7,428 research outputs found
Distributed Estimation of the Operating State of a Single-Bus DC MicroGrid without an External Communication Interface
We propose a decentralized Maximum Likelihood solution for estimating the
stochastic renewable power generation and demand in single bus Direct Current
(DC) MicroGrids (MGs), with high penetration of droop controlled power
electronic converters. The solution relies on the fact that the primary control
parameters are set in accordance with the local power generation status of the
generators. Therefore, the steady state voltage is inherently dependent on the
generation capacities and the load, through a non-linear parametric model,
which can be estimated. To have a well conditioned estimation problem, our
solution avoids the use of an external communication interface and utilizes
controlled voltage disturbances to perform distributed training. Using this
tool, we develop an efficient, decentralized Maximum Likelihood Estimator (MLE)
and formulate the sufficient condition for the existence of the globally
optimal solution. The numerical results illustrate the promising performance of
our MLE algorithm.Comment: Accepted to GlobalSIP 201
Representation of the German transmission grid for Renewable Energy Sources impact analysis
The increasing impact of fossil energy generation on the Earth ecological
balance is pointing to the need of a transition in power generation technology
towards the more clean and sustainable Renewable Energy Sources (RES). This
transition is leading to new paradigms and technologies useful for the
effective energy transmission and distribution, which take into account the RES
stochastic power output. In this scenario, the availability of up to date and
reliable datasets regarding topological and operative parameters of power
systems in presence of RES are needed, for both proposing and testing new
solutions. In this spirit, I present here a dataset regarding the German 380 KV
grid which contains fully DC Power Flow operative states of the grid in the
presence of various amounts of RES share, ranging from realistic up to 60\%,
which can be used as reference dataset for both steady state and dynamical
analysis.Comment: The dataset to which this paper refers can be found in: Mureddu, M.
(2016). Representation of the German transmission grid for Renewable Energy
Sources impact analysis.figshare.
http://doi.org/10.6084/m9.figshare.4233782.v
Consensus-based approach to peer-to-peer electricity markets with product differentiation
With the sustained deployment of distributed generation capacities and the
more proactive role of consumers, power systems and their operation are
drifting away from a conventional top-down hierarchical structure. Electricity
market structures, however, have not yet embraced that evolution. Respecting
the high-dimensional, distributed and dynamic nature of modern power systems
would translate to designing peer-to-peer markets or, at least, to using such
an underlying decentralized structure to enable a bottom-up approach to future
electricity markets. A peer-to-peer market structure based on a Multi-Bilateral
Economic Dispatch (MBED) formulation is introduced, allowing for
multi-bilateral trading with product differentiation, for instance based on
consumer preferences. A Relaxed Consensus+Innovation (RCI) approach is
described to solve the MBED in fully decentralized manner. A set of realistic
case studies and their analysis allow us showing that such peer-to-peer market
structures can effectively yield market outcomes that are different from
centralized market structures and optimal in terms of respecting consumers
preferences while maximizing social welfare. Additionally, the RCI solving
approach allows for a fully decentralized market clearing which converges with
a negligible optimality gap, with a limited amount of information being shared.Comment: Accepted for publication in IEEE Transactions on Power System
Stochastic Model for Power Grid Dynamics
We introduce a stochastic model that describes the quasi-static dynamics of
an electric transmission network under perturbations introduced by random load
fluctuations, random removing of system components from service, random repair
times for the failed components, and random response times to implement optimal
system corrections for removing line overloads in a damaged or stressed
transmission network. We use a linear approximation to the network flow
equations and apply linear programming techniques that optimize the dispatching
of generators and loads in order to eliminate the network overloads associated
with a damaged system. We also provide a simple model for the operator's
response to various contingency events that is not always optimal due to either
failure of the state estimation system or due to the incorrect subjective
assessment of the severity associated with these events. This further allows us
to use a game theoretic framework for casting the optimization of the
operator's response into the choice of the optimal strategy which minimizes the
operating cost. We use a simple strategy space which is the degree of tolerance
to line overloads and which is an automatic control (optimization) parameter
that can be adjusted to trade off automatic load shed without propagating
cascades versus reduced load shed and an increased risk of propagating
cascades. The tolerance parameter is chosen to describes a smooth transition
from a risk averse to a risk taken strategy...Comment: framework for a system-level analysis of the power grid from the
viewpoint of complex network
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