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Pierluigi Siano

University of Salerno, Department of Industrial Engineering, Faculty Member

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Pierluigi Siano (M’09–SM'14) received the M.Sc. degree in electronic engineering and the Ph.D. degree in information and electrical engineering from the University of Salerno, Salerno, Italy, in 2001 and 2006, respectively.
He is a Professor and Scientific Director of the Smart Grids and Smart Cities Laboratory with the Department of Management & Innovation Systems, University of Salerno.
His research activities are centered on demand response, on the integration of distributed energy resources in smart grids and on planning and management of power systems.
He has co-authored more than 420 papers including more than 200 international journal papers that received more than 6600 citations with an H-index equal to 43. He has been the Chair of the IES TC on Smart Grids.
He is an Associate Editor of the IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, of the IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS and of IET Renewable Power Generation.
Phone: +39089964294

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Papers by Pierluigi Siano

A power system telematics architecture for developing services based on ICT

Instantaneous Symmetrical Component Estimator Using Second Order Generalized Integrator under Distorted Voltage Conditions

by Emre Ozsoy, Akhtar Rasool, and Pierluigi Siano

Frequency, amplitude and phase information of the grid voltage are of great importance in constru... more Frequency, amplitude and phase information of the grid voltage are of great importance in constructing a robust controller structure for grid connected inverter systems. This paper presents a simple and robust approach for the instantaneous estimation of positive and negative sequence voltage components under distorted voltage conditions. A second order generalized integrator (SOGI) is used to filter the distorted voltage and to generate orthogonal voltage components for each of the three phases. These filtered and orthogonal components are used for instantaneous calculation of symmetrical components. The implemented method is frequency adaptive; the method is demonstrated and compared to a conventional phase locked loop (PLL) technique with both MATLAB/Simulink simulations and experiments utilizing the dSPACE ds1103 digital controller.

Dynamic State Estimation for Synchronous Machines Based on Adaptive Ensemble Square Root Kalman Filter

by Hassan Haes Alhelou and Pierluigi Siano

Dynamic state estimation (DSE) for generators plays an important role in power system monitoring ... more Dynamic state estimation (DSE) for generators plays an important role in power system monitoring and control. Phasor measurement unit (PMU) has been widely utilized in DSE since it can acquire real-time synchronous data with high sampling frequency. However, random noise is unavoidable in PMU data, which cannot be directly used as the reference data for power grid dispatching and control. Therefore, the data measured by PMU need to be processed. In this paper, an adaptive ensemble square root Kalman filter (AEnSRF) is proposed, in which the ensemble square root filter (EnSRF) and Sage-Husa algorithm are utilized to estimate measurement noise online. Simulation results obtained by applying the proposed method show that the estimation accuracy of AEnSRF is better than that of ensemble Kalman filter (EnKF), and AEnSRF can track the measurement noise when the measurement noise changes.

Islanding Detection of Synchronous Distributed Generator Based on the Active and Reactive Power Control Loops

by Hassan Haes Alhelou and Pierluigi Siano

There has been a considerable importance for the islanding detection due to the growing integrati... more There has been a considerable importance for the islanding detection due to the growing integration of distributed generations (DGs) in the modern power grids. This paper proposes a novel active islanding detection scheme for synchronous DGs, considering two additional compensators and a positive feedback for each of active and reactive power control loops. The added blocks are designed using the small gain theorem and stability margins definition considering characteristics of open loop transfer functions of synchronous DG control loops. Islanding can be detected using the proposed method even where there is an exact match between generation and local load without sacrificing power quality. In addition, the performance of the proposed method can be retained even with high penetration of motor loads. The proposed scheme improves the stability and power quality of the grid, when the synchronous DG is subjected to the grid-connected disturbances. Furthermore, this method augments the stability margins of the system in the grid-connected conditions to enhance the disturbances ride-through capability of the system and reduce the negative impact of the active methods on the power quality. Simultaneous advantages of the proposed scheme are demonstrated by modeling a test system in MATLAB software and time-domain simulation achieved by PSCAD.

Targa Prof. Siano new

Integrated energy optimization of smart home appliances with cost-effective energy management system

by Hassan Haes Alhelou and Pierluigi Siano

CSEE Journal of Power and Energy Systems, 2019

Smart grid enables consumers to control and schedule the consumption pattern of their appliances,... more Smart grid enables consumers to control and schedule the consumption pattern of their appliances, minimize energy cost, peak-to-average ratio (PAR) and peak load demand. In this paper, a general architecture of home energy management system (HEMS) is developed in smart grid scenario with novel restricted and multi-restricted scheduling methods for the residential customers. The optimization problem is developed under time of use pricing (TOUP) scheme. To optimize the formulated problem, powerful meta-heuristic algorithm called grey wolf optimizer (GWO) is utilized, which is compared with particle swarm optimization (PSO) algorithm to show its effectiveness. A rooftop photovoltaic (PV) system is integrated with the system to show the cost effectiveness of the appliances. For analysis, eight different cases are considered under various time scheduling algorithms.

