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This article focuses on the implementation of peer-to-peer (P2P) energy trading and planning of a grid-connected multi-microgrid system based on an advanced optimization approach. The proposed architecture is comprised of three microgrids (MGs) with combinations of distributed energy resources (DERs), including wind turbines, photovoltaic panels, and storage batteries, to meet the load requirement. A game theory technique, Nash equilibrium, is used to structure the proposed model for multiobjective optimization, where the main objectives are used to determine the correct sizing of DERs and optimum payoff values. Due to the variability of DERs, to maintain lower energy costs, the reliability index (IR) and levelized cost of energy are the benchmarks considered for optimization. The proposed model is analyzed, and rigorous comparison is carried out for both peer-to-grid and P2P energy trading schemes, considering the Australian profiles for wind speed, solar irradiation, and residential load. The simulation model is built in MATLAB software, and the particle swarm optimization algorithm is exploited for the optimization. The results illustrate that P2P energy trading reduces the payoff value of the multiobjective function (MOF) to 36%. The robustness of MOF is validated and analyzed with different combinations of constant coefficients K1 and K2. In the end, the most economical and suitable models with DERs are proposed for each MG, and the results are verified with sensitivity analysis. [ABSTRACT FROM AUTHOR]

Sewage sludge from wastewater treatment contains organic matter and plant nutrients that can play an important role in agricultural production and the maintenance of soil fertility. The present study has aimed to evaluate the degree of humification following sewage sludge application of soil organic matter by laser-induced fluorescence and humic acids using ultraviolet-visible fluorescence, and including comparison with Fourier-transform infrared spectroscopy and elemental analysis. Sewage sludge applications to the soil caused a decrease in the degree of humification of the soil organic matter and humic acids for both a Typic Eutrorthox (clayey) soil and a Typic Haplorthox (sandy) soil of around 14 and 27%, respectively. This effect is probably due to incorporation of newly formed humic substances from the sewage sludge into the characteristics of less humified material, and to the indigenous soil humic substances. The minor alterations observed in the clay soil probably occurred due to both the greater mineral association, which better stabilized the indigenous soil organic matter, and the higher microbial activity in this soil, which accelerated sewage sludge mineralization. Sewage sludge applications increased the C content for the clay and sandy soils by 7.4 and 15.4 g [kg.sup.-1], respectively, suggesting a positive effect on these two soils. Abbreviations: FTIR, Fourier-transform infrared; HA, humic acid; LIE laser-induced fluorescence; SOM, soil organic matter; TOC, total organic carbon. doi:10.2136/sssaj2008.0176

This paper presents an improved analysis of a novel Programmable Power-factor-corrected-Based Hybrid Muitipulse Power Rectifier (PFC-HMPR) for utility interface of power electronic converters. The proposed hybrid multipuise rectifier is composed of an ordinary three-phase six-pulse diode-bridge rectifier (Graetz bridge) with a parallel connection of single-phase switched converters in each three-phase rectifier leg. In this paper, the authors present a complete discussion about the controlled rectifiers' power contribution and also a complete analysis concerning the total harmonic distortion of current that can be achieved when the proposed converter operates as a conventional 12-pulse rectifier. The mathematical analysis presented in this paper corroborate, with detailed equations, the experimental results of two 6-kW prototypes implemented in a laboratory. Index Terms--AC motor drives, high power drives for trolley-bus systems, high power factor three-phase rectifiers, multipulse rectifiers, tractions applications, 12-pulse rectifiers.

The implementation of a hybrid fuel cell/battery system is proposed to improve the slow transient response of a fuel cell stack. This system can be used for an autonomous device with quick load variations. A suitable three-port, galvanic isolated, bidirectional power converter is proposed to control the power flow. An energy management method for the proposed three-port circuit is analyzed and implemented. Measurements from a 500-W laboratory prototype are presented to demonstrate the validity of the approach. Index Terms--Battery, fuel cells.

