Alexios Birbas - Academia.edu (original) (raw)

Papers by Alexios Birbas

Research paper thumbnail of Hardware Accelerators based on wavelets for detection of Transient phenomena in smart grids

Research paper thumbnail of An Adaptive Downsampling FPGA-Based TDC Implementation for Time Measurement Improvement

Research paper thumbnail of A Forecasting Model for the Prediction of System Imbalance in the Greek Power System

Research paper thumbnail of Fpga-Enabled Real-Time Power Grid Simulation Using Grid Partitioning

The high penetration of Distributed Energy Resources (DERs) and the IoT devices in the grid, as a... more The high penetration of Distributed Energy Resources (DERs) and the IoT devices in the grid, as a result of policy regulations and economic considerations, physically located everywhere, in all shapes and sizes, both in front (FTM) and behind the meter (BTM) are fundamentally transforming the grid into a decentralized network of new grid assets that participate in multiple hierarchical energy markets. This transformation, however, creates challenges that needs to be managed. In order to adequately capture the transient behavior of the various grid components, detailed component models and Real-Time (RT) simulations are required. Leveraging their inherent parallelism capabilities, FPGA platforms help to achieve high-speed simulation execution, becoming a useful validation and planning tool for power grid management. However, the hardware utilization in these solutions is directly proportional to the size of the network under test, leading to expensive and hardly scalable architectures unsuitable for the simulation of large scale power networks. In this paper, a novel technique is presented, which aims to reduce the FPGA's resources utilization in distribution power grids. There are cases where part of the network under test can be partitioned in a number of identical subnetworks, whose output can be calculated by the same hardware module and thus lead to hardware utilization reduction. As proof of concept of the proposed approach, the implementations of a microgrid with and without applying the partitioning technique are demonstrated and compared in terms of accuracy, simulation speed and FPGA resources utilization.

Research paper thumbnail of Noise and uncertainty in comparator/TDC sensor readout circuits

Time to Digital Conversion (TDC) is an efficient technique to transform sensor readout signals in... more Time to Digital Conversion (TDC) is an efficient technique to transform sensor readout signals into digital read out output through the measurement of a time duration. It is applicable into low frequency capacitive sensor readout circuits as well as in high frequency event-sensing circuits. The choice of the measuring time affects the sensitivity range for a specific physical species and is prone to jitter (noise). The noise itself stems from the readout circuitry and from various parasitic elements. The identification of the noise origin is necessary since it affects not only the range but also the resolution of the sensor, as it appears in the jitter. In high frequency applications the thermal noise behavior of the output noise diminishes jitter as a function of the measurement time while in low frequency capacitive sensor applications, the measurement time increase in order to extend the measurement range, leads to an increased output noise as well (jitter).

Research paper thumbnail of A 100-ps Multi-Time over Threshold Data Acquisition System for Cosmic Ray Detection

arXiv (Cornell University), Feb 3, 2017

Research paper thumbnail of Hardware/software co-design of embedded systems using multiple formalisms for application development

HAL (Le Centre pour la Communication Scientifique Directe), Nov 3, 1998

Research paper thumbnail of Optimization of a Local Energy Market Operation in a Transactive Energy Environment

ICT advancements (low latency new generation networks) transform the Distributed Energy Resources... more ICT advancements (low latency new generation networks) transform the Distributed Energy Resources (DERs) at the edge of the electrical grid gradually into grid assets and drive the energy system towards a decentralized transactive operation. Local Energy Markets (LEMs) have been proposed as a means to facilitate and orchestrate the vast penetration of DERs. We propose here a LEM operation which concludes into fair pricing with monetary gains for both prosumers and consumers participating in the LEM. For the Day-Ahead LEM operation we apply a chance-constrained optimization algorithm in order to tackle the uncertainties governing the Day-Ahead LEM operation. The proposed LEM architecture is validated upon an IEEE low voltage European test feeder benchmark.