An Augmented Prony Method for Power System Oscillation Analysis Using Synchrophasor Data

by Hassan Haes Alhelou, Roozbeh Torkzadeh, and Pierluigi Siano

Energies, 2019

Intrinsic mode functions (IMFs) provide an intuitive representation of the oscillatory modes and ... more Intrinsic mode functions (IMFs) provide an intuitive representation of the oscillatory modes and are mainly calculated using Hilbert-Huang transform (HHT) methods. Those methods, however, suffer from the end effects, mode-mixing and Gibbs phenomena since they use an iterative procedure. This paper proposes an augmented Prony method for power system oscillation analysis using synchrophasor data obtained from a wide-area measurement system (WAMS). In the proposed method, in addition to the estimation of the modal information, IMFs are extracted using a new explicit mathematical formulation. Further, an indicator based on an energy and phase relationship of IMFs is proposed, which allows system operators to recognize the most effective generators/actuators on specific modes. The method is employed as an online oscillation-monitoring framework providing inputs for the so-called wide-area damping control (WADC) module. The efficacy of the proposed method is validated using three test cases, in which the IMFs calculation is simpler and more accurate if compared with other methods.

Exploring the trade-off between competing objectives for electricity energy retailers through a novel multi-objective framework

Energy Conversion and Management, 2015

ABSTRACT Energy retailer is the intermediary between Generation Companies and consumers. In the m... more ABSTRACT Energy retailer is the intermediary between Generation Companies and consumers. In the medium time horizon, in order to gain market share, he has to minimize his selling price while looking at the profit, which is dependent on the revenues from selling and the costs to buy energy from forward contracts and participation in the market pool. In this paper, the two competing objectives are engaged proposing a new multi-objective framework in which a e-constraint mathematical technique is used to produce the Pareto front (set of optimal solutions). The stochasticity of energy prices in the market and customer load demand are coped with the Lattice Monte Carlo Simulation (LMCS) and the method of the roulette wheel, which allow the stochastic multi-objective problem to be turned into a set of deterministic equivalents. The method performance is tested into some case studies.

Special Section on Intelligent Energy Systems

An improved grid-interfaced PV-assisted BSS for grid support

by Satabdy Jena and Pierluigi Siano

—The charging stations for EVs may need the vehicle to be parked for longer hours depending on th... more —The charging stations for EVs may need the vehicle to be parked for longer hours depending on the nature of the charger that may lead to overcrowding and stranding of vehicles at charging stations. This problem can be eliminated by the realization of a Battery Swapping Station (BSS). A BSS can thus be defined as a place at which a vehicle's discharged battery or battery pack can be immediately swapped for a fully charged one, eliminating the delay involved in waiting for the vehicle's battery to charge. The dependency of the BSS on the weak grid for charging can be alleviated by providing a renewable energy input and thus pave the way for distributed generation assisted charging stations. The unnecessary loading on the electrical infrastructure of the distribution network can thus be avoided. The study pertains to the ancillary services of a BSS under different situations of power deficit. A 2-Degree-of-freedom based inverter current and voltage control is also introduced for faster set-point tracking. Extensive simualtions were performed in Matlab/Simulink to validate the efficacy of a grid interfaced PV along with BSS to address power void issues. Keywords—Battery swapping station (BSS)2DoF-PI photo-voltaic (PV) State of Charge (SoC)

HIL based Coordinated Control of grid interfaced Distributed Generation assisted Battery Swapping Station

by Satabdy Jena and Pierluigi Siano

—The large-scale worldwide adoption of Electric Vehicles as a mode of transportation is predicted... more —The large-scale worldwide adoption of Electric Vehicles as a mode of transportation is predicted to create stress on the already loaded power supply network. As such continued efforts in the area of distributed generation assisted charging stations are in full-swing. The paper investigates the outcomes of utilizing a PV assisted Battery Swapping Station to combat and alleviate simultaneously the issues of overburden and energy storage. A BSS can be tethered not only to provide battery swapping services to EVs but also provide for grid support, energy storage, ancillary services, etc. A grid interfaced PV assisted BSS system and its functioning in the smart grid environment has been proposed considering the system has a reliable and secure communication infrastructure. The multiple roles of the BSS and its coordinated functioning with the PV and the grid is examined under various test scenarios. The hardware prototyping of the control strategies for the inverter and the BSS is realized using Virtex-6 FPGA ML605 evaluation kit. The simulation and the hardware co-simulation results are presented to validate the efficacy of the proposed control scheme. Keywords—Battery swapping station (BSS) Hardware-in-loop (HIL) photovoltaic (PV)Field Programmable Gate Array (FPGA)State of Charge (SoC)

Evaluating the impact of sub-hourly unit commitment method on spinning reserve in presence of intermittent generators

by Arman Goudarzi, Pierluigi Siano, and Mehdi Kazemi

Energy, 2016

Doubly-fed induction generators control using the derivative-free nonlinear Kalman Filter

IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society, 2013

ABSTRACT The paper studies differential flatness properties and an input-output linearization pro... more ABSTRACT The paper studies differential flatness properties and an input-output linearization procedure for doubly-fed induction generators (DFIGs). By defining flat outputs which are associated with the rotor&#39;s angle and the magnetic flux of the stator an equivalent DFIG description in the Brunovksy (canonical) form is obtained. For the linearized canonical model of the generator a feedback controller is designed. Moreover, a comparison of the differential flatness theory-based control method against Lie algebra-based control is provided. At a second stage, a novel Kalman Filtering method (derivative-free nonlinear Kalman Filtering) is introduced. The proposed Kalman Filter is redesigned as disturbance observer for estimating additive input disturbances to the DFIG model. These estimated disturbance terms are finally used by a feedback controller that enables the generator&#39;s state variables to track desirable setpoints. The efficiency of the proposed state estimation-based control scheme is tested through simulation experiments.

