413 research outputs found

    Novel Conceptual Architecture for the Next-Generation Electricity Markets to Enhance a Large Penetration of Renewable Energy

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    [EN] A transition to a sustainable energy system is essential. In this context, smart grids represent the future of power systems for efficiently integrating renewable energy sources and active consumer participation. Recently, different studies were performed that defined the conceptual architecture of power systems and their agents. However, these conceptual architectures do not overcome all issues for the development of new electricity markets. Thus, a novel conceptual architecture is proposed. The transactions of energy, operation services, and economic flows among the agents proposed are carefully analysed. In this regard, the results allow setting their activities' boundaries and state their relationships with electricity markets. The suitability of implementing local electricity markets is studied to enforce competition among distributed energy resources by unlocking all the potential that active consumers have. The proposed architecture is designed to offer flexibility and efficiency to the system thanks to a clearly defined way for the exploitation of flexible resources and distributed generation. This upgraded architecture hereby proposed establishes the characteristics of each agent in the forthcoming markets and studies to overcome the barriers to the large deployment of renewable energy sources.This work was supported by the Ministerio de Economia, Industria, y Competitividad (Spanish Government) under research project ENE-2016-78509-C3-1-P, and EU FEDER funds. The authors received funds from these grants for covering the costs to publish in open access. This work was also supported by the Spanish Ministry of Education under the scholarship FPU16/00962.Rodríguez-García, J.; Ribó-Pérez, DG.; Álvarez, C.; Peñalvo-López, E. (2019). Novel Conceptual Architecture for the Next-Generation Electricity Markets to Enhance a Large Penetration of Renewable Energy. 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    GNSS Related Threats to Power Grid Applications

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    As power grid environments are moving towards the smart grid vision of the future, the traditional schemes for power grid protection and control are making way for new applications. The advancements in this field have made the requirements for power grid’s time synchronization accuracy and precision considerably more demanding. So far, the signals provided by Global Navigation Satellite Systems have generally addressed the need for highly accurate and stable reference time in power grid applications. These signals however are highly susceptible to tampering as they are being transmitted. Since electrical power transmission and distribution are critical functions for any modern society, the risks and impacts affiliated with satellite-based time synchronization in power grids ought to be examined. This thesis aims to address the matter. The objective is to examine how Global Navigation Satellite Systems are utilized in the power grids, how different attacks would potentially be carried out by employing interference and disturbance to GNSS signals and receivers and how the potential threats can be mitigated. A major part of the research is done through literature review, and the core concepts and different implementations of Global Navigation Satellite Systems are firstly introduced. The literature review also involves the introduction of different power grid components and subsystems, that utilize Global Positioning System for time synchronization. Threat modeling techniques traditionally practiced in software development are applied to power grid components and subsystems to gain insight about the possible threats and their impacts. The threats recognized through this process are evaluated and potential techniques for mitigating the most notable threats are presented.Sähköverkot ovat siirtymässä kohti tulevaisuuden älykkäitä sähköverkkoja ja perinteiset sähköverkon suojaus- ja ohjausmenetelmät tekevät tilaa uusille sovelluksille. Alan kehitys on tehnyt aikasynkronoinnin tarkkuusvaatimuksista huomattavasti aikaisempaa vaativampia. Tarkka aikareferenssi sähköverkoissa on tähän saakka saavutettu satelliittinavigointijärjestelmien tarjoamien signaalien avulla. Nämä signaalit ovat kuitenkin erittäin alttiita erilaisille hyökkäyksille. Sähkönjakelujärjestelmät ovat kriittinen osa nykyaikaista yhteiskuntaa ja riskejä sekä seuraamuksia, jotka liittyvät satelliittipohjaisten aikasynkronointimenetelmien hyödyntämiseen sähköverkoissa, tulisi tarkastella. Tämä tutkielma pyrkii vastaamaan tähän tarpeeseen. Päämääränä on selvittää, miten satelliittinavigointijärjestelmiä hyödynnetään sähköverkoissa, kuinka erilaisia hyökkäyksiä voidaan toteuttaa satelliittisignaaleja häiritsemällä ja satelliittisignaalivastaanottimia harhauttamalla ja kuinka näiden muodostamia uhkia voidaan lieventää. Valtaosa tästä tutkimuksesta on toteutettu kirjallisuuskatselmoinnin pohjalta. Työ kattaa satelliittinavigointijärjestelmien perusteet ja esittelee erilaisia tapoja, kuinka satelliittisignaaleja hyödynnetään sähköverkoissa erityisesti aikasynkronoinnin näkökulmasta. Työssä hyödynnettiin perinteisesti ohjelmistokehityksessä käytettyjä uhkamallinnusmenetelmiä mahdollisten uhkien ja seurausten analysointiin. Lopputuloksena esitellään riskiarviot uhkamallinnuksen pohjalta tunnistetuista uhkista, sekä esitellään erilaisia menettelytapoja uhkien lieventämiseksi

