Nikolaos Sapountzoglou

CERN | CERN · Electrical Engineering Group (EL)

A R T I C L E I N F O Keywords: Vehicle-to-grid (V2G) Electric Vehicle (EV) Barriers Risk matrix Cross-impact analysis A B S T R A C T The remarkable growth of electric vehicles (EV) popularity in recent years has significantly pushed the EV charging demand, potentially causing significant pressure on the electricity grid. The Vehicle-to-Grid (V2G)...

The current paper defines a framework for the introduction of automated frequency restoration reserve services, enabled by vehicle-to-grid technology, into the business model of an entity owning and operating a network of semi-public Electric Vehicle Supply Equipment. It assesses the profitability of this introduction by performing a case study bas...

Increasing penetration of electric vehicles brings a set of challenges for the electricity system related to its energy, power and balance adequacy. Research related to this topic often requires estimates of charging demand in various forms to feed various models and simulations. This paper proposes a methodology to simulate charging demand for dif...

The current paper defines a framework for the introduction of frequency containment reserve (FCR) services, enabled by vehicle-to-grid (V2G) technology, into the business model of an entity owning and operating electric vehicle (EV) charging infrastructure. Moreover, the defined framework can also be extrapolated, with minor adjustments, to the bus...

Risk management is a risk assessment and analysis method aimed at identifying and assessing risk factors in critical technological systems for the purpose of improving their safety and performance. There are, however, only a handful space mission-level risk classification methods in the literature. NASA was the first to develop such a method consid...

As the circulation of electric vehicles (EVs) has increased rapidly over the past few years, their effect on the operation of active low-voltage (LV) grids has been thoroughly studied. However, to the authors’ knowledge, their effect on fault detection schemes has not been evaluated yet. Electrical Vehicles are big loads whose operation, in contras...

The evolution of the conventional power systems to smart grids has changed the way to conceive and operate them. The part of the grid evolving the most is the distribution grid where the installation of additional sensors and actuators has increased its observability and controllability. These have enabled the development of more accurate and autom...

In this paper, a new robust and reproducible hybrid approach for space mission risk classification is proposed. The method consists of: a) text mining of bibliographic data and b) an Impact-Matrix-Cross-Reference-Multiplication-Applied-to-a-Classification (MICMAC)- inspired analysis that measures the degree of interrelation of the defined classific...

The current work fills in the existing research gap with regard to business modelling approaches applied to the technologically-driven markets. Taking into consideration the highly innovative and evolving nature of the latter ones, this paper combines the most relevant business modelling methods, creating a detailed, dynamic and holistic integrativ...

Electric vehicles (EV) are foreseen as one major technology toward decarbonizing the mobility sector. At the same time, Vehicle to Grid (V2G) technology opens a new market for EV owners. This article identifies the impacts of providing V2G services on the Total Cost of Ownership (TCO) of EVs. Thus, we studied EVs in private, semi-public and public...

The rapid growth of the electrical vehicle (EV) market over the last decade has rendered the existence and accuracy of the business models of the EV charging market a critical factor for a company’s success. To address this issue, this paper presents a quantification framework for the business models of the core participants of the EV charging mark...

Uni- and bi-directional electric vehicle charging schedulers are key enablers in the mitigation of the negative impacts, such as peak powers, of electric vehicles and renewable energy sources on the grid. This paper presents two electric vehicle charging schedulers based on model predictive control algorithms for four different charging strategies...

The increasing penetration rate of electric vehicles, associated with a growing charging demand, could induce a negative impact on the electric grid, such as higher peak power demand. To support the electric grid, and to anticipate those peaks, a growing interest exists for forecasting the day-ahead charging demand of electric vehicles. This paper...

In this thesis, a bibliographic meta-analysis of the risk management field in the space sector is presented and a new robust and reproducible hybrid approach for space mission risk classification is proposed. The method consists of: a) text mining of bibliographic data and b) an Impact-Matrix-Cross-Reference- Multiplication-Applied-to-a-Classificat...

Power outages in electrical grids can have very negative economic and societal impacts rendering fault diagnosis paramount to their secure and reliable operation. In this paper, deep neural networks are proposed for fault detection and location in low-voltage smart distribution grids. Due to its key properties, the proposed method solves some of th...

In this paper, a gradient boosting tree model is proposed to detect, identify and localize single-phase-to-ground and three-phase faults in low voltage (LV) smart distribution grids. The proposed method is based on gradient boosting trees and considers branch-independent input features to be generalizable and applicable to different grid topologies...

A fault localization method for single-phase to ground short-circuit (SC) faults in low voltage (LV) smart distribution grids is presented in this paper. Both the use of rms voltage phase measurements and an analysis of symmetrical components of the voltage were investigated and compared in this study. Phase measurements were found to be more suita...

New smart meters, distributed generation, renewable energy sources and the concern about the environment are redefining the way to conceive and operate electrical grids. To take full advantage of the new electrical smart grids we need to monitor and protect them. The capability of self-healing is thus important in smart grids in order to ensure a p...

PhD thesis defense presentation on fault detection and isolation for low voltage distribution grids with distributed generation.

In this paper, a fault detection and localization method for a Low Voltage (LV) distribution grid are presented. Two fault detection approaches were examined both suitable only for low impedance faults (up to 10 Ω of fault resistance). The first one was based on current measurements at the beginning of the feeder and the second one was based on the...

Results of a fault detection and localization algorithm for low voltage smart distribution grids

A fault localization method for single-phase to ground short-circuit (SC) faults in low voltage (LV) smart distribution grids is presented in this paper. Both the use of rms voltage phase measurements and an analysis of symmetrical components of the voltage were investigated and compared in this study. Phase measurements were found to be more suita...

A fault detection algorithm for grid-connected photovoltaic (GCPV) systems is presented in this paper. After a synthetic description of the most important fault detection techniques up to date, the selection of the signal approach and of the output of the inverter as a measurement point for the monitored electrical variables, for this study, are ex...

Corona discharge is used in a plethora of industrial applications. In power systems corona discharge is associated with power losses, audible noise and electromagnetic interference. In this Diploma Thesis the salient characteristics of dc corona on smooth conductors in the coaxial cylindrical and conductor–plane electrode arrangements have been exp...