81 research outputs found
Topics in Electromobility and Related Applications
In this thesis, we mainly discuss four topics on Electric Vehicles (EVs) in the context of
smart grid and smart transportation systems.
The first topic focuses on investigating the impacts of different EV charging strategies on
the grid. In Chapter 3, we present a mathematical framework for formulating different EV
charging problems and investigate a range of typical EV charging strategies with respect to
different actors in the power system. Using this framework, we compare the performances of
all charging strategies on a common power system simulation testbed, highlighting in each
case positive and negative characteristics.
The second topic is concerned with the applications of EVs with Vehicle-to-Grid (V2G)
capabilities. In Chapter 4, we apply certain ideas from cooperative control techniques to
two V2G applications in different scenarios. In the first scenario, we harness the power
of V2G technologies to reduce current imbalance in a three-phase power network. In the
second scenario, we design a fair V2G programme to optimally determine the power dispatch
from EVs in a microgrid scenario. The effectiveness of the proposed algorithms are verified
through a variety of simulation studies.
The third topic discusses an optimal distributed energy management strategy for power
generation in a microgrid scenario. In Chapter 5, we adapt the synchronised version of the
Additive-Increase-Multiplicative-Decrease (AIMD) algorithms to minimise a cost utility
function related to the power generation costs of distributed resources. We investigate the
AIMD based strategy through simulation studies and we illustrate that the performance of
the proposed method is very close to the full communication centralised case. Finally, we
show that this idea can be easily extended to another application including thermal balancing
requirements.
The last topic focuses on a new design of the Speed Advisory System (SAS) for optimising
both conventional and electric vehicles networks. In Chapter 6, we demonstrate that, by
using simple ideas, one can design an effective SAS for electric vehicles to minimise group
energy consumption in a distributed and privacy-aware manner; Matlab simulation are give
to illustrate the effectiveness of this approach. Further, we extend this idea to conventional
vehicles in Chapter 7 and we show that by using some of the ideas introduced in Chapter
6, group emissions of conventional vehicles can also be minimised under the same SAS
framework. SUMO simulation and Hardware-In-the-Loop (HIL) tests involving real vehicles
are given to illustrate user acceptability and ease of deployment.
Finally, note that many applications in this thesis are based on the theories of a class
of nonlinear iterative feedback systems. For completeness, we present a rigorous proof on
global convergence of consensus of such systems in Chapter 2
Smart Procurement of Naturally Generated Energy (SPONGE) for Plug-in Hybrid Electric Buses
We discuss a recently introduced ECO-driving concept known as SPONGE in the
context of Plug-in Hybrid Electric Buses (PHEB)'s.Examples are given to
illustrate the benefits of this approach to ECO-driving. Finally, distributed
algorithms to realise SPONGE are discussed, paying attention to the privacy
implications of the underlying optimisation problems.Comment: This paper is recently submitted to the IEEE Transactions on
Automation Science and Engineerin
On Money as a Means of Coordination between Network Packets
In this work, we apply a common economic tool, namely money, to coordinate
network packets. In particular, we present a network economy, called
PacketEconomy, where each flow is modeled as a population of rational network
packets, and these packets can self-regulate their access to network resources
by mutually trading their positions in router queues. Every packet of the
economy has its price, and this price determines if and when the packet will
agree to buy or sell a better position. We consider a corresponding Markov
model of trade and show that there are Nash equilibria (NE) where queue
positions and money are exchanged directly between the network packets. This
simple approach, interestingly, delivers improvements even when fiat money is
used. We present theoretical arguments and experimental results to support our
claims
Some simple but challenging Markov processes
In this note, we present few examples of Piecewise Deterministic Markov
Processes and their long time behavior. They share two important features: they
are related to concrete models (in biology, networks, chemistry,. . .) and they
are mathematically rich. Their math-ematical study relies on coupling method,
spectral decomposition, PDE technics, functional inequalities. We also relate
these simple examples to recent and open problems
Plug-and-Play Distributed Algorithms for Optimized Power Generation in a Microgrid
This paper introduces distributed algorithms that
share the power generation task in an optimized fashion among
the several Distributed Energy Resources (DERs) within a
microgrid. We borrow certain concepts from communication network
theory, namely Additive-Increase-Multiplicative-Decrease
(AIMD) algorithms, which are known to be convenient in terms
of communication requirements and network efficiency.We adapt
the synchronized version of AIMD to minimize a cost utility
function of interest in the framework of smart grids. We then
implement the AIMD utility optimisation strategies in a realistic
power network simulation in Matlab-OpenDSS environment, and
we show that the performance is very close to the full-communication
centralized case
Router-based algorithms for improving internet quality of service.
We begin this thesis by generalizing some results related to a recently proposed positive system model of TCP congestion control algorithms. Then, motivated by a mean ¯eld analysis of the positive system model, a novel, stateless, queue management scheme is designed: Multi-Level Comparisons with index l (MLC(l)). In the limit, MLC(l) enforces max-min fairness in a network of TCP flows.
