Non-Repudiation and End-to-End Security for Electric-Vehicle Charging

Contains fulltext : 214851.pdf (Publisher’s version ) (Open Access)2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019, Bucharest, Romania, September 29 - October 2, 201

Security risk modeling in smart grid critical infrastructures in the era of big data and artificial intelligence

Smart grids (SG) emerged as a response to the need to modernize the electricity grid. The current security tools are almost perfect when it comes to identifying and preventing known attacks in the smart grid. Still, unfortunately, they do not quite meet the requirements of advanced cybersecurity. Adequate protection against cyber threats requires a whole set of processes and tools. Therefore, a more flexible mechanism is needed to examine data sets holistically and detect otherwise unknown threats. This is possible with big modern data analyses based on deep learning, machine learning, and artificial intelligence. Machine learning, which can rely on adaptive baseline behavior models, effectively detects new, unknown attacks. Combined known and unknown data sets based on predictive analytics and machine intelligence will decisively change the security landscape. This paper identifies the trends, problems, and challenges of cybersecurity in smart grid critical infrastructures in big data and artificial intelligence. We present an overview of the SG with its architectures and functionalities and confirm how technology has configured the modern electricity grid. A qualitative risk assessment method is presented. The most significant contributions to the reliability, safety, and efficiency of the electrical network are described. We expose levels while proposing suitable security countermeasures. Finally, the smart grid’s cybersecurity risk assessment methods for supervisory control and data acquisition are presented

Facilitating higher photovoltaic penetration in residential distribution networks using demand side management and active voltage control

Abstract Future power networks are certain to have high penetrations of renewable distributed generation such as photovoltaics (PV). At times of high PV generation and low customer demand (e.g., summer), network voltage is likely to rise beyond limits mandated by grid codes resulting in a curtailment of PV generation, unless appropriate control means are used. This leads to a reduction in energy yield and consequently reduces the economic viability of PV systems. This work focuses on scenario‐based impact assessments underpinned by a net prosumer load forecasting framework as part of power system planning to aid sustainable energy policymaking. Based on use‐case scenarios, the efficacy of smart grid solutions demand side management (DSM) and Active Voltage Control in maximizing PV energy yield and therefore revenue returns for prosumers and avoided costs for distribution networks between a developed country (the UK) and developing country (India) is analyzed. The results showed that while DSM could be a preferred means because of its potential for deployment via holistic demand response schemes for India and similar developing nations, technically the combination of the weaker low voltage network with significantly higher solar resource meant that it is not effective in preventing PV energy curtailment

A chronological literature review of electric vehicle interactions with power distribution systems

In the last decade, the deployment of electric vehicles (EVs) has been largely promoted. This development has increased challenges in the power systems in the context of planning and operation due to the massive amount of recharge needed for EVs. Furthermore, EVs may also offer new opportunities and can be used to support the grid to provide auxiliary services. In this regard, and considering the research around EVs and power grids, this paper presents a chronological background review of EVs and their interactions with power systems, particularly electric distribution networks, considering publications from the IEEE Xplore database. The review is extended from 1973 to 2019 and is developed via systematic classification using key categories that describe the types of interactions between EVs and power grids. These interactions are in the framework of the power quality, study of scenarios, electricity markets, demand response, demand management, power system stability, Vehicle-to-Grid (V2G) concept, and optimal location of battery swap and charging stations.Introduction General Overview Chronological Review: Part I Chronological Review: Part II Brief Observations Conclusions and Future Works Final Reflections Author Contributions Funding Acknowledgments Conflicts of Interest Reference

Optimising Energy Flexibility of Boats in PV-BESS Based Marina Energy Systems

Implementation of alternative energy supply solutions requires the broad involvement of local communities. Hence, smart energy solutions are primarily investigated on a local scale, resulting in integrated community energy systems (ICESs). Within this framework, the distributed generation can be optimally utilised, matching it with the local load via storage and demand response techniques. In this study, the boat demand flexibility in the Ballen marina on Samsø—a medium-sized Danish island—is analysed for improving the local grid operation. For this purpose, suitable electricity tariffs for the marina and sailors are developed based on the conducted demand analysis. The optimal scheduling of boats and battery energy storage system (BESS) is proposed, utilising mixed-integer linear programming. The marina’s grid-flexible operation is studied for three representative weeks—peak tourist season, late summer, and late autumn period—with the combinations of high/low load and photovoltaic (PV) generation. Several benefits of boat demand response have been identified, including cost savings for both the marina and sailors, along with a substantial increase in load factor. Furthermore, the proposed algorithm increases battery utilisation during summer, improving the marina’s cost efficiency. The cooperation of boat flexibility and BESS leads to improved grid operation of the marina, with profits for both involved parties. In the future, the marina’s demand flexibility could become an essential element of the local energy system, considering the possible increase in renewable generation capacity—in the form of PV units, wind turbines or wave energy

