27,781 research outputs found
Modeling Weather Impact on a Secondary Electrical Grid
Weather can cause problems for underground electrical grids by increasing the probability of serious “manhole events” such as fires and explosions. In this work, we compare a model that incorporates weather features associated with the dates of serious events into a single logistic regression, with a more complex approach that has three interdependent log linear models for weather, baseline manhole vulnerability, and vulnerability of manholes to weather. The latter approach more naturally incorporates the dependencies between the weather, structure properties, and structure vulnerability
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Photovoltaic and Behind-the-Meter Battery Storage: Advanced Smart Inverter Controls and Field Demonstration
Development of Grid e-Infrastructure in South-Eastern Europe
Over the period of 6 years and three phases, the SEE-GRID programme has
established a strong regional human network in the area of distributed
scientific computing and has set up a powerful regional Grid infrastructure. It
attracted a number of user communities and applications from diverse fields
from countries throughout the South-Eastern Europe. From the infrastructure
point view, the first project phase has established a pilot Grid infrastructure
with more than 20 resource centers in 11 countries. During the subsequent two
phases of the project, the infrastructure has grown to currently 55 resource
centers with more than 6600 CPUs and 750 TBs of disk storage, distributed in 16
participating countries. Inclusion of new resource centers to the existing
infrastructure, as well as a support to new user communities, has demanded
setup of regionally distributed core services, development of new monitoring
and operational tools, and close collaboration of all partner institution in
managing such a complex infrastructure. In this paper we give an overview of
the development and current status of SEE-GRID regional infrastructure and
describe its transition to the NGI-based Grid model in EGI, with the strong SEE
regional collaboration.Comment: 22 pages, 12 figures, 4 table
Stochastic Model for Power Grid Dynamics
We introduce a stochastic model that describes the quasi-static dynamics of
an electric transmission network under perturbations introduced by random load
fluctuations, random removing of system components from service, random repair
times for the failed components, and random response times to implement optimal
system corrections for removing line overloads in a damaged or stressed
transmission network. We use a linear approximation to the network flow
equations and apply linear programming techniques that optimize the dispatching
of generators and loads in order to eliminate the network overloads associated
with a damaged system. We also provide a simple model for the operator's
response to various contingency events that is not always optimal due to either
failure of the state estimation system or due to the incorrect subjective
assessment of the severity associated with these events. This further allows us
to use a game theoretic framework for casting the optimization of the
operator's response into the choice of the optimal strategy which minimizes the
operating cost. We use a simple strategy space which is the degree of tolerance
to line overloads and which is an automatic control (optimization) parameter
that can be adjusted to trade off automatic load shed without propagating
cascades versus reduced load shed and an increased risk of propagating
cascades. The tolerance parameter is chosen to describes a smooth transition
from a risk averse to a risk taken strategy...Comment: framework for a system-level analysis of the power grid from the
viewpoint of complex network
Buildings-to-Grid Integration Framework
This paper puts forth a mathematical framework for Buildings-to-Grid (BtG)
integration in smart cities. The framework explicitly couples power grid and
building's control actions and operational decisions, and can be utilized by
buildings and power grids operators to simultaneously optimize their
performance. Simplified dynamics of building clusters and building-integrated
power networks with algebraic equations are presented---both operating at
different time-scales. A model predictive control (MPC)-based algorithm that
formulates the BtG integration and accounts for the time-scale discrepancy is
developed. The formulation captures dynamic and algebraic power flow
constraints of power networks and is shown to be numerically advantageous. The
paper analytically establishes that the BtG integration yields a reduced total
system cost in comparison with decoupled designs where grid and building
operators determine their controls separately. The developed framework is
tested on standard power networks that include thousands of buildings modeled
using industrial data. Case studies demonstrate building energy savings and
significant frequency regulation, while these findings carry over in network
simulations with nonlinear power flows and mismatch in building model
parameters. Finally, simulations indicate that the performance does not
significantly worsen when there is uncertainty in the forecasted weather and
base load conditions.Comment: In Press, IEEE Transactions on Smart Gri
Modeling and Recognition of Smart Grid Faults by a Combined Approach of Dissimilarity Learning and One-Class Classification
Detecting faults in electrical power grids is of paramount importance, either
from the electricity operator and consumer viewpoints. Modern electric power
grids (smart grids) are equipped with smart sensors that allow to gather
real-time information regarding the physical status of all the component
elements belonging to the whole infrastructure (e.g., cables and related
insulation, transformers, breakers and so on). In real-world smart grid
systems, usually, additional information that are related to the operational
status of the grid itself are collected such as meteorological information.
