134,865 research outputs found
Electrical Power Distribution System Reconfiguration: Case Study of a Real-life Grid in Croatia
This paper describes the application of a nonlinear model predictive control algorithm to the problem of dynamic
reconfiguration of an electrical power distribution system with distributed generation and storage. Power distribution
systems usually operate in a radial topology despite being physically built as interconnected meshed networks. The
meshed structure of the network allows one to modify the network topology by changing the status of the line switches
(open/closed). The goal of the control algorithm is to find an optimal radial network topology and optimal power
references for controllable generators and energy storage units that will minimize cumulative active power losses
while satisfying all system constraints. The validation of the developed algorithm is conducted in a case study of a reallife distribution grid in Croatia. Realistic simulations show that large loss reductions are feasible (more than 13%),
i.e., the developed control algorithm can contribute to significant savings for the grid operato
Electrical Power Distribution System Reconfiguration: Case Study of a Real-life Grid in Croatia
This paper describes the application of a nonlinear model predictive control algorithm to the problem of dynamic
reconfiguration of an electrical power distribution system with distributed generation and storage. Power distribution
systems usually operate in a radial topology despite being physically built as interconnected meshed networks. The
meshed structure of the network allows one to modify the network topology by changing the status of the line switches
(open/closed). The goal of the control algorithm is to find an optimal radial network topology and optimal power
references for controllable generators and energy storage units that will minimize cumulative active power losses
while satisfying all system constraints. The validation of the developed algorithm is conducted in a case study of a reallife distribution grid in Croatia. Realistic simulations show that large loss reductions are feasible (more than 13%),
i.e., the developed control algorithm can contribute to significant savings for the grid operato
Shift factor-based SCOPF topology control MIP formulations with substation configurations
Topology control (TC) is an effective tool for managing congestion, contingency events, and overload control. The majority of TC research has focused on line and transformer switching. Substation reconfiguration is an additional TC action, which consists of opening or closing breakers not in series with lines or transformers. Some reconfiguration actions can be simpler to implement than branch opening, seen as a less invasive action. This paper introduces two formulations that incorporate substation reconfiguration with branch opening in a unified TC framework. The first method starts from a topology with all candidate breakers open, and breaker closing is emulated and optimized using virtual transactions. The second method takes the opposite approach, starting from a fully closed topology and optimizing breaker openings. We provide a theoretical framework for both methods and formulate security-constrained shift factor MIP TC formulations that incorporate both breaker and branch switching. By maintaining the shift factor formulation, we take advantage of its compactness, especially in the context of contingency constraints, and by focusing on reconfiguring substations, we hope to provide system operators additional flexibility in their TC decision processes. Simulation results on a subarea of PJM illustrate the application of the two formulations to realistic systems.The work was supported in part by the Advanced Research Projects Agency-Energy, U.S. Department of Energy, under Grant DE-AR0000223 and in part by the U.S. National Science Foundation Emerging Frontiers in Research and Innovation under Grant 1038230. Paper no. TPWRS-01497-2015. (DE-AR0000223 - Advanced Research Projects Agency-Energy, U.S. Department of Energy; 1038230 - U.S. National Science Foundation Emerging Frontiers in Research and Innovation)http://buprimo.hosted.exlibrisgroup.com/primo_library/libweb/action/openurl?date=2017&issue=2&isSerivcesPage=true&spage=1179&dscnt=2&url_ctx_fmt=null&vid=BU&volume=32&institution=bosu&issn=0885-8950&id=doi:10.1109/TPWRS.2016.2574324&dstmp=1522778516872&fromLogin=truePublished versio
Design, Implementation, and Evaluation of a Distributed Real-Time Kernel for Distributed Robotics (Dissertation Proposal)
Modern robotics applications are becoming more complex due to greater numbers of sensors and actuators. The control of such systems may require multiple processors to meet the computational demands and to support the physical topology of the sensors and actuators. A distributed real-time system is needed to perform the required communication and processing while meeting application-specified timing constraints.