    Power simulator upgrade for smart grid algorithm development and testing

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    This thesis describes the conversion of WVU\u27s analog power simulator into a micro-grid of the future test bed by installing digital relays and intelligent electronic switches. The simulator is a hardware representation of the grid which contains traditional hardware, both digital and analog as well as the recent addition of highly connected, via Ethernet and potentially wireless communication, smart switching and monitoring devices. These new devices were chosen specifically for their cyber security capability to explore that facet of smart grid development. It is important to note that this simulator is a hardware implementation and as such is capable of testing smart grid ideas in the most realistic setting available without affecting real customers. This simulator also has the potential to have renewable resources like wind and solar as well as fuel cell and battery storage distributed resources tied in to test smart grid adaptability to these next generation ideas.;New digital relays were installed. Micro controller units and energy meter integrated circuits were investigated based on the desire to provide many modes of communication and as much processing power as was available in a small package. Solid state switches were designed and implemented for speed, compactness and reduced power consumption

    Operational moving target defences for improved power system cyber-physical security

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    In this work, we examine how Moving Target Defences (MTDs) can be enhanced to circumvent intelligent false data injection (FDI) attacks against power systems. Initially, we show how, by implementing state-of-the-art topology learning techniques, we can commit full-knowledge-equivalent FDI attacks against static power systems with no prior system knowledge. We go on to explore how naive applications of topology change, as MTDs, can be countered by unsupervised learning-based FDI attacks and how MTDs can be combined with physical watermarking to enhance system resilience. A novel intelligent attack, which incorporates dimensionality reduction and density-based spatial clustering, is developed and shown to be effective in maintaining stealth in the presence of traditional MTD strategies. In resisting this new type of attack, a novel implementation of MTD is suggested. The implementation uses physical watermarking to drive detection of traditional and intelligent FDI attacks while remaining hidden to the attackers. Following this, we outline a cyber-physical authentication strategy for use against FDI attacks. An event-triggered MTD protocol is proposed at the physical layer to complement cyber-side enhancements. This protocol applies a distributed anomaly detection scheme based on Holt-Winters seasonal forecasting in combination with MTD implemented via inductance perturbation. To conclude, we developed a cyber-physical risk assessment framework for FDI attacks. Our assessment criteria combines a weighted graph model of the networks cyber vulnerabilities with a centralised residual-based assessment of the physical system with respect to MTD. This combined approach provides a cyber-physical assessment of FDI attacks which incorporates both the likelihood of intrusion and the prospect of an attacker making stealthy change once intruded.Open Acces

    Blockchain in Energy Communities, A proof of concept

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    This report aims at exploring the use of the distributed ledger paradigm to incentive the participation of the citizen to a truly free, open and interoperable energy market, producing a feasibility study and a first demo testbed, taking also into consideration privacy, cybersecurity and big-data issues of the smart-home in the Energy market context. This study is intended to support point 4.1, 4.2 and 4.3 of the DSM (COM(2015)192) and point 2.2 of the Energy Union package (COM(2015)80.JRC.E.3-Cyber and Digital Citizens' Securit

    An Energy Aware and Secure MAC Protocol for Tackling Denial of Sleep Attacks in Wireless Sensor Networks

