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This paper develops a new control strategy for voltage source converter (VSC) based multi-terminal high voltage dc (MT-HVDC) grids for enhancing the mutual frequency support between MT-HVDC interconnected asynchronous ac systems. The existing droop control structure of VSCs is augmented with an additional feedback voltage-based loop that generates a voltage shifting term to be added to the original dc voltage reference. The addition of this integrator-based controller nullifies the difference between voltage errors seen at adjacent converter stations. This action helps to overcome inaccuracies in the mutual frequency support caused by the uneven voltages across a dc system. The proposed strategy uses only local variables for the continuous-time control; thus, it does not rely on a high-bandwidth communication network, and its performance is not affected by the change of ac systems’ parameters. Modal analysis is carried out to investigate the stability of the proposed controller. Finally, comprehensive simulation studies are used to verify the proposed strategy’s performance and compare it with recently reported alternative controllers. [ABSTRACT FROM AUTHOR]

The DC microgrid (DC MG) concept enables the hosting of DC-type renewable energy resources. However, their intermittent nature means that a high penetration of renewables can jeopardize supply adequacy and voltage provision during islanding. The work presented in this paper was therefore directed at developing a probabilistic graphical approach based on Bayesian networks (BNs) for the reliability analysis of renewables-dominated DC MGs. The proposed BN model incorporates a family of novel reliability indices for quantifying the impact of a high penetration of renewables on MG reliability, including loss of renewable power supply, rise in voltage, and reversal of power flow. The model is supported by a newly formulated fast and accurate linearized power flow algorithm for probability calculations. The accuracy of the BN model has been verified against a Monte-Carlo simulation (MCS). The effective application of the new BN model for reasoning and impact assessment reveals that a high penetration of renewables affects reliability indices differently. Case study results suggest that the proposed BN model shows promise as a valuable tool for the reliability analysis of renewables-dominated MGs that feature islanding capability. [ABSTRACT FROM AUTHOR]

AC/DC hybrid microgrids (HMGs) represent a promising architecture that allows the hosting of a mix of ac/dc energy resources and ac/dc loads. Despite their potential, when islanded, HMGs impose operational challenges among of which are precise and stable power sharing, frequency restoration, and voltage regulation. Imprecise power sharing can result in some distributed generators (DGs) being overloaded, while others being underloaded. This article proposes an optimal-power-flow-based optimal power sharing (OPS) scheme to optimize the droop characteristics of DGs and interlinking converters for global power sharing in a multi-DG HMG regardless of DG location and type. The optimized droop parameters might jeopardize the microgrid stability. Thus, the proposed OPS scheme preserves stable power sharing through stability-constrained optimization of the droop characteristics. In addition to DG overloading because of unequal power sharing, voltage-sensitive loads could possibly suffer from voltage deviations because of drooping the voltage with the load increase. The proposed OPS strategy enjoys the ability to regulate the ac/dc voltage within a desired range and restore the nominal frequency. Steady-state and time-domain simulations verify the effectiveness of the proposed sharing scheme in achieving the underlying objectives. Test results also prove the capability of the OPS scheme in zonal power sharing in the case of a distribution grid with multizone ac/dc microgrids. [ABSTRACT FROM AUTHOR]

This article presents a comprehensive design procedure for isolated microgrids with a high penetration of nonlinear loads. The proposed microgrid planning approach simultaneously determines the sizes, locations and types of distributed generators (DGs) and shunt capacitor banks (CBs). The presence of nonlinear loads along with the capacitors of CBs or DGs’ output filters may cause severe voltage distortions. To consider this issue, a harmonic power flow tool tailored for planning applications is developed that takes into account the specific features of isolated microgrids. Given the necessity of supply continuity for isolated microgrids after a contingency, the proposed planning approach takes into consideration the reliability to increase the probability of building successful islands. Unlike previous methods, the proposed approach does not rely merely on supply adequacy, and takes into account the fact that the voltage provision requirement can only be fulfilled through dispatchable DGs. The intermittent natures of loads and renewable DGs are modelled probabilistically. The effectiveness of the proposed planning approach has been validated using the PG&E 69-bus system, and the followings are observed: 1) the significance of applying suitable fundamental-power-flow and harmonic-power-flow algorithms for isolated microgrids, and 2) the possibility of avoiding a severe voltage distortion by utilizing an appropriate planning method and only small increase in the cost. [ABSTRACT FROM AUTHOR]