A novel hybrid three-phase rectifier is proposed. It is capable to achieve high input power factor (PF) and low total harmonic input currents distortion (TH[D.sub.I]. The proposed hybrid high power rectifier is composed by a standard three-phase six-pulse diode rectifier (Graetz bridge) with a parallel connection of single-phase Sepic rectifiers in each three-phase rectifier leg. Such topology results in a structure capable of programming the input current waveform and providing conditions for obtaining high input power factor and low harmonic current distortion. In order to validate the proposed hybrid rectifier, this work describes its principles, with detailed operation, simulation, experimental results, and discussions on power rating of the required Sepic converters as related to the desired total harmonic current distortion. It is demonstrated that only a fraction of the output power is processed through the Sepic converters, making the proposed solution economically viable for very high power installations, with fast investment payback. Moreover, retrofitting to existing installations is also feasible since the parallel path can be easily controlled by integration with the existing dc-link. A prototype has been implemented in the laboratory and it was fully demonstrated to both operate with excellent performance and be feasibly implemented in higher power applications.

In response to a call from the National Science Foundation (NSF) for curriculum reform and elimination of legacy materials in engineering curricula, the faculty at the Colorado School of Mines, Golden, has developed and offered a combined set of course modules in fluids and circuits. These modules consist of a two-credit interdisciplinary course in fundamentals, followed by two one-credit modules focusing on applications in fluids and in circuits, respectively. The course set reduces the overall number of credits from six (three in each of the standard fluids and circuits classes) to four through the 2 + 1 + 1 format. The fundamentals course, consisting of two credits, is based on conservation and accounting principles for the concepts of mass, momentum, energy, and charge. Two applications modules, each of one credit, develop these ideas in the respective disciplines. During the study, four challenges to implementation were uncovered: faculty and administrative buy-in, textbook selection, logistics, and stakeholders' acceptance. Index Terms--Accreditation, Accreditation Board for Engineering & Technology (ABET), circuits, curriculum, fluids, reform.

The simulation of proton-exchange membrane fuel cells (PEMFC) may work as a powerful tool in the development and widespread testing of alternative energy sources. In order to obtain an adequate PEMFC model, (which could be used in the analysis of FC generation systems), it is necessary to define the values for a specific group of modeling parameters. The simulation results are strongly affected by the choice of such modeling parameters. Multiparametric sensitivity analysis is a tool that can be used to define the relative importance of the factors related to the model, because it encompasses the entire parameter space. This paper presents a sensitivity investigation of PEMFC electrochemical models, and aims to determine the relative importance of each parameter on the model results. Index Terms--Fuel cells, modeling and simulation, sensitivity analysis.

This paper demonstrates an application of the parametric cerebellar model articulation controller (P-CMAC) network--a neural structure derived from Albus' CMAC algorithm and Takagi-Sugeno-Kang parametric fuzzy inference systems. It resembles the original CMAC proposed by Albus in the sense that it is a local network, i.e., for a given input vector, only a few of the networks neurons will be active and will effectively contribute to the corresponding network output. The internal mapping structure is built in such a way that it implements, for each CMAC memory location, one linear parametric equation of the network input strengths. First, a new approach to design neural optimal control (NOC) systems is proposed. Gradient-descent techniques are still used here to adjust network weights, but this approach has many differences when compared to classical error backpropagation algorithm. Then, P-CMAC is used to control the output voltage of a proton exchange membrane fuel cell (PEM-FC), by means of NOC. The proposed control system allows the definition of an arbitrary performance/cost criterion to be maximized/minimized, resulting in an approximated optimal control strategy. Practical results of PEM-FC voltage behavior at different load conditions are shown, to demonstrate the effectiveness of the NOC algorithm. Index Terms--Control systems, fuel cells (FCs), neural networks, optimal control.

This paper presents a dynamic electrochemical model for representation, simulation, and evaluation of performance of small size generation systems emphasizing particularly proton exchange membrane fuel-cell (PEMFC) stacks. The results of the model are used to predict the output voltage, efficiency, and power of FCs as a function of the actual load current and of the constructive and operational parameters of the cells. Partial and total load insertion and rejection tests were accomplished to evaluate the dynamic response of the studied models. The results guarantee a better analytical performance of these models with respect to former ones with a consequent reduction in time and costs of projects using FCs as the primary source of energy. Additionally, this electrochemical model was tested for the SR-12 Modular PEM Generator, a stack rated at 500 W, manufactured by Avista Laboratories, for the Ballard Mark V FC and for the BCS 500-W stack. Index Terms--Automation, control, fuel cells (FCs), modeling and simulation.

