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This paper proposes a real time control strategy of battery systems in the frame of dynamically varying energy pricing. The battery, which is supposed to operate in a large industrial facility, is managed in order to reduce the daily costs sustained by the industry owner for the energy consumption. Multi-battery configurations are taken into account and an optimization model is formulated and solved including technical constraints that guarantee an adequate storage-system behavior. A numerical application based on real data of an industrial facility located in the South of Italy demonstrates the effectiveness and advantages of the proposed procedure.

Discrete Fourier Transform (DFT) and high-performance signal-analysis techniques (i.e., Prony, ESPRIT, root-MUSIC methods) have been proposed to calculate Power Quality indices that characterize waveform distortions in power systems. DFT can be affected by spectral leakage problems that cause inaccuracies in the spectral component calculation while high-performance signal-analysis techniques usually involve onerous computational efforts. Recently, hybrid methods were proposed in the relevant literature which make it possible to calculate PQ indices with accuracy and more acceptable computational efforts. This paper proposes a new three-step hybrid method which applies alternatively DFT and Prony methods to sliding windows. This method does not suffer problems of spectral leakage and guarantees a significant reduction of computational efforts compared with the application of the only Prony method. Experiments are conducted and comparisons are made with traditional methods using both synthetic and measured waveforms. The results confirm the effectiveness and efficiency of the proposed scheme.

Microgrids 1 are electrical subsystems which include small generation units, storage devices and loads, which can operate either in grid connected or islanding mode. This paper deals with a DC microgrid that will be realized in an Italian industrial facility of GETRA Group. In particular, in this paper an optimization model is formulated to solve the problem of the day-ahead optimal scheduling of the microgrid. The model aims to optimize storage devices and controllable loads operation minimizing the daily costs of imported energy from AC grid and satisfying operational constraints such as production process constraints. The optimization problem is formulated using the Integer Linear Programming (ILP) theory. Case studies are also investigated in order to show the feasibility and the effectiveness of the proposed approach.

Future distribution networks are undergoing radical changes, due to the high level of penetration of dispersed generation and information/communication technologies, evolving into the new concept of the Smart Grid. Dispersed generation systems, such as wind farms and photovoltaic power plants, require particular attention due to their incorporation of uncertain energy sources. Further and significant well-known uncertainties are introduced by the load demands. In this case, many new technical considerations must be addressed to take into account the impacts of these uncertainties on the planning and operation of distribution networks. This paper proposes novel Bayesian-based approaches to forecast the power production of wind and photovoltaic generators and phase load demands. These approaches are used in a probabilistic short-term steady-state analysis of a Smart Grid obtained by means of a probabilistic load flow performed using the Point Estimate Method. Numerical applications on a 30-busbar, low-voltage distribution test system with wind farms and photovoltaic power plants connected at different busbars are presented and discussed.

Electrical energy storage systems can provide several benefits along the entire value chain of the electrical system. In this paper attention is paid to the end user point of view, with particular reference to industrial customers. An optimal operating strategy is proposed for energy storage systems with the aim of reducing the electricity bill costs sustained by an industrial customer and contemporaneously satisfying technical constraints for the maximization of the storage system efficiency and life cycle. The proposal, which is developed in this paper by means of computer simulations, will be realized in an industrial facility located in the South of Italy in the frame of the GREAT project, a research plan aimed at developing advanced methods and tools for micro-grid applications.

In recent years, modern distribution networks have rapidly evolved toward complex systems due to the increasing level of penetration of distributed generation units, storage systems, and information and communication technologies. In this framework, power quality disturbances such as waveform distortions should be minimized to guarantee optimal system behavior. This article formulates the planning problem of passive filtering systems in a multi-convertor electrical distribution system as a probabilistic multi-objective optimization problem whose input random variables are characterized with probability density functions. A heuristic simplified approach including trade-off analysis issues is applied to solve the planning problem with the aim of optimizing several objectives and meeting proper probabilistic equality and inequality constraints. The approach is able to quickly find solutions on the Pareto frontier that can help the decision-maker to select the final planning alternative for practical operation. The proposed approach is applied to a 17-busbar distribution test system to evidence its effectiveness.

