30 research outputs found
A Generalized Index for Static Voltage Stability of Unbalanced Polyphase Power Systems including Th\'evenin Equivalents and Polynomial Models
This paper proposes a Voltage Stability Index (VSI) suitable for unbalanced
polyphase power systems. To this end, the grid is represented by a polyphase
multiport network model (i.e., compound hybrid parameters), and the aggregate
behavior of the devices in each node by Th\'evenin Equivalents (TEs) and
Polynomial Models (PMs), respectively. The proposed VSI is a generalization of
the known L-index, which is achieved through the use of compound electrical
parameters, and the incorporation of TEs and PMs into its formal definition.
Notably, the proposed VSI can handle unbalanced polyphase power systems,
explicitly accounts for voltage-dependent behavior (represented by PMs), and is
computationally inexpensive. These features are valuable for the operation of
both transmission and distribution systems. Specifically, the ability to handle
the unbalanced polyphase case is of particular value for distribution systems.
In this context, it is proven that the compound hybrid parameters required for
the calculation of the VSI do exist under practical conditions (i.e., for lossy
grids). The proposed VSI is validated against state-of-the-art methods for
voltage stability assessment using a benchmark system which is based on the
IEEE 34-node feeder
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
Distributed Optimal Frequency Control Considering a Nonlinear Network-Preserving Model
This paper addresses the distributed optimal frequency control of power
systems considering a network-preserving model with nonlinear power flows and
excitation voltage dynamics. Salient features of the proposed distributed
control strategy are fourfold: i) nonlinearity is considered to cope with large
disturbances; ii) only a part of generators are controllable; iii) no load
measurement is required; iv) communication connectivity is required only for
the controllable generators. To this end, benefiting from the concept of
'virtual load demand', we first design the distributed controller for the
controllable generators by leveraging the primal-dual decomposition technique.
We then propose a method to estimate the virtual load demand of each
controllable generator based on local frequencies. We derive incremental
passivity conditions for the uncontrollable generators. Finally, we prove that
the closed-loop system is asymptotically stable and its equilibrium attains the
optimal solution to the associated economic dispatch problem. Simulations,
including small and large-disturbance scenarios, are carried on the New England
system, demonstrating the effectiveness of our design
Contraction and Robustness of Continuous Time Primal-Dual Dynamics
The Primal-Dual (PD) algorithm is widely used in convex optimization to
determine saddle points. While the stability of the PD algorithm can be easily
guaranteed, strict contraction is nontrivial to establish in most cases. This
work focuses on continuous, possibly non-autonomous PD dynamics arising in a
network context, in distributed optimization, or in systems with multiple
time-scales. We show that the PD algorithm is indeed strictly contracting in
specific metrics and analyze its robustness establishing stability and
performance guarantees for different approximate PD systems. We derive
estimates for the performance of multiple time-scale multi-layer optimization
systems, and illustrate our results on a primal-dual representation of the
Automatic Generation Control of power systems.Comment: 6 pages, 1 figures, published on LCSS and CDC 201
Robust Decentralized Secondary Frequency Control in Power Systems: Merits and Trade-Offs
Frequency restoration in power systems is conventionally performed by
broadcasting a centralized signal to local controllers. As a result of the
energy transition, technological advances, and the scientific interest in
distributed control and optimization methods, a plethora of distributed
frequency control strategies have been proposed recently that rely on
communication amongst local controllers.
In this paper we propose a fully decentralized leaky integral controller for
frequency restoration that is derived from a classic lag element. We study
steady-state, asymptotic optimality, nominal stability, input-to-state
stability, noise rejection, transient performance, and robustness properties of
this controller in closed loop with a nonlinear and multivariable power system
model. We demonstrate that the leaky integral controller can strike an
acceptable trade-off between performance and robustness as well as between
asymptotic disturbance rejection and transient convergence rate by tuning its
DC gain and time constant. We compare our findings to conventional
decentralized integral control and distributed-averaging-based integral control
in theory and simulations