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This work investigates voltages on overhead distribution lines produced by direct strokes, protected by shield wires, placed both above and below phase conductors. An improved formulation based on transfer matrix method and theory of multiconductor transmission lines with periodic grounding allows to eliminate the need of two characteristic wave impedance matrices. Based on the theoretical formulation developed in the first part of this work, as well as on the models there presented for the pole and grounding systems, we report here a wealth of simulation results concerning the line overvoltages subsequent to a pole being hit by lightning. Results are discussed considering a variety of factors, namely, position of the victim pole, type of load at both ends of the line, presence or absence of underbuilt shield wires, waveform of the lightning current, soil parameters and parameters of the frequency-dependent impedance of the pole grounding system. The good performance of the developed method is assessed by comparing our results with some EMTPRV simulations. The transfer matrix method is then used to show the effect of shield wires in conjunction with periodic grounding: we assess the effects of terminations, frequency dependent models of the pole footing and grounding systems and frequency dependent models of lossy ground.

This work is devoted to the analysis of voltages produced on overhead distribution lines hit by direct lightning. We will consider arbitrary terminations at both line ends and, also, arbitrary positioning of the pole being struck. We will deal with lines protected by shield wires, placed either above or below the phase conductors. The analytical tools chosen to deal with such complex system are the transfer matrix method and the theory of multiconductor transmission lines with periodic grounding. The innovation of an articial symmetrical unit cell has been introduced to eliminate the need of two characteristic wave impedance matrices and to ease computation ow.

In smart grids and microgrids, time series prediction is a fundamental tool for enabling intelligent energy resource management and advanced interactions between heterogeneous agents. In this work, we propose a solution to the energy forecasting problem based on two machine learning techniques: Convolutional Neural Network and Long Short-Term Memory Network. These techniques are combined with a new embedding format to appropriately feed the time series to the stacked network architecture. The resulting novel deep learning scheme is able to retrieve information from the data by inferring time dependent correlation structures. The model is validated using real-world examples, showing good performances with a 3-days forecasting horizon.

In this article, the low-frequency magnetic shielding effectiveness of a planar screen with magnetic and conductive properties in a coplanar-loops configuration (as required in the IEEE Standard 299) is evaluated through a new closed-form formula under the thin-sheet and small-loop approximations. The formulation clearly shows the separate contribution of the permeability and the conductivity of the screen to the shielding performance. The results obtained with the proposed closed-form formulas are compared with the exact ones derived through numerical integrations to assess the relevant accuracy and limits of validity.

A recent analytical formulation for the low-frequency magnetic shielding effectiveness of a thin metal screen against a circular loop source is extended to the case of a screen exhibiting both magnetic and conductive properties. The presence of magnetic properties introduces a series impedance in the equivalent network of the structure, in addition to the shunt admittance associated with the screen conductivity. However, the fields scattered by the two elements do not interact and hence can be treated independently; furthermore, the series impedance gives rise to integrals akin to those stemming from the shunt admittance. A generalized analytical formulation for a combined magnetic and conductive screen is thus obtained, that is favorably compared with both classical approximate formulations and exact results.

This paper investigates a general description of a hybrid energy hub (HEH) including multiple energy carriers, such as electricity, hydrogen gas, and heating. The real hybrid energy hub model is based on a conceptual approach for the inclusion of distributed resources. Couplings between the different energy carriers are regarded explicitly, enabling investigations in power and energy flow. The model consists in a smart microgrid with multiple and hybrid energy sources, storages and loads, including electric vehicles charging stations and hydrogen, completely controlled and monitored by a supervisory control and data acquisition platform (SCADA). All the components communicate by an open protocol to the main control for management, analysis and diagnostic. The completely open and flexible structure makes this platform ideal for the conception, simulation and experimental development of innovative systems in the field of microgrids and hybrid energy systems.

The concept of energy communities is promising to empower alternative ways of organizing and governing energy systems in the next future. Energy communities will provide to end-users democratic, open access to the grid, and collective self-consumption. They will encourage decentralization and promote distributed renewable energy sources applications. Energy communities are widely recognized to be a fundamental step for a sustainable energy transition. The authors present an innovative power-sharing model that can be easily implemented in new and existing multi-apartment buildings. It allows end-users to collect into a democratic energy community and enjoy beneficial ecological effects and economic benefits.