In this paper the authors are to be commended for the significant contribution in the area of wind power prediction. The methodology presented allows the power production calculation through a two-step procedure: in the first step, the wind direction and velocity are predicted some minutes ahead, and then, in the second step, the power output is calculated using power curves direction-dependent. The authors comments on a method for short-term wind power prediction with multiple observation points are appreciated.

The sensitivity to Power Quality (PQ) disturbances is today increasing in micro grids due to the great economic consequences that PQ disturbances can generate. However, micro grids include several distributed energy resources (DER) interconnected to the grid with static converters that can deteriorate the Power Quality levels. Among DER, wind turbine systems (WTSs) are expected to be widely employed due to the forecasted investment cost reduction and economic incentives. WTSs can cause significant time varying voltage and current waveform distortions whose entity depends on the WTS scheme. In case of time varying distortion, standards suggest the use of a windowed Discrete Fourier Transform (DFT) that, however, can suffer of well know spectral leakage problems. Thus, advanced spectral analysis methods should be considered. In this paper, the time varying waveforms distortions caused by different WTSs schemes are analyzed and critically compared applying DFT, some parametric methods (Prony and ESPRIT) and some hybrid methods (ESPRIT-DFT and Prony-DFT) that conjointly use DFT and parametric methods. This paper, which reports the theoretical aspects of the WTS schemes and of the spectral analysis methods, is a companion paper to a paper of the same title, Part II, in which numerical experiments are performed using test waveforms and measured non-stationary voltage and current waveforms of different WTS schemes.

In this paper, we propose a novel scheme that jointly employs sliding-window (SW) Prony and the discrete Fourier transform (DFT) for estimating power-quality indices based on the time-frequency analysis of non-stationary waveforms in power-system disturbances. These indices, recently proposed in the relevant literature, require the separation of the waveform in two parts, i.e., the fundamental component and the disturbance waveform. In the proposed scheme, Prony’s method was applied to calculate only the fundamental component from low-pass, filtered data, while the disturbance waveform is obtained by using DFT. The application of Prony’s method only to the fundamental component reduces the computational effort required by this method significantly and allows the size of the window of the DFT to be set as an integer multiple of the estimated fundamental period, which minimizes the spectral leakage of the DFT. The main advantages of the proposed, new approach include high resolution and accuracy in the estimation of indices and significant reduction of the computational cost. Experiments were conducted and comparisons were made using both synthetic and measured data. The results confirmed the effectiveness and efficiency of the proposed scheme.

This is the companion paper to “Part I: theoretical aspects”. Part I reviews and critically analyses some of the most significant single-objective optimization methodologies proposed for the optimal operation of plug-in electric vehicles (PEVs) operating in Smart Grids. This Part II applies the models presented in Part I to a low voltage test Smart Grid. Analysis of the results highlights the behavior of the considered control strategies in terms of their compliance with both the objective functions and constraints. In the final part of this paper the results are summarized and compared in order to give an useful tool for understanding the more appropriate objectives and constraints to be taken into account for an optimal control of the Smart Grids.

This paper proposes a novel scheme that jointly employs a sliding-window ESPRIT and DFT for estimating harmonic and interharmonic components in power system disturbance data. In the proposed scheme, separate stages are utilized to estimate the voltage fundamental component, harmonics and interharmonics. This includes the estimation of the fundamental component from lowpass filtered data using a sliding-window ESPRIT, of harmonics from a sliding-window DFT with a synchronized window, and of interharmonics from the residuals by applying the sliding-window ESPRIT. Main advantages of the approach include high resolution and accuracy in parameter estimation and significantly reduced computational cost. Experiments and comparisons are made on both synthetic and measurement data. Results have shown the effectiveness and efficiency of the proposed scheme.

Plug-in Electric Vehicles (PEVs) could become remarkable resources for improving quality and reliability of future grids, if adequate control of their onboard storage systems is provided. Hence, the problem of PEVs optimal control strategies is a crucial topic of research in modern power system operation. This is particularly true in the Smart Grid (SG) context, where the presence of bi-directional communications among distributed energy resources and customers makes it possible to obtain an optimized operation of the grid. In this paper a critical overview of some of the most significant single-objective optimization methodologies proposed for the optimal operation of PEVs in electrical distribution networks is presented in order to verify their feasibility in the context of SGs. These methodologies allow the performance of several services, which aim to meet both needs internal to the SG (for example, the losses minimization or the minimization of average voltage deviations) and external to it (for example, ancillary services to the electrical system to whom the SG is interconnected). This paper reports the theoretical aspects of the optimization models, whereas the companion paper “Part II: numerical applications to vehicle fleets” proposes the results of the analysed models.