Research paper thumbnail of Semi-classical noise investigation for sub-40nm metal-oxide-semiconductor field-effect transistors

AIP Advances, Aug 1, 2015

Research paper thumbnail of A Predictive Fuzzy Logic Model for Forecasting Electricity Day-Ahead Market Prices for Scheduling Industrial Applications

Research paper thumbnail of with Binary Tree Structure

Research paper thumbnail of Deep learning-based application for fault location identification and type classification in active distribution grids

Research paper thumbnail of Sampling Points Selection Algorithm For Advanced Photolithography Process

2022 7th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM)

Research paper thumbnail of The prototype detection unit of the KM3NeT detector

The European Physical Journal C, 2016

Research paper thumbnail of Deep sea tests of a prototype of the KM3NeT digital optical module

Research paper thumbnail of A Genetic Algorithms Enhanced Sensor Marks Selection Algorithm For Advanced Photolithography Process

In photolithography process, nanometer level precise, wavefront aberration models enable the mach... more In photolithography process, nanometer level precise, wavefront aberration models enable the machine to be able to meet the overlay (OVL) drift and critical dimension (CD) specifications. Software control algorithms take as input these models and correct any expected wavefront imperfections before reaching the wafer. In such way a near optimal image is exposed on the wafer surface. Optimizing the parameters of these models though, involves several time costly sensor measurements which reduce the throughput performance, in terms of exposed wafers per hour, of the machine. In that case, photolithography machines come across the trade-off between throughput and quality. Therefore one of the most common Optimal Experimental Design (OED) problems in photolithography machines (and not only) is how to choose the minimum amount of sensor measurements that will provide the maximum amount of information. Additionally, each sensor measurement corresponds to a point on the wafer surface and the...

Research paper thumbnail of Deep Reinforcement Learning Acceleration for Real-Time Edge Computing Mixed Integer Programming Problems

Research paper thumbnail of Local Energy Market-Consumer Digital Twin Coordination for Optimal Energy Price Discovery under Thermal Comfort Constraints

Applied Sciences

The upward trend of adopting Distributed Energy Resources (DER) reshapes the energy landscape and... more The upward trend of adopting Distributed Energy Resources (DER) reshapes the energy landscape and supports the transition towards a sustainable, carbon-free electricity system. The integration of Internet of Things (IoT) in Demand Response (DR) enables the transformation of energy flexibility, originated by electricity consumers/prosumers, into a valuable DER asset, thus placing them at the center of the electricity market. In this paper, it is shown how Local Energy Markets (LEM) act as a catalyst by providing a digital platform where the prosumers’ energy needs and offerings can be efficiently settled locally while minimizing the grid interaction. This paper showcases that the IoT technology, which enables control and coordination of numerous devices, further unleashes the flexibility potential of the distribution grid, offered as an energy service both to the LEM participants as well as the external grid. This is achieved by orchestrating the IoT devices through a Consumer Digita...

Research paper thumbnail of Cloud-Edge Architecture With Virtualized Hardware Functionality for Real-Time Diagnosis of Transients in Smart Grids

IEEE Transactions on Cloud Computing

Research paper thumbnail of Holistic System Modelling and Analysis for Energy-Aware Production: An Integrated Framework

Systems

Optimizing and predicting the energy consumption of industrial manufacturing can increase its cos... more Optimizing and predicting the energy consumption of industrial manufacturing can increase its cost efficiency. The interaction of different aspects and components is necessary. An overarching framework is currently still missing, and establishing such is the central research approach in this paper. This paper provides an overview of the current demands on the manufacturing industry from the perspective of digitalization and sustainability. On the basis of the developed fundamentals and parameters, a superordinate framework is proposed that allows the modelling and simulation of energy-specific properties on several product and process levels. A detailed description of the individual methods concludes this work and demonstrates their application potential in an industrial context. As a result, this integrated conceptual framework offers the possibility of optimizing the production system, in relation to different energy flexibility criteria.

