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Widespread outbreaks of infectious disease, i.e., the so-called pandemics that may travel quickly and silently beyond boundaries, can significantly upsurge the morbidity and mortality over large-scale geographical areas. They commonly result in enormous economic losses, political disruptions, social unrest, and quickly evolve to a national security concern. Societies have been shaped by pandemics and outbreaks for as long as we have had societies. While differing in nature and in realizations, they all place the normal life of modern societies on hold. Common interruptions include job loss, infrastructure failure, and political ramifications. The electric power systems, upon which our modern society relies, is driving a myriad of interdependent services, such as water systems, communication networks, transportation systems, health services, etc. With the sudden shifts in electric power generation and demand portfolios and the need to sustain quality electricity supply to end customers (particularly mission-critical services) during pandemics, safeguarding the nation’s electric power grid in the face of such rapidly evolving outbreaks is among the top priorities. This paper explores the various mechanisms through which the electric power grids around the globe are influenced by pandemics in general and COVID-19 in particular, shares the lessons learned and best practices taken in different sectors of the electric industry in responding to the dramatic shifts enforced by such threats, and provides visions for a pandemic-resilient electric grid of the future.
Benjamin Wormuth; Shiyuan Wang; Payman Dehghanian; Masoud Barati; Abouzar Estebsari; Tiago Pascoal Filomena; Mohammad Heidari Kapourchali; Miguel A. Lejeune. Electric Power Grids Under High-Absenteeism Pandemics: History, Context, Response, and Opportunities. IEEE Access 2020, 8, 215727 -215747.
AMA StyleBenjamin Wormuth, Shiyuan Wang, Payman Dehghanian, Masoud Barati, Abouzar Estebsari, Tiago Pascoal Filomena, Mohammad Heidari Kapourchali, Miguel A. Lejeune. Electric Power Grids Under High-Absenteeism Pandemics: History, Context, Response, and Opportunities. IEEE Access. 2020; 8 (99):215727-215747.
Chicago/Turabian StyleBenjamin Wormuth; Shiyuan Wang; Payman Dehghanian; Masoud Barati; Abouzar Estebsari; Tiago Pascoal Filomena; Mohammad Heidari Kapourchali; Miguel A. Lejeune. 2020. "Electric Power Grids Under High-Absenteeism Pandemics: History, Context, Response, and Opportunities." IEEE Access 8, no. 99: 215727-215747.
The demand for renewable energy generation, especially photovoltaic (PV) power generation, has been growing over the past few years. However, the amount of generated energy by PV systems is highly dependent on weather conditions. Therefore, accurate forecasting of generated PV power is of importance for large-scale deployment of PV systems. Recently, machine learning (ML) methods have been widely used for PV power generation forecasting. A variety of these techniques, including artificial neural networks (ANNs), ridge regression, K-nearest neighbour (kNN) regression, decision trees, support vector regressions (SVRs) have been applied for this purpose and achieved good performance. In this paper, we briefly review the most recent ML techniques for PV energy generation forecasting and propose a new regression technique to automatically predict a PV system’s output based on historical input parameters. More specifically, the proposed loss function is a combination of three well-known loss functions: Correntropy, Absolute and Square Loss which encourages robustness and generalization jointly. We then integrate the proposed objective function into a Deep Learning model to predict a PV system’s output. By doing so, both the coefficients of loss functions and weight parameters of the ANN are learned jointly via back propagation. We investigate the effectiveness of the proposed method through comprehensive experiments on real data recorded by a real PV system. The experimental results confirm that our method outperforms the state-of-the-art ML methods for PV energy generation forecasting.
Moein Hajiabadi; Mahdi Farhadi; Vahide Babaiyan; Abouzar Estebsari. Deep Learning with Loss Ensembles for Solar Power Prediction in Smart Cities. Smart Cities 2020, 3, 842 -852.
AMA StyleMoein Hajiabadi, Mahdi Farhadi, Vahide Babaiyan, Abouzar Estebsari. Deep Learning with Loss Ensembles for Solar Power Prediction in Smart Cities. Smart Cities. 2020; 3 (3):842-852.