Hybrid Electric Vehicles: Application of Fuzzy Clustering for Designing a TSK-based Fuzzy Energy Flow Management Unit

Lecture Notes in Computer Science, 2003

... Flow Management Unit Lucio Ippolito, Pierluigi Siano Dipartimento di Ingegneria dell'Inf... more

An H-infinity feedback control approach for three-phase voltage source converters

Iecon 2014 40th Annual Conference of the Ieee Industrial Electronics Society, 2014

An Agent Based Power Flow Control For Hybrid Electric Vehicles

Energy Management for Hybrid Electric Vehicles based on Fuzzy Clustering and Genetic Algorithms

Optimal Siting and Sizing of Wind Turbines Based on Genetic Algorithm and Optimal Power Flow

Green Energy and Technology, 2014

New Trends in Intelligent Energy Systems–An Industrial Electronics Point of View

IEEE Transactions on Industrial Electronics, 2015

Incipient fault detection for electric power transformers using neural modeling and the local statistical approach to fault diagnosis

2012 IEEE Sensors Applications Symposium Proceedings, 2012

A power system telematics architecture for developing services based on ICT

Instantaneous Symmetrical Component Estimator Using Second Order Generalized Integrator under Distorted Voltage Conditions

by Emre Ozsoy, Akhtar Rasool, and Pierluigi Siano

Frequency, amplitude and phase information of the grid voltage are of great importance in constru... more Frequency, amplitude and phase information of the grid voltage are of great importance in constructing a robust controller structure for grid connected inverter systems. This paper presents a simple and robust approach for the instantaneous estimation of positive and negative sequence voltage components under distorted voltage conditions. A second order generalized integrator (SOGI) is used to filter the distorted voltage and to generate orthogonal voltage components for each of the three phases. These filtered and orthogonal components are used for instantaneous calculation of symmetrical components. The implemented method is frequency adaptive; the method is demonstrated and compared to a conventional phase locked loop (PLL) technique with both MATLAB/Simulink simulations and experiments utilizing the dSPACE ds1103 digital controller.

Dynamic State Estimation for Synchronous Machines Based on Adaptive Ensemble Square Root Kalman Filter

by Hassan Haes Alhelou and Pierluigi Siano

Dynamic state estimation (DSE) for generators plays an important role in power system monitoring ... more Dynamic state estimation (DSE) for generators plays an important role in power system monitoring and control. Phasor measurement unit (PMU) has been widely utilized in DSE since it can acquire real-time synchronous data with high sampling frequency. However, random noise is unavoidable in PMU data, which cannot be directly used as the reference data for power grid dispatching and control. Therefore, the data measured by PMU need to be processed. In this paper, an adaptive ensemble square root Kalman filter (AEnSRF) is proposed, in which the ensemble square root filter (EnSRF) and Sage-Husa algorithm are utilized to estimate measurement noise online. Simulation results obtained by applying the proposed method show that the estimation accuracy of AEnSRF is better than that of ensemble Kalman filter (EnKF), and AEnSRF can track the measurement noise when the measurement noise changes.

Islanding Detection of Synchronous Distributed Generator Based on the Active and Reactive Power Control Loops

by Hassan Haes Alhelou and Pierluigi Siano

There has been a considerable importance for the islanding detection due to the growing integrati... more There has been a considerable importance for the islanding detection due to the growing integration of distributed generations (DGs) in the modern power grids. This paper proposes a novel active islanding detection scheme for synchronous DGs, considering two additional compensators and a positive feedback for each of active and reactive power control loops. The added blocks are designed using the small gain theorem and stability margins definition considering characteristics of open loop transfer functions of synchronous DG control loops. Islanding can be detected using the proposed method even where there is an exact match between generation and local load without sacrificing power quality. In addition, the performance of the proposed method can be retained even with high penetration of motor loads. The proposed scheme improves the stability and power quality of the grid, when the synchronous DG is subjected to the grid-connected disturbances. Furthermore, this method augments the stability margins of the system in the grid-connected conditions to enhance the disturbances ride-through capability of the system and reduce the negative impact of the active methods on the power quality. Simultaneous advantages of the proposed scheme are demonstrated by modeling a test system in MATLAB software and time-domain simulation achieved by PSCAD.

Targa Prof. Siano new

Integrated energy optimization of smart home appliances with cost-effective energy management system

by Hassan Haes Alhelou and Pierluigi Siano

CSEE Journal of Power and Energy Systems, 2019

Smart grid enables consumers to control and schedule the consumption pattern of their appliances,... more Smart grid enables consumers to control and schedule the consumption pattern of their appliances, minimize energy cost, peak-to-average ratio (PAR) and peak load demand. In this paper, a general architecture of home energy management system (HEMS) is developed in smart grid scenario with novel restricted and multi-restricted scheduling methods for the residential customers. The optimization problem is developed under time of use pricing (TOUP) scheme. To optimize the formulated problem, powerful meta-heuristic algorithm called grey wolf optimizer (GWO) is utilized, which is compared with particle swarm optimization (PSO) algorithm to show its effectiveness. A rooftop photovoltaic (PV) system is integrated with the system to show the cost effectiveness of the appliances. For analysis, eight different cases are considered under various time scheduling algorithms.

