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Ferdinanda Ponci received a Ph.D. degree in electrical engineering from the Politecnico di Milano, Milan, Italy, in 2002. In 2003, she joined the Department of Electrical Engineering, University of South Carolina, Columbia, SC, USA, as an Assistant Professor, where she became an Associate Professor in 2008. In 2009, she joined the E.ON Research Center, Institute for Automation of Complex Power Systems, RWTH Aachen University, Aachen, Germany, where she is currently a Professor of monitoring and distributed control for power systems. Her current research interests include automation and the advanced monitoring of active distribution systems.
A joint raw moments-based analytical method (JRMAM) is first proposed herein to deal with probabilistic power flow (PPF) of hybrid AC/VSC-MTDC (Alternate Current/Voltage Source Control-Multiple Terminal Direct Current) power systems with integration of the offshore wind farms. JRMAM is able to overcome the challenges of some existing combined methods in estimating the high order moments of target outputs, and the dramatic time consumption of Monte Carlo simulation method (MCSM) in performing PPF analysis particularly due to the complication of deterministic power flow (DPF) model. The proposed JRMAM has a further superiority on efficiency, even compared to the joint cumulants-based analytical method (JCAM). As a preliminary step, discrete Fourier transformation matrix (DFTM) method is applied to calculate the joint raw moments of random inputs which are required by conducting JRMAM, and the probability density function of outputs can be estimated by means of Gram-Charlier expansions. Two modified IEEE test cases connected with DC subsystems through the VSC devices are adopted to verify the effectiveness and the scalability of JRMAM, where the result of MCSM is treated as a reference, and the properties of hybrid AC/VSC-MTDC power system with these master-slave controlled VSCs are investigated for a further acceleration on PPF analysis.
Xingyu Lin; Tong Shu; Junjie Tang; Ferdinanda Ponci; Antonello Monti; Wenyuan Li. Application of Joint Raw Moments-Based Probabilistic Power Flow Analysis for Hybrid AC/VSC-MTDC Power Systems. IEEE Transactions on Power Systems 2021, PP, 1 -1.
AMA StyleXingyu Lin, Tong Shu, Junjie Tang, Ferdinanda Ponci, Antonello Monti, Wenyuan Li. Application of Joint Raw Moments-Based Probabilistic Power Flow Analysis for Hybrid AC/VSC-MTDC Power Systems. IEEE Transactions on Power Systems. 2021; PP (99):1-1.
Chicago/Turabian StyleXingyu Lin; Tong Shu; Junjie Tang; Ferdinanda Ponci; Antonello Monti; Wenyuan Li. 2021. "Application of Joint Raw Moments-Based Probabilistic Power Flow Analysis for Hybrid AC/VSC-MTDC Power Systems." IEEE Transactions on Power Systems PP, no. 99: 1-1.
The increasing and fast deployment of distributed generation is posing challenges to the operation and control of power systems due to the resulting reduction in the overall system rotational inertia and damping. Therefore, it becomes quite crucial for the transmission system operator to monitor the varying system inertia and damping in order to take proper actions to maintain the system stability. This paper presents an inertia estimation algorithm for low-inertia systems to estimate the inertia (both mechanical and virtual) and damping of systems with mixed generation resources and/or the resource itself. Moreover, the effect of high penetration of distributed energy resources and the resulting heterogeneous distribution of inertia on the overall system inertia estimation is investigated. A comprehensive set of case studies and scenarios of the IEEE 39-bus system provides results to demonstrate the performance of the proposed estimator.
Diala Nouti; Ferdinanda Ponci; Antonello Monti. Heterogeneous Inertia Estimation for Power Systems with High Penetration of Converter-Interfaced Generation. Energies 2021, 14, 5047 .
AMA StyleDiala Nouti, Ferdinanda Ponci, Antonello Monti. Heterogeneous Inertia Estimation for Power Systems with High Penetration of Converter-Interfaced Generation. Energies. 2021; 14 (16):5047.
Chicago/Turabian StyleDiala Nouti; Ferdinanda Ponci; Antonello Monti. 2021. "Heterogeneous Inertia Estimation for Power Systems with High Penetration of Converter-Interfaced Generation." Energies 14, no. 16: 5047.
