542 research outputs found

    IoT-teknologian hyödyntÀminen sÀhköverkko-omaisuuden hallinnassa

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    Objective of this thesis is to define and assess changes in energy sector, which will directly or indirectly affect distribution grid operation and management in Finland, and to determine measurable events or variables, which enable identification and monitoring of the recognized changes. Based on assessment of the upcoming changes, possibilities for utilizing IoT technologies in management and monitoring applications of the identified changes, are assessed. In the assessment of upcoming changes, total of eight subjects were covered and microgeneration, electric vehicles and heat pumps were identified to be the most probable changes to realistically penetrate Finnish energy sector within a time scope of approximately 10 years. However, none of the assessed, changes, were found to have significant and wide-scale effects in terms of performance of Finnish distribution networks. For utilization of IoT technologies in distribution networks one application for operational grid monitoring of power quality problems derived from residential photovoltaic generation, and three cases for IoT based asset health and condition monitoring were assessed. Furthermore, requirements and architecture for data storage and analysis platform of IoT based system were discussed. From the evaluated applications condition monitoring scheme of circuit breakers was determined to be the most promising alternative.Diplomityön tavoitteena on mÀÀritellÀ ja arvioida energiasektoriin vaikuttavien tulevien muutosten suoria tai epÀsuoria vaikutuksia jakeluverkon toimintaan ja hallintaan. Havaittujen muutosten vaikutuksista on tarkoitus tunnistaa mitattavia ilmiöitÀ tai suureita, jotka mahdollistavat muutosten tunnistamisen sekÀ seurannan. Muutosanalyysiin pohjautuen tavoitteena on tunnistaa ja arvioida mahdollisuuksia IoT-teknologian hyödyntÀmiseksi havaittujen muutosten aiheuttamien ongelmakohtien tai mahdollisuuksien tunnistamisessa, seurannassa sekÀ hallinnassa. Energiasektoriin vaikuttavien muutosten analyysissÀ arvoitiin kokonaisuudessaan kahdeksaa eri aihealuetta ja lopputuloksena pientuotannon, sÀhköautojen sekÀ lÀmpöpumppujen todettiin olevan todennÀköisimmÀt teknologiat, jotka yleistyvÀt merkittÀvissÀ mÀÀrin suomalaisessa sÀhköverkossa seuraavan kymmenen vuoden aikana. MinkÀÀn kÀsitellyn muutoskohdan ei kuitenkaan todettu aiheuttavan laajamittaisia ja merkittÀviÀ ongelmia jakeluverkon toimintaan. IoT-teknologian hyödyntÀmiseen jakeluverkkotoiminnassa kÀsiteltiin yhtÀ verkon kÀyttöön ja sÀhkön laatuun liittyvÀÀ sovellusta, jonka avulla hajautetun pienaurinkotuotannon vaikutuksia pystytÀÀn seuraamaan, sekÀ lisÀksi kolmeen eri verkkokomponenttiin kohdistuvaa jatkuvan kunnon seurannan sovellusta. TÀmÀn lisÀksi IoT-jÀrjestelmÀn toteuttamiseksi vaadittavalle analyysi- ja tietojÀrjestelmÀalustalle mÀÀriteltiin rakenteellisia ja toiminnallisia tarpeita. TyössÀ kÀsitellyistÀ IoT-sovelluksista lupaavimmaksi todettiin katkaisijoihin kohdistuva jatkuvan kunnonhallinnan sovellus

    European White Book on Real-Time Power Hardware in the Loop Testing : DERlab Report No. R- 005.0

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    The European White Book on Real-Time-Powerhardware-in-the-Loop testing is intended to serve as a reference document on the future of testing of electrical power equipment, with speciïŹ c focus on the emerging hardware-in-the-loop activities and application thereof within testing facilities and procedures. It will provide an outlook of how this powerful tool can be utilised to support the development, testing and validation of speciïŹ cally DER equipment. It aims to report on international experience gained thus far and provides case studies on developments and speciïŹ c technical issues, such as the hardware/software interface. This white book compliments the already existing series of DERlab European white books, covering topics such as grid-inverters and grid-connected storag

    Cross-border Mobility for Electric Vehicles: Selected results from one of the first cross-border field tests in Europe

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    This book provides selected results from the accompanying research of the project CROME. The vision of the project was to create and test a safe, seamless, user-friendly and reliable mobility with electric vehicles between France and Germany as a prefiguration of a pan-European electric mobility system. Major aims were contributions to the European standardisation process of charging infrastructure for electric mobility and corresponding services, and to provide an early customer feedback