Chicago/Turabian StyleMoein Hajiabadi; Mahdi Farhadi; Vahide Babaiyan; Abouzar Estebsari. 2020. "Deep Learning with Loss Ensembles for Solar Power Prediction in Smart Cities." Smart Cities 3, no. 3: 842-852.
Future smart grids with more distributed generation and flexible demand require well-verified control and management services. This paper presents a distributed multi- model co-simulation platform based on Smart Grid Architecture Model (a.k.a. SGAM) to foster general purpose services in smart grids. It aims at providing developers with support to easily set-up a test-bed environment where they can simulate realistic scenarios to assess their algorithms and services. The proposed platform takes advantages of Internet-of-Things communication paradigms and protocols to enable the interoperability among different models and virtual or physical devices that compose a use case. Moreover, the integration of digital real-time simulators unlocks Hardware-In-the-Loop features. To test the functionality of our platform, a novel scheme of fault detection, isolation and restoration is developed, in which communication and interoperability of different functions and devices are crucial. This service is applied on a realistic portion of a power grid in Turin, Italy, where devices communicate over the Internet. Finally, the laboratory experimental results achieved during a real-time co-simulation are discussed.
Luca Barbierato; Abouzar Estebsari; Lorenzo Bottaccioli; Enrico Macii; Edoardo Patti. A Distributed Multimodel Cosimulation Platform to Assess General Purpose Services in Smart Grids. IEEE Transactions on Industry Applications 2020, 56, 5613 -5624.
AMA StyleLuca Barbierato, Abouzar Estebsari, Lorenzo Bottaccioli, Enrico Macii, Edoardo Patti. A Distributed Multimodel Cosimulation Platform to Assess General Purpose Services in Smart Grids. IEEE Transactions on Industry Applications. 2020; 56 (5):5613-5624.
Chicago/Turabian StyleLuca Barbierato; Abouzar Estebsari; Lorenzo Bottaccioli; Enrico Macii; Edoardo Patti. 2020. "A Distributed Multimodel Cosimulation Platform to Assess General Purpose Services in Smart Grids." IEEE Transactions on Industry Applications 56, no. 5: 5613-5624.
One of the essential aspects of power system planning is generation expansion planning (GEP). The purpose of GEP is to enhance construction planning and reduce the costs of installing different types of power plants. This paper proposes a method based on a genetic algorithm (GA) for GEP in the presence of wind power plants. Since it is desirable to integrate the maximum possible wind power production in GEP, the constraints for incorporating different levels of wind energy in power generation are investigated comprehensively. This will allow the maximum reasonable amount of wind penetration in the network to be obtained. Besides, due to the existence of different wind regimes, the penetration of strong and weak wind on GEP is assessed. The results show that the maximum utilization of wind power generation capacity could increase the exploitation of more robust wind regimes. Considering the growth of the wind farm industry and the cost reduction for building wind power plants, the sensitivity of GEP to the variations of this cost is investigated. The results further indicate that for a 10% reduction in the initial investment cost of wind power plants, the proposed model estimates that the overall cost will be minimized.
Ali Sahragard; Hamid Falaghi; Mahdi Farhadi; Amir Mosavi; Abouzar Estebsari. Generation Expansion Planning in the Presence of Wind Power Plants Using a Genetic Algorithm Model. Electronics 2020, 9, 1143 .
AMA StyleAli Sahragard, Hamid Falaghi, Mahdi Farhadi, Amir Mosavi, Abouzar Estebsari. Generation Expansion Planning in the Presence of Wind Power Plants Using a Genetic Algorithm Model. Electronics. 2020; 9 (7):1143.
Chicago/Turabian StyleAli Sahragard; Hamid Falaghi; Mahdi Farhadi; Amir Mosavi; Abouzar Estebsari. 2020. "Generation Expansion Planning in the Presence of Wind Power Plants Using a Genetic Algorithm Model." Electronics 9, no. 7: 1143.