In this article, the authors discuss the crucial aspects of the insulation resistance testing of photovoltaic (PV) installations. This test verifies the integrity of the wiring systems and can be used to detect or prevent damages to wiring as well as ground faults. The insulation resistance test measures the resistance between the ungrounded circuits and the ground under the application of high voltage. The baseline insulation resistance can be compared to measurements over time to assess the degradation of PV arrays or conductors. This test is accepted worldwide as a crucial element of commissioning and acceptance, and it is governed by several technical standards.

Time series classification is a fundamental problem when applied to energy distribution issues. In this paper, the authors propose a solution for the detection of electric energy theft (as well as of electric energy anomalies) by introducing a novel time series classification. Data obtained via actual measurements in industrial sites were employed. Our approach was based on the training of a DNN to recognize whether a measurement of a single-day energy profile were subject to any anomaly. Our proposed method was tested and experimentally validated against the results of accepted benchmarks. The outcomes clearly indicate that the performance of our methodology does outperform the other architectures employed as a benchmark, considering the accuracy and its standard deviation.

A novel deep learning approach in proposed in this paper for multivariate prediction of energy time series. It is developed by using Convolutional Neural Network and Long Short-Term Memory models, in such a way that several correlated time series can be joined and filtered together considering the long term dependencies on the whole information. The learning scheme can be viewed as a stacked deep neural network where one or more layers are superposed, feeding their output in the sequent layer’s input. The new approach is applied to real-world problems in energy area to prove robustness and accuracy.

This paper investigates the feasibility of a recently proposed building energy community scheme where the energy of a single rooftop photovoltaic system is shared by costumers with a open and democratic participation. A Simulink/Matlab model is developed where we focus on the implementation and control aspects of all the relevant components, e.g., voltage source inverters for ac grid connection, dc/dc converter with maximum power point tracking strategy, inverters control for energy sharing among end-user. Preliminary results confirm the efficiency and flexibility of the proposed scheme.

We propose a deep learning approach for multivariate forecasting of energy time series. It is developed by using Long Short-Term Memory deep neural networks so that different related time series, incorporating information of longterm dependencies, can be joined together as a multidimensional input of the deep neural network. The learning scheme can be represented as a stacked LSTM network in which one or more layers are cascaded, feeding their output to the input of the sequent layer. To prove the effectiveness of the approach, it has been tested on real-world problems pertaining to the energy field, where time series prediction is of paramount importance..

The electromagnetic problem of calculating the pulsed radiation from a horizontal magnetic dipole in the presence of a planar thin conductive screen is solved analytically in the time domain via a modified Cagniard-de Hoop approach. The components of the relevant time-domain electric and magnetic dyadic Green's functions are expressed by simple one-dimensional integrals over a finite integration domain. Expressions for the transient electromagnetic fields can thus easily be obtained and numerical results are provided that illustrate the main time-domain shielding characteristics.

The electromagnetic interaction of a vertical magnetic dipole axially symmetric with an infinitesimally thin perfectly conducting circular disk is studied and solved by transforming the original dual integral-equation system describing the problem into two forms of the single second-kind Fredholm integral equation. In this way, simple low- and high-frequency asymptotic solutions are easily derived. Numerical results are provided to validate the proposed solutions.

Metal Oxide Surge Arresters may represent an efficient choice for limiting lightning surges, significantly reducing the outage rate of overhead lines. The present work displays an analysis on the performance of gapless light-weight line surge arresters. The model recommended by IEEE is implemented in an FDTD model of overhead multiconductor lines by means of a local implicit scheme based on a set of non-linear equations. The model proves to ensure robustness and second-order accuracy.

The magnetic shielding effectiveness of a planar metallic screen of infinite extent against a circular loop field source is analytically evaluated in a new closed-form formula under the thin sheet and small-loop approximations. The results obtained with the proposed formulation are compared with the exact ones derived numerically and with those obtained through classical approximate formulations. It is thus shown that the proposed formula is the most accurate closed-form expression proposed so far and the frequency range where a percentage relative error less than $\text{1}\%$ is obtained is clearly identified.

The large-scale deployment of pervasive sensors and decentralized computing in modern smart grids is expected to exponentially increase the volume of data exchanged by power system applications. In this context, the research for scalable, and flexible methodologies aimed at supporting rapid decisions in a data rich, but information limited environment represents a relevant issue to address. To this aim, this paper outlines the potential role of Knowledge Discovery from massive Datasets in smart grid computing, presenting the most recent activities developed in this field by the Task Force on “Enabling Paradigms for High-Performance Computing in Wide Area Monitoring Protective and Control Systems” of the IEEE PSOPE Technologies and Innovation Subcommittee.

