Lithium-ion BESS integration for smart grid applications : ECM modelling approach

Lithium-ion battery energy storage systems (BESS) with their present state of technology and economic maturity possess huge potential for catering short-term flexibility requirements in smart grid environment. However, it is essential to model in detail the complexity of non-linear battery system characteristics and control of their adjoining power electronic interfaces. More detailed and accurate modelling of components, enables improved overall power system optimization studies by considering both, component and system level aspects simultaneously. Therefore, this paper develops an equivalent circuit model (ECM) for Lithium-ion battery and Lithium-ion nickel-manganese-cobalt (NMC) battery cell is modelled as a second order equivalent circuit (SOEC), including C-rate, temperature, state-of-charge and age effects. Secondly, detailed controller design methodology for DC/DC- and DC/AC-converter interfaces are developed to enable advanced grid integration studies. Overall, BESS integration design was validated by simulation studies in Simulink Simpowersystems platform.©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

Accurate Battery Modelling for Control Design and Economic Analysis of Lithium-ion Battery Energy Storage Systems in Smart Grid

Adoption of lithium-ion battery energy storage systems (Li-ion BESSs) as a flexible energy source (FES) has been rapid, particularly for active network management (ANM) schemes to facilitate better utilisation of inverter based renewable energy sources (RES) in power systems. However, Li-ion BESSs display highly nonlinear performance characteristics, which are based on parameters such as state of charge (SOC), temperature, depth of discharge (DOD), charge/discharge rate (C-rate), and battery-aging conditions. Therefore, it is important to include the dynamic nature of battery characteristics in the process of the design and development of battery system controllers for grid applications and for techno-economic studies analyzing the BESS economic profitability. This thesis focuses on improving the design and development of Li-ion BESS controllers for ANM applications by utilizing accurate battery performance models based on the second-order equivalent-circuit dynamic battery modelling technique, which considers the SOC, C-rate, temperature, and aging as its performance affecting parameters. The proposed ANM scheme has been designed to control and manage the power system parameters within the limits defined by grid codes by managing the transients introduced due to the intermittence of RESs and increasing the RES penetration at the same time. The validation of the ANM scheme and the effectiveness of controllers that manage the flexibilities in the power system, which are a part of the energy management system (EMS) of ANM, has been validated with the help of simulation studies based on an existing real-life smart grid pilot in Finland, Sundom Smart Grid (SSG). The studies were performed with offline (short-term transient-stability analysis) and real-time (long-term transient analysis) simulations. In long-term simulation studies, the effect of battery aging has also been considered as part of the Li-ion BESS controller design; thus, its impact on the overall power system operation can be analyzed. For this purpose, aging models that can determine the evolving peak power characteristics associated with aging have been established. Such aging models are included in the control loop of the Li-ion BESS controller design, which can help analyse battery aging impacts on the power system control and stability. These analyses have been validated using various use cases. Finally, the impact of battery aging on economic profitability has been studied by including battery-aging models in techno-economic studies.Aurinkosähköjärjestelmien ja tuulivoiman laajamittainen integrointi sähkövoimajärjestelmän eri jännitetasoille on lisääntynyt nopeasti. Uusiutuva energia on kuitenkin luonteeltaan vaihtelevaa, joka voi aiheuttaa nopeita muutoksia taajuudessa ja jännitteessä. Näiden vaihteluiden hallintaan tarvitaan erilaisia joustavia energiaresursseja, kuten energiavarastoja, sekä niiden tehokkaan hyödyntämisen mahdollistaviea älykkäitä ja aktiivisia hallinta- ja ohjausjärjestelmiä. Litiumioniakkuihin pohjautuvien invertteriliitäntäisten energian varastointijärjestelmien käyttö joustoresursseina aktiiviseen verkonhallintaan niiden pätö- ja loistehon ohjauksen avulla on lisääntynyt nopeasti johtuen niiden kustannusten laskusta, modulaarisuudesta ja teknisistä ominaisuuksista. Litiumioniakuilla on erittäin epälineaariset ominaisuudet joita kuvaavat parametrit ovat esimerkiksi lataustila, lämpötila, purkaussyvyys, lataus/ purkausnopeus ja akun ikääntyminen. Akkujen ominaisuuksien dynaaminen luonne onkin tärkeää huomioida myös akkujen sähköverkkoratkaisuihin liittyvien säätöjärjestelmien kehittämisessä sekä teknis-taloudellisissa kannattavuusanalyyseissa. Tämä väitöstutkimus keskittyy ensisijaisesti aktiiviseen verkonhallintaan käytettävien litiumioniakkujen säätöratkaisuiden parantamiseen hyödyntämällä tarkkoja, dynaamisia akun suorituskykymalleja, jotka perustuvat toisen asteen ekvivalenttipiirien akkumallinnustekniikkaan, jossa otetaan huomioon lataustila, lataus/purkausnopeus ja lämpötila. Työssä kehitetyn aktiivisen verkonhallintajärjestelmän avulla tehtävät akun pätö- ja loistehon ohjausperiaatteet on validoitu laajamittaisten simulointien avulla, esimerkiksi paikallista älyverkkopilottia Sundom Smart Gridiä simuloimalla. Simuloinnit tehtiin sekä lyhyen aikavälin offline-simulaatio-ohjelmistoilla että pitkän aikavälin simulaatioilla hyödyntäen reaaliaikasimulointilaitteistoa. Pitkän aikavälin simulaatioissa akun ikääntymisen vaikutus otettiin huomioon litiumioniakun ohjauksen suunnittelussa jotta sen vaikutusta sähköjärjestelmän kokonaistoimintaan voitiin analysoida. Tätä tarkoitusta varten luotiin akun ikääntymismalleja, joilla on mahdollista määrittää akun huipputehon muutos sen ikääntyessä. Akun huipputehon muutos taas vaikuttaa sen hyödynnettävyyteen erilaisten pätötehon ohjaukseen perustuvien joustopalveluiden tarjoamiseen liittyen. Lisäksi väitöstutkimuksessa tarkasteltiin akkujen ikääntymisen vaikutusta niiden taloudelliseen kannattavuuteen sisällyttämällä akkujen ikääntymismalleja teknis-taloudellisiin tarkasteluihin.fi=vertaisarvioitu|en=peerReviewed