An Augmented Prony Method for Power System Oscillation Analysis Using Synchrophasor Data

by Hassan Haes Alhelou, Roozbeh Torkzadeh, and Pierluigi Siano

Energies, 2019

Intrinsic mode functions (IMFs) provide an intuitive representation of the oscillatory modes and ... more Intrinsic mode functions (IMFs) provide an intuitive representation of the oscillatory modes and are mainly calculated using Hilbert-Huang transform (HHT) methods. Those methods, however, suffer from the end effects, mode-mixing and Gibbs phenomena since they use an iterative procedure. This paper proposes an augmented Prony method for power system oscillation analysis using synchrophasor data obtained from a wide-area measurement system (WAMS). In the proposed method, in addition to the estimation of the modal information, IMFs are extracted using a new explicit mathematical formulation. Further, an indicator based on an energy and phase relationship of IMFs is proposed, which allows system operators to recognize the most effective generators/actuators on specific modes. The method is employed as an online oscillation-monitoring framework providing inputs for the so-called wide-area damping control (WADC) module. The efficacy of the proposed method is validated using three test cases, in which the IMFs calculation is simpler and more accurate if compared with other methods.

Exploring the trade-off between competing objectives for electricity energy retailers through a novel multi-objective framework

Energy Conversion and Management, 2015

ABSTRACT Energy retailer is the intermediary between Generation Companies and consumers. In the m... more ABSTRACT Energy retailer is the intermediary between Generation Companies and consumers. In the medium time horizon, in order to gain market share, he has to minimize his selling price while looking at the profit, which is dependent on the revenues from selling and the costs to buy energy from forward contracts and participation in the market pool. In this paper, the two competing objectives are engaged proposing a new multi-objective framework in which a e-constraint mathematical technique is used to produce the Pareto front (set of optimal solutions). The stochasticity of energy prices in the market and customer load demand are coped with the Lattice Monte Carlo Simulation (LMCS) and the method of the roulette wheel, which allow the stochastic multi-objective problem to be turned into a set of deterministic equivalents. The method performance is tested into some case studies.

Special Section on Intelligent Energy Systems

An improved grid-interfaced PV-assisted BSS for grid support

by Satabdy Jena and Pierluigi Siano

—The charging stations for EVs may need the vehicle to be parked for longer hours depending on th... more —The charging stations for EVs may need the vehicle to be parked for longer hours depending on the nature of the charger that may lead to overcrowding and stranding of vehicles at charging stations. This problem can be eliminated by the realization of a Battery Swapping Station (BSS). A BSS can thus be defined as a place at which a vehicle's discharged battery or battery pack can be immediately swapped for a fully charged one, eliminating the delay involved in waiting for the vehicle's battery to charge. The dependency of the BSS on the weak grid for charging can be alleviated by providing a renewable energy input and thus pave the way for distributed generation assisted charging stations. The unnecessary loading on the electrical infrastructure of the distribution network can thus be avoided. The study pertains to the ancillary services of a BSS under different situations of power deficit. A 2-Degree-of-freedom based inverter current and voltage control is also introduced for faster set-point tracking. Extensive simualtions were performed in Matlab/Simulink to validate the efficacy of a grid interfaced PV along with BSS to address power void issues. Keywords—Battery swapping station (BSS)2DoF-PI photo-voltaic (PV) State of Charge (SoC)

HIL based Coordinated Control of grid interfaced Distributed Generation assisted Battery Swapping Station

by Satabdy Jena and Pierluigi Siano

—The large-scale worldwide adoption of Electric Vehicles as a mode of transportation is predicted... more —The large-scale worldwide adoption of Electric Vehicles as a mode of transportation is predicted to create stress on the already loaded power supply network. As such continued efforts in the area of distributed generation assisted charging stations are in full-swing. The paper investigates the outcomes of utilizing a PV assisted Battery Swapping Station to combat and alleviate simultaneously the issues of overburden and energy storage. A BSS can be tethered not only to provide battery swapping services to EVs but also provide for grid support, energy storage, ancillary services, etc. A grid interfaced PV assisted BSS system and its functioning in the smart grid environment has been proposed considering the system has a reliable and secure communication infrastructure. The multiple roles of the BSS and its coordinated functioning with the PV and the grid is examined under various test scenarios. The hardware prototyping of the control strategies for the inverter and the BSS is realized using Virtex-6 FPGA ML605 evaluation kit. The simulation and the hardware co-simulation results are presented to validate the efficacy of the proposed control scheme. Keywords—Battery swapping station (BSS) Hardware-in-loop (HIL) photovoltaic (PV)Field Programmable Gate Array (FPGA)State of Charge (SoC)

Evaluating the impact of sub-hourly unit commitment method on spinning reserve in presence of intermittent generators

by Arman Goudarzi, Pierluigi Siano, and Mehdi Kazemi

Energy, 2016

Doubly-fed induction generators control using the derivative-free nonlinear Kalman Filter

IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society, 2013

ABSTRACT The paper studies differential flatness properties and an input-output linearization pro... more ABSTRACT The paper studies differential flatness properties and an input-output linearization procedure for doubly-fed induction generators (DFIGs). By defining flat outputs which are associated with the rotor&#39;s angle and the magnetic flux of the stator an equivalent DFIG description in the Brunovksy (canonical) form is obtained. For the linearized canonical model of the generator a feedback controller is designed. Moreover, a comparison of the differential flatness theory-based control method against Lie algebra-based control is provided. At a second stage, a novel Kalman Filtering method (derivative-free nonlinear Kalman Filtering) is introduced. The proposed Kalman Filter is redesigned as disturbance observer for estimating additive input disturbances to the DFIG model. These estimated disturbance terms are finally used by a feedback controller that enables the generator&#39;s state variables to track desirable setpoints. The efficiency of the proposed state estimation-based control scheme is tested through simulation experiments.