Research paper thumbnail of Hardware Accelerators based on wavelets for detection of Transient phenomena in smart grids

Research paper thumbnail of An Adaptive Downsampling FPGA-Based TDC Implementation for Time Measurement Improvement

Research paper thumbnail of A Forecasting Model for the Prediction of System Imbalance in the Greek Power System

Research paper thumbnail of Fpga-Enabled Real-Time Power Grid Simulation Using Grid Partitioning

The high penetration of Distributed Energy Resources (DERs) and the IoT devices in the grid, as a... more The high penetration of Distributed Energy Resources (DERs) and the IoT devices in the grid, as a result of policy regulations and economic considerations, physically located everywhere, in all shapes and sizes, both in front (FTM) and behind the meter (BTM) are fundamentally transforming the grid into a decentralized network of new grid assets that participate in multiple hierarchical energy markets. This transformation, however, creates challenges that needs to be managed. In order to adequately capture the transient behavior of the various grid components, detailed component models and Real-Time (RT) simulations are required. Leveraging their inherent parallelism capabilities, FPGA platforms help to achieve high-speed simulation execution, becoming a useful validation and planning tool for power grid management. However, the hardware utilization in these solutions is directly proportional to the size of the network under test, leading to expensive and hardly scalable architectures unsuitable for the simulation of large scale power networks. In this paper, a novel technique is presented, which aims to reduce the FPGA's resources utilization in distribution power grids. There are cases where part of the network under test can be partitioned in a number of identical subnetworks, whose output can be calculated by the same hardware module and thus lead to hardware utilization reduction. As proof of concept of the proposed approach, the implementations of a microgrid with and without applying the partitioning technique are demonstrated and compared in terms of accuracy, simulation speed and FPGA resources utilization.

Research paper thumbnail of Noise and uncertainty in comparator/TDC sensor readout circuits

Time to Digital Conversion (TDC) is an efficient technique to transform sensor readout signals in... more Time to Digital Conversion (TDC) is an efficient technique to transform sensor readout signals into digital read out output through the measurement of a time duration. It is applicable into low frequency capacitive sensor readout circuits as well as in high frequency event-sensing circuits. The choice of the measuring time affects the sensitivity range for a specific physical species and is prone to jitter (noise). The noise itself stems from the readout circuitry and from various parasitic elements. The identification of the noise origin is necessary since it affects not only the range but also the resolution of the sensor, as it appears in the jitter. In high frequency applications the thermal noise behavior of the output noise diminishes jitter as a function of the measurement time while in low frequency capacitive sensor applications, the measurement time increase in order to extend the measurement range, leads to an increased output noise as well (jitter).

Research paper thumbnail of A 100-ps Multi-Time over Threshold Data Acquisition System for Cosmic Ray Detection

arXiv (Cornell University), Feb 3, 2017

Research paper thumbnail of Hardware/software co-design of embedded systems using multiple formalisms for application development

HAL (Le Centre pour la Communication Scientifique Directe), Nov 3, 1998

Research paper thumbnail of Optimization of a Local Energy Market Operation in a Transactive Energy Environment

ICT advancements (low latency new generation networks) transform the Distributed Energy Resources... more ICT advancements (low latency new generation networks) transform the Distributed Energy Resources (DERs) at the edge of the electrical grid gradually into grid assets and drive the energy system towards a decentralized transactive operation. Local Energy Markets (LEMs) have been proposed as a means to facilitate and orchestrate the vast penetration of DERs. We propose here a LEM operation which concludes into fair pricing with monetary gains for both prosumers and consumers participating in the LEM. For the Day-Ahead LEM operation we apply a chance-constrained optimization algorithm in order to tackle the uncertainties governing the Day-Ahead LEM operation. The proposed LEM architecture is validated upon an IEEE low voltage European test feeder benchmark.