Modelling battery energy storage systems for active network management : coordinated control design and validation

Control of battery energy storage systems (BESS) for active network management (ANM) should be done in coordinated way considering management of different BESS components like battery cells and inverter interface concurrently. In this paper, a detailed and accurate lithium‐ion battery model has been used to design BESS controls, thereby allowing improved overall power system control design optimisation studies by simultaneously considering both component and system‐level aspects. This model is utilised to develop a multi‐objective ANM scheme (a) to enhance utilisation of wind power generation locally by means of active power (P)‐ control of BESSs; (b) to utilise distributed energy resources (i.e. BESS and wind turbine generators) to maintain system voltage within the limits of grid code requirements by reactive power/voltage (QU)‐ and active power/voltage (PU)‐ controls. BESS control strategies to implement the ANM scheme, are designed and validated through real‐time simulation in an existing smart grid pilot, Sundom Smart Grid (SSG), in Vaasa, Finland.© 2021 The Authors. IET Renewable Power Generation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.fi=vertaisarvioitu|en=peerReviewed

Characterisation and modelling Lithium Titanate Oxide battery cell by Equivalent Circuit Modelling Technique

Lithium Titanate Oxide (L TO) battery cells have immense potential as energy storage systems in large-scale stationary grid applications due to their better cycling performance, lower self-discharge and higher safety margins compared to other Lithium based battery chemistries. Hence, accurate L TO performance models at various operating conditions are required for different purposes like determination of their dynamic behaviour, modelling LTO's suitability to an application as well as to the development of battery and energy management systems (BMS and EMS). L TO battery cell performance is mainly affected by parameters such as, state of charge (SOC) and temperature. Hence, in this paper, second order equivalent circuit model (ECM) of an L TO cell will be developed based on their experimental characterisation at different SoC's (every 10% intervals) and temperatures (15 °C, 25 °C, 35 °C and 45 °C), Modified version of the Hybrid pulse power characterisation (HPPC) test method will be utilised for parametrisation of the ECM of 2.9 Ah L TO cell. The simulation model will be developed in Matlab/Simulink platform and compared with the laboratory measurements for ECM validation.©2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