    Innovation in Energy Systems

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    It has been a little over a century since the inception of interconnected networks and little has changed in the way that they are operated. Demand-supply balance methods, protection schemes, business models for electric power companies, and future development considerations have remained the same until very recently. Distributed generators, storage devices, and electric vehicles have become widespread and disrupted century-old bulk generation - bulk transmission operation. Distribution networks are no longer passive networks and now contribute to power generation. Old billing and energy trading schemes cannot accommodate this change and need revision. Furthermore, bidirectional power flow is an unprecedented phenomenon in distribution networks and traditional protection schemes require a thorough fix for proper operation. This book aims to cover new technologies, methods, and approaches developed to meet the needs of this changing field

    Energy Law in Indiana

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    Meeting proceedings of a seminar by the same name, held April 8, 2021

    State-of-the-Art Assessment of Smart Charging and Vehicle 2 Grid services

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    Electro-mobility – especially when coupled smartly with a decarbonised grid and also renewable distributed local energy generation, has an imperative role to play in reducing CO2 emissions and mitigating the effects of climate change. In parallel, the regulatory framework continues to set new and challenging targets for greenhouse gas emissions and urban air pollution. ‱ EVs can help to achieve environmental targets because they are beneficial in terms of reduced GHG emissions although the magnitude of emission reduction really depends on the carbon intensity of the national energy mix, zero air pollution, reduced noise, higher energy efficiency and capable of integration with the electric grid, as discussed in Chapter 1. ‱ Scenarios to limit global warming have been developed based on the Paris Agreement on Climate Change, and these set the EV deployment targets or ambitions mentioned in Chapter 2. ‱ Currently there is a considerable surge in electric cars purchasing with countries such as China, the USA, Norway, The Netherlands, France, the UK and Sweden leading the way with an EV market share over 1%. ‱ To enable the achievement of these targets, charging infrastructures need to be deployed in parallel: there are four modes according to IEC 61851, as presented in Chapter 2.1.4. ‱ The targets for SEEV4City project are as follow: o Increase energy autonomy in SEEV4-City sites by 25%, as compared to the baseline case. o Reduce greenhouse gas emissions by 150 Tonnes annually and change to zero emission kilometres in the SEEV4-City Operational Pilots. o Avoid grid related investments (100 million Euros in 10 years) by introducing large scale adoption of smart charging and storage services and make existing electrical grids compatible with an increase in electro mobility and local renewable energy production. ‱ The afore-mentioned objectives are achieved by applying Smart Charging (SC) and Vehicle to Grid (V2G) technologies within Operational Pilots at different levels: o Household. o Street. o Neighbourhood. o City. ‱ SEEV4City aims to develop the concept of 'Vehicle4Energy Services' into a number of sustainable business models to integrate electric vehicles and renewable energy within a Sustainable Urban Mobility and Energy Plan (SUMEP), as introduced in Chapter 1. With this aim in mind, this project fills the gaps left by previous or currently running projects, as reviewed in Chapter 6. ‱ The business models will be developed according to the boundaries of the six Operational Pilots, which involve a disparate number of stakeholders which will be considered within them. ‱ Within every scale, the relevant project objectives need to be satisfied and a study is made on the Public, Social and Private Economics of Smart Charging and V2G. ‱ In order to accomplish this work, a variety of aspects need to be investigated: o Chapter 3 provides details about revenue streams and costs for business models and Economics of Smart Charging and V2G. o Chapter 4 focuses on the definition of Energy Autonomy, the variables and the economy behind it; o Chapter 5 talks about the impacts of EV charging on the grid, how to mitigate them and offers solutions to defer grid investments; o Chapter 7 introduces a number of relevant business models and considers the Economics of Smart Charging and V2G; o Chapter 8 discusses policy frameworks, and gives insight into CO2 emissions and air pollution; o Chapter 9 defines the Data Collection approach that will be interfaced with the models; o Chapter 10 discusses the Energy model and the simulation platforms that may be used for project implementation

    Design of a hybrid wind-electric vehicles power plant model fleet model for ancillary services provision in Bornholm

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    As part of the ongoing European project "Insulae", this thesis analyses the effects of power regulation in an HPP composed of three wind turbines installed in Kalby and an aggregation of EVs in the testbed of the Danish island of Bornholm. A selected model of the Bornholm power system with a focus on the substation of Ã
kirkeby is utilized to perform simulations in DIgSILENT's software PowerFactory (PF) environment. Detailed EV fleet model and related controllers need to be designed

    Multi-objective network planning for the integration of electric vehicles as responsive demands