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    Wireless sensor networks which form part of the core for the Internet of Things consist of resource constrained sensors that are usually powered by batteries. Therefore, careful energy awareness is essential when working with these devices. Indeed,the introduction of security techniques such as authentication and encryption, to ensure confidentiality and integrity of data, can place higher energy load on the sensors. However, the absence of security protection c ould give room for energy drain attacks such as denial of sleep attacks which have a higher negative impact on the life span ( of the sensors than the presence of security features. This thesis, therefore, focuses on tackling denial of sleep attacks from two perspectives A security perspective and an energy efficiency perspective. The security perspective involves evaluating and ranking a number of security based techniques to curbing denial of sleep attacks. The energy efficiency perspective, on the other hand, involves exploring duty cycling and simulating three Media Access Control ( protocols Sensor MAC, Timeout MAC andTunableMAC under different network sizes and measuring different parameters such as the Received Signal Strength RSSI) and Link Quality Indicator ( Transmit power, throughput and energy efficiency Duty cycling happens to be one of the major techniques for conserving energy in wireless sensor networks and this research aims to answer questions with regards to the effect of duty cycles on the energy efficiency as well as the throughput of three duty cycle protocols Sensor MAC ( Timeout MAC ( and TunableMAC in addition to creating a novel MAC protocol that is also more resilient to denial of sleep a ttacks than existing protocols. The main contributions to knowledge from this thesis are the developed framework used for evaluation of existing denial of sleep attack solutions and the algorithms which fuel the other contribution to knowledge a newly developed protocol tested on the Castalia Simulator on the OMNET++ platform. The new protocol has been compared with existing protocols and has been found to have significant improvement in energy efficiency and also better resilience to denial of sleep at tacks Part of this research has been published Two conference publications in IEEE Explore and one workshop paper

    Energy flow problem solution based on state estimation approaches and smart meter data

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    Accurate electric energy (EE) measurements and billing estimations in a power system necessitate the development of an energy flow distribution model. This paper summarizes the results of investigations on a new problem related to the determination of EE flow in a power system over time intervals ranging from minutes to years. The problem is referred to as the energy flow problem (EFP). Generally, the grid state and topology may fluctuate over time. An attempt to use instantaneous (not integral) power values obtained from telemetry to solve classical electrical engineering equations leads to significant modeling errors, particularly with topology changes. A promoted EFP model may be suitable in the presence of such topological and state changes. Herein, EE flows are determined using state estimation approaches based on direct EE measurement data in Watt-hours (Volt-ampere reactive-hours) provided by electricity meters. The EFP solution is essential for a broad set of applications, including meter data validation, zero unbalance EE billing, and nontechnical EE loss check. © 202

    Towards Secure Deep Neural Networks for Cyber-Physical Systems

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    In recent years, deep neural networks (DNNs) are increasingly investigated in the literature to be employed in cyber-physical systems (CPSs). DNNs own inherent advantages in complex pattern identifying and achieve state-of-the-art performances in many important CPS applications. However, DNN-based systems usually require large datasets for model training, which introduces new data management issues. Meanwhile, research in the computer vision domain demonstrated that the DNNs are highly vulnerable to adversarial examples. Therefore, the security risks of employing DNNs in CPSs applications are of concern. In this dissertation, we study the security of employing DNNs in CPSs from both the data domain and learning domain. For the data domain, we study the data privacy issues of outsourcing the CPS data to cloud service providers (CSP). We design a space-efficient searchable symmetric encryption scheme that allows the user to query keywords over the encrypted CPS data that is stored in the cloud. After that, we study the security risks that adversarial machine learning (AML) can bring to the CPSs. Based on the attacker properties, we further separate AML in CPS into the customer domain and control domain. We analyze the DNN-based energy theft detection in advanced meter infrastructure as an example for customer domain attacks. The adversarial attacks to control domain CPS applications are more challenging and stringent. We then propose ConAML, a general AML framework that enables the attacker to generate adversarial examples under practical constraints. We evaluate the framework with three CPS applications in transportation systems, power grids, and water systems. To mitigate the threat of adversarial attacks, more robust DNNs are required for critical CPSs. We summarize the defense requirements for CPS applications and evaluate several typical defense mechanisms. For control domain adversarial attacks, we demonstrate that defensive methods like adversarial detection are not capable due to the practical attack requirements. We propose a random padding framework that can significantly increase the DNN robustness under adversarial attacks. The evaluation results show that our padding framework can reduce the effectiveness of adversarial examples in both customer domain and control domain applications
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