Integration of electric vehicles into electric power system brings both challenges and solutions in the operation of power grids. On the one hand, simultaneously charging a large number of electric vehicles causes branch congestion or large voltage drop. Operating the electric vehicles in the discharging mode, on the other hand, introduces the provision of several ancillary services like peak power shaving and spinning reserves. From the electric vehicles operation point of view, thus, the distribution system operators require a real-time monitoring infrastructure to capture the states of electric vehicle chargers and accordingly operate their grids in the safe mode with respect to the power quality standards (e.g., EN 50160). In this context, the real-time smart charging and storage platform of the EU Horizon 2020 “MEISTER” project, based on the information and communication technology, manages the availability of electric vehicles as a potential source of energy in the need of one or more flexibility services demanded by low voltage distribution system operators. In addition to the implemented information and communication technology platform, this paper presents how the smart use of the electric vehicle resources supports the power quality of the distribution system in terms of system voltage support, bidirectional power flow management, harmonic alleviation and power factor control.
Behzad Zargar; Ting Wang; Manuel Pitz; Rainer Bachmann; Moritz Maschmann; Angelina Bintoudi; Lampros Zyglakis; Ferdinanda Ponci; Antonello Monti; Dimosthenis Ioannidis. Power Quality Improvement in Distribution Grids via Real-Time Smart Exploitation of Electric Vehicles. Energies 2021, 14, 3533 .
AMA StyleBehzad Zargar, Ting Wang, Manuel Pitz, Rainer Bachmann, Moritz Maschmann, Angelina Bintoudi, Lampros Zyglakis, Ferdinanda Ponci, Antonello Monti, Dimosthenis Ioannidis. Power Quality Improvement in Distribution Grids via Real-Time Smart Exploitation of Electric Vehicles. Energies. 2021; 14 (12):3533.
Chicago/Turabian StyleBehzad Zargar; Ting Wang; Manuel Pitz; Rainer Bachmann; Moritz Maschmann; Angelina Bintoudi; Lampros Zyglakis; Ferdinanda Ponci; Antonello Monti; Dimosthenis Ioannidis. 2021. "Power Quality Improvement in Distribution Grids via Real-Time Smart Exploitation of Electric Vehicles." Energies 14, no. 12: 3533.
Direct Current (DC) grids are considered an attractive option for integrating high shares of renewable energy sources in the electrical distribution grid. Hence, in the future, Alternating Current (AC) and DC systems could be interconnected to form hybrid AC-DC distribution grids. This paper presents a two-step state estimation formulation for the monitoring of hybrid AC-DC grids. In the first step, state estimation is executed independently for the AC and DC areas of the distribution system. The second step refines the estimation results by exchanging boundary quantities at the AC-DC converters. To this purpose, the modulation index and phase angle control of the AC-DC converters are integrated into the second step of the proposed state estimation formulation. This allows providing additional inputs to the state estimation algorithm, which eventually leads to improve the accuracy of the state estimation results. Simulations on a sample AC-DC distribution grid are performed to highlight the benefits resulting from the integration of these converter control parameters for the estimation of both the AC and DC grid quantities.
Gaurav Roy; Marco Pau; Ferdinanda Ponci; Antonello Monti. A Two-Step State Estimation Algorithm for Hybrid AC-DC Distribution Grids. Energies 2021, 14, 1967 .
AMA StyleGaurav Roy, Marco Pau, Ferdinanda Ponci, Antonello Monti. A Two-Step State Estimation Algorithm for Hybrid AC-DC Distribution Grids. Energies. 2021; 14 (7):1967.
Chicago/Turabian StyleGaurav Roy; Marco Pau; Ferdinanda Ponci; Antonello Monti. 2021. "A Two-Step State Estimation Algorithm for Hybrid AC-DC Distribution Grids." Energies 14, no. 7: 1967.
The development of strategies for distribution network management is an essential element for increasing network performance and reducing the upgrade of physical assets. This paper analyzes a multi-timescale framework to control the voltage of distribution grids characterized by a high penetration of renewables. The multi-timescale solution is based on three levels that coordinate Distributed Generation (DG) and Energy Storage Systems (ESSs), but differs in terms of the timescales and objectives of the control levels. Realistic load and photovoltaic generation profiles were created for cloudy and clean sky conditions to evaluate the performance features of the multi-timescale framework. The proposed solution was also compared with different frameworks featuring two of the three levels, to highlight the contribution of the combination of the three levels in achieving the best performance.