Line current differential relays (LCDRs) detect faults accurately and promptly, by comparing all currents flowing into the line. This type of relay has been identified in the literature as a reliable protection for lines in DC microgrids (MGs). LCDRs, however, lack the required resiliency against cyber intrusions, such as false data injection attacks (FDIAs) and time synchronization attacks (TSAs), due to their high dependence on communication infrastructure and/or the Global Positioning System (GPS). This paper first introduces coordinated attacks—i.e., several almost-simultaneous FDIAs or TSAs that are carried out independently to achieve a specific objective—as potential threats for MGs. Then, through a case study, it shows how coordinated FDIAs and TSAs can initiate a sequence of events that result in instability of an entire MG. Afterwards, an approach is presented to detect FDIAs and TSAs, and to distinguish them from real faults. The proposed method is comprised of passive oscillator circuits (POCs) installed in series with each converter. During faults, the resultant RLC circuit causes the POCs to resonate and generate a damped sinusoidal component with a specific frequency, i.e., $f_{d}$. However, $f_{d}$ is not generated during FDIAs and TSAs, since unlike faults, which are physical events that trigger the natural frequencies of a system, cyber-attacks happen in the cyber layer without provoking natural frequencies of the physical layer. Thus, an LCDR pickup without detecting $f_{d}$ denotes an FDIA or a TSA. Since $f_{d}$ is locally measured and analyzed by each LCDR, the proposed detection approach cannot be targeted by cyber-attacks. The proposed method is evaluated on a simulated ±2.5 kV DC MG. Numerical analysis confirms that the proposed method (i) is system-independent; (ii) detects FDIAs and TSAs in less than 1 ms; (iii) is sensitive to high-resistance faults; (iv) can determine fault types, and (v) reduces faults’ peak currents. [ABSTRACT FROM AUTHOR]

High penetration of distributed generation (DG) results in technical problems as voltage rise, voltage unbalance, substation reverse power, and transformer overloading. These problems adversely affect the connectivity of DGs either in the planning stage by decreasing the number of connected DGs, or in the operation stage by applying DGs’ active power curtailment (APC). This paper presents a techno-economic approach for the enhancement of photovoltaic (PV) DGs connectivity. The proposed approach first employs a probabilistic economic technique for determining the non-curtailable portion of the PV DG power that ensures profitable DG investment. This portion is integrated, as an economic constraint, in the planning phase of the proposed approach that aims to maximize the number of PV DGs connected to the system. In the operation phase, the proposed approach utilizes the capabilities of the existing equipment on the system, i.e., regulators, capacitors, DGs reactive power, and DGs APC to mitigate all technical problems. The overall objective of this stage is to minimize the total DGs APC while fulfilling all technical and economic constraints. The proposed approach is tested on the modified IEEE 123-bus feeder. The results clarify the efficiency of the proposed techniques in increasing the connectivity of PV DGs while maintaining profitable DG project. [ABSTRACT FROM AUTHOR]

A major concern associated with the connection of distributed generators (DGs) to distribution systems is the voltage rise problem. A solution introduced in many voltage control schemes is DG active power curtailment. However, this measure has a negative effect on both DG revenue and DG investment. This paper proposes the use of existing system resources to mitigate the voltage rise problem. Based on the big bang-big crunch optimization and the reactive power compensation method, the new technique controls the distribution system voltage profile while avoiding DG active power curtailment. The proposed method minimizes voltage deviations by determining the regulator taps and reactive power contributions of both the capacitors and the DGs. The approach is implemented online by a central control unit that optimally determines appropriate control decisions and then communicates them to the voltage regulators, capacitors, and DGs. Eliminating the voltage deviation problem associated with the network installation of DGs provides a cost-effective means of increasing DG penetration. The new algorithm was implemented and tested on the 33-bus test feeder. The results demonstrate the effective control of the voltage profile and fast convergence speed provided by the developed technique. [ABSTRACT FROM AUTHOR]