Power Electronics and Energy Management for Battery Storage Systems

The deployment of distributed renewable generation and e-mobility systems is creating a demand for improved dynamic performance, flexibility, and resilience in electrical grids. Various energy storages, such as stationary and electric vehicle batteries, together with power electronic interfaces, will play a key role in addressing these requests thanks to their enhanced functionality, fast response times, and configuration flexibility. For the large-scale implementation of this technology, the associated enabling developments are becoming of paramount importance. These include energy management algorithms; optimal sizing and coordinated control strategies of different storage technologies, including e-mobility storage; power electronic converters for interfacing renewables and battery systems, which allow for advanced interactions with the grid; and increase in round-trip efficiencies by means of advanced materials, components, and algorithms. This Special Issue contains the developments that have been published b researchers in the areas of power electronics, energy management and battery storage. A range of potential solutions to the existing barriers is presented, aiming to make the most out of these emerging technologies

Design and control of harbour area smart grids with application of battery energy storage system

Global trade occurs mostly on seaborne vessels, and harbours exist as the most significant part for enabling the economic development of any country. However, the amount of fossil fuels used by conventional diesel-engine powered vessels produce a great number of types of toxic emissions, such as air pollution particles at harbours, which create a threat to human health that can contribute to higher morbidity and mortality rates among humans. Therefore, the International maritime organisation and the European Directives recommend that ships implement methods that limit toxic gas emissions and air pollution, such as using onshore power supply and fuel with low-sulphur content for on-board power generation in vessels while remaining at harbours. This research presents cutting-edge methods and tools for contributing to the development of future marine solutions and analyses of modern vessel technological requirements as well as harbour grids, and it proposes novel models of harbour area smart grids for facilitating the support of onshore power supply and charging of batteries for those vessels that require it. This research explores the usage of multiple battery-charging configurations with either slow- or fast-charging systems for electric or hybrid vessels, and it analyses the technical challenges that could inhibit or prevent the practicality of their implementation. The suitable size and allocation of battery energy storage systems for real-world case power systems of Åland Islands harbour grid are also investigated to enhance power capacity of harbour grids. Moreover, a control algorithm for the battery energy storage controller was first developed in MATLAB/Simulink for the Vaasa harbour grid, and then its performance was tested in the OPAL-RT real-time simulator by conducting a controller hardware-in-the-loop test to maintain the power balance inside the harbour grid. The proposed harbour grid models can reduce the degree of pollution that degrades the environment while providing onshore power supply and battery-charging stations for hybrid or electric vessels. Moreover, this dissertation acts as a foundation for developing future business strategies for ship owners, port administrators, and local authorities to solve similar problems as technology develops and environmental degradation continues to be a problem of every country in the world.Maailmanlaajuinen kauppa tapahtuu pääasiassa merialuksilla, ja satamista on tulossa merkittävin osa minkä tahansa maan talouskehitystä. Perinteisten dieselmoottorialusten käyttämä fossiilinen polttoaine aiheuttaa kuitenkin satamissa monenlaisia myrkyllisiä päästöjä ja ilmansaasteita, jotka ovat uhka ihmisten terveydelle ja aiheuttavat monenlaisia vaarallisia sairauksia. Tästä syystä Kansainvälinen merenkulkujärjestö IMO ja EU-direktiivit suosittelevat, että alukset käyttävät satamissa ollessaan maalta tulevaa sähkönsyöttöä tai vähärikkistä polttoainetta myrkyllisten kaasupäästöjen ja ilmansaasteiden rajoittamiseksi. Tämä tutkimus esittelee uusimpia ja tulevaisuuden merenkulun ratkaisuja, analysoi nykyaikaisten alusten teknisiä vaatimuksia sekä satamaverkkoja ja esittelee uusia malleja satama-alueen älykkäille sähköverkoille, joilla tuetaan maasähkön käyttöä ja akkujen lataamista vaativia aluksia. Tutkimuksessa tarkasteltiin useita akkuenergiavarastojen latauskonfiguraatioita sekä hitailla että nopeilla latausjärjestelmillä sähkö-/hybridialuksille ja analysoitiin niiden käytännön toteutukseen liittyviä teknisiä haasteita. Akkuenergiavarastojen sopivaa kokoa ja sijoittelua satamaverkkojen tehokapasiteetin parantamiseksi selvitettiin todelliseen verkkoon perustuvassa tapaustutkimuksessa, jossa parannettiin Ahvenanmaan verkon satamien tehokapasiteettia. Lisäksi kehitettiin akkuenergiavarastojen ohjausalgoritmi tehotasapainon ylläpitämiseksi Vaasan satamaverkossa ensin MATLAB/Simulink-mallina, jonka jälkeen sen suorituskykyä testattiin OPAL-RT reaaliaika-simulaattorilla suorittamalla ns. laitesilmukkasimulaatioita. Ehdotetuilla satamaverkkomalleilla voidaan vastata ilmansaasteista aiheutuviin ympäristöongelmiin sekä mahdollistaa maasähkönsyöttö ja akkujen latausasemat tuleville hybridi- ja sähköaluksille. Lisäksi tämä väitöskirja voi toimia pohjana uusien liiketoimintastrategioiden kehittämiselle alusten omistajien, satamajohtajien ja paikallisviranomaisten tarpeisiin.fi=vertaisarvioitu|en=peerReviewed