Edoardo De Din; Fabian Bigalke; Marco Pau; Ferdinanda Ponci; Antonello Monti. Analysis of a Multi-Timescale Framework for the Voltage Control of Active Distribution Grids. Energies 2021, 14, 1965 .
AMA StyleEdoardo De Din, Fabian Bigalke, Marco Pau, Ferdinanda Ponci, Antonello Monti. Analysis of a Multi-Timescale Framework for the Voltage Control of Active Distribution Grids. Energies. 2021; 14 (7):1965.
Chicago/Turabian StyleEdoardo De Din; Fabian Bigalke; Marco Pau; Ferdinanda Ponci; Antonello Monti. 2021. "Analysis of a Multi-Timescale Framework for the Voltage Control of Active Distribution Grids." Energies 14, no. 7: 1965.
Our economies and societies are becoming more and more knowledge based which implies that increasing numbers of people need to be educated and trained on new subjects and processes. Thus, the reduction of the effort needed to design and prepare educational and training programmes that meet the needs of the society and the market is of paramount importance. To achieve this goal, first, we define a learning programme model so that programme designers can easily exchange and re-use programme structures and learning materials. The proposed model additionally enables easier creation of interdisciplinary programmes which is another need of today’s market. Second, we deploy a web-based tool that adopts this model towards facilitating the re-use of structures and materials. Third, to reduce the time required for the training actors to sense the market needs, we propose the establishment of an educational programme marketplace. All three endeavours have been validated in the energy transition sector and (positively) evaluated by experts during an international workshop.
Helen C. Leligou; Ferdinanda Ponci; Rosanna De Rosa; Panagiotis A. Karkazis; Constantinos S. Psomopoulos. Designing an innovative educational toolbox to support the transition to new technologies. SN Social Sciences 2021, 1, 1 -22.
AMA StyleHelen C. Leligou, Ferdinanda Ponci, Rosanna De Rosa, Panagiotis A. Karkazis, Constantinos S. Psomopoulos. Designing an innovative educational toolbox to support the transition to new technologies. SN Social Sciences. 2021; 1 (3):1-22.
Chicago/Turabian StyleHelen C. Leligou; Ferdinanda Ponci; Rosanna De Rosa; Panagiotis A. Karkazis; Constantinos S. Psomopoulos. 2021. "Designing an innovative educational toolbox to support the transition to new technologies." SN Social Sciences 1, no. 3: 1-22.
Power flow (PF) is a fundamental tool for operation, automation and optimization of the power systems. Due to the nonlinearity of the PF system equations, the classical PF solutions are computationally very demanding. As a common approach in solving the nonlinear equations, linearization is a potential technique which can simplify and accelerate the PF calculations. In this context, this paper proposes a linear fast iterative method based on the fixed-point iteration technique in which a linearized model of generator along with a ZI load model are integrated in a simplified system of linear equations (SLE) of $Yv=i$ . The relaxation method is used during the deriving process of generator equivalent current in this approach. However, the already developed ZI load model based on the curve-fitting technique has been exploited in this work. The accuracy of the proposed PF method has been compared with calculated results from DIgSILENT PowerFactory on the benchmark IEEE 33-bus test system and on a large medium voltage network in Germany.
Behzad Zargar; Antonello Monti; Ferdinanda Ponci; Jose R. Marti. Linear Iterative Power Flow Approach Based on the Current Injection Model of Load and Generator. IEEE Access 2020, 9, 11543 -11562.
AMA StyleBehzad Zargar, Antonello Monti, Ferdinanda Ponci, Jose R. Marti. Linear Iterative Power Flow Approach Based on the Current Injection Model of Load and Generator. IEEE Access. 2020; 9 ():11543-11562.
Chicago/Turabian StyleBehzad Zargar; Antonello Monti; Ferdinanda Ponci; Jose R. Marti. 2020. "Linear Iterative Power Flow Approach Based on the Current Injection Model of Load and Generator." IEEE Access 9, no. : 11543-11562.