This paper proposes a two-stage energy management scheme (EMS) for AC–DC hybrid smart distribution systems (DSs). The proposed EMS is formulated as a multi-objective optimization problem to minimize the DS operation costs and energy losses. The proposed EMS is achieved in two stages. In the first stage, a network reconfiguration algorithm determines the optimal day-ahead reconfiguration schedule for a hybrid DS. In the second stage, a real-time optimal power flow algorithm determines the real-time operational schedule of the energy resources. This paper also introduces a new linearized power flow model for AC–DC hybrid DSs. This new model facilitates the formulation of the first-stage algorithm as a mixed-integer linear programming problem and the formulation of the second-stage algorithm as a linear programming problem. The proposed two-stage EMS was tested on a case study of a hybrid DS that included different types of loads and distributed generators. The results demonstrate the efficacy of the proposed EMS: the optimal day-ahead reconfiguration schedule was successfully obtained in the first stage, and the proper and optimal real-time operation was achieved in the second stage. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive reliability framework for incorporating different plug-in electric vehicle (PEV) charging load models into the evaluation of generation adequacy. The proposed framework comprises special treatment and innovative models to achieve an accurate determination of the impact of PEV load models on reliability. First, a goodness-of-fit statistical model determines the probability distribution functions (PDFs) that best reflect the main characteristics of driver behavior. Second, robust and detailed stochastic methods are developed for modeling different charging scenarios (uncontrolled charging and charging based on time-of-use (TOU) pricing). These models are based on the use of a Monte Carlo simulation in conjunction with the fitted PDFs to generate and assess a large number of possible scenarios, while handling the uncertainties associated with driver behavior, penetration levels, charging levels, battery capacities, and customer response to TOU pricing. A novel reliability-based framework for the application of dynamic critical event call programs for use with PEV charging loads is also proposed. The effectiveness of the proposed framework with respect to improving system reliability is demonstrated using several case studies applied on the IEEE Reliability Test System. [ABSTRACT FROM AUTHOR]

The deployment of smart grids has facilitated the integration of a variety of investor assets into power distribution systems, giving rise to the consequent necessity for positive and active interaction between those investors and local distribution companies (LDCs). This paper proposes a novel incentive-based distribution system expansion planning model that enables an LDC and distributed generation (DG) investors to work in a collaborative way for their mutual benefit. Using the proposed model, the LDC would establish a bus-wise incentive program based on long-term contracts, which would encourage DG investors to integrate their projects at specific system buses that would benefit both parties. The model guarantees that the LDC will incur minimum expansion and operation costs while concurrently ensuring the feasibility of DG investors’ projects. To derive appropriate incentives for each project, the model enforces several economic metrics including internal rate of return, profit investment ratio, and discounted payback period. All investment plans committed to by the LDC and the DG investors for the full extent of the planning period are then coordinated accordingly. Several linearization approaches are applied to convert the proposed model into an MILP model. The intermittent nature of both system demand and wind- and PV-based DG output power is handled probabilistically, and a number of DG technologies are taken into account. Case study results have demonstrated the value of the proposed model. [ABSTRACT FROM AUTHOR]

This paper proposes a novel stochastic planning model for AC-DC hybrid distribution systems (DSs). Taking into account the possibility of each line/bus being AC or DC, the model finds the optimal AC-DC hybrid configuration of buses and lines in the DS. It incorporates consideration of the stochastic behavior of load demands and renewable-based distributed generators (DGs). The stochastic variations are addressed using a Monte-Carlo simulation technique. The objective of the planning model is the minimization of DS installation and operation costs. The optimal planning solution is obtained by dividing the hybrid planning problem into two nested optimization problems: 1) the main problem is formulated using a genetic algorithm (GA) to search for the optimal AC-DC configuration and 2) the subproblem is used for determining the optimal power flow solution for each configuration generated by the GA. The proposed model has been employed for finding the optimal configuration for a suggested case study that included photovoltaic panels, wind-based DG, and electric vehicle charging stations. The same case study was also solved using a traditional AC planning technique in order to evaluate the effectiveness of the proposed model and the associated cost-savings. The results demonstrate the advantages offered by the proposed model. The proposed framework represents an effective technique that can be used by DS operators to identify the optimal AC-DC network configuration of future DSs. [ABSTRACT FROM PUBLISHER]