Distribution system planners have frequently to choose among different solutions either in deterministic framework or under problem data uncertainty. In these conditions, adequate methods are needed to choose the optimal solution. This paper refers to electrical distribution systems with static converters and formulates the planning problem of passive filtering systems as a multi-objective optimization problem. A heuristic simplified approach including tradeoff/risk analysis issues is proposed to solve the problem with the aim of optimizing several objectives and meeting proper equality and inequality constraints. The approach is able to quickly find solutions on the Pareto frontier that can help the Decision Maker in selecting the final planning alternative to be practically operated. Both deterministic and uncertain frameworks are taken into account. This paper is a companion paper to a paper of the same title, Part II [1], in which the proposed approach is applied on a 17-busbars distribution test system. (8 pages)

This is a companion to a paper of the same title, Part I [1], which deals with the theoretical aspects of the optimal allocation of passive filters in distribution electrical networks with static converters. Part I formulates the multiobjective optimization model and proposes a heuristic solution procedure based on trade-off/risk analysis. This Part II presents and discusses numerical applications of the approach proposed in Part I, in order to illustrate the implementation problems and practical applications. The numerical tests refer to a 16-node Medium Voltage distribution system and consider both deterministic and uncertain frameworks. (7 pages)

In recent years, modern distribution networks are rapidly evolving toward the new concept of Smart Grid (SG) due to the increasing level of penetration of distributed generation (DG) units, storage systems and information and communication technologies. In the framework of low voltage distribution systems, SGs based on either AC or DC grids have been proposed and compared in the technical literature, evidencing their advantages and drawbacks. Only recently, hybrid SGs that include both DC and AC grids have been proposed with the aim of optimizing the whole system behavior. In this paper, an innovative hybrid low voltage SG that includes properly controlled AC and DC grids is analyzed. The DC grids - including storage systems and interconnected to the AC grid through AC/DC PWM-controlled static converters - highly contribute to improve both quality and continuity of supply to AC and DC sensitive loads. The AC grid is optimally controlled to perform several system services (i.e., minimize power losses and optimize voltage profiles at fundamental frequency and at harmonic frequencies). Time domain simulations on a 30-node low voltage hybrid SG are presented and discussed to evidence the effectiveness of the considered solution.

Distributed generation units in microgrids are typically inadequate to meet the total loads demand during the peak hours, whereas a surplus of energy can be available during the hours of the day characterized by low demand. On the other hand, the foreseeable large use of plug-in electric vehicles storage systems could enable to modify the microgrid daily load demand; plug-in electric vehicles batteries, in fact, can have the multiple role of loads and energy sources. On the basis of the above considerations, this paper focuses on the economical scheduling of electric vehicles powers by proposing a single-objective optimization model that minimizes the total amount of daily cost suffered for the energy imported from the upstream network. The model includes also a constraint on the active power at the interconnection bus of the microgrid, thus enabling the peak shaving service. The effectiveness of the single-objective strategy is demonstrated with numerical applications to a low voltage test microgrid.

The problem of developing a definition that adequately assesses power-quality (PQ) levels in the presence of distributed generation (DG) is addressed by using proper probabilistic indices for distribution networks. In the planning of new DG installations, these indices take the variation of PQ level into account and use weighting functions properly. They are useful in quantifying the impact of the installation of DG units because they can consider several PQ disturbances simultaneously. Also, they indicate how each PQ disturbance may affect the decision concerning the installation of DG units. Several tests on real distribution networks were performed and discussed in order to show the usefulness of these indices in evidencing the impact of DG on PQ levels. The analysis of the electrical distribution systems on the basis of the considered indices is valuable also to help decide the best allocation and size of distributed generators.

