG in the distribution system has been potential to improve voltage stability of the system. The effect of DG on the weakest bus is analyzed by constructing the PV curve. The effectiveness of the proposed method is tested on 38-node and 69-node radial distribution systems. [ABSTRACT FROM AUTHOR]

This paper proposes a solution methodology for optimal allocation and sizing of renewable based DG units in radial distribution systems. The objectives are to minimize total power losses, to minimize system's investment cost and to improve voltage stability. The multi-objective genetic optimization algorithm is used to generate the optimal Pareto front and a fuzzy decision making function is used, as a hybrid function, to obtain the best compromise solution. The proposed technique is applied to typical IEEE bus systems including 33-bus system, 69-bus system and 119-bus system. This technique is implemented using different scenarios including all possible combinations of renewable DG units; to prove the effectiveness of the proposed methodology. The effect of DG based renewable energy allocation on the most sensitive buses to collapse is also carried out considering different load models. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: The increase in the levels of penetration of distributed generation (DG) and the introduction of smart grid functionalities like network reconfiguration to the distribution network have made its fault current levels unpredictable and complicated the design of its protection. This paper studies the use of distribution grid code requirements, which regulate the fault response of DGs, to control the fault current levels in the network. The paper proposes an algorithm to follow when choosing the grid code requirements for DG dynamic voltage support that would allow for the continued use of traditional protection setups with sufficient speed and reliability; this would help avoid the need for more complicated schemes that heavily rely on an external communication layer that might negatively impact the reliability of the system. A motivating example is used to show that depending on the network configuration different voltage support requirements might be needed. By studying all possible configurations, a common range of requirements can be identified. The paper also considers changing the requirements progressively, such that requirements set for DGs currently connected can be different than those added in the future. This is demonstrated with a second case study where DGs are added in three phases. The results show that DGs added in later phases would need to be subject to stricter requirements than those connected in the initial phase. [ABSTRACT FROM AUTHOR]