The need of reliable prediction algorithms of energy production is increasing due to the spread of smart solution for grid, plant and resource management. Recurrent neural networks are a viable solution for prediction but their performance is somewhat insufficient when the time series is generated by an underlying process that behaves in a complex manner. In this paper, a new combination of echo state network and genetic algorithms is employed in order to improve the prediction accuracy of photovoltaic time series. The genetic algorithm is used to embed past samples of the time series to be used for predicting a new one. It aims at a feature extraction in order to regularize data being fed into a neural network model, so that it is able to learn more robust and generalizable prediction models. The experimental tests prove that the proposed approach is suited to the application focused in this paper.

In the modern power grid framework, Renewable Energy Sources must be integrated into the existing energy systems to optimally deal with load, power and electromagnetic imbalance issues. In this context, smart grids have a pivotal role in transforming the aggregation of decentralized power sources. In order to implement these complex systems and to enable such an integration, machine learning techniques must be investigated and adopted where necessary. The realization of smart systems to solve dispatchability problems must rely on various learning schemes, in particular forecasting of time series regarding load, price, and power. In this paper, an emerging machine learning paradigm is proposed, which makes use of a distributed architecture based on the Long Short-Term Memory Network model, a type of recurrent neural network that is tailored to the aforementioned forecasting problems.

Academic laboratories should be a safe environment in which one can teach, learn, and conduct research. Sharing a common principle, the prevention of potential accidents and imminent injuries is a fundamental goal in the laboratory environments. In addition, academic laboratories are attributed exceptional responsibility to instill in students the culture of the safety, the basis of risk assessment, and of the exemplification of the prudent practices around energized objects. Undergraduate laboratory assignments may normally be framed based upon the repetition of established experiments and procedures, whereas academic research laboratories may involve new methodologies and/or apparatus, for which the hazards may not be completely known to the faculty and student researchers. Yet, the academic laboratory should be an environment free of electrical hazards for both routine experiments and research endeavors, and faculty should offer practical inputs and safety-driven insights to academic administration to achieve such a paramount objective. In this article, the authors discuss the challenges to electrical safety in modern academic laboratories, where users may be exposed to harmful touch voltages.

In this paper, the authors discuss the crucial aspects of the insulation resistance testing of PV installations. This test verifies the integrity of wiring systems, and can be used to detect or prevent damages to wiring and ground faults. The insulation resistance test measures the resistance between ungrounded circuits and ground, under the application of high-voltage. Baseline insulation resistance can be compared to measurements over time to assess degradation of PV arrays or conductors. This test is worldwide accepted as a crucial element of commissioning, and acceptance, and is governed by several technical standards. In this paper, the authors critically discuss technical issues related to the insulation resistance test, which can be challenging in large PV systems, and the correct application of standards. In addition, a case study is presented, which includes the results of insulation measurements performed on a 4.9 MWp free-field grid-connected PV installation, located in Southern Italy, whose operation was affected by continuous insulation failures.

Academic laboratories should be a safe environment in which one can teach, learn, and conduct research. Sharing a common principle, the prevention of potential accidents and imminent injuries is a fundamental goal of laboratory environments. In addition, academic laboratories are attributed the exceptional responsibility to instill in students the culture of the safety, the basis of risk assessment, and of the exemplification of the prudent practice around energized objects. Undergraduate laboratory assignments may normally be framed based upon the repetition of established experiments and procedures, whereas, academic research laboratories may involve new methodologies and/or apparatus, for which the hazards may not be completely known to the faculty and student researchers. Yet, the academic laboratory should be an environment free of electrical hazards for both routine experiments and research endeavors, and faculty should offer practical inputs and safety-driven insights to academic administration to achieve such a paramount objective. In this paper, the authors discuss the challenges to the electrical safety in modern academic laboratories, where users may be exposed to harmful touch voltages.

The classical problem represented by a planar thin conductive shield in the presence of vertical dipole field sources (electric or magnetic) is solved analytically in the time domain via the Cagniard-de Hoop technique. Comparisons with numerical solutions carried out by means of efficient integration algorithms are provided and discussed.