This study considers a distribution system with a number of dispersed generation (DG) units interconnected to the AC grid through power electronic interfaces. Some selected DG units were able to provide energy service and system ancillary services (in particular, voltage regulation and partial compensation or elimination of some power quality disturbances, such as waveform distortions and voltage unbalances) through a proper centralised control system that provides the reference signals to the converters of the DG units in real time. In addition, the problem of time delays owing to data acquisition and digital signal processing for reference signal calculations and the effects of these delays on compensation actions were studied. Several time-domain simulations of an actual distribution system are reported, taking into account different DG units and time-delay scenarios.

The paper deals with energy storage systems applications in Smart Grids. Several services can be performed thanks to the energy storage systems use, with objectives aimed at meeting needs internal or external to the Smart Grid. Optimal nonlinear constrained problems can be formulated and properly solved in order to perform the services in the best economical and technical way. In this paper, optimal control strategies are proposed in order to allow the Smart Grid to minimize internal losses and to sell energy and ancillary services during high power prices periods. The procedure involves the formulation of optimal power flow problems; proper objective functions and constraints are imposed to satisfying the services that have to be carried out. A numerical application on a 30-bus low voltage Smart Grid shows the effectiveness of the proposed procedure.

In this paper, the problem of the use of dispersed generation (DG) for providing ancillary services in electrical distribution systems is addressed. Fuel cell-based, photovoltaic cell-based, and wind generation systems are connected to the distribution network through power electronic interfaces, each with a proper storage system for the optimal grid operation. Thanks also to the storage system, the DG units are able to provide ancillary services such as load following, back-up, peak shaving, reactive power support and power quality disturbance compensation. A centralized control system coordinates the DG units. Time domain simulations on an actual distribution system are reported and discussed.

Distribution networks are undergoing radical changes due to the high level of penetration of dispersed generation. Dispersed generation systems require particular attention due to their incorporation of uncertain energy sources, such as wind farms, and due to the impacts that such sources have on the planning and operation of distribution networks. In particular, the foreseeable, extensive use of wind turbine generator units in the future requires that distribution system engineers properly account for their impacts on the system. Many new technical considerations must be addressed, including protection coordination, steady-state analysis, and power quality issues. This paper deals with the very short-term, steady-state analysis of a distribution system with wind farms, for which the time horizon of interest ranges from one hour to a few hours ahead. Several wind-forecasting methods are presented in order to obtain reliable input data for the steady-state analysis. Both deterministic and probabilistic methods were considered and used in performing deterministic and probabilistic load-flow analyses. Numerical applications on a 17-bus, medium-voltage, electrical distribution system with various wind farms connected at different busbars are presented and discussed.

In this paper, the point estimate method is applied to account for the uncertainties that affect the evaluation of the steady state operating conditions of an unbalanced three-phase power system in the presence of wind farms. The accuracy of the proposed technique is tested on the three-phase unbalanced IEEE 34-bus test system adequately modified to take into account the presence of wind farms; the results obtained by applying the Monte Carlo simulation are assumed as a reference. The main conclusion is that the point estimate method gives good solutions in terms of accuracy and computational efforts.

Genetic algorithms (GAs) are widely used for optimal allocation of capacitors in distribution systems. When dealing with large-scale systems, such as in case of unbalanced multi-converter distribution systems, these algorithms can require significant computational efforts, which reduce their effectiveness. In order to reduce processing time for GAs and simultaneously maintain adequate levels of accuracy, methods based on the reduction of the search space of GAs or based on micro-genetic algorithms have been proposed. These methods generally guarantee good solutions with acceptable levels of computational effort. In this paper, some fast, GA-based methods are compared and applied for solving the problem of optimal sizing and siting of capacitors in unbalanced multi-converter distribution systems. The algorithms have been implemented and tested on the unbalanced IEEE 34-bus test distribution system, and their performances have been compared with the performance of the simple genetic algorithm technique.

The problem of choosing the optimal location and size for shunt capacitors in unbalanced distribution systems can be formulated as a mixed, non-linear, constrained multi-objective optimization problem, and is usually solved in deterministic scenarios. However, distribution systems are stochastic in nature, which leads to inaccurate deterministic solutions.