As of March 13, 2020, the director general of the World Health Organization (WHO) considered Europe as the centre of the global COVID-19 outbreak. All countries within Europe had a confirmed case of COVID-19 by March 17. In response to the pandemic, different European countries took different approaches. This paper compares the impact of different containment measures taken by European countries in response to COVID-19 on their electricity consumption profiles. The comparisons are made for Spain, Italy, Belgium and the UK as countries with severe restrictions, and for the Netherlands and Sweden as countries with less restrictive measures. The results show that the consumption profiles reflect the difference in peoples’ activities in different countries using various measures.
Alireza Bahmanyar; Abouzar Estebsari; Damien Ernst. The impact of different COVID-19 containment measures on electricity consumption in Europe. Energy Research & Social Science 2020, 68, 101683 -101683.
AMA StyleAlireza Bahmanyar, Abouzar Estebsari, Damien Ernst. The impact of different COVID-19 containment measures on electricity consumption in Europe. Energy Research & Social Science. 2020; 68 ():101683-101683.
Chicago/Turabian StyleAlireza Bahmanyar; Abouzar Estebsari; Damien Ernst. 2020. "The impact of different COVID-19 containment measures on electricity consumption in Europe." Energy Research & Social Science 68, no. : 101683-101683.
The smart electricity grids have been evolving to a more complex cyber-physical ecosystem of infrastructures with integrated communication networks, new carbon-free sources of power generation, advanced monitoring and control systems, and a myriad of emerging modern physical hardware technologies. With the unprecedented complexity and heterogeneity in dynamic smart grid networks comes additional vulnerability to emerging threats such as cyber attacks. Rapid development and deployment of advanced network monitoring and communication systems on one hand, and the growing interdependence of the electric power grids to a multitude of lifeline critical infrastructures on the other, calls for holistic defense strategies to safeguard the power grids against cyber adversaries. In order to improve the resilience of the power grid against adversarial attacks and cyber intrusions, advancements should be sought on detection techniques, protection plans, and mitigation practices in all electricity generation, transmission, and distribution sectors. This survey discusses such major directions and recent advancements from a lens of different detection techniques, equipment protection plans, and mitigation strategies to enhance the energy delivery infrastructure resilience and operational endurance against cyber attacks. This undertaking is essential since even modest improvements in resilience of the power grid against cyber threats could lead to sizeable monetary savings and an enriched overall social welfare.
Tien Nguyen; Shiyuan Wang; Mohannad Alhazmi; Mostafa Nazemi; Abouzar Estebsari; Payman Dehghanian. Electric Power Grid Resilience to Cyber Adversaries: State of the Art. IEEE Access 2020, 8, 87592 -87608.
AMA StyleTien Nguyen, Shiyuan Wang, Mohannad Alhazmi, Mostafa Nazemi, Abouzar Estebsari, Payman Dehghanian. Electric Power Grid Resilience to Cyber Adversaries: State of the Art. IEEE Access. 2020; 8 (99):87592-87608.
Chicago/Turabian StyleTien Nguyen; Shiyuan Wang; Mohannad Alhazmi; Mostafa Nazemi; Abouzar Estebsari; Payman Dehghanian. 2020. "Electric Power Grid Resilience to Cyber Adversaries: State of the Art." IEEE Access 8, no. 99: 87592-87608.
The integration of more renewable energy resources into distribution networks makes the operation of these systems more challenging compared to the traditional passive networks. This is mainly due to the intermittent behavior of most renewable resources such as solar and wind generation. There are many different solutions being developed to make systems flexible such as energy storage or demand response. In the context of demand response, a key factor is to estimate the amount of load over time properly to better manage the demand side. There are many different forecasting methods, but the most accurate solutions are mainly found for the prediction of aggregated loads at the substation or building levels. However, more effective demand response from the residential side requires prediction of energy consumption at every single household level. The accuracy of forecasting loads at this level is often lower with the existing methods as the volatility of single residential loads is very high. In this paper, we present a hybrid method based on time series image encoding techniques and a convolutional neural network. The results of the forecasting of a real residential customer using different encoding techniques are compared with some other existing forecasting methods including SVM, ANN, and CNN. Without CNN, the lowest mean absolute percentage of error (MAPE) for a 15 min forecast is above 20%, while with existing CNN, directly applied to time series, an MAPE of around 18% could be achieved. We find the best image encoding technique for time series, which could result in higher accuracy of forecasting using CNN, an MAPE of around 12%.