Hybrid Electric Vehicles: Application of Fuzzy Clustering for Designing a TSK-based Fuzzy Energy Flow Management Unit

Lecture Notes in Computer Science, 2003

... Flow Management Unit Lucio Ippolito, Pierluigi Siano Dipartimento di Ingegneria dell'Inf... more

An H-infinity feedback control approach for three-phase voltage source converters

Iecon 2014 40th Annual Conference of the Ieee Industrial Electronics Society, 2014

An Agent Based Power Flow Control For Hybrid Electric Vehicles

Energy Management for Hybrid Electric Vehicles based on Fuzzy Clustering and Genetic Algorithms

Optimal Siting and Sizing of Wind Turbines Based on Genetic Algorithm and Optimal Power Flow

Green Energy and Technology, 2014

New Trends in Intelligent Energy Systems–An Industrial Electronics Point of View

IEEE Transactions on Industrial Electronics, 2015

Incipient fault detection for electric power transformers using neural modeling and the local statistical approach to fault diagnosis

2012 IEEE Sensors Applications Symposium Proceedings, 2012

Deregulation e controllo nel decreto Gasparri

Misura dell’esposizione alle radiazioni non ionizzanti e scelte localizzative

NONLINEAR EMBEDDED CONTROL OF SPARK-IGNITED ENGINES USING THE DERIVATIVE-FREE NONLINEAR KALMAN FILTER

FLATNESS-BASED ADAPTIVE FUZZY CONTROL OF SPARK-IGNITED ENGINES

Fuzzy Kalman Filter Validation Using the Local Statistical Approach

In fuzzy Kalman filtering, each local Kalman filter makes use of its own model about the system’s... more In fuzzy Kalman filtering, each local Kalman filter makes use of its own model about the system’s dynamics and the local state estimates are fused into one single state estimate through fuzzy weighting. These models can be inaccurate or the system’s dynamics may change. The objective of the paper is to provide a method for finding out which one of the models used by the local Kalman filters contains parameters that deviate from the nominal values of the parameters of the real system. This is a problem of validation of the fuzzy Kalman filter, that is solved with the use of the local statistical approach to fault diagnosis. The development of a tool which can detect incipient changes in the parameters of the fuzzy Kalman filter is important, since such types of distributed Kalman filters are used in numerous applications that need precision and reliability in the provided state estimation (sensor networks, navigation systems, industrial production systems etc.).

Nonlinear H-infinity Feedback Control for Asynchronous Motors of Electric Trains

A new method for feedback control of asynchronous electrical machines is introduced, with applica... more A new method for feedback control of asynchronous electrical machines is introduced, with application example the problem of the traction system of electric trains. The control method consists of a repetitive solution of an H-infinity control problem for the asynchronous motor, that makes use of a locally linearized model of the motor and takes place at each iteration of the control algorithm. The asynchronous motor’s model is locally linearized round its current operating point through the computation of the associated Jacobian matrices. Using the linearized model of the electrical machine an H-infinity feedback control lawis computed. The known robustness features of H-infinity control enable to compensate for the errors of the approximative linearization, as well as to eliminate the effects of external perturbations. The efficiency of the proposed control scheme is shown analytically and is confirmed through simulation experiments.

Flatness-Based Adaptive Fuzzy Control of Autonomous Submarines

The paper proposes adaptive fuzzy control based on differential flatness theory for autonomous su... more The paper proposes adaptive fuzzy control based on differential flatness theory for autonomous submarines. It is proven that the dynamic model of the submarine, having as state variables the vessel’s depth and its pitch angle, is a differentially flat one. This means that all its state variables and its control inputs can be written as differential functions of the flat output and its derivatives. By exploiting differential flatness properties the system’s dynamic model is written in the multivariable linear canonical (Brunovsky) form, for which the design of a state feedback controller becomes possible. After this transformation, the new control inputs of the system contain unknownnonlinear parts, which are identified with the use of neurofuzzy approximators. The learning procedure for these estimators is determined by the requirement the first derivative of the closed-loop’s Lyapunov function to be a negative one. Moreover, the Lyapunov stability analysis shows that H-infinity tracking performance is succeeded for the feedback control loop and this assures improved robustness to the aforementioned model uncertainty as well as to external perturbations. The efficiency of the proposed adaptive fuzzy control scheme is confirmed through simulation experiments.