This paper shows fundamentals and applications of the parametric cerebellar model arithmetic computer (P-CMAC) network: a neural structure derived from the Albus CMAC algorithm and Takagi-Sugeno--Kang parametric fuzzy inference systems. It resembles the original CMAC proposed by Albus in the sense that it is a local network, (i.e., for a given input vector, only a few of the networks nodes--or neurons--will be active and will effectively contribute to the corresponding network output). The internal mapping structure is built in such a way that it implements, for each CMAC memory location, one linear parametric equation of the network input strengths. This mapping ran be corresponded to a hidden layer in a multilayer perceptron (MLP) structure. The output of the active equations are then weighted and averaged to generate the actual outputs to the network. A practical comparison between the proposed network and other structures is, thus, accomplished. P-CMAC, MLP, and CMAC networks are applied to approximate a nonlinear function. Results show advantages of the proposed algorithm based on the computational efforts needed by each network to perform nonlinear function approximation. Also, P-CMAC is used to solve a practical problem at mobile telephony, approximating an RF mapping at a given region to help operational people while maintaining service quality. Index Terms--Cerebellar model arithmetic computers (CMACs), communication systems, mobile communication, neural networks.

This paper presents the guidelines for simulation of fuel-cell (FC) stacks by using a computer-controlled high-power converter, which drives actual electric loads, or injects power to the grid. The FC output static and dynamic characteristics are closely reproduced in such a way the actual loads are seamlessly driven as if they were supplied by the simulated FC. The simulator characteristics include the membrane temperature and humidity, efficiency, flow of the reactants, cooling air fan and water pumps, the actual air environmental temperature and humidity, and the regimen of operation of the actual electrical load. Any type of FC of ordinary size can be simulated without having to use hydrogen with improved safety, variety of tests, flexibility, and demo facilities. Those features allied to the low cost of this FC simulator contribute for market analysis and life-cycle studies of a site installation. Index Terms--Alternative energy, computer control, fuel cells (FCs), interconnection, modeling, rectifiers, simulation.

This paper presents a comprehensive review of the industrial applications of artificial neural networks (ANNs), in the last 12 years. Common questions that arise to practitioners and control engineers while deciding how to use NNs for specific industrial tasks are answered. Workable issues regarding implementation details, training and performance evaluation of such algorithms are also discussed, based on a judiciously chronological organization of topologies and training methods effectively used in the past years. The most popular ANN topologies and training methods are listed and briefly discussed, as a reference to the application engineer. Finally, ANN industrial applications are grouped and tabulated by their main functions and what they actually performed on the referenced papers. The authors prepared this paper bearing in mind that an organized and normalized review would be suitable to help industrial managing and operational personnel decide which kind of ANN topology and training method would be adequate for their specific problems. Index Terms--Architecture, industrial control, neural network (NN) applications, training.

Although the use of a series capacitor increases the transmission line (TL) capacity, it inverts the voltage/current and creates a sub-harmonic frequency that results in unintended operation of the protection devices, which further decreases the transient stability under fault conditions. Restoring the transient stability requires an accurate diagnosis of faults in TLs, which further requires exploration of in-depth features. This imposes challenges for the existing approaches as they demand a large amount of data. In this paper, a self-attentive weight-sharing capsule network (WSCN) is proposed to achieve robust and high classification performance while utilizing a limited amount of data. The capsule network, with the weight-sharing mechanism delivers robust performance in detecting and classifying the faults in the TL domain. Simultaneously, the self-attention layer highlights the more dominant features that make the network work upon the limited data effectively. A Western-System-Coordinating-Council WSCC 9-bus and 3-machine test model, which was modified with the series capacitor was studied to quantify the robustness of the self-attention WSCN. The results were compared with those of others networks to confirm the explicit classification ability of the proposed network. A study on real-world data obtained from power network was also conducted to validate the proposed self-attention WSCN. [ABSTRACT FROM AUTHOR]

This paper presents the design, analysis, simulation, and modeling of a high-torque low-speed multiphase permanent-magnet brushless machine. The machine fits an in-wheel motor arrangement to be used for electric vehicle applications. This paper presents issues regarding the high-level modeling comprised of a transient model in conjunction with their corresponding experimental evaluation. Analysis was made to combine the modeling efforts with the expected behavior concerned with mutual inductance and armature reaction effects, so as to have realistic simulation results verified by the experimental setup. Comprehensive experimental results corroborate the work. Index Terms--Brushless machines, digital signal processors, electric machines, modeling, motor drives.