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    The integration of electric vehicles (EVs) into distribution networks presents substantial challenges to Distribution Network Operators (DNOs) internationally. In the 12 months from November 2017, EV registrations in Great Britain have increased by ~22% [A.1], though it is noted that EVs account for only 6% of all UK vehicle registrations [A.1] in 2018. With the UK Government announcement in 2017 [A.2] that "by 2040 there will be an end to the sale of all conventional petrol and diesel cars and vans", the penetration of EVs will require to - unless a new technology emerges - grow exponentially over the next 10 to 20 years towards 100% penetration by 2050. However, the increasing penetration of EVs can provide to the system multiple benefits and assist in mitigating issues; if EV integration is optimally planned using a suitable method. The managed charging of multiple EVs can assist in better utilising power generated by intermittent renewables, which will provide substantial benefits such as peak shifting, deferred reinforcement costs and the reduced requirement for imported energy to support the network at times of need.;Accurately assessing the impact that EVs will have on distribution networks is critical to DNOs [A.3]. In particular, the aim of this thesis is to identify the optimal location, battery size, charger power output and operational envelope for multiple EVs when used as responsive demands in high voltage/low voltage (HV/LV) distribution networks. Societal benefits can include reduced or deferred asset investment costs; reduced technical losses and increasing the utilisation of renewable generation [A.3]. System benefits must be accounted for and can support and inform planning and operational decisions - such as asset investment and network reinforcement. Coordinated smart charging of multiple EVs can assist in managing peaks in the demand curve and increase the utilisation of intermittent renewables. Unmanaged EV charging at times of peak demand would require the DNO to invest in reinforcement solutions to ensure the required additional capacity is made available. However, one approach is to cluster EV charging in periods when the base load would otherwise be low, to lessen the need for asset reinforcement as EV charging during the period of peak demand would be avoided.;Time periods for charging EVs (dependent on the chosen objectives) will be identified and then correlated to times when renewable generation availability is high and when base demand is low. The use of the presented network planning tool will identify EV charging strategies that can be applied to multiple EVs (based on the chosen objectives and with respect to constraints) whilst optimising the type, number and location on a specific modelled network. The planning framework utilises the Strength Pareto Evolutionary Algorithm 2 (SPEA2); the use of this algorithm will ensure that the network constraints are not breached and that multiple objectives are included in the analyses. This thesis investigates the impact that the inclusion of multiple EVs (when used as responsive demands); will have on the HV distribution network when the additional EV load is smartly scheduled to meet specific objectives and to correspond with the availability of intermittent renewables. The ultimate aim of this planning approach is to offer DNOs low cost solutions to multiobjective problems relating to EV integration and operation. [References A1-A3 for Abstract available p. XV of thesis.]The integration of electric vehicles (EVs) into distribution networks presents substantial challenges to Distribution Network Operators (DNOs) internationally. In the 12 months from November 2017, EV registrations in Great Britain have increased by ~22% [A.1], though it is noted that EVs account for only 6% of all UK vehicle registrations [A.1] in 2018. With the UK Government announcement in 2017 [A.2] that "by 2040 there will be an end to the sale of all conventional petrol and diesel cars and vans", the penetration of EVs will require to - unless a new technology emerges - grow exponentially over the next 10 to 20 years towards 100% penetration by 2050. However, the increasing penetration of EVs can provide to the system multiple benefits and assist in mitigating issues; if EV integration is optimally planned using a suitable method. The managed charging of multiple EVs can assist in better utilising power generated by intermittent renewables, which will provide substantial benefits such as peak shifting, deferred reinforcement costs and the reduced requirement for imported energy to support the network at times of need.;Accurately assessing the impact that EVs will have on distribution networks is critical to DNOs [A.3]. In particular, the aim of this thesis is to identify the optimal location, battery size, charger power output and operational envelope for multiple EVs when used as responsive demands in high voltage/low voltage (HV/LV) distribution networks. Societal benefits can include reduced or deferred asset investment costs; reduced technical losses and increasing the utilisation of renewable generation [A.3]. System benefits must be accounted for and can support and inform planning and operational decisions - such as asset investment and network reinforcement. Coordinated smart charging of multiple EVs can assist in managing peaks in the demand curve and increase the utilisation of intermittent renewables. Unmanaged EV charging at times of peak demand would require the DNO to invest in reinforcement solutions to ensure the required additional capacity is made available. However, one approach is to cluster EV charging in periods when the base load would otherwise be low, to lessen the need for asset reinforcement as EV charging during the period of peak demand would be avoided.;Time periods for charging EVs (dependent on the chosen objectives) will be identified and then correlated to times when renewable generation availability is high and when base demand is low. The use of the presented network planning tool will identify EV charging strategies that can be applied to multiple EVs (based on the chosen objectives and with respect to constraints) whilst optimising the type, number and location on a specific modelled network. The planning framework utilises the Strength Pareto Evolutionary Algorithm 2 (SPEA2); the use of this algorithm will ensure that the network constraints are not breached and that multiple objectives are included in the analyses. This thesis investigates the impact that the inclusion of multiple EVs (when used as responsive demands); will have on the HV distribution network when the additional EV load is smartly scheduled to meet specific objectives and to correspond with the availability of intermittent renewables. The ultimate aim of this planning approach is to offer DNOs low cost solutions to multiobjective problems relating to EV integration and operation. [References A1-A3 for Abstract available p. XV of thesis.
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