This paper applies the point estimate method to account for the uncertainties that affect the evaluation of the steady state operating condition of an unbalanced three-phase power system. Moreover, since the point estimate method requires that the input random variables are uncorrelated, a suitable adjustment to take into account the correlation is applied. Different point estimate schemes (2m, 2m + 1 and 4m + 1 schemes) are presented and tested. The accuracy of the proposed techniques is tested on a three-phase unbalanced IEEE 34-bus test system; the results obtained applying the Monte Carlo simulation are assumed as reference . Both correlated and uncorrelated input random variables are considered, and multimodal probability density functions are tested. The conclusion is that the 2m + 1 scheme gives the best solution in terms of accuracy and computational efforts; in the case of correlated input random variables, an adequate procedure to take into account the correlation must be applied.

– An electrical distribution system with several dispersed generation (DG) units interconnected to the AC grid through PWM static converters is considered. The DG units can provide both energy and system ancillary services (e.g. voltage regulation, voltage harmonic distortion and unbalance compensation). The DG unit converters are coordinated through a centralized control system that provides in real time the reference signals to the control systems of the DG static converters allowing them to provide the aforementioned services. The centralized control system calculates the reference signals using an optimization procedure whose inputs are measurements from the distribution network busbars and whose outputs are the reference signals; thus, the compensation action is depending on the unavoidable time delays introduced in the whole process by data acquisition, digital processing and data communication. With particular reference to the waveform distortion compensation, the paper proposes a new procedure to compensate them. Time domain simulations on an actual distribution system are reported in order to analyze the delay effects and show the effectiveness of the proposed compensation procedure.

The presence of the new liberalized markets has increased the interest in power-quality (PQ) disturbances due to their economic effect. In particular, in the case of disturbances caused by a single event (such as a capacitor switching or voltage sag), the waveform assessment can be difficult due to the rapid variations in waveform spectral component characteristics; these difficulties require a suitable choice of signal-processing techniques for spectral analysis and, in particular, the resort to time-frequency representations. In this paper, the adaptive Prony method is proposed to calculate PQ indices based on a time-frequency analysis of waveforms. Numerical applications on a simulated transient due to capacitor switching, a measured voltage sag, and a test waveform are also presented and discussed in order to investigate the validity of the proposed method.

Discrete Fourier Transform (DFT) is recommended for waveform distortion assessment in IEC Standard framework. One of the most important problems for DFT application is the spectral leakage. It was shown in the literature that the most remarkable errors due to leakage problems in power system waveform assessment are mainly due to the errors in synchronizing fundamental and harmonics. In this paper, a new two-steps signal processing technique based on ESPRIT and DFT methods is proposed. This technique guarantees a fast and accurate synchronization of fundamental and harmonics; it also allows to obtain an accurate evaluation of the low frequency interharmonics. The proposed method is applied on test waveforms in order to demonstrate its effectiveness in terms of reduced computational efforts and accuracy of the results.

The increasing penetration of dispersed generation (DG) influences the power quality (PQ) levels in the distribution networks. Then, an accurate assessment of PQ disturbances in presence of DG is needed and adequate probabilistic indices should be adopted to properly quantify the random nature of the disturbances. In this paper, a tool for the calculation of slow voltage variations, waveform distortions, unbalances, voltage fluctuations and voltage sag probabilistic indices has been developed by using DigSilent Power Factory software. Numerical applications are performed on a 120-bus distribution network whose DG units are wind generators and gas turbine units.

Electrical power system robustness is defined as the intrinsic capacity of an electrical power system to maintain assigned disturbance levels when external conditions change. This paper compares two methods for estimating voltage dip severity: the critical distance method and the fault position method. Their differences are not linked to the type of network but to the type of results which we are searching for. This paper proposes a graphical color visualization of the during fault voltage matrices that immediately correlates dip severity with colors defined by a proper scale. New robustness indices are also proposed to synthesize bus performance in terms of affected and exposed areas. Numerical applications refer to real transmission and real distribution systems.

In this paper, the problem of the optimal allocatio n and sizing of capacitors in unbalanced distribution sys tems is formulated as a multi-objective optimization proble m. This problem is solved by means of the e-constrained technique. Besides, some methods for determining a reduced fea sible region and a micro genetic algorithm are used. The solving method proposed is tested on the IEEE 34-node unbal anced distribution system in order to demonstrate the eff ectiveness of the approaches in terms of reduced computational efforts and accuracy of the results.