Real-time grouped management of Electric Vehicle Battery Chargers (EVBCs) for voltage profile improvement in radial distribution networks

Voltage limit violation is one of the main factors that impact large-scale integration of electric vehicles in distribution networks. In order to improve voltage profiles, active charging management techniques can be deployed in real-time, considering voltage sensitivities of customer buses. The study in this paper investigates a real-time charging management approach for electric vehicles, clustered according to voltage sensitivities among the customer buses, in a local network. Constant power (CP) and constant current (CC) models, representing a range of electric vehicle battery chargers (EVBCs), are used in simulations with high-resolution stochastic EV charging and residential demand profiles. The paper quantifies the performance of the proposed management approach in a local network model based on real data and IEEE European Low Voltage (LV) Test Feeder

Compliance of Distribution System Reactive Flows with Transmission System Requirements

Transmission system operators (TSOs) often set requirements to distribution system operators (DSOs) regarding the exchange of reactive power on the interface between the two parts of the system they operate, typically High Voltage and Medium Voltage. The presence of increasing amounts of Distributed Energy Resources (DERs) at the distribution networks complicates the problem, but provides control opportunities in order to keep the exchange within the prescribed limits. Typical DER control methods, such as constant cosϕ or Q/V functions, cannot adequately address these limits, while power electronics interfaced DERs provide to DSOs reactive power control capabilities for complying more effectively with TSO requirements. This paper proposes an optimisation method to provide power set-points to DERs in order to control the hourly reactive power exchanges with the transmission network. The method is tested via simulations using real data from the distribution substation at the Sundom Smart Grid, in Finland, using the operating guidelines imposed by the Finnish TSO. Results show the advantages of the proposed method compared to traditional methods for reactive power compensation from DERs. The application of more advanced Model Predictive Control techniques is further explored.©2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).Part of this work was carried out in the SolarX research project with financial support provided by Business Finland, 2019–2021 (grant No. 6844/31/2018).fi=vertaisarvioitu|en=peerReviewed

Accelerated Real-Time Simulations for Testing a Reactive Power Flow Controller in Long-Term Case Studies

This paper presents the development of an accelerated real-time cosimulation and testing platform, especially for long-term simulations of power systems. The platform is planned to be utilized in the development and testing of active network management functions for microgrids and smart grids. Long-term simulations are needed in order to study, for example, the potential weekly, monthly, or yearly usage of distribution-network-connected distributed energy resources for different technical flexibility services. In order to test new algorithms in long-term study cases, real-time simulations or hardware-in-the-loop tests should be accelerated. This paper analyzes the possibilities and challenges of accelerated long-term simulations in studying the potential use of a large-scale wind turbine for reactive power flow control between distribution system operator (DSO) and transmission system operator (TSO) networks. To this end, the reactive power flow control is studied for different voltage levels (HV and MV) in the Sundom Smart Grid in Vaasa, Finland. The control of reactive power flow between HV and MV networks is realized with a reactive power window control algorithm for a 3.6 MW MV-network-connected wind turbine with a full-scale power converter. The behaviour of the reactive power controller during long-term simulations is studied by offline and real-time simulations. Moreover, the real-time simulations are performed with both software-in-the-loop and controller-hardware-in-the-loop.Copyright © 2020 Katja H. Sirviö et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.fi=vertaisarvioitu|en=peerReviewed

Simulation of Incidental Distribution Generation Curtailment to Maximize the Integration of Renewable Energy Generation in Power Systems

Power system security is increasingly endangered due to novel power flow situations caused by the growing integration of distributed generation. Consequently, grid operators are forced to request the curtailment of distributed generators to ensure the compliance with operational limits more often. This research proposes a framework to simulate the incidental amount of renewable energy curtailment based on load flow analysis of the network. Real data from a 110 kV distribution network located in Germany are used to validate the proposed framework by implementing best practice curtailment approaches. Furthermore, novel operational concepts are investigated to improve the practical implementation of distributed generation curtailment. Specifically, smaller curtailment level increments, coordinated selection methods, and an extension of the n-1 security criterion are analyzed. Moreover, combinations of these concepts are considered to depict interdependencies between several operational aspects. The results quantify the potential of the proposed concepts to improve established grid operation practices by minimizing distributed generation curtailment and, thus, maximizing power system integration of renewable energies. In particular, the extension of the n-1 criterion offers significant potential to reduce curtailment by up to 94.8% through a more efficient utilization of grid capacities