Evaluating the effectiveness of normal boundary intersection method for short-term environmental/economic hydrothermal self-scheduling

The problem of the optimal scheduling of available hydro and thermal generating units considering... more The problem of the optimal scheduling of available hydro and thermal generating units considering a short scheduling period (one day-one week) in order to maximize the total profit is denoted as short-term hydro thermal self-scheduling (SHTSS). Mixed-integer linear programming (MILP) method is proposed to model the SHTSS problem in the day-ahead energy and reserve markets. MILP formulation allows for considering a precise model for the prohibited working zones, dynamic ramp rate constraints and operating services of thermal generating units, as well as the characteristics of multi-head power discharge for hydro generating units and reservoirs' spillage. This problem is modelled as a multi-objective (MO) optimization one, having two objectives, i.e. maximization of the profit of Generation Company's (GENCO's) and minimization of emissions from thermal units. In order to solve the problem and generate the non-inferior solutions, normal boundary intersection (NBI) method is applied. The main advantage is the provision of set of uniformly distributed non-dominated solutions regardless of the scales of objective functions values. Then, a fuzzy based decision maker is employed in order to select a non-inferior solution. In order to demonstrate the effectiveness of the presented method, several numerical simulations are presented. Furthermore, the obtained results are compared with those obtained considering different methods for obtaining non-inferior solutions, such as weighted sum method, evolutionary programming-based interactive fuzzy satisfying method, differential evolution, particle swarm optimization and hybrid multi-objective cultural algorithm.

Decentralised control of parallel inverters connected to microgrid using the derivativefree non-linear Kalman filter

Decentralised control for parallel inverters connected to the power grid is developed using diffe... more Decentralised control for parallel inverters connected to the power grid is developed using differential flatness theory and the derivative-free nonlinear Kalman filter. It is proven that the model of the inverters, is a differentially flat one. This means that all its state variables and the control inputs can be written as differential functions of a single algebraic variable which is the flat output. By exploiting differential flatness properties it is shown that the multiple inverters model can be transformed into a set of local inverter models which are decoupled and linearized. For each local inverter the design of a state feedback controller becomes possible. Such a controller processes measurements not only coming from the individual inverter but also coming from other inverters which are connected to the grid. Moreover, to estimate the non-measurable state variables of each local inverter, the derivative-free nonlinear Kalman filter is used. Furthermore, by redesigning the aforementioned filter as a disturbance observer it becomes also possible to estimate and compensate for disturbance terms that affect each local inverter.

Innovative control logics for a rational utilization of electric loads and air-conditioning systems in a residential building

The paper focuses on the evaluation of the impact on residential buildings of innovative control ... more The paper focuses on the evaluation of the impact on residential buildings of innovative control logicsdefined for a rational utilization of the electric loads and air-conditioning systems. The control logics areimplementable thanks to a Decision Support and Energy Management Systems developed by the sameauthors and easily installable in new and still-existing houses.The paper shows how a significant reduction of the primary energy consumption can be obtained bycontrolling the air-conditioning units together with the other electric loads of the house.After having explained how the control logics operate, a simulation tool is described, developed for apreliminary evaluation of their effects on the energy consumptions of residential buildings in the designstage. An application of the simulation tool on a typical house, considering different scenarios and varyingthe climatic conditions and the energy performance class of the envelope, is presented.Finally, a measurement campaign on two real existing houses, equipped with the Decision Support andEnergy Management System, is described, and the effects of the control logics are assessed.

A New Nonlinear H-infinity Feedback Control Approach to the Problem of Autonomous Robot Navigation

This research work introduces a new control method for feedback control of nonlinear dynamical sy... more This research work introduces a new control method for feedback control of nonlinear dynamical systems with application example the problem of trajectory tracking by an autonomous robotic vehicle. The control method consists of a repetitive solution of an H-infinity control problem for the mobile robot, that makes use of a locally linearized model of the robot and takes place at each iteration of the control algorithm. The vehicle’s model is locally linearized round its current position through the computation of the associated Jacobian matrices. Using the linearized model of the vehicle an H-infinity feedback control law is computed. The known robustness features of H-infinity control enable to compensate for the errors of the approximative linearization, as well as to eliminate the effects of external perturbations. The efficiency of the proposed control scheme is shown analytically and is confirmed through simulation experiments. The method can be applied to a wide class of nonlinear dynamical systems.

Journal of Intelligent Industrial Systems: Preface to Volume 1 Issue No 4

Journal of Intelligent Industrial Systems: Preface to Volume 1 Issue No 2

Economic-environmental active and reactive power scheduling of modern distribution systems in presence of wind generations: A distribution market-based approach

Distribution System Operator (DSO) is responsible for active and reactive power scheduling in a d... more Distribution System Operator (DSO) is responsible for active and reactive power scheduling in a distribution system. DSO purchases its active and reactive power requirements from Distributed Energy Resources (DERs) as well as the wholesale electricity market. In this paper, a new economical/environmental operational scheduling method based on sequential day-ahead active and reactive power markets at distribution level is proposed to dispatch active and reactive powers in distribution systems with high penetration of DERs. In the proposed model, after day-ahead active power market was cleared the participants submit their reactive power bids and then the reactive power market will be settled. At distribution level, developing a Var market, in which DERs like synchronous machine-based Distributed Generation (DG) units and Wind Turbines (WTs) could offer their reactive power prices, DERs are motivated to actively participate in the Volt/VAr Control (VVC) problem. To achieve this purpose, based on the capability curves of considered DERs, innovative multi-component reactive power bidding structures for DERs are introduced. Moreover, the effect of reactive power market clearing on the active power scheduling is explicitly considered into the proposed model by rescheduling of active power by usage of energybalance service bids. On the other hand, environmental concerns that arise from the operation of fossil fuel fired electric generators are included in the proposed model by employing CO2 emission penalty cost. The suggested reactive power market is cleared through a mixed-integer nonlinear optimization program. The effectiveness of the proposed scheduling model is investigated through a typical 22-bus distribution test system over a 24-h period.