Abouzar Estebsari; Roozbeh Rajabi. Single Residential Load Forecasting Using Deep Learning and Image Encoding Techniques. Electronics 2020, 9, 68 .
AMA StyleAbouzar Estebsari, Roozbeh Rajabi. Single Residential Load Forecasting Using Deep Learning and Image Encoding Techniques. Electronics. 2020; 9 (1):68.
Chicago/Turabian StyleAbouzar Estebsari; Roozbeh Rajabi. 2020. "Single Residential Load Forecasting Using Deep Learning and Image Encoding Techniques." Electronics 9, no. 1: 68.
For planning and development and in real-time operation of smart grids, it is important to evaluate the impacts of photovoltaic (PV) distributed generation. In this paper, we present an integrated platform, constituted by two main components: a PV simulator and a real-time distribution network simulator. The first, designed and developed following the microservice approach and providing REST web services, simulates real-sky solar radiation on rooftops and estimates the PV energy production; the second, based on a digital real-time power systems simulator, simulates the behaviour of the electric network under the simulated generation scenarios. The platform is tested on a case study based on real data for a district of the city of Turin, Italy. In the results, we show possible applications of the platform for power flow forecasting during real-time operation and to detect possible voltage and transformers capacity problems during planning due to high penetration of Renewable Energy Sources. In particular, the results show that the case study distribution network, in the actual configuration, is not ready to accommodate all the generation capacity that can be installed as, in certain hours of the day and in certain days of the year, the capacity of some transformers is exceeded.
Lorenzo Bottaccioli; Abouzar Estebsari; Edoardo Patti; Enrico Pons; Andrea Acquaviva. Planning and real-time management of smart grids with high PV penetration in Italy. Proceedings of the Institution of Civil Engineers - Engineering Sustainability 2019, 172, 272 -282.
AMA StyleLorenzo Bottaccioli, Abouzar Estebsari, Edoardo Patti, Enrico Pons, Andrea Acquaviva. Planning and real-time management of smart grids with high PV penetration in Italy. Proceedings of the Institution of Civil Engineers - Engineering Sustainability. 2019; 172 (6):272-282.
Chicago/Turabian StyleLorenzo Bottaccioli; Abouzar Estebsari; Edoardo Patti; Enrico Pons; Andrea Acquaviva. 2019. "Planning and real-time management of smart grids with high PV penetration in Italy." Proceedings of the Institution of Civil Engineers - Engineering Sustainability 172, no. 6: 272-282.
The increase in electricity demands has increased the dimension and loading of today radial distribution feeders, which in turn would result in more losses and voltage drops. Such issues together with the demand for higher power quality has raised a need for modern power system management techniques such as using power electronic devices. Among, DSTATCOM is introduced as an effective solution for reactive power control in power distribution level. To make a better use of DSTATCOM in improving the network power quality, it should be sized and placed in accordance with parallel capacitors. A multi-objective optimization method is proposed in this paper to find the optimal location and size of DSTATCOM and parallel capacitors simultaneously. The cost of power losses, voltage profile and voltage stability are selected as objectives to be improved. The obtained results on the IEEE 33-node test system indicate that the proposed method satisfies the defined objectives and considerably improves the network operational characteristics.
Arash Zeinalzadeh; Abouzar Estebsari; Alireza Bahmanyar. Simultaneous Optimal Placement and Sizing of DSTATCOM and Parallel Capacitors in Distribution Networks Using Multi-Objective PSO. 2019 IEEE Milan PowerTech 2019, 1 -6.
AMA StyleArash Zeinalzadeh, Abouzar Estebsari, Alireza Bahmanyar. Simultaneous Optimal Placement and Sizing of DSTATCOM and Parallel Capacitors in Distribution Networks Using Multi-Objective PSO. 2019 IEEE Milan PowerTech. 2019; ():1-6.