This paper describes the development of a neural-network-based prediction of mooring forces of a deep-sea oil exploitation production process. The evolvement of a neural network simulator for analysis of the dynamic behavior of a system consisting of a turret-floating production storage and offloading (FPSO) system and a shuttle ship in tandem configuration is described. The turret-FPSO is a vessel with a cylindrical anchoring system fixed to the sea bed my mooring lines and a shuttle ship is connected during the oil transference. This system has quite complex dynamics owing to interactions of the forces and moments due to current, wind, and waves. In general, the mathematical model that represents the dynamics of these connected floating units involves a set of nonlinear equations requiring several parameters difficult to be obtained. In order to deal with such complexities, a neural network has been devised to simulate an FPSO tandem system. This approach opens new horizons for maintenance of mooring lines, preventing commons of the ships. Index Terms--Neural networks, offshore simulation, oil exploitation.

Artificial intelligence techniques, such as fuzzy logic, neural network, and genetic algorithm, are recently showing a lot of promise in the application of power electronic systems. The paper describes the control strategy development, design, and experimental performance evaluation of a fuzzy-logic-based variable-speed wind generation system that uses a cage-type induction generator and double-sided pulsewidth-modulated (PWM) converters. The system can feed a utility grid maintaining unity power factor at all conditions or can supply an autonomous load. The fuzzy-logic-based control of the system helps to optimize efficiency and enhance performance. A complete 3.5-kW generation system has been developed, designed, and thoroughly evaluated by laboratory tests, in order to validate the predicted performance improvements. The system gives excellent performance and can easily be translated to a larger size in the field. Index Terms - Fuzzy logic, intelligent control, power electronics, wind generation.

The paper describes a variable speed wind generation system where fuzzy logic principles are used for efficiency optimization and performance enhancement control. A squirrel cage induction generator feeds the power to a double-sided pulse width modulated converter system which pumps power to a utility grid or can supply to an autonomous system. The generation system has fuzzy logic control with vector control in the inner loops. A fuzzy controller tracks the generator speed with the wind velocity to extract the maximum power. A second fuzzy controller programs the machine flux for light load efficiency improvement, and a third fuzzy controller gives robust speed control against wind gust and turbine oscillatory torque. The complete control system has been developed, analyzed, and validated by simulation study. Performances have then been evaluated in detail.

This paper investigates the Multilevel Current Source Converter (MCSC) STATCOM. It proposes a new method of modulation. The new modulation method produces less THD and di/dt at the terminals of the MCSC STATCOM when compared to the widely used Phase-Shifted Carrier SPWM (PSC-SPWM). To ensure the inductors' currents remain balanced, a Current Balancing Algorithm (CBA) is presented. The CBA does not require any controls. It relies on assigning optimum switching states to each CSC module in real-time. In addition, two control strategies are presented in this paper. The first one assumes the STATCOM to be a SISO. Therefore, it only requires one PI controller. However, the gains for the controller must be changed if the STATCOM was to transition from capacitive mode to inductive mode, or vice versa. The second control strategy overcomes this problem by implementing a TITO integral state feedback controller. The contributions of this paper are validated via simulation and experimental results. [ABSTRACT FROM AUTHOR]

Power quality (PQ) events are referred to any abnormal deviation from the standard sinusoidal behavior of power signals within a power system. PQ events are usually studied by tracking the behavior of voltage signals over observation points of the system. IEEE Standards have defined standard categories for PQ events based on their time behavior. Each class of these events may have different level of importance from different contributors’ perspective (utilities, system operators, or costumers). Due to increasing the usage of sensitive technological loads such as transportation, banking systems, and databases on one hand in addition to the uncertainty injected to the system from aggregation of renewables on the other hand, the fast and reliable PQ events classification is an important monitoring task in the future smart grid. In this paper, combining the theory of sparse recovery with a new high-dimensional convex hull approximation framework we have developed a fast, reliable, and adaptive PQ events classification methodology named “compressive-informative sparse representation-based” PQ events classifier. Unlike usual classification approaches, the proposed classifier does not need any training procedure while due to its linear mathematical formulation acts inherently fast. Moreover, it can be easily adapted to recognize the challenging combined PQ events in addition to any permanent change in the behavior of PQ patterns. [ABSTRACT FROM AUTHOR]