The design of intelligent strategies for grid management is a cost-effective solution to increase the hosting capacity of distribution grids without investing in the reinforcement of the grid assets. This paper presents a distributed voltage control algorithm to coordinate Energy Storage Systems (ESSs) and Distributed Generation (DG) in a scenario of high renewable penetration. The proposed control algorithm relies on a dual decomposition approach and aims at mitigating possible voltage rise events occurring in the Low Voltage (LV) grid by solving an optimization problem of power minimization. Instead of using local control strategies, in the proposed solution, the voltage control burden is distributed among all the available resources in the grid, which cooperate to resolve the existing voltage violations. The performance of the developed voltage control has been tested under realistic distribution grid scenarios, using stochastic load profiles together with photovoltaic generation profiles obtained in the presence of both clear sky and cloudy sky conditions. The algorithm is also compared to a strategy that considers only DG management, highlighting the benefits associated to the proposed coordination of DG and Energy Storage Systems (ESSs).
Edoardo De Din; Marco Pau; Ferdinanda Ponci; Antonello Monti. A Coordinated Voltage Control for Overvoltage Mitigation in LV Distribution Grids. Energies 2020, 13, 2007 .
AMA StyleEdoardo De Din, Marco Pau, Ferdinanda Ponci, Antonello Monti. A Coordinated Voltage Control for Overvoltage Mitigation in LV Distribution Grids. Energies. 2020; 13 (8):2007.
Chicago/Turabian StyleEdoardo De Din; Marco Pau; Ferdinanda Ponci; Antonello Monti. 2020. "A Coordinated Voltage Control for Overvoltage Mitigation in LV Distribution Grids." Energies 13, no. 8: 2007.
Interoperability testing is widely recognized as a key to achieve seamless interoperability of smart grid applications, given the complex nature of modern power systems. In this work, the interoperability testing methodology proposed by the European Commission Joint Research Centre is applied to a specific use case in the context of smart grids. The selected use case examines a flexibility activation mechanism in a power grid system and includes DSO SCADA, Remote Terminal Unit and flexibility source, interacting to support a voltage regulation service. The adopted test bed consists of a real-time power grid simulator, a communication network emulator and use case actors’ models in a hardware-in-the-loop setup. The breakdown of the interoperability testing problem is accomplished by mapping the use case to the SGAM layers, specifying the Basic Application Profiles together with the Basic Application Interoperability Profiles (BAIOPs) and defining the design of experiments to carry out during the laboratory testing. Furthermore, the concepts of inter- and intra-BAIOP testing are formalized to reflect complementary interests of smart grid stakeholders. Experimental results prove the applicability of the methodology for testing the interoperability of large-scale and complex smart grid systems and reveal interesting features and possible pitfalls which should be considered when investigating the parameters responsible for the disruption of a system interoperability.
Mirko Ginocchi; Amir Ahmadifar; Ferdinanda Ponci; Antonello Monti. Application of a Smart Grid Interoperability Testing Methodology in a Real-Time Hardware-In-The-Loop Testing Environment. Energies 2020, 13, 1648 .
AMA StyleMirko Ginocchi, Amir Ahmadifar, Ferdinanda Ponci, Antonello Monti. Application of a Smart Grid Interoperability Testing Methodology in a Real-Time Hardware-In-The-Loop Testing Environment. Energies. 2020; 13 (7):1648.
Chicago/Turabian StyleMirko Ginocchi; Amir Ahmadifar; Ferdinanda Ponci; Antonello Monti. 2020. "Application of a Smart Grid Interoperability Testing Methodology in a Real-Time Hardware-In-The-Loop Testing Environment." Energies 13, no. 7: 1648.
This paper presents a new Kalman filter approach to Power System State Estimation based on PMUs, in which the knowledge of the system frequency is exploited to ensure the accuracy of the estimated quantities even under off-nominal conditions. In the proposed solution, the frequency is added as a new state variable to be estimated, so that its value can be known with lower uncertainty, thus leading to more accurate estimates also for node voltages and branch currents. All the frequency measurements available from PMUs can be exploited through the presented method to improve the estimation. In order to assess the benefits given by the integration of the frequency knowledge, the performance of the new approach is compared to different state estimation methodologies, by means of simulations carried out on the New England IEEE 39-bus system under different realistic operating conditions and measurement configurations. Performed tests take into account, in particular, the possible occurrence of off-nominal frequency conditions, highlighting the issues associated to traditional PMUbased Kalman filter approaches and proving the effectiveness of the proposed solution.
