35 research outputs found
Assessing the effect of geographically correlated failures on interconnected power-communication networks
We study the reliability of power transmission networks under regional disasters. Initially, we quantify the effect of large-scale non-targeted disasters and their resulting cascade effects on power networks. We then model the dependence of data networks on the power systems and consider network reliability in this dependent network setting. Our novel approach provides a promising new direction for modeling and designing networks to lessen the effects of geographical disasters.National Science Foundation (U.S.). (grant CNS-1017800)National Science Foundation (U.S.). (grant CNS-0830961)United States. Defense Threat Reduction Agency (HDTRA-09-1-005 )United States. Defense Threat Reduction Agency (HDTRA-1-13-10021
Less is More: Real-time Failure Localization in Power Systems
Cascading failures in power systems exhibit non-local propagation patterns
which make the analysis and mitigation of failures difficult. In this work, we
propose a distributed control framework inspired by the recently proposed
concepts of unified controller and network tree-partition that offers strong
guarantees in both the mitigation and localization of cascading failures in
power systems. In this framework, the transmission network is partitioned into
several control areas which are connected in a tree structure, and the unified
controller is adopted by generators or controllable loads for fast timescale
disturbance response. After an initial failure, the proposed strategy always
prevents successive failures from happening, and regulates the system to the
desired steady state where the impact of initial failures are localized as much
as possible. For extreme failures that cannot be localized, the proposed
framework has a configurable design, that progressively involves and
coordinates more control areas for failure mitigation and, as a last resort,
imposes minimal load shedding. We compare the proposed control framework with
Automatic Generation Control (AGC) on the IEEE 118-bus test system. Simulation
results show that our novel framework greatly improves the system robustness in
terms of the N-1 security standard, and localizes the impact of initial
failures in majority of the load profiles that are examined. Moreover, the
proposed framework incurs significantly less load loss, if any, compared to
AGC, in all of our case studies
MILP formulation for controlled islanding of power networks
This paper presents a flexible optimization approach to the problem of intentionally forming islands in a power network. A mixed integer linear programming (MILP) formulation is given for the problem of deciding simultaneously on the boundaries of the islands and adjustments to generators, so as to minimize the expected load shed while ensuring no system constraints are violated. The solution of this problem is, within each island, balanced in load and generation and satisfies steady-state DC power flow equations and operating limits. Numerical tests on test networks up to 300 buses show the method is computationally efficient. A subsequent AC optimal load shedding optimization on the islanded network model provides a solution that satisfies AC power flow. Time-domain simulations using second-order models of system dynamics show that if penalties were included in the MILP to discourage disconnecting lines and generators with large flows or outputs, the actions of network splitting and load shedding did not lead to a loss of stability
An Implicit Optimization Approach for Survivable Network Design
We consider the problem of designing a network of minimum cost while
satisfying a prescribed survivability criterion. The survivability criterion
requires that a feasible flow must still exists (i.e. all demands can be
satisfied without violating arc capacities) even after the disruption of a
subset of the network's arcs. Specifically, we consider the case in which a
disruption (random or malicious) can destroy a subset of the arcs, with the
cost of the disruption not to exceed a disruption budget. This problem takes
the form of a tri-level, two-player game, in which the network operator designs
(or augments) the network, then the attacker launches a disruption that
destroys a subset of arcs, and then the network operator attempts to find a
feasible flow over the residual network. We first show how this can be modeled
as a two-stage stochastic program from the network operator's perspective, with
each of the exponential number of potential attacks considered as a disruption
scenario. We then reformulate this problem, via a Benders decomposition, to
consider the recourse decisions implicitly, greatly reducing the number of
variables but at the expense of an exponential increase in the number of
constraints. We next develop a cut-generation based algorithm. Rather than
\emph{explicitly} considering each disruption scenario to identify these
Benders cuts, however, we develop a bi-level program and corresponding
separation algorithm that enables us to \emph{implicitly} evaluate the
exponential set of disruption scenarios. Our computational results demonstrate
the efficacy of this approach
A Cycle-Based Formulation and Valid Inequalities for DC Power Transmission Problems with Switching
It is well-known that optimizing network topology by switching on and off
transmission lines improves the efficiency of power delivery in electrical
networks. In fact, the USA Energy Policy Act of 2005 (Section 1223) states that
the U.S. should "encourage, as appropriate, the deployment of advanced
transmission technologies" including "optimized transmission line
configurations". As such, many authors have studied the problem of determining
an optimal set of transmission lines to switch off to minimize the cost of
meeting a given power demand under the direct current (DC) model of power flow.
This problem is known in the literature as the Direct-Current Optimal
Transmission Switching Problem (DC-OTS). Most research on DC-OTS has focused on
heuristic algorithms for generating quality solutions or on the application of
DC-OTS to crucial operational and strategic problems such as contingency
correction, real-time dispatch, and transmission expansion. The mathematical
theory of the DC-OTS problem is less well-developed. In this work, we formally
establish that DC-OTS is NP-Hard, even if the power network is a
series-parallel graph with at most one load/demand pair. Inspired by Kirchoff's
Voltage Law, we give a cycle-based formulation for DC-OTS, and we use the new
formulation to build a cycle-induced relaxation. We characterize the convex
hull of the cycle-induced relaxation, and the characterization provides strong
valid inequalities that can be used in a cutting-plane approach to solve the
DC-OTS. We give details of a practical implementation, and we show promising
computational results on standard benchmark instances
An Integrated Approach for Failure Mitigation & Localization in Power Systems
The transmission grid is often comprised of several control areas that are
connected by multiple tie lines in a mesh structure for reliability. It is also
well-known that line failures can propagate non-locally and redundancy can
exacerbate cascading. In this paper, we propose an integrated approach to grid
reliability that (i) judiciously switches off a small number of tie lines so
that the control areas are connected in a tree structure; and (ii) leverages a
unified frequency control paradigm to provide congestion management in real
time. Even though the proposed topology reduces redundancy, the integration of
tree structure at regional level and real-time congestion management can
provide stronger guarantees on failure localization and mitigation. We
illustrate our approach on the IEEE 39-bus network and evaluate its performance
on the IEEE 118-bus, 179-bus, 200-bus and 240-bus networks with various network
congestion conditions. Simulations show that, compared with the traditional
approach, our approach not only prevents load shedding in more failure
scenarios, but also incurs smaller amounts of load loss in scenarios where load
shedding is inevitable. Moreover, generators under our approach adjust their
operations more actively and efficiently in a local manner.Comment: Accepted to the 21st Power Systems Computation Conference (PSCC 2020