Chicago/Turabian StyleArash Zeinalzadeh; Abouzar Estebsari; Alireza Bahmanyar. 2019. "Simultaneous Optimal Placement and Sizing of DSTATCOM and Parallel Capacitors in Distribution Networks Using Multi-Objective PSO." 2019 IEEE Milan PowerTech , no. : 1-6.
Integration of renewable energy resources in distribution networks with intermittent behaviour increases the challenge of power balance in transmission systems. To mitigate the undesired impacts, transmission operator involves distribution operators to get local contribution from their flexible resources. In this paper, we address the flexibility offered by some electric car sharing agents which can serve some reserve capacity to distribution system. A Markov Chain modelling based approach is proposed to support system operator to properly estimate the number of electric vehicles required to be booked in advance as reserve. Underestimation would result in imperfect demand correction, and overestimation would imply extra costs. Using a realistic case under a near future scenario of high PV integration and EV accommodation, we demonstrate the contribution of our approach to this problem of planning or scheduling. Obtained results quantifies the performance of the proposed method in terms of average energy difference based on number of EVs. The results can be used as a basis to decide the appropriate number of EV reservations.
Marjan Yazdani; Abouzar Estebsari; Motahhareh Estebsari; Roozbeh Rajabi. Markov Chain Modelling-Based Approach to Reserve Electric Vehicles in Parking Lots for Distribution System Energy Management. 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) 2019, 1 -5.
AMA StyleMarjan Yazdani, Abouzar Estebsari, Motahhareh Estebsari, Roozbeh Rajabi. Markov Chain Modelling-Based Approach to Reserve Electric Vehicles in Parking Lots for Distribution System Energy Management. 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). 2019; ():1-5.
Chicago/Turabian StyleMarjan Yazdani; Abouzar Estebsari; Motahhareh Estebsari; Roozbeh Rajabi. 2019. "Markov Chain Modelling-Based Approach to Reserve Electric Vehicles in Parking Lots for Distribution System Energy Management." 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) , no. : 1-5.
Growing perception of diverse generation resources and demand response operation of power system with high uncertainty has increased the attention to a more dynamic and accurate day-ahead load prediction. In this paper, we develop an stochastic model for short term load forecasting based on the Gaussian process, in which the non parametric estimator of the regression functions are obtained by using Bernstein polynomials. One of the major features of this model is its ability to predict a continuous load at any time of the day with a regression function. We use the historical data for training and the constrained marginal likelihood problem is optimized for finding the hyperparameters of the model. Real data sets from California ISO were used for training and testing the model. The results are compared to the day ahead piecewise constant load and the real time load. The common error measures are employed to infer the deviation of the load forecast from the real data.
Roya Nikjoo; Abouzar Estebsari; Mohammad Nazari. Non-parametric Regression Model for Continuous-time Day Ahead Load Forecasting with Bernstein Polynomial. 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) 2019, 1 -5.
AMA StyleRoya Nikjoo, Abouzar Estebsari, Mohammad Nazari. Non-parametric Regression Model for Continuous-time Day Ahead Load Forecasting with Bernstein Polynomial. 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). 2019; ():1-5.
Chicago/Turabian StyleRoya Nikjoo; Abouzar Estebsari; Mohammad Nazari. 2019. "Non-parametric Regression Model for Continuous-time Day Ahead Load Forecasting with Bernstein Polynomial." 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) , no. : 1-5.
Phasor Measurement Units are widely utilized in power systems to provide synchrophasor data for a verity of applications, mainly performed by Energy Management Systems (EMS). Synchrophasors are measured at different parts of the network and transmitted to Phasor Data Concentrator (PDC) at a rate of 30-60 samples per second. The synchronization is done by means of a phase locked oscillator inside PMU which uses clock signal of the Global Positioning System (GPS). In this paper a novel charge pump with an appropriate operation capability in phaselocked-loops is presented. By using this phase locked loop in phasor measurement unit, the total performance of this circuit will be improved. The proposed charge pump uses current mirror techniques in order to achieve a wide range of output voltage to control the oscillator and also has a good performance in a wide frequency range from 33MHz to 555MHz. This circuit is designed and simulated in TSMC 0.18μm CMOS technology. The proposed charge pump only consumes 390μW power in supply voltage of 1.8V at 500MHz and has a maximum current of 16.43μA with an acceptable current matching between source and sink currents. It is also capable to be used in a wide frequency range and low power applications.