Carlo Muscas; Paolo Attilio Pegoraro; Sara Sulis; Marco Pau; Ferdinanda Ponci; Antonello Monti. New Kalman Filter Approach Exploiting Frequency Knowledge for Accurate PMU-Based Power System State Estimation. IEEE Transactions on Instrumentation and Measurement 2020, 69, 6713 -6722.
AMA StyleCarlo Muscas, Paolo Attilio Pegoraro, Sara Sulis, Marco Pau, Ferdinanda Ponci, Antonello Monti. New Kalman Filter Approach Exploiting Frequency Knowledge for Accurate PMU-Based Power System State Estimation. IEEE Transactions on Instrumentation and Measurement. 2020; 69 (9):6713-6722.
Chicago/Turabian StyleCarlo Muscas; Paolo Attilio Pegoraro; Sara Sulis; Marco Pau; Ferdinanda Ponci; Antonello Monti. 2020. "New Kalman Filter Approach Exploiting Frequency Knowledge for Accurate PMU-Based Power System State Estimation." IEEE Transactions on Instrumentation and Measurement 69, no. 9: 6713-6722.
Phasor Measurement Units (PMUs) are measurement devices long used in transmission systems and today even more essential for a proper monitoring of distribution grids. The expected massive penetration of distributed energy resources (DERs) is slowly taking place, carrying along a new set of challenges that put to test traditional instruments and requiring more performance and flexibility to adapt to this evolving scenario. Cheap devices based on single board computer (SBC) are proving to be a valid alternative to traditional PMU architectures, able to combine together high-performance, great versatility and low-cost. However, such devices lack a proper modeling of their measurement errors that conversely would be extremely useful for improving their design and evaluate their performance in accordance with the relevant standards. The paper intends to fill this gap by discussing the error sources and their effects on the observed signals. An analysis of error statistics is presented, in order to give a more complete metrological characterization.
Carlo Guarnieri Calo Carducci; Gianluca Lipari; Nicola Giaquinto; Ferdinanda Ponci; Antonello Monti. Error Model in Single-Board Computer-Based Phasor Measurement Units. IEEE Transactions on Instrumentation and Measurement 2020, 69, 6155 -6164.
AMA StyleCarlo Guarnieri Calo Carducci, Gianluca Lipari, Nicola Giaquinto, Ferdinanda Ponci, Antonello Monti. Error Model in Single-Board Computer-Based Phasor Measurement Units. IEEE Transactions on Instrumentation and Measurement. 2020; 69 (9):6155-6164.
Chicago/Turabian StyleCarlo Guarnieri Calo Carducci; Gianluca Lipari; Nicola Giaquinto; Ferdinanda Ponci; Antonello Monti. 2020. "Error Model in Single-Board Computer-Based Phasor Measurement Units." IEEE Transactions on Instrumentation and Measurement 69, no. 9: 6155-6164.
Distribution system state estimation (DSSE) is one of the key functions used by distribution system operators (DSOs) for management and control of the distribution grids. In general, distribution networks are featured by a very large number of nodes. Thus, performing the state estimation (SE) of the whole network is computationally very demanding. From the system observability point of view, the scarcity of the installed measurement units in the distribution systems is a big barrier to perform the DSSE. Moreover, the unbalanced nature of distribution systems makes estimators based on the positive-sequence model unfit. To tackle these issues, this paper presents a new data-driven three-phase state estimator based on artificial neural network (ANN) and sparse measurements from Phasor Measurement Units (PMUs), together with its observability assessment. Unlike the existing estimators performing week under the non-Gaussian noise, the proposed estimator provides accurate estimates. The proposed state estimation technique is executed tremendously fast (few milliseconds). This feature facilitates the real-time monitoring of the distribution grids since the estimators are coupled with the PMUs. In this context, PMUs play a crucial role as they can provide synchronized phasor measurements with high reporting rate (f PMU>1Hz). To address the problem size challenge with distributed computation, moreover, multiple ANN three-phase estimators are executed in parallel and integrated in a Multiarea state estimation architecture. Simulation results on the benchmark IEEE 123-bus test system support the feasibility of the solution.