The emerging interest in deployment of plug-in electric vehicles (PEVs) in distribution networks represents a great challenge to both system planners and owners of PEV-parking lots. The owners of PEV-parking lots might be interested in maximizing their profit via installing charging units to supply the PEV demand. However, with stringent rules of network upgrades, installing these charging units would be very challenging. Network constraints could be relaxed via controlling the net demand through integrating distributed generation (DG) and/or storage units. This paper presents an optimization model for determining the optimal mix of solar-based DG and storage units, as well as the optimal charging prices for PEVs. The main objective is to maximize the benefit of the PEV-parking lot's owner without violating system constraints. Two cases are considered in this paper: uncoordinated and coordinated PEV demand. A novel mathematical model is further developed whereby the behavior of vehicles’ drivers, in response to different charging prices, is considered in generating the energy consumption of PEVs. [ABSTRACT FROM PUBLISHER]

Smart grids have been emerging nowadays as an initiative to operate modern distribution systems in a more economic and efficient way. Energy storage systems (ESSs) are one of the promising technologies that can achieve the goals of smart grids via facilitating the connection of renewable sources, improving system reliability, and controlling the net demand through peak load shaving, etc. In this paper, a comprehensive planning framework is introduced for ascertaining the most cost effective siting and sizing of ESSs that maximize their benefits in distribution networks. A probabilistic approach is further adopted that includes the consideration of the stochastic nature of system components. Such approach allows determining the optimal operation of ESS at each load state. Moreover, contingency planning decisions, in the form of load points to be shed during contingencies, are identified through the approach proposed. [ABSTRACT FROM PUBLISHER]

There has been a growing interest in image fusion technologies, but how to objectively evaluate the quality of fused images has not been fully understood. Here, we propose a method for objective quality assessment of multiexposure multifocus image fusion based on the evaluation of three key factors of fused image quality: 1) contrast preservation; 2) sharpness; and 3) structure preservation. Subjective experiments are conducted to create an image fusion database, based on which, performance evaluation shows that the proposed fusion quality index correlates well with subjective scores, and gives a significant improvement over the existing fusion quality measures. [ABSTRACT FROM AUTHOR]

Recent years have seen increased interest in green technologies such as photovoltaic (PV) electricity and plug-in hybrid electric vehicles (PHEVs). Such technologies, however, have been found to be detrimental to distribution networks. This paper introduces a novel distribution system architecture that can better accommodate the expected growth in PV electricity and PHEVs. In the proposed architecture, the distribution system becomes a bilayer system composed of the traditional ac layer that serves existing system loads, plus an embedded dc layer that interfaces with PV arrays and PHEVs. A bidirectional converter interconnects the two layers and controls the power flows between them. This paper presents the key design and operational aspects of the proposed architecture, with consideration of different uncertainties inherent in the system. To this end, a probabilistic benchmark has been developed for modeling these uncertainties and for use with the sizing and scheduling of different system components. Monte Carlo (MC) simulations confirmed the technical and economic merit of the proposed design methodology. [ABSTRACT FROM PUBLISHER]

The recent deployment of distributed generation has led to a revolution in the use of distribution systems and the emergence of “smart grid” concepts. Smart grids are intended primarily as a means of facilitating the integration of renewable energy sources and of achieving greater system reliability and efficiency. Energy storage systems (ESSs) offer a number of benefits that can help utilities move toward those goals. One of those benefits is the capacity to improve the utilization of network infrastructure by means of proper load management. This paper proposes a methodology for allocating ESSs in distribution systems in order to defer system upgrades, minimize system losses, and take advantage of the arbitrage benefit. The cost and arbitrage benefit of energy storage installation are optimized with respect to system upgrade and energy losses costs. The primary goal of this research is to determine the optimal size and location of storage units to be installed, in addition to their optimal operation, so that total system costs are minimized, while system benefits are maximized. In this paper, a probabilistic load model is adopted instead of utilizing time-series based models, which provide an optimal solution that is valid only for the time-series pattern that is applied. [ABSTRACT FROM PUBLISHER]

An approach to link maintenance and replacement decisions is presented in this paper. This approach proposes a methodical decision-making system to determine the optimal time to replace equipment. It essentially investigates the cost-effectiveness of replacing the equipment both before and after the lifetime is extended by maintenance. To properly investigate the effect of maintenance, maintenance activities should first be scheduled effectively. Therefore, this approach introduces a maintenance strategy based on reliability-centered maintenance (RCM) concept and genetic algorithm (GA) to optimally schedule maintenance activities. Two replacement studies are conducted: with and without the effect of maintenance. A comparison between replacement studies is discussed in the proposed approach. The proposed approach is applied to one of the most critical pieces of equipment in power systems: power transformer. [ABSTRACT FROM AUTHOR]