Motahhareh Estebsari; Abouzar Estebsari. A Wide Range and High Swing Charge Pump for Phase Locked Loop in Phasor Measurement Unit. 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) 2019, 1 -5.
AMA StyleMotahhareh Estebsari, Abouzar Estebsari. A Wide Range and High Swing Charge Pump for Phase Locked Loop in Phasor Measurement Unit. 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). 2019; ():1-5.
Chicago/Turabian StyleMotahhareh Estebsari; Abouzar Estebsari. 2019. "A Wide Range and High Swing Charge Pump for Phase Locked Loop in Phasor Measurement Unit." 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) , no. : 1-5.
The installation of facilities replicating the realworld condition is often required for carrying out meaningful tests on new devices and for collecting data with the aim to create realistic device model. However, these facilities require huge investments, as well as areas where they can be properly installed. In this paper, we present a test infrastructure exploiting the concept of Remote Power Hardware-In-the-Loop (RPHIL), applied for characterizing the performances of a 8kW Proton Exchange Membrane (PEM) electrolyser installed at the Hanze University of Applied Sciences in Groningen (The Netherlands). The electrolyser is subjected to different test conditions imposed both locally and remotely. The results show that this measurement procedure is effective and can open new perspectives in the way to share and exploit the existing research infrastructure in Europe.
Andrea Mazza; Abouzar Estebsari; Giulia Morandi; Ettore Bompard; Harm Lok. Remote Hardware-In-the-Loop Measurement System for Electrolyser Characterization. 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) 2019, 1 -6.
AMA StyleAndrea Mazza, Abouzar Estebsari, Giulia Morandi, Ettore Bompard, Harm Lok. Remote Hardware-In-the-Loop Measurement System for Electrolyser Characterization. 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). 2019; ():1-6.
Chicago/Turabian StyleAndrea Mazza; Abouzar Estebsari; Giulia Morandi; Ettore Bompard; Harm Lok. 2019. "Remote Hardware-In-the-Loop Measurement System for Electrolyser Characterization." 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) , no. : 1-6.
Arash Zeinalzadeh; Abouzar Estebsari; Alireza Bahmanyar. Multi-Objective Optimal Placement of Recloser and Sectionalizer in Electricity Distribution Feeders. 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) 2019, 1 .
AMA StyleArash Zeinalzadeh, Abouzar Estebsari, Alireza Bahmanyar. Multi-Objective Optimal Placement of Recloser and Sectionalizer in Electricity Distribution Feeders. 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). 2019; ():1.
Chicago/Turabian StyleArash Zeinalzadeh; Abouzar Estebsari; Alireza Bahmanyar. 2019. "Multi-Objective Optimal Placement of Recloser and Sectionalizer in Electricity Distribution Feeders." 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) , no. : 1.
Growing deployment of more efficient communication systems serving electric power grids highlights the importance of designing more advanced intelligent electronic devices and communication-enabled measurement units. In this context, phasor measurement units (PMUs) are being widely deployed in power systems. A common block in almost all PMUs is a phase locked oscillator which uses a voltage controlled oscillator (VCO). In this paper, a triple frequency based voltage controlled oscillator is presented with low phase noise and robust start-up. The VCO consists of a detector, a comparator, and triple frequency. A VCO starts-up in class AB, then steadies oscillation in class C with low current oscillation. The frequency of the VCO, which is from 13.17 GHz to 16.03 GHz, shows that the frequency is tripling to 41.14–48.11 GHz. Therefore, its application is not limited to PMUs. This work has been simulated in a standard 0.18 µm CMOS process. The simulated VCO achieves a phase noise of −99.47 dBc/Hz at 1 MHz offset and −121.8 dBc/Hz at 10 MHz offset from the 48.11 GHz carrier.
Abbas Nasri; Siroos Toofan; Motahhareh Estebsari; Abouzar Estebsari. Design of a 41.14–48.11 GHz Triple Frequency Based VCO. Electronics 2019, 8, 529 .