Behzad Zargar; Andrea Angioni; Ferdinanda Ponci; Antonello Monti. Multiarea Parallel Data-Driven Three-Phase Distribution System State Estimation Using Synchrophasor Measurements. IEEE Transactions on Instrumentation and Measurement 2020, 69, 6186 -6202.
AMA StyleBehzad Zargar, Andrea Angioni, Ferdinanda Ponci, Antonello Monti. Multiarea Parallel Data-Driven Three-Phase Distribution System State Estimation Using Synchrophasor Measurements. IEEE Transactions on Instrumentation and Measurement. 2020; 69 (9):6186-6202.
Chicago/Turabian StyleBehzad Zargar; Andrea Angioni; Ferdinanda Ponci; Antonello Monti. 2020. "Multiarea Parallel Data-Driven Three-Phase Distribution System State Estimation Using Synchrophasor Measurements." IEEE Transactions on Instrumentation and Measurement 69, no. 9: 6186-6202.
This work deals with two paramount devices when Smart Grids are concerned: phasor measurement units (PMUs) and low-power instrument transformers (LPITs). In particular, a simple calibration procedure to test the measurement chain PMU + LPIT has been developed. The procedure involves steady-state conditions of the grid and off-nominal input signals for testing current, voltage, frequency, and rate of change of frequency (ROCOF). In addition, the procedure includes a preliminary testing of the PMU without the LPIT to understand the influence of the latter. The procedure is then applied to a specific case study: a low-cost PMU developed by the authors and one of the most common LPITs adopted in Italian medium voltage networks. The obtained results are promising for two reasons. First, the low-cost PMU works correctly even in off-nominal conditions of the grid; second, the presented calibration procedure demonstrated to be effective and applicable to very common equipment, using a rather simple test setup.
Alessandro Mingotti; Lorenzo Peretto; Roberto Tinarelli; Andrea Angioni; Antonello Monti; Ferdinanda Ponci. A Simple Calibration Procedure for an LPIT plus PMU System Under Off-Nominal Conditions. Energies 2019, 12, 4645 .
AMA StyleAlessandro Mingotti, Lorenzo Peretto, Roberto Tinarelli, Andrea Angioni, Antonello Monti, Ferdinanda Ponci. A Simple Calibration Procedure for an LPIT plus PMU System Under Off-Nominal Conditions. Energies. 2019; 12 (24):4645.
Chicago/Turabian StyleAlessandro Mingotti; Lorenzo Peretto; Roberto Tinarelli; Andrea Angioni; Antonello Monti; Ferdinanda Ponci. 2019. "A Simple Calibration Procedure for an LPIT plus PMU System Under Off-Nominal Conditions." Energies 12, no. 24: 4645.
This article investigates the problem of measurement selection for data-driven monitoring approaches. Several approaches to input variable selection (IVS) are analyzed, and a general procedure for finding the optimal order for the selection of candidate measurements is presented. The method is based on the extensions of partial correlation and minimal redundancy maximum relevance criteria to support IVS problems involving multiple outputs. This method can be used to find the minimal set of measurements for achieving a target estimation accuracy. The results demonstrate the advantages and limits of the introduced method in comparison to the other approaches discussed in this article.
Mohsen Ferdowsi; Andrea Benigni; Antonello Monti; Ferdinanda Ponci. Measurement Selection for Data-Driven Monitoring of Distribution Systems. IEEE Systems Journal 2019, 13, 4260 -4268.
AMA StyleMohsen Ferdowsi, Andrea Benigni, Antonello Monti, Ferdinanda Ponci. Measurement Selection for Data-Driven Monitoring of Distribution Systems. IEEE Systems Journal. 2019; 13 (4):4260-4268.
Chicago/Turabian StyleMohsen Ferdowsi; Andrea Benigni; Antonello Monti; Ferdinanda Ponci. 2019. "Measurement Selection for Data-Driven Monitoring of Distribution Systems." IEEE Systems Journal 13, no. 4: 4260-4268.