The recent deployment of distributed generation has led to a revolution in the use of distribution systems and the emergence of smart-grid concepts. Smart grids are intended primarily as a means of facilitating the integration of renewable energy sources and of achieving greater system reliability and efficiency. Energy storage systems offer a number of benefits that can help utilities move toward those goals. One of those benefits is the capacity to improve system reliability through successful islanding operation. This paper proposes a methodology for the cost-effective improvement of system reliability through the allocation of distributed storage units in distribution systems. The costs of energy storage installation are optimized with respect to reliability value expressed as customers' willingness to pay in order to avoid power interruptions. The primary goal of this research was thus to determine the optimal combination of storage units to be installed and the loads to be shed so that all possible contingencies can be effectively addressed. A probabilistic approach is therefore adopted that includes consideration of the stochastic nature of system components. [ABSTRACT FROM PUBLISHER]

Integration of large-scale energy storage systems (ESSs) is desirable nowadays to achieve higher reliability and efficiency for smart grids. Controlling ESS operation usually depends on electricity market prices so as to charge when the price is low and discharge when the price is high. On the other hand, the market-clearing price itself is determined based on the net demand, i.e., including energy storage output, at every hour. Therefore, it is crucial to develop a mathematical model to determine the optimal ESS operation as well as the market-clearing prices. The problem is formulated as a mixed complementarity problem (MCP) that allows the representation of special (incentive) prices, which cannot be represented in a single optimization model. The proposed model is useful for power system operators to determine the optimal storage dispatch simultaneously with the market-clearing price in addition to the conventional generation dispatch. The impact of energy storage size and location on market price, total generation cost, energy storage arbitrage benefit, and total consumer payment is further investigated in this paper. The latter analysis provides some guidelines for power system planners to identify the optimal size and location for installing large-scale ESSs. [ABSTRACT FROM PUBLISHER]

This paper presents the development of a probabilistic benchmark for assessing the impacts of the uncontrolled charging of plug-in hybrid electric vehicles (PHEVs) on residential distribution networks. Unlike the previous research, which adopted several assumptions and approximations, this paper analyzes the available load and transportation data to extract probability distribution functions describing different uncertainties characterizing the charging process. Monte Carlo simulation is utilized to handle these uncertainties and to predict the anticipated impacts of PHEVs on a representative test network. Finally, conclusions are drawn to assist utilities in integrating PHEVs into their networks. [ABSTRACT FROM PUBLISHER]

This paper presents a novel probabilistic distribution load flow (PDLF) algorithm to study the effect of connecting a wind turbine (WT) to a distribution system. This probabilistic approach is used to capture the stochastic behavior of the generation of WTs. Three different models of WTs are developed to be embedded in the PDLF. Consequently, a probabilistic approach to evaluate the impact of wind penetration into distribution systems is developed. Futhermore, the effect of WT penetration on feeder losses, voltage profile and substation powers is presented. [ABSTRACT FROM PUBLISHER]

In this paper a decentralized reactive power control scheme is proposed to optimally control the switched capacitor in the system in order to minimize system losses and maintain acceptable voltage profile. The proposed technique is based on placing a remote terminal unit (RTUs) at each DG and each at line capacitor. These RTUs being coordinated together through communication protocols form a multiagent system. Novel decentralized algorithm is proposed to estimate the voltage profile change as a result of injecting reactive power at the capacitor bus. Simulation results are presented to show the validity and the effectiveness of the proposed technique. [ABSTRACT FROM PUBLISHER]

Distributed generation (DG) exists in distribution systems and is installed by either the utility or the customers. This paper proposes a novel utilization of the existing DG interface to not only control the active power flow, but also to mitigate unbalance, harmonics and voltage flicker, and manage the reactive power of the system. The proposed flexible distributed generation (FDG) is similar in functionality to FACTS, but works at the distribution level. Moreover, a novel recursive least square (RLS) structure is presented. The new structure is applied to multi-output (MO) systems for parameter tracking/estimation, and is called MO-RLS. It is dedicated to symmetrical components estimation. An innovative processing unit-based RLS is investigated to deal with unbalance, harmonics, and reactive power compensation. In addition, this paper portrays a technique for flicker mitigation based on the RLS algorithm for instantaneous tracking of the measured voltage envelope. One advantage of the proposed control system is its insensitivity to parameter variation, a necessity for distribution system applications. Simulations of the suggested FDG based control algorithm are conducted to evaluate the performance of the proposed system. [ABSTRACT FROM PUBLISHER]

