2,156 research outputs found
Paradigm and Paradox in Topology Control of Power Grids
Corrective Transmission Switching can be used by the grid operator to relieve
line overloading and voltage violations, improve system reliability, and reduce
system losses. Power grid optimization by means of line switching is typically
formulated as a mixed integer programming problem (MIP). Such problems are
known to be computationally intractable, and accordingly, a number of heuristic
approaches to grid topology reconfiguration have been proposed in the power
systems literature. By means of some low order examples (3-bus systems), it is
shown that within a reasonably large class of greedy heuristics, none can be
found that perform better than the others across all grid topologies. Despite
this cautionary tale, statistical evidence based on a large number of
simulations using using IEEE 118- bus systems indicates that among three
heuristics, a globally greedy heuristic is the most computationally intensive,
but has the best chance of reducing generation costs while enforcing N-1
connectivity. It is argued that, among all iterative methods, the locally
optimal switches at each stage have a better chance in not only approximating a
global optimal solution but also greatly limiting the number of lines that are
switched
Paradigm and paradox in topology control of power grids
Corrective Transmission Switching can be used by the grid operator to relieve line overloading and voltage violations, improve system reliability, and reduce system losses. Power grid optimization by means of line switching is typically formulated as a mixed integer programming problem (MIP). Such problems are known to be computationally intractable, and accordingly, a number of heuristic approaches to grid topology reconfiguration have been proposed in the power systems literature. By means of some low order examples (3-bus systems), it is shown that within a reasonably large class of “greedy” heuristics, none can be found that perform better than the others across all grid topologies. Despite this cautionary tale, statistical evidence based on a large number of simulations using IEEE 118-bus systems indicates that among three heuristics, a globally greedy heuristic is the most computationally intensive, but has the best chance of reducing generation costs while enforcing N-1 connectivity. It is argued that, among all iterative methods, the locally optimal switches at each stage have a better chance in not only approximating a global optimal solution but also greatly limiting the number of lines that are switched.First author draf
Taming Instabilities in Power Grid Networks by Decentralized Control
Renewables will soon dominate energy production in our electric power system.
And yet, how to integrate renewable energy into the grid and the market is
still a subject of major debate. Decentral Smart Grid Control (DSGC) was
recently proposed as a robust and decentralized approach to balance supply and
demand and to guarantee a grid operation that is both economically and
dynamically feasible. Here, we analyze the impact of network topology by
assessing the stability of essential network motifs using both linear stability
analysis and basin volume for delay systems. Our results indicate that if
frequency measurements are averaged over sufficiently large time intervals,
DSGC enhances the stability of extended power grid systems. We further
investigate whether DSGC supports centralized and/or decentralized power
production and find it to be applicable to both. However, our results on
cycle-like systems suggest that DSGC favors systems with decentralized
production. Here, lower line capacities and lower averaging times are required
compared to those with centralized production.Comment: 21 pages, 6 figures This is a pre-print of a manuscript submitted to
The European Physical Journal. The final publication is available at Springer
via http://dx.doi.org/10.1140/epjst/e2015-50136-
Models for the modern power grid
This article reviews different kinds of models for the electric power grid
that can be used to understand the modern power system, the smart grid. From
the physical network to abstract energy markets, we identify in the literature
different aspects that co-determine the spatio-temporal multilayer dynamics of
power system. We start our review by showing how the generation, transmission
and distribution characteristics of the traditional power grids are already
subject to complex behaviour appearing as a result of the the interplay between
dynamics of the nodes and topology, namely synchronisation and cascade effects.
When dealing with smart grids, the system complexity increases even more: on
top of the physical network of power lines and controllable sources of
electricity, the modernisation brings information networks, renewable
intermittent generation, market liberalisation, prosumers, among other aspects.
In this case, we forecast a dynamical co-evolution of the smart grid and other
kind of networked systems that cannot be understood isolated. This review
compiles recent results that model electric power grids as complex systems,
going beyond pure technological aspects. From this perspective, we then
indicate possible ways to incorporate the diverse co-evolving systems into the
smart grid model using, for example, network theory and multi-agent simulation.Comment: Submitted to EPJ-ST Power Grids, May 201
Paradigm and paradox in power networks
Well known in the theory of network flows, Braess paradox states that adding path(s) to a congested road network may increase overall journey time. In transportation networks, the phenomenon results from selfish routing. In power systems, an analogous increase in congestion can arise as a consequence of Kirchhoff's laws, suggesting opportunities to optimize grid topology.
The thesis starts with the discussion of Braess-like congestion phenomena in linear circuits. We prove that adding electrical path(s) always increases congestion in networks powered by voltage sources, while the opposite in networks driven by current sources. Although such predictability is not present in networks controlled by a mixture of voltage and current sources, our results offer a clean decomposition that completely separates the effect of current sources and voltage sources on total loss. The culmination of this research is a set of four equivalent methods of computing I^2R loss in mixed-source networks.
We go on to explore network decomposition in combination with greedy sequential line switching heuristics to address the NP-hardness of power grid topology control. By means of some low order examples, it is shown that within a reasonably large class of greedy heuristics, none can be found that perform better than the others across all grid topologies. Despite this cautionary tale, statistical evidence indicates that, among three most representative heuristics, the global greedy heuristic is most computationally intensive but has the best chance of reducing generation cost while enforcing connectivity.
The final part of the thesis presents a new approach to grid decomposition using vertex cut sets. We show that each vertex cut set and corresponding grid decomposition establishes a natural upper bound on the interactions between subgrids as nodal injections are regulated within each. Using such decomposition, it becomes possible to isolate congestion effects to a relatively small subgrid. A fast grid decomposition heuristic based on vertex cut sets and locational marginal prices is then proposed and studied through simulations on IEEE 118-bus system. On average, the computational cost is significantly reduced and the generation cost saving is similar to what is obtained with a global greedy algorithm
Power Grid Decomposition Based on Vertex Cut Sets and Its Applications to Topology Control and Power Trading
It is well known that the reserves/redundancies built into the transmission
grid in order to address a variety of contingencies over a long planning
horizon may, in the short run, cause economic dispatch inefficiency.
Accordingly, power grid optimization by means of short term line switching has
been proposed and is typically formulated as a mixed integer programming
problem by treating the state of the transmission lines as a binary decision
variable, i.e. in-service or out-of-service, in the optimal power flow problem.
To handle the combinatorial explosion, a number of heuristic approaches to grid
topology reconfiguration have been proposed in the literature. This paper
extends our recent results on the iterative heuristics and proposes a fast grid
decomposition algorithm based on vertex cut sets with the purpose of further
reducing the computational cost. The paper concludes with a discussion of the
possible relationship between vertex cut sets in transmission networks and
power trading
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