4,903 research outputs found
Choice of State Estimation Solution Process for Medium Voltage Distribution Systems
As distribution networks are turning into active systems, enhanced observability and continuous monitoring becomes essential for effective management and control. The state estimation (SE) tool is therefore now considered as the core component in future distribution management systems. The development of a novel distribution system SE tool is required to accommodate small to very large networks, operable with limited real time measurements and able to execute the computation of large volumes of data in a limited time frame. In this context, the paper investigates the computation time and voltage estimation qualities of three different SE optimization solution methods in order to evaluate their effectiveness as potential distribution SE candidate solutions
Detection of Non-Technical Losses in Smart Distribution Networks: a Review
With the advent of smart grids, distribution utilities have
initiated a large deployment of smart meters on the premises of the
consumers. The enormous amount of data obtained from the consumers
and communicated to the utility give new perspectives and possibilities
for various analytics-based applications. In this paper the current
smart metering-based energy-theft detection schemes are reviewed and
discussed according to two main distinctive categories: A) system statebased,
and B) arti cial intelligence-based.Comisión Europea FP7-PEOPLE-2013-IT
On the Impact of Smartification Strategies for the State Estimation of Low Voltage Grids
The decarbonization of for example the energy or heat sector leads to the
transformation of distribution grids. The expansion of decentralized energy
resources and the integration of new consumers due to sector coupling (e.g.
heat pumps or electric vehicles) into low voltage grids increases the need for
grid expansion and usage of flexibilities in the grid. A high observability of
the current grid status is needed to perform these tasks efficiently and
effectively. Therefore, there is a need to increase the observability of low
voltage grids by installing measurement technologies (e.g. smart meters).
Multiple different measurement technologies are available for low voltage grids
which can vary in their benefit to observation quality and their installation
costs. Therefore, Bayernwerk Netz GmbH and E.DIS AG in cooperation with
E-Bridge Consulting GmbH and the Institute for High Voltage Equipment and
Grids, Digitalization and Energy Economics (IAEW) investigated the
effectiveness of different strategies for the smartification of low voltage
grids. This paper presents the methodology used for the investigation and
exemplary results focusing on the impact of intelligent cable distribution
cabinets and smart meters on the quality of the state estimation.Comment: In proceedings of the 13th "Internationale Energiewirtschaftstagung"
(IEWT2023), February 15-17, 2023, Vienna, Austri
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Diagnostic Applications for Micro-Synchrophasor Measurements
This report articulates and justifies the preliminary selection of diagnostic applications for data from micro-synchrophasors (µPMUs) in electric power distribution systems that will be further studied and developed within the scope of the three-year ARPA-e award titled Micro-synchrophasors for Distribution Systems
Distribution System Monitoring for Smart Power Grids with Distributed Generation Using Artificial Neural Networks
The increasing number of distributed generators connected to distribution
grids requires a reliable monitoring of such grids. Economic considerations
prevent a full observation of distribution grids with direct measurements.
First approaches using a limited number of measurements to monitor such grids
exist, some of which use artificial neural networks (ANN). The current
ANN-based approaches, however, are limited to static topologies, only estimate
voltage magnitudes, do not work properly when confronted with a high amount of
distributed generation and often yield inaccurate results. These strong
limitations have prevented a true applicability of ANN for distribution grid
monitoring. The objective of this paper is to overcome the limitations of
existing approaches. We do that by presenting an ANN-based scheme, which
advances the state-of-the-art in several ways: Our scheme can cope with a very
low number of measurements, far less than is traditionally required by the
state-of-the-art weighted least squares state estimation (WLS SE). It can
estimate both voltage magnitudes and line loadings with high precision and
includes different switching states as inputs. Our contribution consists of a
method to generate useful training data by using a scenario generator and a
number of hyperparameters that define the ANN architecture. Both can be used
for different grids even with a high amount of distributed generation.
Simulations are performed with an elaborate evaluation approach on a real
distribution grid and a CIGRE benchmark grid both with a high amount of
distributed generation from photovoltaics and wind energy converters. They
demonstrate that the proposed ANN scheme clearly outperforms state-of-the-art
ANN schemes and WLS SE under normal operating conditions and different
situations such as gross measurement errors when comparing voltage magnitude
and line magnitude estimation errors.Comment: 12 pages, 10 figures, 5 tables, preprin
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