AMA StyleAbbas Nasri, Siroos Toofan, Motahhareh Estebsari, Abouzar Estebsari. Design of a 41.14–48.11 GHz Triple Frequency Based VCO. Electronics. 2019; 8 (5):529.
Chicago/Turabian StyleAbbas Nasri; Siroos Toofan; Motahhareh Estebsari; Abouzar Estebsari. 2019. "Design of a 41.14–48.11 GHz Triple Frequency Based VCO." Electronics 8, no. 5: 529.
In order to systematically shift existing control and management paradigms in distribution systems to new interoperable communication supported schemes in smart grids, we need to map newly developed use cases to standard reference models like Smart Grid Architecture Model (SGAM). From the other side, any new use cases should be tested and validated ex-ante before being deployed in the real-world system. Considering various types of actors in smart grids, use cases are usually tested using co-simulation platforms. Currently, there is no efficient co-simulation platform which supports interoperability analysis based on SGAM. In this paper, we present our developed test platform which offers a support to design new use cases based on SGAM. We used this platform to develop a new scheme for wide area monitoring of existing distribution systems under growing penetration of Photovoltaic production. Off-the-shelf solutions of state estimation for wide area monitoring are either used for passive distribution grids or applied to the active networks with wide measurement of distributed generators. Our proposed distribution state estimation algorithm does not require wide area measurements and relies on the data provided by a PV simulator we developed. This practical scheme is tested experimentally on a realistic urban distribution grid. The monitoring results shows a very low error rate of about 1 % by using our PV simulator under high penetration of PV with about 30 % error of load forecast. Using our SGAM-based platform, we could propose and examine an Internet-of-Things-based infrastructure to deploy the use case.
Abouzar Estebsari; Luca Barbierato; Alireza Bahmanyar; Lorenzo Bottaccioli; Enrico Macii; Edoardo Patti. A SGAM-Based Test Platform to Develop a Scheme for Wide Area Measurement-Free Monitoring of Smart Grids under High PV Penetration. Energies 2019, 12, 1417 .
AMA StyleAbouzar Estebsari, Luca Barbierato, Alireza Bahmanyar, Lorenzo Bottaccioli, Enrico Macii, Edoardo Patti. A SGAM-Based Test Platform to Develop a Scheme for Wide Area Measurement-Free Monitoring of Smart Grids under High PV Penetration. Energies. 2019; 12 (8):1417.
Chicago/Turabian StyleAbouzar Estebsari; Luca Barbierato; Alireza Bahmanyar; Lorenzo Bottaccioli; Enrico Macii; Edoardo Patti. 2019. "A SGAM-Based Test Platform to Develop a Scheme for Wide Area Measurement-Free Monitoring of Smart Grids under High PV Penetration." Energies 12, no. 8: 1417.
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.
The Global Real-Time Superlaboratory (Global RT Superlab) represents a vendor-neutral distributed platform based on the virtual interconnection of digital real-time simulators (DRTSs) and hardware-in-the-loop (HIL) setups hosted at eight geographically distributed laboratories in the United States and Europe (Figure 1). This article describes the efforts toward the realization of this largescale virtual infrastructure and explains a demonstration of the multilab setup for simulation and testing of next-generation global power grids.
Antonello Monti; Marija Stevic; Steffen Vogel; Rik W. De Doncker; Ettore Bompard; Abouzar Estebsari; Francesco Profumo; Rob Hovsapian; Manish Mohanpurkar; Jack David Flicker; Vahan Gevorgian; Siddharth Suryanarayanan; Anurag K. Srivastava; Andrea Benigni. A Global Real-Time Superlab: Enabling High Penetration of Power Electronics in the Electric Grid. IEEE Power Electronics Magazine 2018, 5, 35 -44.
AMA StyleAntonello Monti, Marija Stevic, Steffen Vogel, Rik W. De Doncker, Ettore Bompard, Abouzar Estebsari, Francesco Profumo, Rob Hovsapian, Manish Mohanpurkar, Jack David Flicker, Vahan Gevorgian, Siddharth Suryanarayanan, Anurag K. Srivastava, Andrea Benigni. A Global Real-Time Superlab: Enabling High Penetration of Power Electronics in the Electric Grid. IEEE Power Electronics Magazine. 2018; 5 (3):35-44.