The staircase modulation strategy is the best choice for asymmetric cascaded H-bridge multilevel inverter (ACMI) because it makes the output voltage to present a high number of levels and makes one of the ACMI modules to operate at low frequency. However, the staircase modulation is usually employed without giving its deserved attention. This paper presents a clear understanding of the staircase modulation strategy and its applications in both isolated and grid-connected ACMI.  The main novelty of this paper is the obtaining of the switching function for each module. The principle of operation is carefully described, also indicating how to command the ACMI transistors. The output voltage of the two superior modules is evaluated for different values of iterations. Special attention is given to the power distribution among the ACMI modules when the staircase modulation is applied. It is demonstrated on how the power is processed in each module considering an ACMI with three modules. The analysis is presented showing the staircase modulation within a closed-loop control strategy for isolated and grid-connected modes of operation, showing that the content of this paper is valid for both modes. Experimental results clarify and show the efficacy of the content presented in this paper. [ABSTRACT FROM AUTHOR]

Real-time power line outage detection (POD) and localization is an important monitoring task for the modern smart grid. Reliable monitoring of power lines status plays a critical role in the system-wide blackout prevention. In this paper, the main aim is to address the multiple POD problems by exploiting the compressive system identification—a time-efficient approach in a complex network analysis. A typical power network is considered as a single graph, and the mathematical formulation of the POD problem is initialized using the dc power-flow model and graph theory concepts. Next, a sparse representation-based formulation for this problem (POD-SRP) is reported and further improved and generalized in case of multiple large-scale outages. Practical and technical challenges associated with this sparse recovery problem are partially addressed by developing new SRP solvers. Furthermore, a new sparse-based mathematical formulation for POD is introduced and termed as “Binary-POD-SRP,” which specifically deals with two particular issues, namely, the high coherence and the signal dynamic outrange. Finally, the identification performance of the proposed framework is evaluated by a variety of case studies, which are modeled using IEEE standard test-beds. We specifically discuss how the inherent challenges within large-scale multiple-outages can be solved by applying these new techniques and formulations. [ABSTRACT FROM AUTHOR]

Penetration rate of grid-connected photovoltaic (PV) generation to the existing utility grid is rapidly increasing over the years. Since the power generated from PV systems fluctuates according to the weather condition, e.g., cloud passing, this can significantly disturb the stability of a weak utility grid. The integration of energy storage devices and its ramp-rate control technique are required to reduce the impact of PV systems output fluctuations and augment the stability of the utility grid. In this paper, ramp-rate control is applied to the direct connection of energy storage devices in PV generation system configuration. The direct connection of supercapacitors string and battery combination scheme is proposed to reduce the number of power converters so that the efficiency of the system is increased. In this work, the PV system output is controlled by directly controlling the energy storage system (ESS) to limit the changing rate of the PV output to a desired ramp-rate value, hence reducing the battery charge/discharge cycles and extending the expected lifetime of the ESS. The performance of the proposed direct connection scheme of the ESS and its ramp-rate control strategy is verified using a 1-kW PV system prototype. [ABSTRACT FROM AUTHOR]

Power theories are advancing signal decomposition approaches used for electrical power signal analysis. Currently, they are key tools for designing reliable and efficient power electronic interface controllers. Due to the inherent uncertainty in the power generation within new technology of distributed generation units (such as renewable-based microgrids), most of these theories are not directly applicable in the era of new power engineering systems. Furthermore, the traditional formulations are not appropriate once we face the nonlinearity in the consumption along a weak grid that may not maintain steady voltage or frequency. Therefore, a new signal decomposition method with a higher level of selectivity must be developed to modify the traditional power theories and improve the control strategies from a design viewpoint. This paper describes a novel formulation of an instantaneous power theory, enhanced instantaneous power theory (EIPT), for unbalanced and nonlinear three-phase power systems. EIPT establishes a proper decomposition of current components for cases of balanced, unbalanced, and distorted voltage sources. In addition to mathematical analysis, this research provides comprehensive simulations under different loads and source conditions, which supports the performance of the EIPT in the active filtering methods. Moreover, the performance of the proposed method is compared with the state-of-the-art approach widely known as the conservative power theory. Our results indicate that this new comprehensive approach is helpful in optimizing control strategies for power electronic interfaces and power quality compensators. [ABSTRACT FROM AUTHOR]

