Optimal Regulation Response of Batteries Under Cycle Aging Mechanisms

When providing frequency regulation in a pay-for-performance market, batteries need to carefully balance the trade-off between following regulation signals and their degradation costs in real-time. Existing battery control strategies either do not consider mismatch penalties in pay-for-performance markets, or cannot accurately account for battery cycle aging mechanism during operation. This paper derives an online control policy that minimizes a battery owner's operating cost for providing frequency regulation in a pay-for-performance market. The proposed policy considers an accurate electrochemical battery cycle aging model, and is applicable to most types of battery cells. It has a threshold structure, and achieves near-optimal performance with respect to an offline controller that has complete future information. We explicitly characterize this gap and show it is independent of the duration of operation. Simulation results with both synthetic and real regulation traces are conducted to illustrate the theoretical results

Factoring the Cycle Aging Cost of Batteries Participating in Electricity Markets

When participating in electricity markets, owners of battery energy storage systems must bid in such a way that their revenues will at least cover their true cost of operation. Since cycle aging of battery cells represents a substantial part of this operating cost, the cost of battery degradation must be factored in these bids. However, existing models of battery degradation either do not fit market clearing software or do not reflect the actual battery aging mechanism. In this paper we model battery cycle aging using a piecewise linear cost function, an approach that provides a close approximation of the cycle aging mechanism of electrochemical batteries and can be incorporated easily into existing market dispatch programs. By defining the marginal aging cost of each battery cycle, we can assess the actual operating profitability of batteries. A case study demonstrates the effectiveness of the proposed model in maximizing the operating profit of a battery energy storage system taking part in the ISO New England energy and reserve markets

A Convex Cycle-based Degradation Model for Battery Energy Storage Planning and Operation

A vital aspect in energy storage planning and operation is to accurately model its operational cost, which mainly comes from the battery cell degradation. Battery degradation can be viewed as a complex material fatigue process that based on stress cycles. Rainflow algorithm is a popular way for cycle identification in material fatigue process, and has been extensively used in battery degradation assessment. However, the rainflow algorithm does not have a closed form, which makes the major difficulty to include it in optimization. In this paper, we prove the rainflow cycle-based cost is convex. Convexity enables the proposed degradation model to be incorporated in different battery optimization problems and guarantees the solution quality. We provide a subgradient algorithm to solve the problem. A case study on PJM regulation market demonstrates the effectiveness of the proposed degradation model in maximizing the battery operating profits as well as extending its lifetime

Techno-Economic Analysis and Optimal Control of Battery Storage for Frequency Control Services, Applied to the German Market

Optimal investment in battery energy storage systems, taking into account degradation, sizing and control, is crucial for the deployment of battery storage, of which providing frequency control is one of the major applications. In this paper, we present a holistic, data-driven framework to determine the optimal investment, size and controller of a battery storage system providing frequency control. We optimised the controller towards minimum degradation and electricity costs over its lifetime, while ensuring the delivery of frequency control services compliant with regulatory requirements. We adopted a detailed battery model, considering the dynamics and degradation when exposed to actual frequency data. Further, we used a stochastic optimisation objective while constraining the probability on unavailability to deliver the frequency control service. Through a thorough analysis, we were able to decrease the amount of data needed and thereby decrease the execution time while keeping the approximation error within limits. Using the proposed framework, we performed a techno-economic analysis of a battery providing 1 MW capacity in the German primary frequency control market. Results showed that a battery rated at 1.6 MW, 1.6 MWh has the highest net present value, yet this configuration is only profitable if costs are low enough or in case future frequency control prices do not decline too much. It transpires that calendar ageing drives battery degradation, whereas cycle ageing has less impact.Comment: Submitted to Applied Energ

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

Application of a simplified thermal-electric model of a sodium-nickel chloride battery energy storage system to a real case residential prosumer

Recently, power system customers have changed the way they interact with public networks, playing a more and more active role. End-users first installed local small-size generating units, and now they are being equipped with storage devices to increase the self-consumption rate. By suitably managing local resources, the provision of ancillary services and aggregations among several end-users are expected evolutions in the near future. In the upcoming market of household-sized storage devices, sodium-nickel chloride technology seems to be an interesting alternative to lead-acid and lithium-ion batteries. To accurately investigate the operation of the NaNiCl2 battery system at the residential level, a suitable thermoelectric model has been developed by the authors, starting from the results of laboratory tests. The behavior of the battery internal temperature has been characterized. Then, the designed model has been used to evaluate the economic profitability in installing a storage system in the case that end-users are already equipped with a photovoltaic unit. To obtain realistic results, real field measurements of customer consumption and solar radiation have been considered. A concrete interest in adopting the sodium-nickel chloride technology at the residential level is confirmed, taking into account the achievable benefits in terms of economic income, back-up supply, and increased indifference to the evolution of the electricity market

Improved testing strategies from standards for new growing battery applications in the industrial and e-mobility sectors

In the current energy challenges, related to both climate change and the sudden rise in energy prices, batteries plays a key role in providing and storing energy. Before batteries are sent to market, the batteries are repeatedly subjected to different types of tests since it is crucial to verify that the performance and safety of these technologies are ensured in the different applications. This master’s thesis is dedicated to improving battery testing methodologies to address the growing industrial and e-mobility sectors. By identifying and tackling gaps in existing international standards, this research aims to enhance the link between battery testing and real-life operation of batteries, with the final objective of developing an adaptable testing framework for AVL, a leading powertrain systems company. The study investigates the factors driving battery testing, the impact of diverse applications on battery characteristics, and the need for refined testing strategies. The methodology includes a comprehensive background study of battery behavior, a review of battery performance parameters, and an analysis of prevailing testing procedures. The research results in the development of an algorithm for adaptable synthetic duty cycles, along with new testing procedures for capacity and cycle lifetime tests. The optimization of testing procedures enables AVL to take a prominent role in electrification and battery testing, offering more accurate and effective testing solutions. Ultimately, this contributes to a more sustainable industry by facilitating the secure and efficient use of battery technologies in emerging applications, particularly within the transport secto