BUSCADOR RECOLECTA

Comunicació presentada a "Tenth Protection, Automation and Control (PAC) World Conference", celebrada del 17 al 20 de juny de 2019 a la University of Strathclyde a Glasgow, UK, PAC World Conference (10th: 2019: Glasgow,UK), This work presents the development and results of an automated event detection strategy based on principal component analysis (PCA) for low voltage distribution grids with the presence of distributed generation (DG) and phasor measurement units (PMUs). The proposed methodology, relying on measurements provided by PMUs installed at different nodes, is capable of correctly identifying and distinguishing abnormal operating conditions (AOC) from normal operating conditions (NOC) without requiring any information about the network topology or electrical parameters of its components. Moreover, it is tested and validated under voltage sags and swells in a real-based power distribution network simulated in MATLAB with PMUs deployed in distinct settings

Comunicació presentada a: 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019), A model for day-ahead scheduling of batteries and branch switches in the low voltage grid, considering forecasts uncertainties, is proposed. The objective is to reduce the energy losses of the distribution lines and avoid critical events such as congestions or over and under-voltages in the local network. Simulations of different day-ahead situations are performed with a modified particle swarm optimisation algorithm. The results show that critical events are avoided and energy self-consumption within the local network is increased, This work has been developed under the European project RESOLVD of the
Horizon 2020 research and innovation program (topic LCE-01-2016-2017) and
grant agreement N773715

Comunicació presentada a: 25th International Conference on Electricity Distribution: Madrid, 3-6 June 2019, This paper analyses the impact of batteries in the hosting capacity of a low voltage grid with prosumers with photovoltaic generation installed under different scenarios. Storage location in the grid has been selected with the criterion of reducing congestion. Two scenarios have been considered: the first with current demand of consumers in the grid and the second by increasing their demand profile proportionally, whilst maintaining the daily load curve shape, until a congestion situation is reached. Simulation of increasing PV generation and storage capacity is performed until a congestion is given, resulting for the first scenario an increase of 140% of PV production is achieved with 100kWh of storage. In the second scenario 230 kWp of maximum hosting capacity can be achieved with 400kWh of storage, This work has been developed in collaboration with the European project RESOLVD of the Horizon 2020 research and innovation program (topic LCE-01-2016-2017) and grant agreement N773715

Comunicació presentada a: 25th International Conference on Electricity Distribution: Madrid, 3-6 June 2019, The paper presents the RESOLVD (Renewable penetration
levered by efficient low voltage distribution grids) project,
which aims to improve the efficiency and the hosting
capacity of distribution networks in a context of highly
distributed renewable generation by introducing flexibility
(storage management) and control in the low voltage (LV)
grid. The analysis methodology - which follows the Smart
Grid Architecture Model (SGAM) framework paradigm- is
presented, along with the identified use cases and actors.
The proposed initial architecture is also presented, as
derived from the use case analysis process together with a
cybersecurity analysis of integration and interoperability
issues. The research is being motivated by business models
and the expected impacts are summarized in the paper, This work has been developed under the European project
RESOLVD of the Horizon 2020 research and innovation
program (topic LCE-01-2016-2017) and grant agreement N773715

Comunicació de congrés presentada a: The Eleventh Conference on Innovative Smart Grid Technologies (ISGT 2020), sponsored by the IEEE Power & Energy Society (PES), will be held February 17-20, 2020 at the Grand Hyatt Washington, Washington D.C., This paper presents a new strategy based on multivariate
statistical analysis for fault location and classification in
power distribution networks with distributed energy resources,
variable loads, and switches enabling grid reconfiguration. The
statistical method relies on impedance measurements acquired
at the substation buses to build a data-driven model of the
network operating conditions with dimensionality reduction,
and considers a few reference scenarios representing standard
operating conditions and short-circuit operation to perform fault
location and classification with use of similarity criteria in the
principal component subspace. Moreover, this paper includes
a case study with a real-based low voltage power distribution
network to test and validate the methodology, This research was supported by the European Union’s Horizon 2020
research and innovation programme, call LCE-01-2016-2017, under the auspices of the project Renewable penetration levered by Efficient Low Voltage
Distribution grids, grant agreement number 773715, and University of Girona
scholarship