DREMUS:A Data-Restricted Multi-Physics Simulation Model for Lithium-Ion Battery Storage

This paper presents a modelling approach to support the techno-economic analysis of Li-Ion battery energy storage systems (BESS) for third party organisations considering the purchase or use of BESS but lacking the detailed knowledge of battery operation and degradation. It takes into account the severe data-limitations and provides the best possible approximation for its long-term electrical, thermal and ageing performance. This is achieved by constructing flexible and scalable ageing models from experimental data based on manufacturer's datasheets, warranties and manuals as key inputs. The precision of the individual models has been determined using experimental data and has been found with <8 % normalised root-mean-square deviation (NRMSD) in all cases to be sufficiently accurate. Through linearization methods, this model is able to compare the long-term performance of BESS and quantify the degradative impact of specific charge/discharge mission profiles, which improves the tangibility of BESS as value generating asset

Advances in Batteries, Battery Modeling, Battery Management System, Battery Thermal Management, SOC, SOH, and Charge/Discharge Characteristics in EV Applications

The second-generation hybrid and Electric Vehicles are currently leading the paradigm shift in the automobile industry, replacing conventional diesel and gasoline-powered vehicles. The Battery Management System is crucial in these electric vehicles and also essential for renewable energy storage systems. This review paper focuses on batteries and addresses concerns, difficulties, and solutions associated with them. It explores key technologies of Battery Management System, including battery modeling, state estimation, and battery charging. A thorough analysis of numerous battery models, including electric, thermal, and electro-thermal models, is provided in the article. Additionally, it surveys battery state estimations for a charge and health. Furthermore, the different battery charging approaches and optimization methods are discussed. The Battery Management System performs a wide range of tasks, including as monitoring voltage and current, estimating charge and discharge, equalizing and protecting the battery, managing temperature conditions, and managing battery data. It also looks at various cell balancing circuit types, current and voltage stressors, control reliability, power loss, efficiency, as well as their advantages and disadvantages. The paper also discusses research gaps in battery management systems.publishedVersio

Integration and control of lithium-ion BESSs for active network management in smart grids : Sundom smart grid backup feeding case

Lithium-ion battery energy storage systems (Li-ion BESS), due to their capability in providing both active and reactive power services, act as a bridging technology for efficient implementation of active network management (ANM) schemes for land-based grid applications. Due to higher integration of intermittent renewable energy sources in the distribution system, transient instability may induce power quality issues, mainly in terms of voltage fluctuations. In such situations, ANM schemes in the power network are a possible solution to maintain operation limits defined by grid codes. However, to implement ANM schemes effectively, integration and control of highly flexible Li-ion BESS play an important role, considering their performance characteristics and economics. Hence, in this paper, an energy management system (EMS) has been developed for implementing the ANM scheme, particularly focusing on the integration design of Li-ion BESS and the controllers managing them. Developed ANM scheme has been utilized to mitigate MV network issues (i.e. voltage stability and adherence to reactive power window). The efficiency of Li-ion BESS integration methodology, performance of the EMS controllers to implement ANM scheme and the effect of such ANM schemes on integration of Li-ion BESS, i.e. control of its grid-side converter (considering operation states and characteristics of the Li-ion BESS) and their coordination with the grid side controllers have been validated by means of simulation studies in the Sundom smart grid network, Vaasa, Finland.© The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.fi=vertaisarvioitu|en=peerReviewed