The paper deals with the reactive power control in a MV distribution system in presence of Dispersed Generation (DG). The control variables are the reactive powers of DG units and capacitors, and the tap position of the on-load tap changer of the HV/MV transformer. Single-objective and multi-objective optimization problems are formulated and solved in order to achieve the optimal control, even containing the impact of the waveform distortions. Numerical applications performed on a 109-bus test distribution system give evidence of the effectiveness of the proposed procedure.

The International Electrotechnical Commission (IEC) standards characterize the waveform distortions in power systems with the amplitudes of harmonic and interharmonic groups and subgroups. These groups/subgroups utilize the waveform spectral components obtained from a fixed frequency-resolution discrete Fourier transform (DFT). Using the IEC standards allows for a compromise among the different goals, such as the needs for accuracy, simplification, and unification. In some cases, however, the power-system waveforms are characterized by spectral components that the DFT cannot capture with enough accuracy due to the fixed frequency resolution and/or the spectral leakage phenomenon. This paper investigates the possibility of a group/subgroup evaluation using the following advanced spectrum estimation methods: adaptive Prony, estimation of signal parameters via rotational invariance techniques, and root multiple-signal classification (MUSIC). These adaptive methods use variable lengths of time windows of analysis to ensure the best fit of the waveforms; they are not characterized by the fixed frequency resolution and do not suffer from the spectral leakage phenomenon. This paper also presents the results of the applications of these methods to three test waveforms, to current and voltage waveforms obtained from simulations of a real DC arc-furnace plant, and to waveforms measured at the point of common coupling of the low-voltage network supplying a high-performance laser printer.

The problem of sizing and location of capacitor banks in unbalanced distribution systems with nonlinear loads is addressed. This problem can be solved by means of genetic algorithm based procedures that have been proven to find good solutions. However, when dealing with multiconverter unbalanced large scale systems, these algorithms may require significant computational effort which will reduce their effectiveness. In this paper a hybrid method, which significantly reduces the computational effort without affecting the level of accuracy is proposed. The hybrid method involves a two step procedure: first a small number of nodes are selected as candidate buses for the capacitor allocation through the application of the inherent structure theory of networks; then, a heuristic procedure based on sequential placement of discrete capacitor units is applied to the selected buses. Numerical examples are presented to demonstrate the efficiency of the proposed procedure.

The voltage continuity and quality are two different aspects of the quality on the electrical supply. Their regulation is of great importance due to the economical consequences associated with the presence of the disturbances in the electrical power systems. While voltage continuity has been regulated in several countries for his undouble importance, the voltage quality has only recently become an important concern for utilities, customers and consulting engineers. Actually, a fervid international debate is underway to find the best economic regulatory mechanism to improve the voltage quality. This paper illustrates some mechanisms of economic voltage quality regulation proposed in the most recent international literature.

The presence of the new liberalized markets has increased interest in power quality disturbances due to their economic value. Customers have more choices; then disturbances are becoming bigger issues and suppliers and customers should regulate them in the frame of power quality contracts. A single global power quality index can be very useful for characterizing the overall level of the voltage waveform quality; in particular, this index can provide global indications regarding different aspects of voltage quality and allows a strong reduction of the measurement data needed to cover all power quality disturbances, in this paper, a global power quality index (GPQI) for discrete disturbances is proposed, based on the discrete severity indicators (DSI). We present the results of a GPQI evaluation of an Italian distribution system on voltage dips, whose measured data are available on the website of the project QuEEN led by CESI Ricerca.

Dispersed Generation (DG) is often connected to the network with power-electronic interfaces for a proper coupling with the distribution networks (e.g. photovoltaic panels, fuel cells, microturbines, wind turbines, etc.). Such power electronics can perforin functions other than the supply of real power thus representing an opportunity to increase the value of DG as provider of new additional services. In particular, the innovation and the improvements in electronic devices allow using DG for the provision of ancillary services (voltage control, power quality disturbance compensation, and so on), representing, in this way, an interesting chance to improve the quality of the service. For these reasons, specific planning tools for the optimal siting and sizing of DG should be adopted to take into consideration the multiple and contrasting goals that the Distribution System Operators (DSO) strive to achieve. In the paper the optimal siting and sizing of DG connected through electronic interfaces is performed by means of multiobjective programming and an -constrained technique is used for the solution of the problem. Particular attention is paid to the modelling of electronic interfaces in order to obtain the required ancillary service provision. Simulation results on a test system demonstrate the usefulness of the proposed methodology as well as the advantages obtained by the use of electronic interfaces in comparison to solutions employing electric generators directly coupled to the distribution network.