Chicago/Turabian StyleAntonello Monti; Marija Stevic; Steffen Vogel; Rik W. De Doncker; Ettore Bompard; Abouzar Estebsari; Francesco Profumo; Rob Hovsapian; Manish Mohanpurkar; Jack David Flicker; Vahan Gevorgian; Siddharth Suryanarayanan; Anurag K. Srivastava; Andrea Benigni. 2018. "A Global Real-Time Superlab: Enabling High Penetration of Power Electronics in the Electric Grid." IEEE Power Electronics Magazine 5, no. 3: 35-44.
The evolution of the power systems towards the smart grid paradigm is strictly dependent on the modernization of distribution grids. To achieve this target, new infrastructures, technologies and applica- tions are increasingly required. This paper presents a smart metering infrastructure that unlocks a large set of possible services aimed at the automation and management of distribution grids. The proposed architecture is based on a cloud solution, which allows the communication with the smart meters from one side and provides the needed interfaces to the distribution grid services on the other one. While a large number of applications can be designed on top of the cloud, in this paper the focus will be on a real-time distributed state estimation algorithm that enables the automatic reconfiguration of the grid. The paper will present the key role of the cloud solution for obtaining scalability, interoperability and flexibility, and for enabling the integration of different services for the automation of the distribution system. The distributed state estimation algorithm and the automatic network reconfiguration will be presented as an example of coordinated operation of different distribution grid services through the cloud
Marco Pau; Edoardo Patti; Luca Barbierato; Abouzar Estebsari; Enrico Pons; Ferdinanda Ponci; Antonello Monti. A cloud-based smart metering infrastructure for distribution grid services and automation. Sustainable Energy, Grids and Networks 2018, 15, 14 -25.
AMA StyleMarco Pau, Edoardo Patti, Luca Barbierato, Abouzar Estebsari, Enrico Pons, Ferdinanda Ponci, Antonello Monti. A cloud-based smart metering infrastructure for distribution grid services and automation. Sustainable Energy, Grids and Networks. 2018; 15 ():14-25.
Chicago/Turabian StyleMarco Pau; Edoardo Patti; Luca Barbierato; Abouzar Estebsari; Enrico Pons; Ferdinanda Ponci; Antonello Monti. 2018. "A cloud-based smart metering infrastructure for distribution grid services and automation." Sustainable Energy, Grids and Networks 15, no. : 14-25.
In this paper, we present a novel distributed software infrastructure to foster new services in smart grids with particular emphasis on supporting self-healing distribution systems. This infrastructure exploits the rising Internet-of-Things paradigms to build and manage an interoperable peer-to-peer network of our prototype smart meters, also presented in this paper. The proposed three-phase smart meter, called 3-SMA, is a low cost and open-source Internet-connected device that provides features for self-configuration. In addition, it selectively run on-board-algorithms for smart grid management depending on its deployment on the distribution network. Finally, we present the experimental results of Hardware-In-the-Loop simulations we performed.
Abouzar Estebsari; Matteo Orlando; Enrico Pons; Andrea Acquaviva; Edoardo Patti. A Novel Internet-of-Things Infrastructure to Support Self-Healing Distribution Systems. 2018 International Conference on Smart Energy Systems and Technologies (SEST) 2018, 1 -6.
AMA StyleAbouzar Estebsari, Matteo Orlando, Enrico Pons, Andrea Acquaviva, Edoardo Patti. A Novel Internet-of-Things Infrastructure to Support Self-Healing Distribution Systems. 2018 International Conference on Smart Energy Systems and Technologies (SEST). 2018; ():1-6.
Chicago/Turabian StyleAbouzar Estebsari; Matteo Orlando; Enrico Pons; Andrea Acquaviva; Edoardo Patti. 2018. "A Novel Internet-of-Things Infrastructure to Support Self-Healing Distribution Systems." 2018 International Conference on Smart Energy Systems and Technologies (SEST) , no. : 1-6.