The optimal operation of an oil well requires the periodic measurement of temperature and pressure at the downhole. In this paper, acoustic waves are used to transmit data to the surface through the pipeline column of the well, making up a wireless transmission system. Binary data is transmitted in two frequencies, using frequency-shift keying modulation. Such transmission faces problems with noise, attenuation, and, at pipeline joints, multiple reflections and nonlinear distortion. Hence, conventional demodulation techniques do not work well in this case. The neural network presented here classifies signals received by the receiver to estimate transmitted data, using a linear-vector-quantization-based network, with the help of a preprocessing procedure that transforms time-domain incoming signals in three-dimensional images. The results have been successfully verified. The neural network estimation principles presented in this paper can be easily applied to other patterns and time-domain recognition applications. Index Terms--Acoustic data transmission, neural network, oil pipeline.

The conservative power theory (CPT) is a time-domain theory applicable to any periodic signal single- or polyphase system with or without a neutral conductor. The principle operation is the orthogonal decomposition of electrical variables, resulting in electrical quantities with physical meaning. An important feature of the CPT is the current decomposition. It consists of decomposing any current into five parts. The label of these parts is active current, reactive current, scattered active current, scattered reactive current, and generated current. This paper proposes the application of the current decomposition of the CPT in distributed energy resources (DERs). A supervisory controller (SC) uses the current decomposition in a load power-sharing strategy. The combination of these two issues is the main contribution of this paper. Moreover, the proposal of this paper is more attractive than the conventional droop strategy since the DERs follow their current reference in a current-controlled mode, making the load sharing faster, more reliable, and more accurate. A clear understanding of how the CPT decomposes load currents into its parts is presented, as well as the drawback found in droop strategy when dealing with load power sharing. Later, the SC load power-sharing strategy is described, indicating that the proposal of this paper makes an SC to have a broad option when managing a smart grid with dispatchable DERs. A case study with experimental results shows the efficacy of applying current decomposition of the CPT in load power-sharing strategies. [ABSTRACT FROM AUTHOR]

Cooperative control of power converters in a microgrid offers power quality enhancement at sensitive load buses. Such cooperation is particularly important in the presence of reactive, nonlinear, and unbalanced loads. In this paper, a multi-master–slave-based control of distributed generators interface converters in a three-phase four-wire islanded microgrid using the conservative power theory (CPT) is proposed. Inverters located in close proximity operate as a group in master–salve mode. Slaves inject the available energy and compensate selectively unwanted current components of local loads with the secondary effect of having enhanced voltage waveforms while masters share the remaining load power autonomously with distant groups using frequency droop. The close proximity makes it practical for control signals to be communicated between inverters in one group with the potential to provide rapid load sharing response for mitigation of undesirable current components. Since each primary source has its own constraints, a supervisory control is considered for each group to determine convenient sharing factors. The CPT decompositions provide decoupled current and power references in abc-frame, resulting in a selective control strategy able to share each current component with desired percentage among the microgrid inverters. Simulation results are presented to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper discusses the use of a cascaded multilevel converter for flexible power conditioning in smart-grid applications. The main feature of the proposed scheme is the use of independent dc links with reduced voltages, which makes such a topology an ideal candidate for medium- and high-power applications with increased reliability. The developed control strategy regulates independent dc-link voltages in each H-bridge cell, and allows the selective and flexible compensation of disturbing currents under a variety of voltage conditions without requiring any reference frame transformation. The selective control strategies are based on the decompositions proposed in the conservative power theory, which result in several current-related terms associated with specific load characteristics. These current components are independent of each other and may be used to define different compensation strategies, which can be selective in minimizing particular effects of disturbing loads. Experimental results are provided to validate the possibilities and performance of the proposed control strategies, considering ideal and deteriorated voltage conditions. [ABSTRACT FROM PUBLISHER]