Comunicació de congrés presentada a: VI Congreso Smart Grids: Madrid, 12 Diciembre 2019, organitzat per GrupoTecmaRed i co-organitzat per FutuRed, RESOLVD (Renewable penetration levered by efficient low volatge distribution grids) es un proyecto de investigación financiado por el programa europeo H2020 (2017/20, LCE-01-2016-2017, Ref. 773715,) que tiene como objetivo construir un piloto de red de baja tensión inteligente y eficiente, con capacidad de operación y gestión energética local, que maximice la capacidad de generación renovable inyectable en dicha red y su consumo local. La operación consiste en posibilitar la conexión de líneas de baja tensión de diferentes centros con el propósito de evitar congestiones y variaciones de tensiones en episodios de alta generación o consumo. La gestión energética se realiza mediante baterías instaladas en el centro de transformación con el propósito de minimizar la importación de energía de la red, RESOLVD (Renewable penetration levered by efficient low volatge distribution grids) es un proyecto de investigación financiado por el programa europeo H2020 (2017/20, LCE-01-2016-2017, Ref. 773715)

This article presents a monitoring strategy based on multilayer principal component analysis (PCA) to detect and diagnose power system disturbances in large amounts of data collected by intelligent electronic devices in low voltage smart grids. The PCA models are built on multiple sliding windows, sized (in terms of length and sampling time) according to the type of phenomena to detect. Abnormalities are detected with use of two complementary statistical indexes, then diagnosed by computing the individual contributions of each monitored variable to the constraint violation of those statistics. As a result, its implementation enables an automatic analysis of multiple phenomena of interest in parallel over time using distinct electrical quantities. Furthermore, the method is demonstrated within the RESOLVD project with data from the OpenLV project containing measurements of active and reactive power gathered at different low voltage distribution substations, This work has been supported by the European Union’s
Horizon 2020 research and innovation framework under the auspices of the project Renewable penetration levered by Efficient Low Voltage
Distribution grids, grant agreement number 773715, and University of
Girona scholarship

Comunicació de congrés presentada a: 2020 IEEE Power and Energy Society General Meeting, Montreal, QC, Canada, 2020, 3-6 August. https://pes-gm.org/2020/, Principal component analysis (PCA) is a dimensionality
reduction technique often applied to process and detect
events in large amounts of data collected by phasor measurement
units (PMU) at transmission and distribution level. This article
considers five different approaches to select an appropriate
number of principal components, builds the statistical model
of the PMU data online over a sliding window of 10 seconds
and 1 minute, and evaluates the computation times and the
accuracy of correct event detections with use of two statistical
tests in a 1−hour data file from the UT-Austin Independent
Texas Synchrophasor Network with phasor quantities collected
at different PMU substations, This research was supported by the European Union’s
Horizon 2020 research and innovation programme, call LCE-
01-2016-2017, under the auspices of the project “Renewable
penetration levered by Efficient Low Voltage Distribution
grids”, grant agreement number 773715, and University of
Girona scholarship.

Comunicació de congrés presentada a: 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), organitzat per l'IEEE Power & Energy Society (PES) i la Delft University of Technology (Països Baixos), del 26 a 28 d'octubre de 2020. https://ieee-isgt-europe.org/, This article compares distinct signal-based and
knowledge-based approaches often applied to process and detect
events in vast amounts of data collected by phasor measurement
units (PMU). The computation times and the accuracy of correct
event detections are tested and evaluated in a 1-hour data file
from the UT-Austin Independent Texas Synchrophasor Network
with phasor quantities plus an additive noise gathered at different
PMU substations. A sliding time window is considered to build
a representative model of the system operating conditions on the
fly and search for power system phenomena as soon as new data
are available, This research was supported by the European Union’s Horizon 2020 research and innovation programme, call LCE-01-2016-2017, under the auspices of the project “Renewable penetration levered by Efficient Low Voltage Distribution grids”, grant agreement number 773715, and University of Girona scholarship

Comunicació de congrés presentada a: 2020 IEEE PES Transmission & Distribution Conference & Exposition Latin America (28 setembre - 2 octubre 2020: Montevideo, Uruguay). https://www.ieee-tdla2020.org/, This article provides an evaluation of power system
resilience enhancements in low-income neighborhoods. Lowincome
households and communities may be subject to risks
of different nature, such as natural hazards and human-made
attacks, hereby considered as particular cases of high-impact,
low-probability events that are highly likely to damage power grid
infrastructures. Such events may result in long interruption times
and lead to permanent disconnection from the grid in extreme
cases, and consequently, the value of load lost may be much
higher than the investment cost associated with prevention and
mitigation alternatives. In this scenario, this article analyzes the
value of load lost and the costs associated with installation, operation,
and repair of grid components affected by extreme events
to determine the benefits of different strategies for power system
resilience improvements targeted at low-income neighborhoods, This research was supported by the European Union’s Horizon 2020 research
and innovation programme, call LCE-01-2016-2017, under the auspices
of the project “Renewable penetration levered by Efficient Low Voltage
Distribution grids”, grant agreement number 773715, and University of Girona scholarship