The power flow study is an exigency for planning, operation, and optimization of future smart microgrids. In this paper, an interior point-based power flow solution for balanced microgrids operating in islanded mode is presented. In the proposed method, the power flow problem is set up as a constrained interior-point optimization problem in which nonlinear power mismatch equations are iteratively solved without defining a slack bus. Unlike conventional power flow problems, the unknown frequency of the microgrid and droop equations for distributed generation units are also taken into account. Moreover, fixed, voltage-dependent, and frequency-dependent distributed loads are also considered. The computational efficiency of the proposed method is verified using two tools and tested with various case studies. The proposed method has a good convergence pattern and execution time for all types of distributed generation units and loads in islanded networks that are arbitrarily complex. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Distributed generation (DG) sources have recently become more significant in the distribution system due to the increasing demand of electricity energy. Choosing the most suitable size of DG is an essential step to ensure tremendous effect on its operation and power system control. An optimal DG size will result in the reduction of electrical power loss as well as the cost of operation. Power loss reduction can also be achieved through optimal network reconfiguration. By considering optimal network reconfiguration and DG sizing, the effectiveness and efficiency of the system can be improved while having lower power loss in the power system. Therefore, this paper presents the simultaneous method to identify the optimal network reconfiguration and DG sizing using evolutionary programming. The main goal of this work was to reduce the power loss and increase the voltage profile, while at the same time fulfill the operating constraints. The developed method was tested on 33-bus and 69-bus system with different operating conditions. The test results showed a great improvement of power loss reduction and overall voltage profile of the system. The implementation of reconfiguration and DG technique in 33-bus and 69-bus systems which were operated simultaneously had shown tremendous improvement in terms of the number of iterations to reach the optimal value of power losses and DG sizing. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper examines the influence of correlated pseudo measurements on the three-phase (sequence component-based) micro-grid state estimation. Pseudo measurements are used as the external inputs to replace the unavailable real-time measurements on distributed generation (DG) units and loads to provide the minimum bus observability. Output powers of unmonitored DG (photovoltaic and wind-based) units and loads are evaluated using the weather (either measured or forecasted) data, historically recorded state estimation patterns and available real-time measurements. The historical data are classified into clusters by the Self-Organization Map Artificial Neural Network (SOM ANN). The correlation coefficients between dependent pseudo measurements are calculated from clustered weather data and corresponding powers from DG units or loads, where the Feed Forward Artificial Neural Networks (FF ANNs) with backpropagation are used for approximating the output active power of unmonitored elements. The results and practical aspects of the proposed three-phase state estimation methodology with correlated measurements are demonstrated on two (benchmark and real-world) micro-grids. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper presents a mixed-integer nonlinear optimization model for distributed generation (DG) placement in the distribution system. A multiperiod ac optimal power-flow model is developed for minimizing annual energy losses and determining the optimal site and size of DG units. Various system constraints and time-varying demands are incorporated in the model. A novel iterative method for solving the multiperiod DG placement problem based on the Benders decomposition technique is proposed, which reduces the computational burden and facilitates its practical application. Two case studies are presented to illustrate the efficacy of the proposed method. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Low-voltage direct current (DC) microgrids will have a significant position in smart grids. Of course, currently, DC microgrids are mainly used in the areas with sensitive electrical loads. The main issue in these microgrids is the voltage control. In this paper, a practical, reliable, modular, autonomous, and decentralized voltage control method, namely the voltage-based power-voltage (VbPV) control method, is proposed for the most common type of DC microgrids, that is, the DC microgrids with sensitive loads. The proposed voltage control method leads to the flattest voltage profile, which is essential for the DC microgrids. Besides, the presented method minimizes the power loss and maximizes the line capacity release. It is noteworthy that the VbPV control method requires no telecommunication infrastructure. Furthermore, contrary to some other DC voltage control methods, it is applicable to different real DC microgrids. Here, some numerical examples are mentioned to discuss and clarify the remarkable achievements of the VbPV control method. The analytic and simulation results confirm the successful performance of the VbPV control method. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In recent years, Distributed Generation (DG) has been utilized in electric power networks increasingly. DG units can affect the system operational conditions in different ways such as voltage profile improvement, amending voltage stability, reliability enhancement, securing power market, etc. if they are managed properly. Otherwise, they may have undesirable impacts on technical issues of power grids. A lot of studies have been done on various aspects of control and operation of DG units to find the optimal placement, sizing and also the proper technology of them. This paper proposes a novel comprehensive economic method for planning DG units which considers both the Distribution Company's (DisCo) and the DG Owner's (DGO) profits simultaneously. Multi-objective particle swarm optimization technique is used to simulate many case studies on the IEEE 33-bus distribution test system and finally find the best solution for the placement, size and contract price of the generated power of DGs. The proposed methodology not only considers operational aspects such as power loss reduction, voltage profile and stability improvement and reliability enhancement, but also leads to an accurate analysis which satisfies both the DisCo's and the DGO's economic viewpoints. Finally, an encouragement to invest more on DG technologies is proposed based on the gained results. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Industrial plants/commercial facilities with synchronous generation, seek reliable and continuous operation even at the time of grid outages. Thus, islanding detection methods have been proposed in the literature that can be used to change the operating mode of the employed distributed generators from grid-parallel to stand-alone. Among the few solutions previously presented for switching the control mode in the reverse event of reconnecting to the grid, the method presented in this paper is unique. This grid-reconnection detection technique is low cost, fast, and does not interact with the power quality of the island although it only uses one, locally measured, variable. The method implies processing of oscillatory modes in frequency signal and is independent of the autonomous island's boundary. The investigation also includes a discussion on similar event of merging of adjacent islands. Simulations confirm the successful discrimination between reconnection event and other switching/power quality events. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY Distributed generation (DG) systems are small-scale power generation technologies that offer better reliability of supply, reduced transmission, and distribution losses and cost. The benefits of DG greatly depend on their placement and size. Most of the existing analytical methods developed so far are applicable for single DG installation only. Further, in meta-heuristic-based methods, location and sizing problem of DG were dealt separately in which optimal locations are identified with sensitivity-based methods, and optimal sizing is obtained using meta-heuristic algorithms which may lead to incorrect location and suboptimal sizing. In this paper, a novel method that employs harmony search algorithm with differential operator is proposed to install multiple DG units optimally in distribution system with an objective of minimizing active power loss and improving voltage profile. The proposed method is tested on 33-bus and 69-bus radial distribution systems to demonstrate its performance and efficacy. Results show that the proposed method is superior to existing methods in quality of solution. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper proposes a new approach to distribution system named Three-wire Network (3-NET). Considering the integration of different distributed generation (DG) technologies as well as the diversity of loads, the idea of 3-NET is splitting a single power network into three qualitatively different networks: (i) a high quality direct current (DC) network; (ii) a conventional alternating current (AC) network; and (iii) a low quality DC network. By this configuration, the multi-stage conversion of energy from DG sources can be reduced, whereas loads can be supplied with different power quality and reliability levels as desired. In order to evaluate the potential benefits of 3-NET, the operational strategy is formulated in a market model; the reliability performance is investigated using Monte Carlo simulation and quantified in terms of interruption costs. In the case study, the proposed 3-NET is considered for integrating a certain amount of DG into a specific distribution system and then compared with another system approach: hybrid AC-DC microgrid. The simulation shows that although the operation costs can be slightly higher, the 3-NET shows a great improvement in reliability performance in comparison with the hybrid microgrid. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY: In this paper, a modified simulated annealing technique is proposed for the simultaneous improvement of power quality and optimal placement and the sizing of fixed capacitor banks in a modern distribution network. The latter is supplying a mix of linear and nonlinear loads imposing voltage and current harmonics. Besides, the network includes integrated variable‐speed wind turbines as distributed generation. The stochastic power output of the wind generation is considered by performing the Monte Carlo simulation of the distribution power flow. Operational and power quality constraints include the bounds of node voltage magnitude, the node voltage total harmonic distortion, and the number/size of installed capacitors. The net annual economic saving is defined as the associated objective function that accounts for the cost of the released power capacity because of the power losses reduction, the cost change of energy losses, and the extra cost of the searched capacitor banks. Solution results are discussed for a model‐distorted distribution system under different conditions. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: This paper presents an improved version of the direct power control (DPC) for the distributed generation systems. The improvement is exemplified in using an adaptive proportional‐integral (PI) controller, whose parameters are recursively tuned at any operating condition to reach the minimum error in the shortest possible transient time. This improved DPC is applied to a distributed generation unit that is based on the 5‐level diode‐clamped inverter so that its output power can be easily controlled in a grid‐connected mode. This paper also introduces an innovative technique called direct voltage control to stabilize the loads' voltage in a stand‐alone mode at balanced and unbalanced loads. Both control schemes for DPC and direct voltage control depend on this new combination of the self‐adaptive PI controllers and estimation of the feedback parameters. The simulation results are provided to show the superior performance of the proposed control schemes compared with some other common techniques such as voltage oriented control, conventional DPC, and conventional DPC operated by regular PI controllers. Experimental results are also presented to prove the practicality of the presented adaptive PI controller in a grid‐connected mode. [ABSTRACT FROM AUTHOR]