In this paper a novel coordinated voltage control scheme is proposed to enable voltage regulator to efficiently regulate the voltage of multiple feeders in the presence of DGs. The proposed technique is based on placing a remote terminal unit (RTUs) at each DG and each line capacitor. These RTUs coordinate together, through communication, and form a multiagent system. Detailed analysis is given for the estimation of the voltage profile based on the RTUs readings. The conditions under which the usage of one voltage regulator for the regulation of multiple-feeders fails are presented along with proposed solutions for such situation. Simulation results show that this technique enable a considerable increase in the allowed DG injected power to the system. [ABSTRACT FROM PUBLISHER]

Analyzing the impacts of large on-grid photovoltaic (PV) systems on the performance of the electric network is an essential task prior to the installation of these systems. To quantify these impacts, a method based on chronological simulations can be used. The main advantage of this method is its ability to provide information about the impacts of the fluctuation of the power generated from the PV systems. However, this method requires performing extensive analysis and simulations, making it impractical for utility studies, especially if long historical data with subhourly time resolution is used. In this paper, a new method that utilizes the data efficiently while preserving the temporal information of the generated PV power is proposed. The method takes advantage of the clustering techniques to group together segments of the output PV power having similar features. Hence, a representative segment for each group can be chosen and used in the analysis and simulations. This representative segment can provide information about the expected performance of other segments of the group. The validity and usefulness of the proposed method are demonstrated by identifying the suitable size and site of a large PV system. [ABSTRACT FROM PUBLISHER]

In this paper, a new method is proposed for the control of voltage regulators that enables the regulation of multiple feeders having diversified loads using only one regulator. The selection of the tap position of the regulator is chosen based on the solution of an integer linear optimization problem. The main advantage of the method is that it has a closed-form solution for the optimal tap; a merit which is very valuable in real-time operation. The constraints for having the voltage of the regulating points within the range of permissible values were ensured. Also, the necessary condition for feasible solutions was examined. A simulation study was carried out to validate the proposed method. [ABSTRACT FROM PUBLISHER]

This paper presents an adaptive grid-voltage sensor- less control scheme for inverter-based distributed generation units based on an adaptive grid-interfacing model. An adaptive grid- interfacing model is proposed to estimate, in real time, the inter- facing parameters seen by the inverter and the grid-voltage vector simultaneously. A reliable solution to the present nonlinear estimation problem is presented by combining a grid-voltage estimator with an interfacing parameter estimator in a parallel structure. Both estimators adjust the grid-interfacing model in a manner that minimizes the current error between the grid model and the actual current dynamics, which acts as a reference model. The estimated quantities are utilized within the inner high-bandwidth current control loop and the outer power controller to realize an adaptive grid-voltage sensorless interfacing scheme. Theoretical analysis and simulation results are provided to demonstrate the validity and usefulness of the proposed interfacing scheme. [ABSTRACT FROM AUTHOR]

This paper focuses on extracting and analyzing different spectral features from transrectal ultrasound (TRUS) images for prostate cancer recognition. First, the information about the images' frequency domain features and spatial domain features are combined using a Gabor filter and then integrated with the expert radiologist's information to identify the highly suspicious regions of interest (ROIs). The next stage of the proposed algorithm is to scan each identified region in order to generate the corresponding 1-D signal that represents each region. For each ROI, possible spectral feature sets are constructed using different new geometrical features extracted from the power spectrum density (PSD) of each region's signal. Next, a classifier-based algorithm for feature selection using particle swarm optimization (PSO) is adopted and used to select the optimal feature subset from the constructed feature sets. A new spectral feature set for the TRUS images using estimation of signal parameters via rotational invariance technique (ESPRIT) is also constructed, and its ability to represent tissue texture is compared to the PSD-based spectral feature sets using the support vector machines (SVMs) classifier. The accuracy obtained ranges from 72.2% to 94.4%, with the best accuracy achieved by the ESPRIT feature set. [ABSTRACT FROM AUTHOR]