The paper deals with the power converter to be used in realising small scale generation units of electric and thermal energy. Polymeric fuel cells supplied with hydrogen obtained with natural gas reforming are considered as the most adequate fuel cell type for low and medium size applications. The complete structure of multistage converters is presented together with proper modelling of fuel cell. The model of fuel cell accounts for parameter variations with temperature and with reformer output. The simulations are performed using also experimental data obtained at Department of Industrial Engineering with existing 1.2 kW polymeric fuel cell system.

A probabilistic method is proposed to take into account the uncertainties of loads and wind production in electrical unbalanced distribution systems. The proposed method is based on Monte-Carlo simulation applied to the nonlinear three-phase load flow equations including wind farms, thereby taking into account all load and line unbalances that can characterise the distribution systems. The method allows the evaluation of phase-voltage and unbalance factor probability functions and in particular the maximum values and 95th percentiles, being the statistical measures of greatest interest in many international standards for power quality. Numerical applications are presented and discussed with reference to the three-phase unbalanced IEEE 34-bus test distribution system in presence of wind farms connected at different busbars.

Several transmission and distribution systems are known to have unbalanced lines and line sections carrying a mixture of single, double, and three-phase loads; moreover, their steady-state conditions are affected by unavoidable uncertainties that require to analyze these systems with probabilistic approaches. In this article, a probabilistic three-phase load flow using a multi-linear simulation algorithm is proposed. The method properly extends to the field of unbalanced systems a probabilistic method proposed for balanced systems. Numerical examples on the three-phase unbalanced IEEE 13-bus and 34-bus distribution test systems are provided and discussed to illustrate the application of the proposed method. The results obtained with the proposed algorithm are compared with the ones obtained using a Monte Carlo simulation algorithm, which includes the non linear three-phase load flow equations. Copyright © 2006 John Wiley & Sons, Ltd.

A primary problem in waveform distortion assessment in power systems is to examine ways to reduce the effects of spectral leakage. In the framework of DFT approaches, line frequency synchronization techniques or algorithms to compensate for desynchronization are necessary; alternative approaches such as those based on the Prony and ESPRIT methods are not sensitive to desynchronization, but they often require significant computational burden. In this paper, the signal processing aspects of the problem are considered; different proposals by the same authors regarding DFT-, Prony-, and ESPRIT-based advanced methods are reviewed and compared in terms of their accuracy and computational efforts. The results of several numerical experiments are reported and analysed; some of them are in accordance with IEC Standards, while others use more open scenarios.

The wide use of the induction motors for industrial and transport applications leads to increase the interest in their monitoring for on-line detection of incipient faults. The traditional diagnostic techniques are based on the stator current or torque spectral analysis by FFT-based methods. However, the well known spectral leakage phenomena of FFT can cause not accurate estimation of the spectral components; moreover, its frequency resolution problems limits a fast detection of the fault condition. In order to solve these problems, this paper presents an high resolution method, the ESPRIT method, to make the fault identification faster and accurate. A proper dynamic model of the induction machine is used to simulate the occurring of a fault condition. Simulation results allow to compare the ESPRIT and FFT-based methods, considering the case of some rotor bars broken.

The method of fault position is useful for characterising power-system performance in the presence of voltage dips due to faults. It is based on short-circuit simulations repeated for all the system nodes and for many points along the system lines: fault voltages that are below a preset threshold are the required voltage dips. These dips are stored in so-called dip matrices which contain only the dips in all the system nodes when faults occur at points along the lines. The paper proposes a new compact analytical formulation of dip matrices for balanced and unbalanced faults in terms of bidimensional vector relations and for site- and system-voltage dip indexes. Compact formulations are very useful tools when several sensitivity analyses have to be conducted to estimate variation of site- and system-voltage dip indexes in relation to possible reinforcement and/or compensation devices. Graphical presentation of dip matrices is also proposed as a valuable tool to ascertain the critical area for system performance. Numerical applications to an actual transmission system are presented to demonstrate the easy applicability of the model.