Designing a suitable recognition (discrimination) model of faults in a
real-world smart grid system is hence a challenging task. This follows from the
heterogeneity of the information that actually determine a typical fault
condition. The second point is that, for synthesizing a recognition model, in
practice only the conditions of observed faults are usually meaningful.
Therefore, a suitable recognition model should be synthesized by making use of
the observed fault conditions only. In this paper, we deal with the problem of
modeling and recognizing faults in a real-world smart grid system, which
supplies the entire city of Rome, Italy. Recognition of faults is addressed by
following a combined approach of multiple dissimilarity measures customization
and one-class classification techniques. We provide here an in-depth study
related to the available data and to the models synthesized by the proposed
one-class classifier. We offer also a comprehensive analysis of the fault
recognition results by exploiting a fuzzy set based reliability decision rule
Modeling and Real-Time Scheduling of DC Platform Supply Vessel for Fuel Efficient Operation
DC marine architecture integrated with variable speed diesel generators (DGs)
has garnered the attention of the researchers primarily because of its ability
to deliver fuel efficient operation. This paper aims in modeling and to
autonomously perform real-time load scheduling of dc platform supply vessel
(PSV) with an objective to minimize specific fuel oil consumption (SFOC) for
better fuel efficiency. Focus has been on the modeling of various components
and control routines, which are envisaged to be an integral part of dc PSVs.
Integration with photovoltaic-based energy storage system (ESS) has been
considered as an option to cater for the short time load transients. In this
context, this paper proposes a real-time transient simulation scheme, which
comprises of optimized generation scheduling of generators and ESS using dc
optimal power flow algorithm. This framework considers real dynamics of dc PSV
during various marine operations with possible contingency scenarios, such as
outage of generation systems, abrupt load changes, and unavailability of ESS.
The proposed modeling and control routines with real-time transient simulation
scheme have been validated utilizing the real-time marine simulation platform.
The results indicate that the coordinated treatment of renewable based ESS with
DGs operating with optimized speed yields better fuel savings. This has been
observed in improved SFOC operating trajectory for critical marine missions.
Furthermore, SFOC minimization at multiple suboptimal points with its treatment
in the real-time marine system is also highlighted
ANOMALY INFERENCE BASED ON HETEROGENEOUS DATA SOURCES IN AN ELECTRICAL DISTRIBUTION SYSTEM
Harnessing the heterogeneous data sets would improve system observability. While the current metering infrastructure in distribution network has been utilized for the operational purpose to tackle abnormal events, such as weather-related disturbance, the new normal we face today can be at a greater magnitude. Strengthening the inter-dependencies as well as incorporating new crowd-sourced information can enhance operational aspects such as system reconfigurability under extreme conditions. Such resilience is crucial to the recovery of any catastrophic events. In this dissertation, it is focused on the anomaly of potential foul play within an electrical distribution system, both primary and secondary networks as well as its potential to relate to other feeders from other utilities. The distributed generation has been part of the smart grid mission, the addition can be prone to electronic manipulation.
This dissertation provides a comprehensive establishment in the emerging platform where the computing resources have been ubiquitous in the electrical distribution network. The topics covered in this thesis is wide-ranging where the anomaly inference includes load modeling and profile enhancement from other sources to infer of topological changes in the primary distribution network. While metering infrastructure has been the technological deployment to enable remote-controlled capability on the dis-connectors, this scholarly contribution represents the critical knowledge of new paradigm to address security-related issues, such as, irregularity (tampering by individuals) as well as potential malware (a large-scale form) that can massively manipulate the existing network control variables, resulting into large impact to the power grid
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