We are designing and implementing a real-time kernel for distributed robotics applications. The kernel\u27s salient features are consistent, user-definable scheduling, explicit dynamic timing constraints, and a two-tiered interrupt approach. The kernel wi1l be evaluated by implementing a two-arm robot control example. Its goal is to locate and manipulate cylindrical objects with spillable contents. Using the application and the kernel, we will investigate the effects of time granularity, network type and protocol, and the handling of external events using interrupts versus polling. Our research will enhance understanding of real-time kernels for distributed robotics control
Generalized Proportional Allocation Policies for Robust Control of Dynamical Flow Networks
We study a robust control problem for dynamical flow networks. In the
considered dynamical models, traffic flows along the links of a transportation
network --modeled as a capacited multigraph-- and queues up at the nodes,
whereby control policies determine which incoming queues at a node are to be
allocated service simultaneously, within some predetermined scheduling
constraints. We first prove a fundamental performance limitation by showing
that for a dynamical flow network to be stabilizable by some control policy it
is necessary that the exogenous inflows belong to a certain stability region,
that is determined by the network topology, link capacities, and scheduling
constraints. Then, we introduce a family of distributed controls, referred to
as Generalized Proportional Allocation (GPA) policies, and prove that they
stabilize a dynamical transportation network whenever the exogenous inflows
belong to such stability region. The proposed GPA control policies are
decentralized and fully scalable as they rely on local feedback information
only. Differently from previously studied maximally stabilizing control
strategies, the GPA control policies do not require any global information
about the network topology, the exogenous inflows, or the routing, which makes
them robust to demand variations and unpredicted changes in the link capacities
or the routing decisions. Moreover, the proposed GPA control policies also take
into account the overhead time while switching between services. Our
theoretical results find one application in the control of urban traffic
networks with signalized intersections, where vehicles have to queue up at
junctions and the traffic signal controls determine the green light allocation
to the different incoming lanes
A Systematic Approach to Constructing Incremental Topology Control Algorithms Using Graph Transformation
Communication networks form the backbone of our society. Topology control
algorithms optimize the topology of such communication networks. Due to the
importance of communication networks, a topology control algorithm should
guarantee certain required consistency properties (e.g., connectivity of the
topology), while achieving desired optimization properties (e.g., a bounded
number of neighbors). Real-world topologies are dynamic (e.g., because nodes
join, leave, or move within the network), which requires topology control
algorithms to operate in an incremental way, i.e., based on the recently
introduced modifications of a topology. Visual programming and specification
languages are a proven means for specifying the structure as well as
consistency and optimization properties of topologies. In this paper, we
present a novel methodology, based on a visual graph transformation and graph
constraint language, for developing incremental topology control algorithms
that are guaranteed to fulfill a set of specified consistency and optimization
constraints. More specifically, we model the possible modifications of a
topology control algorithm and the environment using graph transformation
rules, and we describe consistency and optimization properties using graph
constraints. On this basis, we apply and extend a well-known constructive
approach to derive refined graph transformation rules that preserve these graph
constraints. We apply our methodology to re-engineer an established topology
control algorithm, kTC, and evaluate it in a network simulation study to show
the practical applicability of our approachComment: This document corresponds to the accepted manuscript of the
referenced journal articl
A Systematic Approach to Constructing Families of Incremental Topology Control Algorithms Using Graph Transformation
In the communication systems domain, constructing and maintaining network
topologies via topology control (TC) algorithms is an important cross-cutting
research area. Network topologies are usually modeled using attributed graphs
whose nodes and edges represent the network nodes and their interconnecting
links. A key requirement of TC algorithms is to fulfill certain consistency and
optimization properties to ensure a high quality of service. Still, few
attempts have been made to constructively integrate these properties into the
development process of TC algorithms. Furthermore, even though many TC
algorithms share substantial parts (such as structural patterns or tie-breaking
strategies), few works constructively leverage these commonalities and
differences of TC algorithms systematically. In previous work, we addressed the
constructive integration of consistency properties into the development
process. We outlined a constructive, model-driven methodology for designing
individual TC algorithms. Valid and high-quality topologies are characterized
using declarative graph constraints; TC algorithms are specified using
programmed graph transformation. We applied a well-known static analysis
technique to refine a given TC algorithm in a way that the resulting algorithm
preserves the specified graph constraints.
In this paper, we extend our constructive methodology by generalizing it to
support the specification of families of TC algorithms. To show the feasibility
of our approach, we reneging six existing TC algorithms and develop e-kTC, a
novel energy-efficient variant of the TC algorithm kTC. Finally, we evaluate a
subset of the specified TC algorithms using a new tool integration of the graph
transformation tool eMoflon and the Simonstrator network simulation framework.Comment: Corresponds to the accepted manuscrip
Optical Network Models and their Application to Software-Defined Network Management
Software-defined networking is finding its way into optical networks. Here,
it promises a simplification and unification of network management for optical
networks allowing automation of operational tasks despite the highly diverse
and vendor-specific commercial systems and the complexity and analog nature of
optical transmission. A fundamental component for software-defined optical
networking are common abstractions and interfaces. Currently, a number of
models for optical networks are available. They all claim to provide open and
vendor agnostic management of optical equipment. In this work, we survey and
compare the most important models and propose an intent interface for creating
virtual topologies that is integrated in the existing model ecosystem.Comment: Parts of the presented work has received funding from the European
Commission within the H2020 Research and Innovation Programme, under grant
agreeement n.645127, project ACIN
A holistic DC link architecture design method for multiphase Integrated Modular Motor Drives
This article describes a holistic DC link architecture design method that considers the end-application of the drive and its corresponding constraints e.g. the maximum battery ripple current for a battery-supplied inverter. Also, the levers that are available to comply with the design criteria are presented e.g. the use of interleaved carrier waves. This holistic approach will result in a feasible and performant Integrated Modular Motor Drive from an application point of view. Finally, a platform is presented that was developed for feasibility and performance assessment of various DC link architectures obtained from the holistic design approach. The platform comprises a fifteen phase integrable modular motor drive for an Axial Flux Permanent Magnet Synchronous Machine. It allows non-intrusive reconfiguration of the DC link architecture and implementation of various control strategies and interleaved PWM schemes
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