2,969 research outputs found
Optimal Topology Design for Disturbance Minimization in Power Grids
The transient response of power grids to external disturbances influences
their stable operation. This paper studies the effect of topology in linear
time-invariant dynamics of different power grids. For a variety of objective
functions, a unified framework based on norm is presented to analyze the
robustness to ambient fluctuations. Such objectives include loss reduction,
weighted consensus of phase angle deviations, oscillations in nodal frequency,
and other graphical metrics. The framework is then used to study the problem of
optimal topology design for robust control goals of different grids. For radial
grids, the problem is shown as equivalent to the hard "optimum communication
spanning tree" problem in graph theory and a combinatorial topology
construction is presented with bounded approximation gap. Extended to loopy
(meshed) grids, a greedy topology design algorithm is discussed. The
performance of the topology design algorithms under multiple control objectives
are presented on both loopy and radial test grids. Overall, this paper analyzes
topology design algorithms on a broad class of control problems in power grid
by exploring their combinatorial and graphical properties.Comment: 6 pages, 3 figures, a version of this work will appear in ACC 201
Joint Frequency Regulation and Economic Dispatch Using Limited Communication
We study the performance of a decentralized integral control scheme for joint
power grid frequency regulation and economic dispatch. We show that by properly
designing the controller gains, after a power flow perturbation, the control
achieves near-optimal economic dispatch while recovering the nominal frequency,
without requiring any communication. We quantify the gap between the
controllable power generation cost under the decentralized control scheme and
the optimal cost, based on the DC power flow model. Moreover, we study the
tradeoff between the cost and the convergence time, by adjusting parameters of
the control scheme.
Communication between generators reduces the convergence time. We identify
key communication links whose failures have more significant impacts on the
performance of a distributed power grid control scheme that requires
information exchange between neighbors
Online Learning of Power Transmission Dynamics
We consider the problem of reconstructing the dynamic state matrix of
transmission power grids from time-stamped PMU measurements in the regime of
ambient fluctuations. Using a maximum likelihood based approach, we construct a
family of convex estimators that adapt to the structure of the problem
depending on the available prior information. The proposed method is fully
data-driven and does not assume any knowledge of system parameters. It can be
implemented in near real-time and requires a small amount of data. Our learning
algorithms can be used for model validation and calibration, and can also be
applied to related problems of system stability, detection of forced
oscillations, generation re-dispatch, as well as to the estimation of the
system state.Comment: 7 pages, 4 figure
Real-Time Local Volt/VAR Control Under External Disturbances with High PV Penetration
Volt/var control (VVC) of smart PV inverter is becoming one of the most
popular solutions to address the voltage challenges associated with high PV
penetration. This work focuses on the local droop VVC recommended by the grid
integration standards IEEE1547, rule21 and addresses their major challenges
i.e. appropriate parameters selection under changing conditions, and the
control being vulnerable to instability (or voltage oscillations) and
significant steady state error (SSE). This is achieved by proposing a two-layer
local real-time adaptive VVC that has two major features i.e. a) it is able to
ensure both low SSE and control stability simultaneously without compromising
either, and b) it dynamically adapts its parameters to ensure good performance
in a wide range of external disturbances such as sudden cloud cover, cloud
intermittency, and substation voltage changes. A theoretical analysis and
convergence proof of the proposed control is also discussed. The proposed
control is implementation friendly as it fits well within the integration
standard framework and depends only on the local bus information. The
performance is compared with the existing droop VVC methods in several
scenarios on a large unbalanced 3-phase feeder with detailed secondary side
modeling.Comment: IEEE Transactions on Smart Grid, 201
Smart Grid for the Smart City
Modern cities are embracing cutting-edge technologies to improve the services they offer to the citizens from traffic control to the reduction of greenhouse gases and energy provisioning. In this chapter, we look at the energy sector advocating how Information and Communication Technologies (ICT) and signal processing techniques can be integrated into next generation power grids for an increased effectiveness in terms of: electrical stability, distribution, improved communication security, energy production, and utilization. In particular, we deliberate about the use of these techniques within new demand response paradigms, where communities of prosumers (e.g., households, generating part of their electricity consumption) contribute to the satisfaction of the energy demand through load balancing and peak shaving. Our discussion also covers the use of big data analytics for demand response and serious games as a tool to promote energy-efficient behaviors from end users
Improving Grid Hosting Capacity and Inertia Response with High Penetration of Renewable Generation
To achieve a more sustainable supply of electricity, utilizing renewable energy resources is a promising solution. However, the inclusion of intermittent renewable energy resources in electric power systems, if not appropriately managed and controlled, will raise a new set of technical challenges in both voltage and frequency control and jeopardizes the reliability and stability of the power system, as one of the most critical infrastructures in the today’s world. This dissertation aims to answer how to achieve high penetration of renewable generations in the entire power system without jeopardizing its security and reliability. First, we tackle the data insufficiency in testing new methods and concepts in renewable generation integration and develop a toolkit to generate any number of synthetic power grids feathering the same properties of real power grids. Next, we focus on small-scale PV systems as the most growing renewable generation in distribution networks and develop a detailed impact assessment framework to examine its impacts on the system and provide installation scheme recommendations to improve the hosting capacity of PV systems in the distribution networks. Following, we examine smart homes with rooftop PV systems and propose a new demand side management algorithm to make the best use of distributed renewable energy. Finally, the findings in the aforementioned three parts have been incorporated to solve the challenge of inertia response and hosting capacity of renewables in transmission network
- …