Evolutionary algorithms (EAs) are well-known optimization approaches to deal with nonlinear and complex problems. However, these population-based algorithms are computationally expensive due to the slow nature of the evolutionary process. This paper presents a novel algorithm to accelerate the differential evolution (DE). The proposed opposition-based DE (ODE) employs opposition-based learning (OBL) for population initialization and also for generation jumping. In this work, opposite numbers have been utilized to improve the convergence rate of DE. A comprehensive set of 58 complex benchmark functions including a wide range of dimensions is employed for experimental verification. The influence of dimensionality, population size, jumping rate, and various mutation strategies are also investigated. Additionally, the contribution of opposite numbers is empirically verified. We also provide a comparison of ODE to fuzzy adaptive DE (FADE). Experimental results confirm that the ODE outperforms the original DE and FADE in terms of convergence speed and solution accuracy. [ABSTRACT FROM AUTHOR]

The dynamic voltage restorer (DVR) is an effective solution for power quality problems related to voltage. One of the most common control algorithms that are used for the DVR is the symmetrical components method. This paper introduces a new approach for the estimation of the symmetrical components. A modified delta rule structure is proposed and developed which is capable of dealing with multioutput systems for the parameters estimation. An innovative feedforward control, based on the new delta rule structure, is proposed for the series compensator not only to compensate for the zero and negative sequence components, but also to regulate the positive sequence component at the nominal load voltage. One advantage of the proposed control scheme is its insensitivity to parameter variation, a necessity for the series compensator. Experimental verification of the new delta rule algorithm, by using a DSP, is provided. Numerical simulations of the proposed control strategy are conducted to show the robustness, high accuracy, and fast dynamic performance of this novel control algorithm. [ABSTRACT FROM AUTHOR]

In this paper, the dynamic models for adjustable speed drive (ASD) and distribution-static compensator (DSTATCOM) are presented. An eigen domain approach to the transient response investigation is formulated by means of dqo variable in synchronously rotating reference frame to study the dynamic interactions between ASDs and DSTATCOM. Two inverter topologies of ASD, current source inverter and voltage source inverter, are included in the study as well as two control techniques of the DSTATCOM, namely voltage and current control. The study shows that the voltage control DSTATCOM improves the stability boundaries of the ASD utilizing either current or voltage source inverters, while the current control DSTATCOM has minor influence. In addition, the system dynamics show less sensitivity to the dc link capacitance for the voltage control DSTATCOM. These results are supported by analytical study of the characteristic equation of both the voltage and the current control DSTATCOM. [ABSTRACT FROM AUTHOR]

In this paper, a novel algorithm, based on calculating the energy operator of a sinusoidal waveform to track the voltage flicker, is presented. The mathematical derivation of the proposed algorithm different circuit designs required to realize it are described. The proposed algorithm is fast and robust and requires only a few samples to calculate the energy. The simulation and the experimental results prove that the new algorithm can successfully track the envelope. There are no spikes in the envelope even when the voltage signal is suddenly changed at its peak value. [ABSTRACT FROM AUTHOR]

Distributed measurement architecture, due to its efficiency, is used to monitor the power quality in the electric systems. This paper introduces a novel algorithm to determine the optimum allocations of power quality monitors to reduce the cost of the distributed monitoring system taking into account the data redundancy. The optimization problem is formulated as a covering and packing one which can be manipulated by integer linear programm algorithms. The appropriate constraints are deduced by the electrical circuit topology independent of the load parameters. In addition, the problem is adopted to a general form which can be implemented by any optimization package. The proposed algorithm is applied to five different systems for validation. Then, the results are discussed in terms of the cost and data redundancy. [ABSTRACT FROM AUTHOR]

This paper introduces a novel method for the mitigation of the voltage sag and voltage flicker by using Kalman filter and its derivatives (adaptive, and extended). The Kalman filter is used as a tool to extract both the instantaneous envelope of the voltage sags, and to extract the Instantaneous Flicker Level (IFL) of the voltage flicker. Also, this paper demonstrates the advantages of using the Kalman filter instead of the existing tools for tracking and extracting voltage disturbances. Digital simulation results are presented to illustrate the mitigation of unbalanced voltage sags, and the compensation of the cyclic and noncyclic voltage flicker by employing the proposed algorithm. [ABSTRACT FROM PUBLISHER]