The share of power converter based renewable generation is steadily increasing at the expense of rotating inertia. Virtual Synchronous Machines are deemed to ensure system stability, however, there are no widely accepted criteria for the design of their controllers. In converter-dominated power systems, one of the main challenges will be to analyze power angle stability, because of the large number (and possibly divergent design) of converters. Converters, however, also offer the possibility to shape system dynamics in a way that was impossible with synchronous machines. In this paper we elaborate the new concept of Linearized and Uniform Swing Dynamics. This allows the linearization of the nonlinear swing behavior over almost the entire power range, thereby extending the validity of the small-signal stability analysis techniques for larger disturbances. By properly choosing the controller parameters, the dynamics of the large number of converters expected in the system can be made unified and predictable.
David Raisz; Aysar Musa; Ferdinanda Ponci; Antonello Monti. Linear and Uniform Swing Dynamics. IEEE Transactions on Sustainable Energy 2019, 10, 1513 -1522.
AMA StyleDavid Raisz, Aysar Musa, Ferdinanda Ponci, Antonello Monti. Linear and Uniform Swing Dynamics. IEEE Transactions on Sustainable Energy. 2019; 10 (3):1513-1522.
Chicago/Turabian StyleDavid Raisz; Aysar Musa; Ferdinanda Ponci; Antonello Monti. 2019. "Linear and Uniform Swing Dynamics." IEEE Transactions on Sustainable Energy 10, no. 3: 1513-1522.
Lisette Cupelli; Marco Cupelli; Ferdinanda Ponci; Antonello Monti. Data-Driven Adaptive Control for Distributed Energy Resources. IEEE Transactions on Sustainable Energy 2019, 10, 1575 -1584.
AMA StyleLisette Cupelli, Marco Cupelli, Ferdinanda Ponci, Antonello Monti. Data-Driven Adaptive Control for Distributed Energy Resources. IEEE Transactions on Sustainable Energy. 2019; 10 (3):1575-1584.
Chicago/Turabian StyleLisette Cupelli; Marco Cupelli; Ferdinanda Ponci; Antonello Monti. 2019. "Data-Driven Adaptive Control for Distributed Energy Resources." IEEE Transactions on Sustainable Energy 10, no. 3: 1575-1584.
While the initial aim of smart meters is to provide energy readings for billing purposes, the availability of these measurements could open new opportunities for the management of future distribution grids. This paper presents a multilevel state estimator that exploits the smart meter measurements for monitoring both low and medium voltage grids. The goal of this paper is to present an architecture that is able to efficiently integrate smart meter measurements and to show the accuracy performance achievable if the use of real-time smart meter measurements for state estimation purposes was enabled. The design of the state estimator applies the uncertainty propagation theory for the integration of the data at different hierarchical levels. The coordination of the estimation levels is realized through a cloud-based infrastructure, which also provides the interface to auxiliary functions and the access to the estimation results for other distribution grid management applications. A mathematical analysis is performed to characterize the estimation algorithm in terms of accuracy and to show the performance achievable at different levels of the distribution grid when using the smart meter data. Simulations are presented, which validate the analytical results and demonstrate the operation of the multilevel estimator in coordination with the cloud-based platform.
Marco Pau; Edoardo Patti; Luca Barbierato; Abouzar Estebsari; Enrico Pons; Ferdinanda Ponci; Antonello Monti. Design and Accuracy Analysis of Multilevel State Estimation Based on Smart Metering Infrastructure. IEEE Transactions on Instrumentation and Measurement 2019, 68, 4300 -4312.
AMA StyleMarco Pau, Edoardo Patti, Luca Barbierato, Abouzar Estebsari, Enrico Pons, Ferdinanda Ponci, Antonello Monti. Design and Accuracy Analysis of Multilevel State Estimation Based on Smart Metering Infrastructure. IEEE Transactions on Instrumentation and Measurement. 2019; 68 (11):4300-4312.
Chicago/Turabian StyleMarco Pau; Edoardo Patti; Luca Barbierato; Abouzar Estebsari; Enrico Pons; Ferdinanda Ponci; Antonello Monti. 2019. "Design and Accuracy Analysis of Multilevel State Estimation Based on Smart Metering Infrastructure." IEEE Transactions on Instrumentation and Measurement 68, no. 11: 4300-4312.