A Novel RBF Training Algorithm for Short-Term Electric Load Forecasting and Comparative Studies

Because of their excellent scheduling capabilities, artificial neural networks (ANNs) are becomin... more Because of their excellent scheduling capabilities, artificial neural networks (ANNs) are becoming popular in short-term electric power system forecasting, which is essential for ensuring both efficient and reliable operations and full exploitation of electrical energy trading as well. For such a reason, this paper investigates the effectiveness of some of the newest designed algorithms in machine learning to train typical radial basis function (RBF) networks for 24-h electric load forecasting: support vector regression (SVR), extreme learning machines (ELMs), decay RBF neural networks (DRNNs), improves second order, and error correction, drawing some conclusions useful for practical implementations.

Multiobjective Optimal Design of Photovoltaic Synchronous Boost Converters Assessing Efficiency, Reliability, and Cost Savings

Optimal design of switching converters for the integration and optimal exploitation of renewable ... more Optimal design of switching converters for the integration and optimal exploitation of renewable energy sources (RES) represents a crucial issue often debated in the recent power electronics literature. The design problem required to carry out a multiobjective optimization characterized by simultaneous conflicting objectives, such as efficiency, reliability, and price, where the best compromise solution should be found by the decision maker among Pareto-optimal solutions. In this paper, a novel design method for distributed maximum power point tracking (DMPPT) synchronous boost converter is proposed. The method is based on nondominated sorting genetic algorithm with the aim to obtain the best synchronous rectification (SR) boost topology while considering different targets such as converter efficiency and reliability maximization, as well as converter price minimization. New weighted indices are also proposed for a more realistic characterization of the devices.

New Trends in Intelligent Energy Systems-An Industrial Electronics Point of View

Journal of Intelligent Industrial Systems: Preface to Volume 1 Issue No 3

Journal of Intelligent Industrial Systems: Preface to Volume 1 Issue No 1

Robust day-ahead scheduling of smart distribution networks considering demand response programs

Increasing penetration of variable loads and renewable resources in smart distribution networks b... more Increasing penetration of variable loads and renewable resources in smart distribution networks brings about great challenges to the conventional scheduling and operation due to the uncertain nature. This paper presents a novel uncertainty handling framework, based on the underlying idea of robust optimization approach, to portray the uncertainties of load demands and wind power productions over uncertainty sets. Accordingly, a tractable min–max–min cost model is proposed to find a robust optimal day-ahead scheduling of smart distribution network immunizing against the worst-case realization of uncertain variables. In addition, considering demand response programs as one of the important resources in the smart distribution network, participation of customers in both energy and reserve scheduling is explicitly formulated. As the proposed min–max–min cost model cannot be solved directly by commercial optimization packages, a decomposition algorithm is presented based on dual cutting planes to decouple the problem into a master problem and a sub-problem. The master problem finds the day-ahead scheduling, while the sub-problem determines the worst-case realization of uncertain variables within uncertainty sets. Computational results for the modified version of IEEE 33-bus distribution test network demonstrate the effectiveness and efficiency of the proposed model.

Qualità dell’alimentazione nei sistemi di trasporto elettrificati per l’Alta Velocità italiana

Fuzzy Clustering applied to power flow management for Parallel Hybrid Electric Vehicles

A Fuzzy Decision Support System for Multi-Objective Optimal Power Flow to Reduce Magnetic Fields from Power Lines

A TSK-based fuzzy unit for Hybrid Electric Vehicles energy flow

An Agent Based System for Electrical Components Protection

DG and protection systems in distributed networks: failure monitoring system based on Petri Nets

A power system telematics architecture for developing services based on ICT

A power system telematics architecture for developing services based on ICT

Derivative-free nonlinear Kalman Filtering for control of three-phase voltage source converters

Flatness-based embedded control of air-fuel ratio in combustion engines

Designing a customized electric power storage device for Smart Grids

A nonlinear Kalman filtering approach to embedded control of turbocharged diesel engines

An H-infinity feedback control approach to autonomous robot navigation

Validation of the Fuzzy Kalman Filter for ship tracking applications

Tracking of ships’ motion and monitoring of maritime traffic can be performed with the use of dis... more Tracking of ships’ motion and monitoring of maritime traffic can be performed with the use of distributed Kalman Filtering. However, some of the local Kalman Filters which constitute distributed estimation schemes may be based on inaccurate models of the vessel’s dynamics or kinematics and in such a case the aggregate state estimate provided by the distributed filter is unreliable. To treat this problem the paper proposes a statistical method of optimized performance for the validation of Fuzzy Kalman Filters used in ship tracking. This statistical validation test is capable of detecting the faulty local filter within the distributed estimation method, even in the case of small errors in the local model’s parameters which do not exceed 1% of the associated nominal values.

Nonlinear synchronizing control of parallel inverters connected to the electricity grid

To assure power quality and stability of the electricity network it is important to perform contr... more To assure power quality and stability of the electricity network it is important to perform control and synchronization of the inverters which are used in the connection of distributed DC power generation units to the grid. It is proven that the model of the inverters, is a differentially flat one. By exploiting differential flatness properties it is shown that the multiple inverters model can be transformed into a set of local inverter models which are decoupled and linearized. For each local inverter the design of a state feedback controller becomes possible, e.g. using pole placement methods. Such a controller processes measurements not only coming from the individual inverter but also coming from other inverters which are connected to the grid. Moreover, to estimate the nonmeasurable state variables of each local inverter, the Derivativefree nonlinear Kalman Filter is used. This consists of the Kalman Filter recursion applied to the local linearized model of the inverter and of an inverse transformation that is based on differential flatness theory, which enables to compute estimates of the state variables of the initial nonlinear model of the inverter. Furthermore, by redesigning the aforementioned filter as a disturbance observer it becomes also possible to estimate and compensate for disturbance terms that affect each local inverter.

