3,262 research outputs found
On security and privacy of consensus-based protocols in blockchain and smart grid
In recent times, distributed consensus protocols have received widespread attention in the area of blockchain and smart grid. Consensus algorithms aim to solve an agreement problem among a set of nodes in a distributed environment. Participants in a blockchain use consensus algorithms to agree on data blocks containing an ordered set of transactions. Similarly, agents in the smart grid employ consensus to agree on specific values (e.g., energy output, market-clearing price, control parameters) in distributed energy management protocols.
This thesis focuses on the security and privacy aspects of a few popular consensus-based protocols in blockchain and smart grid. In the blockchain area, we analyze the consensus protocol of one of the most popular payment systems: Ripple. We show how the parameters chosen by the Ripple designers do not prevent the occurrence of forks in the system. Furthermore, we provide the conditions to prevent any fork in the Ripple network. In the smart grid area, we discuss the privacy issues in the Economic Dispatch (ED) optimization problem and some of its recent solutions using distributed consensus-based approaches. We analyze two state of the art consensus-based ED protocols from Yang et al. (2013) and Binetti et al. (2014). We show how these protocols leak private information about the participants. We propose privacy-preserving versions of these consensus-based ED protocols. In some cases, we also improve upon the communication cost
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
Mission-Critical Communications from LMR to 5G: a Technology Assessment approach for Smart City scenarios
Radiocommunication networks are one of the main support tools of agencies that carry out
actions in Public Protection & Disaster Relief (PPDR), and it is necessary to update these
communications technologies from narrowband to broadband and integrated to information
technologies to have an effective action before society. Understanding that this problem
includes, besides the technical aspects, issues related to the social context to which these
systems are inserted, this study aims to construct scenarios, using several sources of
information, that helps the managers of the PPDR agencies in the technological decisionmaking
process of the Digital Transformation of Mission-Critical Communication considering
Smart City scenarios, guided by the methods and approaches of Technological Assessment
(TA).As redes de radiocomunicações são uma das principais ferramentas de apoio dos órgãos que
realizam ações de Proteção Pública e Socorro em desastres, sendo necessário atualizar essas
tecnologias de comunicação de banda estreita para banda larga, e integra- las às tecnologias
de informação, para se ter uma atuação efetiva perante a sociedade . Entendendo que esse
problema inclui, além dos aspectos técnicos, questões relacionadas ao contexto social ao qual
esses sistemas estão inseridos, este estudo tem por objetivo a construção de cenários,
utilizando diversas fontes de informação que auxiliem os gestores destas agências na tomada
de decisão tecnológica que envolve a transformação digital da Comunicação de Missão Crítica
considerando cenários de Cidades Inteligentes, guiado pelos métodos e abordagens de
Avaliação Tecnológica (TA)
Smart Grid Communications: Overview of Research Challenges, Solutions, and Standardization Activities
Optimization of energy consumption in future intelligent energy networks (or
Smart Grids) will be based on grid-integrated near-real-time communications
between various grid elements in generation, transmission, distribution and
loads. This paper discusses some of the challenges and opportunities of
communications research in the areas of smart grid and smart metering. In
particular, we focus on some of the key communications challenges for realizing
interoperable and future-proof smart grid/metering networks, smart grid
security and privacy, and how some of the existing networking technologies can
be applied to energy management. Finally, we also discuss the coordinated
standardization efforts in Europe to harmonize communications standards and
protocols.Comment: To be published in IEEE Communications Surveys and Tutorial
On an Information and Control Architecture for Future Electric Energy Systems
This paper presents considerations towards an information and control
architecture for future electric energy systems driven by massive changes
resulting from the societal goals of decarbonization and electrification. This
paper describes the new requirements and challenges of an extended information
and control architecture that need to be addressed for continued reliable
delivery of electricity. It identifies several new actionable information and
control loops, along with their spatial and temporal scales of operation, which
can together meet the needs of future grids and enable deep decarbonization of
the electricity sector. The present architecture of electric power grids
designed in a different era is thereby extensible to allow the incorporation of
increased renewables and other emerging electric loads.Comment: This paper is accepted, to appear in the Proceedings of the IEE
Techniques, Taxonomy, and Challenges of Privacy Protection in the Smart Grid
As the ease with which any data are collected and transmitted increases,
more privacy concerns arise leading to an increasing need to protect and preserve
it. Much of the recent high-profile coverage of data mishandling and public mis-
leadings about various aspects of privacy exasperates the severity. The Smart Grid
(SG) is no exception with its key characteristics aimed at supporting bi-directional
information flow between the consumer of electricity and the utility provider. What
makes the SG privacy even more challenging and intriguing is the fact that the very
success of the initiative depends on the expanded data generation, sharing, and pro-
cessing. In particular, the deployment of smart meters whereby energy consumption
information can easily be collected leads to major public hesitations about the tech-
nology. Thus, to successfully transition from the traditional Power Grid to the SG
of the future, public concerns about their privacy must be explicitly addressed and
fears must be allayed. Along these lines, this chapter introduces some of the privacy
issues and problems in the domain of the SG, develops a unique taxonomy of some
of the recently proposed privacy protecting solutions as well as some if the future
privacy challenges that must be addressed in the future.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111644/1/Uludag2015SG-privacy_book-chapter.pd
Hierarchical Coordinated Fast Frequency Control using Inverter-Based Resources for Next-Generation Power Grids
The proportion of inverter-connected renewable energy resources (RES) in the grid is
expanding, primarily displacing conventional synchronous generators. This shift significantly impacts the objective of maintaining grid stability and reliable operations. The increased penetration of RESs contributes to the variability of active power supply and
a decrease in the rotational inertia of the grid, resulting in faster system dynamics and larger, more frequent frequency events.
These emerging challenges could make traditional centralized frequency control strategies ineffective, necessitating the adoption of modern, high-bandwidth control schemes. In this thesis, we propose a novel hierarchical and coordinated real-time frequency control scheme. It leverages advancements in grid monitoring and communication infrastructure
to employ local, flexible inverter-based resources for promptly correcting power imbalances in the system. We solve two research problems that, when combined, yield a practical, real-time, next-generation frequency control scheme. This scheme blends localized control with high-bandwidth wide-area coordination.
For the first problem, we propose a layered architecture where control, estimation, and optimization tasks are efficiently aggregated and decentralized across the system. This layered control structure, comprising decentralized, distributed, and centralized assets, enables fast, localized control responses to local power imbalances, integrated with wide-
area coordination.
For the second problem, we propose a data-driven extension to the framework to enhance model flexibility. Achieving high accuracy in system models used for control design is a considerable challenge due to the increasing scale, complexity, and evolving dynamics of the power system. In our proposed approach, we leverage collected data to provide direct data-driven controller designs for fast frequency regulation.
The devised scheme ensures swift and effective frequency control for the bulk grid by accurately re-dispatching inverter-based resources (IBRs) to compensate for unmeasured net-load changes. These changes are computed in real-time using frequency and area tie power flow measurements, alongside collected historical data, thus eliminating reliance on proprietary power system models. Validated through detailed simulations under various scenarios such as load increase, generation trips, and three-phase faults, the scheme is practical, provides rapid, localized frequency control, safeguards data privacy, and eliminates
the need for system models of the increasingly complex power system
- …