Despite the positive contributions of controllable electric loads such as electric vehicles (EV) and heat pumps (HP) in providing demand-side flexibility, uncoordinated operation of these loads may lead to congestions at distribution networks. This paper aims to propose a market-based mechanism to alleviate distribution network congestions through a centralized coordinated home energy management system (HEMS). In this model, the distribution system operator (DSO) implements dynamic tariffs (DT) and daily power-based network tariffs (DPT) to manage congestions induced by EVs and HPs. In this framework, the HP and EV loads are directly controlled by the retail electricity provider (REP). As DT and DPT price signals target the aggregated nodal demand, the individual uncoordinated HEMS models operating under these price signals are unable to effectively alleviate congestion. A large number of flexible residential customers with EV and HP loads are modeled in this paper, and the REP schedules the consumption based on the comfort preferences of the customers through HEMS. The effectiveness of the market-based concept in managing the congestion is demonstrated by using the IEEE 33-bus distribution system with 706 residential customers. The case study results show that considering both pricing systems can considerably mitigate the overloading occurrences in distribution lines, while applying DTs without considering DPTs may lead to severe overloading occurrences at some periods.
Mohammad Ali Fotouhi Ghazvini; Gianluca Lipari; Marco Pau; Ferdinanda Ponci; Antonello Monti; João Soares; Rui Castro; Zita Vale. Congestion management in active distribution networks through demand response implementation. Sustainable Energy, Grids and Networks 2019, 17, 100185 .
AMA StyleMohammad Ali Fotouhi Ghazvini, Gianluca Lipari, Marco Pau, Ferdinanda Ponci, Antonello Monti, João Soares, Rui Castro, Zita Vale. Congestion management in active distribution networks through demand response implementation. Sustainable Energy, Grids and Networks. 2019; 17 ():100185.
Chicago/Turabian StyleMohammad Ali Fotouhi Ghazvini; Gianluca Lipari; Marco Pau; Ferdinanda Ponci; Antonello Monti; João Soares; Rui Castro; Zita Vale. 2019. "Congestion management in active distribution networks through demand response implementation." Sustainable Energy, Grids and Networks 17, no. : 100185.
Marco Pau; Paolo Attilio Pegoraro; Antonello Monti; Carlo Muscas; Ferdinanda Ponci; Sara Sulis. Impact of Current and Power Measurements on Distribution System State Estimation Uncertainty. IEEE Transactions on Instrumentation and Measurement 2018, 68, 3992 -4002.
AMA StyleMarco Pau, Paolo Attilio Pegoraro, Antonello Monti, Carlo Muscas, Ferdinanda Ponci, Sara Sulis. Impact of Current and Power Measurements on Distribution System State Estimation Uncertainty. IEEE Transactions on Instrumentation and Measurement. 2018; 68 (10):3992-4002.
Chicago/Turabian StyleMarco Pau; Paolo Attilio Pegoraro; Antonello Monti; Carlo Muscas; Ferdinanda Ponci; Sara Sulis. 2018. "Impact of Current and Power Measurements on Distribution System State Estimation Uncertainty." IEEE Transactions on Instrumentation and Measurement 68, no. 10: 3992-4002.
Lukas Razik; Nicolas Berr; Sara Khayyam; Ferdinanda Ponci; Antonello Monti; Sara Khayyamim. REM-S–Railway Energy Management in Real Rail Operation. IEEE Transactions on Vehicular Technology 2018, 68, 1266 -1277.
AMA StyleLukas Razik, Nicolas Berr, Sara Khayyam, Ferdinanda Ponci, Antonello Monti, Sara Khayyamim. REM-S–Railway Energy Management in Real Rail Operation. IEEE Transactions on Vehicular Technology. 2018; 68 (2):1266-1277.
Chicago/Turabian StyleLukas Razik; Nicolas Berr; Sara Khayyam; Ferdinanda Ponci; Antonello Monti; Sara Khayyamim. 2018. "REM-S–Railway Energy Management in Real Rail Operation." IEEE Transactions on Vehicular Technology 68, no. 2: 1266-1277.