The magnetic shielding effectiveness of finite-width thick planar screens against near-field sources producing extremely low-frequency magnetic fields is studied in detail. In particular, by means of a careful numerical analysis, the effects of several screen parameters (such as dimensions, constitutive parameters, and position with respect to the source) are accurately assessed, in addition to shedding light into the main field penetration mechanisms.

Offshore wind towers may influence each other in the presence of faults or lightning strokes through the grounding system and the leakage currents. These phenomena are investigated by taking into account the non-uniform media surrounding the towers. In particular, simplified (in the quasistatic approximation) analytical expressions for the ground resistance are provided, and their numerical validation is presented, with specific reference to actual types of foundations currently adopted.

Power lines are longitudinally nonuniform, nonsymmetrical systems, where ordinary modal analysis, originally conceived for uniform multiconductor transmission lines (MTL), can be utilized only as a zeroth-order approximation. In this paper, we present an accurate analysis of nonuniform MTLs based on the frequency-domain transmission-matrix formalism for 2 $n$ -port systems, where two unequal characteristic immittance matrices need to be defined, one for forward propagation and another for backward propagation. This paper, focused on the characteristic (or surge) immittance matrices, shows how they can be computed, describes their general properties, and reveals, for the first time, that in some cases they may not be physically realizable, meaning that a matched termination made of purely passive lumped components may not exist. The matrix theory developed in the paper is illustrated with simulation results concerning three-phase power line configurations where resonance phenomena take place at certain critical frequencies.

Large-scale ground-mounted PV plants, because of their large extend and localization, can be subject to lightning strikes. When a lightning strike falls into the area of the PV plant, the earthing system is affected by the current flowing in the lightning channel and potentially dangerous overvoltages may occur. Thus, the investigation on the performance of the grounding system is of paramount interest for the prediction of the potential threats either for people working in (or animals passing through) the solar farm area and for the installed electric and electronic equipments. The analysis of grounding systems is conducted in the frequency domain and an hybrid approach, based on circuit theory and Method of Moments, is adopted in order to fully account for resistive, inductive and capacitive couplings between elements of the ground system. The actual transient behavior is obtained by means of an Inverse Fourier Transform. A real case study grounding system configuration is considered and analyzed. We show that, even if the requirements of the international standards are fulfilled, and touch and step voltages are controlled with special care, overvoltages may cause failures of internal systems.

The paper describes a measurement campaign conducted at the Engineering Department of Astronautics, Electrical and Energetic, Sapienza University of Rome. Starting from measurement campaign, in the context of building an urban microgrid, a PV plant and a energy storage system has been proposed. The measurements were conducted in two relevant period of the year in order to know the power consumption of the facility. The knowledge of total energy demand by electrical loads allows the identification of most efficient strategies for energy utilization by using the PV production and energy storage.

High penetration level of intermittent and variable renewable electricity generation introduces signicant challenges to energy management of modern smart grids. Solar photo-voltaics and wind energy have uncertain and non-dispatchable output which leads to concerns regarding the technical and economic feasibility of a reliable integration of large amounts of variable generation into electric grids. In this scenario, accurate forecasting of renewable generation outputs is of paramount importance to secure operation of smart grids. In this paper, we present a study on the use of fuzzy neural networks and their application to the prediction of solar photovoltaic outputs. The new learning strategy is suited to any fuzzy inference model. The comparison with respect to well-known neural and fuzzy neural models will prove that our approach is able to follow the behavior of the underlying unknown process with a good prediction of the observed time series.

The shielding effectiveness of thin planar shields against magnetic field is investigated in the time domain. The analysis is performed considering a vertical magnetic dipole as the source and a classical twelve inches diameter loop as receiving antenna. The computations are performed through a recently proposed analytical solution. The relevant features of classical configurations are extracted and the effects of shield constitutive parameters on the relevant time-domain shielding parameters are presented.

The performance of electromagnetically thin planar shields are investigated in the time domain considering near field sources in order to extract the relevant features of reference configurations. The analysis is performed numerically and the influence of shield constitutive parameters and of the source distance on the relevant time-domain shielding parameters is also presented.

In the last ten years, after the first Italian feed-in-tariff, it has been observed that during the operation and maintenance of large-scale grid-connected photovoltaic systems, several unexpected problems may occur whose solution calls for specific strategies not initially planned at the design stage. Based on information gathered from more than 80 plants located in Italy, this work outlines the most widespread issues, the principal typologies of failures and unexpected events that occur in photovoltaic plants and tries to propose the best ways to solve them.

