741 research outputs found
Modelling and simulation of hybrid PV & BES systems as flexible resources in smartgrids - Sundom smart grid case
Ever-growing energy needs and larger penetration of renewable energy in the power grids with higher intermittency in power generation cause the need for flexible energy sources. Flexible sources such as distributed generation, demand response, electric vehicles etc. play a dominant role in providing flexibility in services such as frequency, voltage and power balance control in smart grids. Given the present state of technology and economic maturity of battery energy storage systems (BESS), has a lot of potential to fulfill increasing power systems rapid, short-term flexibility needs. In this paper, a case study on hybrid photovoltaic (PV) arrays & lithium ion based BESS as flexible energy sources are integrated in medium voltage (MV) network side in local pilot network, Sundom Smart Grid (SSG). Vaasa, Finland. Sundom Smart grid is modelled based on real time data on energy consumption and generation streamed from network. Role of batteries as a flexible energy source in the PV & BESS hybrid for power balance flexibility application is demonstrated by means of Matlab simulations.fi=vertaisarvioitu|en=peerReviewed
Evaluating the robustness of an active network management function in an operational environment
This paper presents the integration process of a distribution network Active Network Management (ANM) function within an operational environment in the form of a Micro-Grid Laboratory. This enables emulation of a real power network and enables investigation into the effects of data uncertainty on an online and automatic ANM algorithm's control decisions. The algorithm implemented within the operational environment is a Power Flow Management (PFM) approach based around the Constraint Satisfaction Problem (CSP). This paper show the impact of increasing uncertainty, in the input data available for an ANM scheme in terms of the variation in control actions. The inclusion of a State Estimator (SE), with known tolerances is shown to improve the ANM performance
Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions
Traditional power grids are being transformed into Smart Grids (SGs) to
address the issues in existing power system due to uni-directional information
flow, energy wastage, growing energy demand, reliability and security. SGs
offer bi-directional energy flow between service providers and consumers,
involving power generation, transmission, distribution and utilization systems.
SGs employ various devices for the monitoring, analysis and control of the
grid, deployed at power plants, distribution centers and in consumers' premises
in a very large number. Hence, an SG requires connectivity, automation and the
tracking of such devices. This is achieved with the help of Internet of Things
(IoT). IoT helps SG systems to support various network functions throughout the
generation, transmission, distribution and consumption of energy by
incorporating IoT devices (such as sensors, actuators and smart meters), as
well as by providing the connectivity, automation and tracking for such
devices. In this paper, we provide a comprehensive survey on IoT-aided SG
systems, which includes the existing architectures, applications and prototypes
of IoT-aided SG systems. This survey also highlights the open issues,
challenges and future research directions for IoT-aided SG systems
Requirements to Testing of Power System Services Provided by DER Units
The present report forms the Project Deliverable ‘D 2.2’ of the DERlab NoE project, supported by the EC under Contract No. SES6-CT-518299 NoE DERlab. The present document discuss the power system services that may be provided from DER units and the related methods to test the services actually provided, both at component level and at system level
False Data Injection Attacks in Smart Grids: State of the Art and Way Forward
In the recent years cyberattacks to smart grids are becoming more frequent
Among the many malicious activities that can be launched against smart grids
False Data Injection FDI attacks have raised significant concerns from both
academia and industry FDI attacks can affect the internal state estimation
processcritical for smart grid monitoring and controlthus being able to bypass
conventional Bad Data Detection BDD methods Hence prompt detection and precise
localization of FDI attacks is becomming of paramount importance to ensure
smart grids security and safety Several papers recently started to study and
analyze this topic from different perspectives and address existing challenges
Datadriven techniques and mathematical modelings are the major ingredients of
the proposed approaches The primary objective of this work is to provide a
systematic review and insights into FDI attacks joint detection and
localization approaches considering that other surveys mainly concentrated on
the detection aspects without detailed coverage of localization aspects For
this purpose we select and inspect more than forty major research contributions
while conducting a detailed analysis of their methodology and objectives in
relation to the FDI attacks detection and localization We provide our key
findings of the identified papers according to different criteria such as
employed FDI attacks localization techniques utilized evaluation scenarios
investigated FDI attack types application scenarios adopted methodologies and
the use of additional data Finally we discuss open issues and future research
direction
Deployment and Implementation Aspects of Radio Frequency Fingerprinting in Cybersecurity of Smart Grids
Smart grids incorporate diverse power equipment used for energy optimization in intelligent cities. This equipment may use Internet of Things (IoT) devices and services in the future. To ensure stable operation of smart grids, cybersecurity of IoT is paramount. To this end, use of cryptographic security methods is prevalent in existing IoT. Non-cryptographic methods such as radio frequency fingerprinting (RFF) have been on the horizon for a few decades but are limited to academic research or military interest. RFF is a physical layer security feature that leverages hardware impairments in radios of IoT devices for classification and rogue device detection. The article discusses the potential of RFF in wireless communication of IoT devices to augment the cybersecurity of smart grids. The characteristics of a deep learning (DL)-aided RFF system are presented. Subsequently, a deployment framework of RFF for smart grids is presented with implementation and regulatory aspects. The article culminates with a discussion of existing challenges and potential research directions for maturation of RFF.publishedVersio
Smart Vehicle to Grid Interface Project: Electromobility Management System Architecture and Field Test Results
This paper presents and discusses the electromobility management system
developed in the context of the SMARTV2G project, enabling the automatic
control of plug-in electric vehicles' (PEVs') charging processes. The paper
describes the architecture and the software/hardware components of the
electromobility management system. The focus is put in particular on the
implementation of a centralized demand side management control algorithm, which
allows remote real time control of the charging stations in the field,
according to preferences and constraints expressed by all the actors involved
(in particular the distribution system operator and the PEV users). The results
of the field tests are reported and discussed, highlighting critical issues
raised from the field experience.Comment: To appear in IEEE International Electric Vehicle Conference (IEEE
IEVC 2014
Future smart energy software houses
Software is the key enabling technology (KET) as digitalization is cross-cutting future energy systems spanning the production sites, distribution networks, and consumers particularly in electricity smart grids. In this paper, we identify systematically what particular software competencies are required in the future energy systems focusing on electricity system smart grids. The realizations of that can then be roadmapped to specific software capabilities of the different future software houses' across the networks. Our instrumental method is software competence development scenario path construction with environmental scanning of the related systems elements. The vision of future software-enabled smart energy systems with software houses is mapped with the already progressing scenarios of energy systems transitions on the one hand coupled with the technology foresight of software on the other hand. Grounding on the Smart Grid Reference Architecture Model (SGAM), it tabulates the distinguished software competencies and attributes them to the different partiesincluding customers/consumers (Internet of People, IoP)involved in future smart energy systems. The resulting designations can then be used to recognize and measure the necessary software competencies (e.g., fog computing) in order to be able to develop them in-house, or for instance to partner with software companies, depending on the future desirability. Software-intensive systems development competence becomes one of the key success factors for such cyber-physical-social systems (CPSS). Further futures research work is chartered with the Futures Map frame. This paper contributes preliminarily toward that by identifying pictures of the software-enabled futures and the connecting software competence-based scenario paths.Peer reviewe
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