Distributed Generation (DG) is used widely in the modern distribution systems. This paper proposes a novel functionality of the interface between DG and the utility network to mitigate the voltage flicker and to regulate the voltage at the Point of Common Coupling (PCC) in addition to its main function of controlling the power flow. A new control algorithm for the DG interface based on the Hilbert transform (HT) is presented. The HT is employed as an effective technique for tracking the voltage flicker levels in distribution systems. The mathematical simplicity of the proposed technique, compared with the commonly used algorithms in the literature, renders them competitive candidates for the on-line tracking of voltage flicker. The accurate tracking of the HT facilitates its implementation for the control of flicker mitigation devices. Simulation results are provided to verify the tracking capabilities of the HT and to evaluate the performance of the proposed DG interface for multifunction operation. [ABSTRACT FROM PUBLISHER]

This paper presents a generalized control algorithm for voltage disturbance extraction and mitigation. The proposed mitigating device is the dynamic voltage restorer (DVR). A DVR is commonly used to mitigate the voltage sags. In this paper the proposed DVR can compensate the voltage unbalance and mitigate voltage harmonics in the time of normal operation as well as performs its basic function during the fault condition. The suggested control algorithm employs an adaptive perceptron to effectively and adaptively track and extract the most common voltage harmonics, voltage unbalance (which include negative and zero sequence voltage drops), and different types of voltage sags, which include balanced and unbalanced voltage sags. Digital simulation results are obtained using PSCADIEMTDC to verify the effectiveness of the proposed control algorithm. Experimental results are demonstrated to prove the practicality of the mitigating device. [ABSTRACT FROM AUTHOR]

Envelope tracking has many important applications in electrical distribution systems for either flicker meters or flicker compensators. This paper presents a novel control technique for flicker mitigation. This technique is based on the instantaneous tracking of the measured voltage envelope. The ADAptive LINEar neuron (ADALINE) algorithm, and the Recursive Least Square (RLS) algorithm are introduced for the flicker envelope tracking. The ADALINE algorithm is characterized by a light computational demand, unlike that of existing techniques; the RLS algorithm outperforms the ADALINE algorithm by its fast con- vergence and robust tracking performance. Both the ADALINE and the RLS algorithms give accurate results even under rapid dynamic changes. The paper investigates the effects of different parameters on the performance of the ADALINE algorithm and that of the RLS algorithm. Extensive simulations of the proposed flicker tracking algorithms are conducted to evaluate their performance for the tracking and mitigation of voltage flicker. The ADALINE and the RLS algorithms are examined by tracking and mitigating the flicker produced by a resistance welder and an arc furnace in a simple distribution system simulated in the PSCAD/EMTDC package. [ABSTRACT FROM AUTHOR]

Distributed Generation (DG) exists in distribution systems and is installed by either the utility or the customers. This paper proposes a novel utilization of the existing DG nonlinear interface not only to control the active power flow, but also to mitigate unbalance and harmonics, and to manage the reactive power of the system. The proposed Flexible Distributed Generation (FDG) is similar in functionality to FACTS, but works at the distribution level. Moreover, a novel ADAptive LINEar neuron (ADALINE) structure is presented. The new structure is applied to multi output (MO) systems for parameter tracking/estimation, and is called MO-ADALINE. It is dedicated to symmetrical components estimation. The control loop combines a Fuzzy Logic Controller (FLC) for voltage regulation, and a processing unit-based ADALINE to deal with unbalance, harmonics and reactive power compensation. One advantage of the proposed control system is its insensitivity to parameter variation, a necessity for distribution system applications. Simulations of the suggested FDG based control algorithm are conducted to evaluate the performance of the novel system. [ABSTRACT FROM AUTHOR]

Symmetrical components as well as harmonic tracking are of great importance in many applications in power systems such as power quality and protection. This paper introduces a novel Adaptive linear combiner (ADALINE) structure for symmetrical components estimation. This structure is capable of dealing with multi-output systems for parameter tracking/estimation rather than the existing ADALINE, which deals only with single output systems. As the new topology deals with Multi-Output systems, it is called MO-ADALINE. Moreover, the paper presents a new processing unit, which can estimate sym- metrical and harmonic components from the measured current signals. The advantages of this proposed unit are its independence of the voltage waveform and its ability to give information about the reactive component of the resolved current Simulation results are given to validate the proposed algorithms. [ABSTRACT FROM AUTHOR]

An introduction to a special section of the journal, which is devoted to distributed generation and microgrids, is presented.