In the modern distributed generation scenario, the installation of domestic-scale energy generation systems has dramatically growth, raising a number of problems on both the prosumer and distribution sides whose solution calls for new concepts of demand-side energy management of smart grids. These new strategies require an improved smartness of the distribution networks, but also encourage customers not only to participate in energy generation but also in an efficient electricity consumption. The widespread penetration of energy storage systems (ESS) at the domestic domestic level could be an important step toward the application of modern strategies which incentivate energy consumption/production scheduling games. In this paper we develop a Matlab model to simulate the behaviour of a prosumer with a domestic-rated photovoltaic (PV) system, a battery ESS and an electric vehicle (EV) charging station. Simulation results confirm the effectiveness of the ESS in reducing the energy exchanged with the grid as well consumer daily electricity charges.

The continuity of shield wires is often broken for losses reduction purposes in high voltage transmission lines. The accurate simulation of the effects of this practice on power line communications in multiconductor transmission lines is performed in the time domain by means of a finite-difference method. Losses in wires and ground are accounted for by means of transient per unit length parameters and recursive convolution. The method overcomes most of the usual problems encountered by frequency-domain modal analysis techniques.

The ability to forecast the power produced by renewable energy plants in short and middle terms is a key issue to allow an high-level penetration of the distributed generation into the grid infrastructure. Forecasting energy production is mandatory for dispatching and distribution issues, at the Trasmission System Operator level, as well as electrical distributors and power system operators level. In this paper we present three techniques based on neural and fuzzy neural networks, which are well suited to predict data sequences stemming from real-world applications. The preliminary results concerning the prediction of the power generated by a large-scale photovoltaic plant in Italy confirm the reliability and accuracy of the proposed approaches.

Propagation and attenuation properties of modes supported by graphene nano-ribbons placed on top of a grounded dielectric substrate are investigated by means of a spectral-domain Method-of-Moments approach together with a dyadic description of the graphene conductivity obtained based on semiclassical and quantum-mechanical arguments. Such a description takes into account the possible presence of static biasing fields or spatial-dispersion effects. The attenuation features are investigated and are compared to those of similar metal structures.

ZnO is receiving a considerable attention for the development of novel cost-effective nanostructures with outstanding functional properties for applications in electronics and energy. In this paper, we investigate the effects of the nonlinear piezoelectricity, that has been recently observed in ZnO nanostructures, on the piezotronic effect of ZnO nanowires (NWs). We insert a physically-based model of the nonlinear direct piezoelectric effect into a fully-coupled thermo-mechanical-electric scheme to study the current-voltage characteristic of ZnO NWs under a purely vertical compressive/tensile strain. Our results show for the first time that the nonlinear piezoelectricity deeply affects the current transport processes inside the NW and the behavior of devices for piezoelectric-piezotronic applications and provides remarkable insights into the underlying physics. © 2002-2012 IEEE.

A novel Frequency Selective Surface (FSS) is proposed for the design of polarization-insensitive metamaterial absorbers that operate around 1 GHz, where the first resonances of small commercial enclosures take place. The novel FSS is based on the simplification of an alternative Roman maze. It shows a strong sub-wavelength response and is promising for the design of compact planar absorbers with excellent angular and polarization stability.

Prediction of the potential threats due to direct lightning strokes of sensitive targets, e.g., overhead power-line towers, substations or buildings, requires accurate modeling of the transient impedance of grounding systems. When large-scale simulations are needed, detailed and computationally intensive models are hardly viable, although they usually offer great accuracies. In this work we investigate the suitability and compare the accuracies of two different approaches. In the first we adopt a hybrid circuit-field approach to predict the behavior of grounding systems at any frequency of interest. This approach is based on circuit theory and Method of Moments, and is capable to fully account for resistive, inductive and capacitive couplings between elements of the grounding system. Since the analysis is carried out in the frequency domain, the actual transient behavior can be obtained by means of an Inverse Fourier Transform. In the second approach we consider a fully circuital approach. It is a genetic algorithm-based procedure able to synthesize a generalized equivalent pi-circuit model that is used to simulate the impulse response of complex grounding systems, including possible nonlinear soil ionization, working directly in the time domain.

Fundamental properties of plasmon modes propagating along graphene nanoribbons are investigated by means of a Method-of-Moments approach together with a dyadic description of a nonlocal graphene conductivity. Modal propagation, field distributions, and characteristic impedances are studied in details showing the dramatic effects of spatial dispersion.