It is expected that the use of distributed generation (DG) will increase sharply in distribution systems, especially with the realization of smart grids. In spite of the benefits of DG in distribution systems, high penetration level of DGs could cause some challenges for the network. Therefore, the optimal sizing and siting of DGs should be identified carefully. In addition, different operating conditions have to be taken into account in this process. The DGs are usually installed depending on optimal siting and sizing techniques considering normal operating periods. During repairing fault periods, different locations and capacities of DGs may be preferable. In this paper, 2 scenarios of switching strategies are presented for attaining the optimal sizing and siting of DGs during repairing fault period starting from the optimal allocation obtained for normal operating period. Genetic algorithm is used for solving the optimization problem that is implemented for an actual loop distribution system in Egypt. [ABSTRACT FROM AUTHOR]

Summary: Distributed generation (DG) technologies are considered an integral part of power distribution networks. The desired performance of power distribution networks can be obtained through the optimal accommodation of DG units. This paper proposes an analytical method called Branch Loss Bus Injection Index (BLBII) to solve the multi‐objective optimal accommodation of distributed generation (MO‐OADG) problem of power distribution networks. Four objectives were considered in the optimisation model: energy loss minimisation, overall bus voltage deviation minimisation, overall voltage stability margin maximisation, and energy not served (ENS) minimisation. A multiple criteria decision‐making method such as the analytical hierarchy process is employed to optimise the weight coefficients of the individual objectives as the optimisation problem is solved based on the weighted‐sum method. The proposed method is demonstrated on benchmark radial power distribution networks of IEEE 33‐bus and INDIAN 85‐bus. The applicability of the proposed BLBII has been validated, and results are presented. [ABSTRACT FROM AUTHOR]

The distributed generations (DGs) and dynamic voltage restorer (DVR) play an important role in the context of environmental problems and sustainable development throughout the world. The traditional DG and DVR locating and sizing method is based on a fixed network structure, which is assumed to be unchangeable during the planning period. The research presented here discusses a hybrid approach working on Monte Carlo simulation (MCS) and genetic algorithm (GA), which can be used for enhancement of system power factor (SPF) and voltage profile (VP) by the integration of DGs with DVR planning in distribution networks with ZIP load models from the minimization of total real power loss of the system viewpoint. The proposed methodology was applied to a 75‐bus distribution network. This article is useful for researchers as well as practitioners who are working in the fields of integration of DG with DVR for improvement of system performances such as power factors and voltage profile from minimizing the losses. [ABSTRACT FROM AUTHOR]

The integration of distributed generations (DGs), dynamic voltage restorer (DVR), and distribution static compensator (DSC) plays an important role in the context of environmental problems and sustainable development throughout the world. The traditional DG, DVR, and DSC locating and sizing methods are based on a fixed network structure, which is assumed to be unchangeable during the planning period. The research presented here discusses a hybrid approach working on genetic algorithm (GA) and Monte Carlo simulation (MCS) which can be used for enhancement of system power factor (SPF) and voltage profile (VP) by the integration of DG, DVR, and DSC planning in distribution networks with constant impedance (Z), constant current (I), constant power (P) load models (ZIP‐LMs) from the minimization of total real power loss of the system viewpoint. The proposed methodology is applied to a 75‐bus distribution network. This article is useful for researchers as well as practitioners who are working in the fields of integration of DG, DVR, and DSC for the improvement of system performances such as SPF and voltage profile from the minimization of total real power loss of the system viewpoint. [ABSTRACT FROM AUTHOR]

A solution technique using sequential second‐order cone programming to solve the optimum power flow problem in low voltage (LV) distribution networks with distributed generation is developed. A novel bound tightening method is suggested to get exact solutions with few iterations. A novel approximation method is suggested to increase exactness by approximating phase angle dependent components. The performance of the suggested solution method is compared with linear programming, genetic algorithm, particle swarm, sequential quadratic programming with multiple start points, and global search‐based optimization methods. The exactness of the generated solutions is validated after comparison with a load flow. The proposed algorithm provides better performance in optimality, execution time, and exactness compared to other methods. [ABSTRACT FROM AUTHOR]