This paper proposes a simplified small-signal model for output voltage control of a single-phase asymmetrical cascaded H-bridge multilevel inverter (ACHMI). The ACHMI is an n-series connected H-bridge converter, each one with a unique value at the dc link and usually scaled at 1:2:6:… or 1:3:9:…. By assuming that the small-signal variation component is equal in all n converter terminal ports, a simplified small-signal model is obtained. This assumption is carefully described and justified. To verify the veracity of the proposed model, two distinct control strategies are applied. One is a single-loop control scheme based on a modified proportional-integral (PI) controller. The other one is a double-loop control scheme based on a PI controller with feedforward action of the load current. Both controllers are tuned based on the dynamic behavior of the proposed model. Since the designed controllers based on the simplified model make the ACHMI output voltage to follow the reference without steady-state error, the proposed simplified model truly represents the inverter. Experimental results show the efficacy of the simplified model of the ACHMI through the two mentioned control strategies as well as the ACHMI installed in a microgrid. [ABSTRACT FROM PUBLISHER]

A comprehensive control of a wind turbine system connected to an industrial plant is discussed in this paper, where an algorithm has been developed allowing a control structure that utilizes a four-leg inverter connected to the grid side to inject the available energy, as well as to work as an active power filter mitigating load current disturbances and enhancing power quality. A four-wire system is considered with three-phase and single-phase linear and nonlinear loads. During the connection of the wind turbine, the utility-side controller is designed to compensate the disturbances caused in presence of reactive, nonlinear, and/or unbalanced single- and intra-phase loads, in addition to providing active and reactive power as required. When there is no wind power available, the controller is intended to improve the power quality using the dc-link capacitor with the power converter attached to the grid. The main difference of the proposed methodology with respect to others in the literature is that the proposed control structure is based on the conservative power theory decompositions. This choice provides decoupled power and current references for the inverter control, offering very flexible, selective, and powerful functionalities. Real-time software benchmarking has been conducted in order to evaluate the performance of the proposed control algorithm for full real-time implementation. The control methodology is implemented and validated in hardware-in-the-loop based on the real time simulator “Opal-RT” and a TMSF28335 DSP microcontroller. The results corroborated our power quality enhancement control and allowed to exclude passive filters, contributing to a more compact, flexible, and reliable electronic implementation of a smart-grid based control. [ABSTRACT FROM AUTHOR]

A multifunctional control strategy for a single-phase asymmetrical cascaded H-bridge multilevel inverter (ACHMI), suitable for microgrid systems with nonlinear loads, is presented. The primary advantage of ACHMI is to produce a staircase output voltage with low harmonic content utilizing unequal dc voltages on the individual H-bridge cells. In a grid-connected mode of operation, the control strategy of the ACHMI is based on the conservative power theory, providing selective disturbing current compensation besides injecting its available energy. In autonomous mode of operation, two different control methods along with a damping resistor in the filter circuit are developed for regulation of the ACHMI instantaneous output voltage in a variety of load conditions. The first method is a single-loop voltage control scheme without the need of any current measurement. The second one is a multiloop voltage control scheme with a load current feedforward compensation strategy and preservation of the grid-connected current control scheme. The steady-state response and stability of both voltage control schemes are analyzed, and based on the application requirement, the control schemes are implemented individually. The effectiveness of each control strategy is experimentally verified using a hardware-in-the-loop setup with the control algorithm implemented in the TMSF28335 DSP microcontroller. [ABSTRACT FROM PUBLISHER]

This paper proposes an effective technique to control the power flow among different phases of a three-phase four-wire distribution power system by means of single-phase converters arbitrarily connected among the phases. The aim is to enhance the power quality at the point-of-common-coupling of a microgrid, improve voltage profile through the lines, and reduce the overall distribution losses. The technique is based on a master/slave organization where the distributed single-phase converters act as slave units driven by a centralized master controller. Active, reactive, and unbalance power terms are processed by the master controller and shared proportionally among distributed energy resources to achieve the compensation target at the point-of-common-coupling. The proposed control technique is evaluated in simulation considering the model of a real urban power distribution grid under non-sinusoidal and asymmetrical voltage conditions. The main results, concerning both steady-state and transient conditions, are finally reported and discussed. [ABSTRACT FROM PUBLISHER]