Research paper thumbnail of Semi-classical noise investigation for sub-40nm metal-oxide-semiconductor field-effect transistors

AIP Advances, Aug 1, 2015

Research paper thumbnail of A Predictive Fuzzy Logic Model for Forecasting Electricity Day-Ahead Market Prices for Scheduling Industrial Applications

Research paper thumbnail of with Binary Tree Structure

Research paper thumbnail of Deep learning-based application for fault location identification and type classification in active distribution grids

Research paper thumbnail of Sampling Points Selection Algorithm For Advanced Photolithography Process

2022 7th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM)

Research paper thumbnail of The prototype detection unit of the KM3NeT detector

The European Physical Journal C, 2016

Research paper thumbnail of Deep sea tests of a prototype of the KM3NeT digital optical module

Research paper thumbnail of A Genetic Algorithms Enhanced Sensor Marks Selection Algorithm For Advanced Photolithography Process

In photolithography process, nanometer level precise, wavefront aberration models enable the mach... more In photolithography process, nanometer level precise, wavefront aberration models enable the machine to be able to meet the overlay (OVL) drift and critical dimension (CD) specifications. Software control algorithms take as input these models and correct any expected wavefront imperfections before reaching the wafer. In such way a near optimal image is exposed on the wafer surface. Optimizing the parameters of these models though, involves several time costly sensor measurements which reduce the throughput performance, in terms of exposed wafers per hour, of the machine. In that case, photolithography machines come across the trade-off between throughput and quality. Therefore one of the most common Optimal Experimental Design (OED) problems in photolithography machines (and not only) is how to choose the minimum amount of sensor measurements that will provide the maximum amount of information. Additionally, each sensor measurement corresponds to a point on the wafer surface and the...

Research paper thumbnail of Deep Reinforcement Learning Acceleration for Real-Time Edge Computing Mixed Integer Programming Problems

Research paper thumbnail of Local Energy Market-Consumer Digital Twin Coordination for Optimal Energy Price Discovery under Thermal Comfort Constraints

Applied Sciences

The upward trend of adopting Distributed Energy Resources (DER) reshapes the energy landscape and... more The upward trend of adopting Distributed Energy Resources (DER) reshapes the energy landscape and supports the transition towards a sustainable, carbon-free electricity system. The integration of Internet of Things (IoT) in Demand Response (DR) enables the transformation of energy flexibility, originated by electricity consumers/prosumers, into a valuable DER asset, thus placing them at the center of the electricity market. In this paper, it is shown how Local Energy Markets (LEM) act as a catalyst by providing a digital platform where the prosumers’ energy needs and offerings can be efficiently settled locally while minimizing the grid interaction. This paper showcases that the IoT technology, which enables control and coordination of numerous devices, further unleashes the flexibility potential of the distribution grid, offered as an energy service both to the LEM participants as well as the external grid. This is achieved by orchestrating the IoT devices through a Consumer Digita...

Research paper thumbnail of Cloud-Edge Architecture With Virtualized Hardware Functionality for Real-Time Diagnosis of Transients in Smart Grids

IEEE Transactions on Cloud Computing

Research paper thumbnail of Holistic System Modelling and Analysis for Energy-Aware Production: An Integrated Framework

Systems

Optimizing and predicting the energy consumption of industrial manufacturing can increase its cos... more Optimizing and predicting the energy consumption of industrial manufacturing can increase its cost efficiency. The interaction of different aspects and components is necessary. An overarching framework is currently still missing, and establishing such is the central research approach in this paper. This paper provides an overview of the current demands on the manufacturing industry from the perspective of digitalization and sustainability. On the basis of the developed fundamentals and parameters, a superordinate framework is proposed that allows the modelling and simulation of energy-specific properties on several product and process levels. A detailed description of the individual methods concludes this work and demonstrates their application potential in an industrial context. As a result, this integrated conceptual framework offers the possibility of optimizing the production system, in relation to different energy flexibility criteria.