Nonlinear H-infinity feedback control for asynchronous motors of electric trains

A new method for feedback control of asynchronous electrical machines is introduced, with applica... more A new method for feedback control of asynchronous electrical machines is introduced, with application example the problem of the traction system of electric trains. The control method consists of a repetitive solution of an H-infinity control problem for the asynchronous motor, that makes use of a locally linearized model of the motor and takes place at each iteration of the control algorithm. The asynchronous motor’s model is locally linearized round its current operating point through the computation of the associated Jacobian matrices. Using the linearized model of the electrical machine an H-infinity feedback control law is computed. The known robustness features of H-infinity control enable to compensate for the errors of the approximative linearization, as well as to eliminate the effects of external perturbations. The efficiency of the proposed control scheme is shown analytically and is confirmed through simulation experiments.

Target tracking by distributed autonomous vessels using the Derivative-free nonlinear Kalman Filter

In this paper a distributed control problem for unmanned surface vessels (USVs) is formulated as ... more In this paper a distributed control problem for unmanned surface vessels (USVs) is formulated as follows: there are N USVs which pursue another vessel (moving target). At each time instant each USV can obtain measurements of the target’s cartesian coordinates. The objective is to make the USVs converge in a synchronized manner towards the target, while avoiding collisions between them and avoiding collisions with obstacles in their motion plane. A distributed control law is developed for the USVs which enables not only convergence of the USVs to the goal position, but also makes possible to maintain the cohesion of the USVs fleet. Moreover, distributed filtering is performed, so as to obtain an estimate of the target vessel’s state vector. This provides the desirable state vector to be tracked by each one of the USVs. To this end, a new distributed nonlinear filtering method of improved accuracy and computation speed is introduced. This filtering approach, under the name Derivative-free distributed nonlinear Kalman Filter is based on differential flatness theory and on an exact linearization of the target vessel’s dynamic/kinematic model.

Adaptive fuzzy control based on output feedback for synchronization of distributed power generators

Flatness-based adaptive fuzzy control of autonomous submarines

Flatness-based adaptive fuzzy control for active power filters

A new method of adaptive control for active power filters is developed in this article. By provin... more A new method of adaptive control for active power filters is developed in this article. By proving that the active power filter is a differentially flat system, its transformation to the linear canonical (Brunovsky) form becomes possible. In this new description the control input of the active power filter comprises unknown nonlinear terms which are identified by neurofuzzy networks and through an adaptation / learning procedure. These estimated parts of the system’s dynamics are used in an indirect adaptive control scheme, which finally makes the outputs of the active power filter converge to the desirable setpoints. The learning rate in the aforementioned adaptation procedure is given a value which assures that a suitably chosen Lyapunov function will remain negative definite. Under the proposed control method, the closed loop of the active power filter is shown to satisfy the Hinfinity tracking criterion, which implies a maximum capability for rejection of external perturbations as well as of modelling errors. flatness-based adaptive fuzzy control based on differential flatness theory is a completely model-free control method. When designing the controller, there is no need for prior knowledge of the system’s parameters and state-space equations.

Sensorless Control of DC and Induction Motors Using Kalman Filtering

A derivative-free Extended Information Filtering approach for sensorless control of nonlinear systems

Nonlinear System Modeling with Invariance to Fourier Transform for Fault Diagnosis: Application to Power Transformers

Differential flatness properties and feedback control of the Fokker-Planck PDE

OPTIMIZATION OF CHARACTERISTIC PARAMETERS FOR MOBILE IP DISCOVERED FACTS TO BE APPLIED IN INDUSTRY INFORMATICS

A Survey and Evaluation of the Potentials of Distributed Ledger Technology for Peer-to-Peer Transactive Energy Exchanges in Local Energy Markets

The unpredictability and intermittency introduced by Renewable Energy Sources (RESs) in power sys... more The unpredictability and intermittency introduced by Renewable Energy Sources (RESs) in power systems may lead to unforeseen peaks of energy production, which might differ from energy demand. To manage these mismatches, a proper communication between prosumers (i.e., users with RESs that can either inject or absorb energy) and active users (i.e., users that agree to have their loads changed according to the system needs) is required. To achieve this goal, the centralized approach used in traditional power systems is no longer possible because both pro-sumers and active users would like to take part in energy transactions , and a decentralized approach based on transactive energy systems (TESs) and Peer-to-Peer (P2P) energy transactions should be adopted. In this context, the Distributed Ledger Technology (DLT), based on the blockchain concept arises as the most promising solution to enable smart contracts between prosumers and active users, which are safely guarded in blocks with cryptographic hashes. The aim of this paper is to provide a review about the deployment of decentralized TESs and to propose and discuss a transactive management infrastructure. In this context, the concept of Proof of Energy is proposed as a novel consensus protocol for P2P energy exchanges managed by DLT. An application of the proposed infrastructure considering a Virtual Power Plant (VPP) aggregator and residential prosumers endowed with a new transactive controller to manage the electrical storage system is discussed.