We go further, showing that counting past drops at a congested link provides su±cient information to enforce max-min fairness among long-lived flows and to reduce the flow completion times of short-lived flows. Analytical models are presented, and the accuracy of predictions are validated by packet level ns2 simulations.
We then move our attention to e±cient measurement and monitoring techniques. A small active counter architecture is presented that addresses the problem of accurate approximation of statistics counter values at very-high speeds that can be both updated and estimated on a per-packet basis. These algorithms are necessary in the design of router-based flow control algorithms since on-chip
Static RAM (SRAM) currently is a scarce resource, and being economical with its usage is an important task. A highly scalable method for heavy-hitter identifcation that uses our small active counters architecture is developed based on heuristic argument. Its performance is compared to several state-of-the-art algorithms and shown to out-perform them.
In the last part of the thesis we discuss the delay-utilization tradeoff in the congested Internet links.
While several groups of authors have recently analyzed this tradeoff, the lack of realistic assumption in their models and the extreme complexity in estimation of model parameters, reduces their applicability at real Internet links. We propose an adaptive scheme that regulates the available queue space to keep utilization at desired, high, level. As a consequence, in large-number-of-users regimes, sacrifcing 1-2% of bandwidth can result in queueing delays that are an order of magnitude smaller than in the standard BDP-bu®ering case. We go further and introduce an optimization framework for describing the problem of interest and propose an online algorithm for solving it
Router-based algorithms for improving internet quality of service.
We begin this thesis by generalizing some results related to a recently proposed positive system model of TCP congestion control algorithms. Then, motivated by a mean ¯eld analysis of the positive system model, a novel, stateless, queue management scheme is designed: Multi-Level Comparisons with index l (MLC(l)). In the limit, MLC(l) enforces max-min fairness in a network of TCP flows.
We go further, showing that counting past drops at a congested link provides su±cient information to enforce max-min fairness among long-lived flows and to reduce the flow completion times of short-lived flows. Analytical models are presented, and the accuracy of predictions are validated by packet level ns2 simulations.
We then move our attention to e±cient measurement and monitoring techniques. A small active counter architecture is presented that addresses the problem of accurate approximation of statistics counter values at very-high speeds that can be both updated and estimated on a per-packet basis. These algorithms are necessary in the design of router-based flow control algorithms since on-chip
Static RAM (SRAM) currently is a scarce resource, and being economical with its usage is an important task. A highly scalable method for heavy-hitter identifcation that uses our small active counters architecture is developed based on heuristic argument. Its performance is compared to several state-of-the-art algorithms and shown to out-perform them.
In the last part of the thesis we discuss the delay-utilization tradeoff in the congested Internet links.
While several groups of authors have recently analyzed this tradeoff, the lack of realistic assumption in their models and the extreme complexity in estimation of model parameters, reduces their applicability at real Internet links. We propose an adaptive scheme that regulates the available queue space to keep utilization at desired, high, level. As a consequence, in large-number-of-users regimes, sacrifcing 1-2% of bandwidth can result in queueing delays that are an order of magnitude smaller than in the standard BDP-bu®ering case. We go further and introduce an optimization framework for describing the problem of interest and propose an online algorithm for solving it
Development and application of techniques for predicting and analysing phonon-derived materials properties
The thermodynamic properties of materials are of great interest for both scientists and engineers. A large contribution to many properties stems from the vibrational motion of the atoms in the material. An understanding of the dynamics of the vibrating atoms is therefore important for many other areas as well, including, e.g., electronic and optical properties. Since many materials of particular technological interest are crystalline, the vibrations can be studied in the framework of lattice dynamics. One of the main challenges in lattice dynamics is to acquire the force constants that describe the atomic interactions. Using crystal symmetries it is possible to reduce and cast this problem to a linear regression problem. This approach has been implemented in the present work in the hiphive package. The force constants (an interatomic potential) can be fitted to forces obtained from, e.g., density functional theory calculations.Although the problem of linear regression is well studied from a theoretical point of view the number of unknown coefficients in the force constant expansion is typically very large. Obtaining good models from limited data is possible via regularized regression, which has been successfully applied in many areas of physics. However, how well these techniques work in general for practical problems involving force constants is not well understood. By interfacing with the scikit-learn package, here, the hiphive package has been used to explore how well these techniques work in practice. It is found that many concepts from machine (or statistical) learning can be useful in order to predict macroscopic properties and quantify model uncertainties.Moving beyond the domain of pure lattice dynamics we also studied the thermal conductivity of rotationally disordered layered materials, which feature weak van-der-Waals interactions between the layers. These structures exhibit a remarkably low through-plane thermal conductivity and their dynamic properties can be described as one-dimensional glasses (a property worth further studies). By performing molecular dynamics simulations on state-of-the-art graphical processing units using the Green-Kubo formalism excellent agreement with experiments could be achieved
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