For enhancing the awareness and competitiveness of distributed energy resources (DER) in energy markets, an optimal and implementation and operation of these resources. To address this issue, in this paper, objective, DERs that can collaborate with other DER installed as closer or far topologies, forming coalitions for gaining competitiveness between each other in the energy market, have been selected for study. The profit allocation due to coalition between DERs is being identified as an important issue for ensuring renewable sources installation in smart grids. A methodology with, bi-level, structures is proposed to maximize the profit in a competitive market and allocate profit resulting from a coalition formation between multiple energy districts encompassing DERs. In the primary level analysis, a mechanism based on noncooperative game theory is presented with the aim of creating a competitive market, as well as, to study the supply energy strategies based on pricing mechanisms of multiple energy suppliers. In the second level, various distribution methods, namely, Shapley, Nucleolus, and Merge and Split, are compared with each other for profit allocation analysis. Our study highlights that the disconnection of DERs resulting from pricing decisions allows them to collaborate together with aggregated facilities to achieve higher profits due to excess production and avoid penalties due to shortages in production, which in essence, demonstrates a significant operational increase in their profits, a concept that favors the likelihood for all energy suppliers and producers to form a coalition for economic optimizations. [ABSTRACT FROM AUTHOR]

Summary: Transient stability in distribution systems has gained special interest because of the continuous increase of distributed generation connected to the grid. Besides the dynamic behavior of the generation system, the distribution networks present extensive branches and unbalanced loads with a specific set of equipment, what increases the complexity of the numerical analysis of transient stability. In this context, this work proposes a new methodology for transient analysis in distribution networks with distributed generation, which is divided in 3 major steps: (1) the representation of the network model through a simplified model, (2) the selection of disturbances types and buses for application, and (3) and the adjustment of stability control systems. The methodology is suitable for unbalanced networks and a demonstration of a single‐pole switching is presented. Some case studies were simulated and analyzed for a real network model. [ABSTRACT FROM AUTHOR]

Summary: A novel low‐voltage ride‐through capable energy management control system is proposed for a grid‐connected hybrid photovoltaic‐fuel cell power source. The scheme is designed to enable the hybrid power source to follow a power demand from the grid operator. Additionally, the system is able to ride through both symmetrical and asymmetrical voltage sags while providing active and reactive power support to the grid. The injected active power is kept constant during asymmetrical voltage sags without requiring a phase locked loop or positive‐negative sequence extraction, thus lowering the computational complexity and design requirements of the control system. Several test cases are simulated using the SimPowerSystems toolbox of MATLAB/Simulink computing environment to demonstrate effectiveness of the proposed strategy both under normal and voltage sag conditions. Results of the control algorithm's digital implementation on a low‐cost microcontroller are also presented. [ABSTRACT FROM AUTHOR]

Summary: Determining the penetration level of the distributed generation (DG) is an effective tool to site and size DGs in distribution networks. A multiobjective function of optimizing the DG penetration level, subject to constraints including short circuit capacity, voltage limits, transformer capacity, reverse power flow, and congestion of lines, is introduced to minimize the real and reactive losses and to ensure the voltage stability considering the variations of loads, different locations and power factors of DGs, and statistical nature of DG powers especially renewable energy resources. This optimization is performed based on a combined probabilistic modeling of the chronological behavior of wind speed, solar irradiance, and load with different types. The dynamical behavior of the compensators and on‐load tap changers is modeled by optimization subfunctions. An improved bee algorithm is used through conducting searches in the neighboring areas based on a new nonlinear function for a higher fitness and coherency speed. [ABSTRACT FROM AUTHOR]

Summary: This manuscript presents a novel approach of islanding detection based on hybrid signal processing techniques comprised with mathematical morphology and wavelet transform. The combination of mathematical morphological filter and translational invariant wavelet is considered as a preprocessing filter unit to decrease the random noises in the original power signal. This technique uses the 2 basic mathematical morphology operator erosion dilation difference filter and opening‐closing difference operator to operate on negative sequence voltage and current signal received at target distribution generation bus for the extraction of different useful features. An extreme learning machine‐based machine learning technique is further used as a classifier to discriminate islanding events from nonislanding events. Apart from that, another islanding detection method based on the combination of proposed preprocessing filter unit and wavelet transform is presented. The comparative result demonstrates improved accuracy for the proposed approach of islanding detection and classification, even under certain extremely noisy conditions. [ABSTRACT FROM AUTHOR]