Lithium-ion Battery Energy Storage Research Articles

Homogeneous Adsorption of Multiple Potassiation Products of Red Phosphorus Anode toward Stable Potassium Storage

Homogeneous Adsorption of Multiple Potassiation Products of Red Phosphorus Anode toward Stable Potassium Storage

Freeze-drying synthesis of metal element (Zr, Cr, Co)–doped Li4Ti5O12 anode material for enhanced electrochemical energy storage in lithium-ion batteries

Freeze-drying synthesis of metal element (Zr, Cr, Co)–doped Li4Ti5O12 anode material for enhanced electrochemical energy storage in lithium-ion batteries

DEVELOPMENT OF ULTRA CAPACITOR BASED REGENERATIVE BRAKING SYSTEM FOR ELECTRIC VEHICLES

Regenerative braking is a technique for converting a moving vehicle's kinetic energy into usable form while slowing it down. When an automobile brakes violently, it usually emits heat. If we could conserve energy rather than waste it, that would be amazing, right? That's where regenerative braking technology comes in handy, especially for electric vehicles. It stores the wasted energy in a battery or ultra-capacitor, so it can be used later to start or accelerate the vehicle. In our project, we looked at how effective regenerative braking is during both braking and starting modes. We compared starting the motor with a battery, ultra-capacitor, or a combination of both (HESS), and also analyzed how storing energy during braking works with these systems. Although not all of the regenerated energy is reinvested in the battery, the motor acts as a generator, charging the vehicle's battery. To move the vehicle forward, regenerative braking uses the kinetic energy it temporarily stores during deceleration. We used a lithium-ion battery and ultra-capacitor module energy storage system coupled to a BLDC motor via a converter. These brakes help batteries last longer without needing to be charged externally. They enable efficient power transfer during regenerative braking and acceleration. Our project discusses whether regenerative braking increases or decreases efficiency. of state of charge of battery and ultra- capacitor when starting and braking applied in discharging(in running of motor) and charging(in regenerative braking of motor). And also BLDC motor speed control in starting and braking mode. The model is simulated using MATLAB Simulink software. Keywords: Regenerative braking, kinetic energy, electric vehicles, energy storage, battery, ultra-capacitor, starting mode, braking mode, Hybrid Energy Storage System (HESS), efficiency, motor generator

Model predictive control-based energy management system for an isolated electro-thermal microgrid in the Amazon region of Ecuador

Access to electricity is a fundamental key to developing countries' growth. Microgrids (MG) have become potential solutions to provide energy to isolated rural areas in a safe and environmentally friendly way. Therefore, proposals for alternative solutions to bridge the electrification gap in the Ecuadorian Amazon – which has the most significant percentage of its population without access to electricity – are of significant interest. Consequently, this paper presents the design of an Energy Management System (EMS) based on Model Predictive Control (MPC) for an isolated electro-thermal microgrid comprising a photovoltaic generator, a diesel generator, a lithium-ion battery Energy Storage System (ESS), electrical loads, and a domestic hot water system. The EMS aims to supply energy reliably and safely, minimize the MG's operation costs, and extend the ESS's useful life while satisfying the end users' comfort. This study includes an estimated degradation model for the ESS’s State of Health (SOH), an essential parameter contributing to reducing the microgrid's operating costs in the long term. Simulation results using one-year data present the influence of the prediction horizon on the MG’s scheduling. In addition, the benefits of the proposed EMS are highlighted by comparing it with the results achieved by a Unit Commitment approach, where it is demonstrated that the proposed EMS presents a reduction in MG operating costs and greenhouse gas emissions while maximizing the utilization of renewable energy and extending the lifespan of the ESS. Finally, an experimental validation, using a Typhoon Hardware-in-the-loop HIL-402 device in real-time operation, stands out the effectiveness and feasibility of the proposed MPC-based EMS.

Integration of Carbon-Based Nanomaterials for Hybrid Energy Storage in Lithium-Ion Batteries

Hybrid energy storage systems benefit significantly from incorporating nanoparticles containing metallic oxides, potassium phosphate, chemical compounds, and sulfides. The current technological problem is to increase the device’s electrical capacity without decreasing its energy capacity. The energy storage capacity of lithium-ion cells has been greatly improved by the use of tiny carbon particles owing to their conductive qualities, extensive specific surface area, customizable form, and intrinsic resilience. Further biologically active layouts, thinner ion-diffusion dimensions, and increased aboard carrier-/charge-transport motion are all made possible by incorporating effective bi-dimensional nanomaterials into future-oriented battery packs. For applications like lithium-ion batteries and electrochemical capacitors, this research presents carbon-based energy storage (CES) using a support vector machine (SVM) incorporating Particle Swarm Optimization (CES-SVM) to investigate the long-term stability of nanoparticle alloy forms of a specific shape and chemical makeup. This paper provides a potential improvement to the intermittent particle swarm optimization technique and its accompanying algorithmic architecture. Hybrid nanocomposites have been successfully synthesized, allowing the easy synthetic pathway and unique growth of nanostructuring technology to be used for electrodes with outstanding electrochemical effectiveness in conventional lithium-ion batteries. This paper shows how the cell’s conductivity, the electrode/electrolyte contact, and ion diffusion all affect impedance performance. Carbonaceous electrodes for lithium-ion battery systems, electrochemical storage units, and related combination devices are examined as a final area.

3D hierarchical mesoporous carbon with P and N dual-doped as electrocatalyst host for high-performance Li-S batteries

Lithium-sulfur (Li-S) batteries are thought to be the most likely to replace traditional intercalation-based lithium-ion batteries for energy storage devices because of its high theoretical mass energy density. However, the poor cycling stability resulting from dissolution of polysulfide intermediates (Li2Sx, 3≤ x ≤8) greatly hampers the commercial applications. Herein, a 3D hierarchical mesoporous carbon with P/N dual-doped (3D-PNMC) as a catalytic host for sulfur electrode is successfully prepared. The as-prepared Li-S batteries with S@3D-PNMC cathode deliver a specific capacity of 1326 mAh g−1 at 0.1 C and the corresponding area capacity of up to 5.57 mAh cm−2. And also, the calculative capacity decay rate of S@3D-PNMC cathode is only 0.05% per cycle, which significantly lower than that of S@C electrode (0.21%). The satisfactory electrochemical performance can be ascribed to the 3D host not only provides space for the active sulfur loading, but also accelerates the electron transfer inside the electrode. Especially, electroactive sites created by phosphorus and nitrogen doping can effectively improve the electrochemical reaction kinetics to achieving long cycling stability.

High specific capacity of Li3V2(PO4)3/C glass-ceramic with ultralow carbon content

Li3V2(PO4)3 glass-ceramic, as an intrinsic insulator, necessitates compositing with conductive carbon to function as a cathode for energy storage in lithium-ion batteries, inevitably reducing the specific energy of the final devices. This study synthesized Li3V2(PO4)3/C composite with an ultralow carbon content (1.39 wt%) using a sol-gel method with glucomannan as a soft template. The Li3V2(PO4)3/C composite cathode achieved an initial discharge specific capacity of 128.22 mA h g−1 at 0.1 C, which is 97.14% of the theoretical specific capacity. Additionally, it demonstrated excellent rate capabilities, with 106.20 mA h g−1 at 5 C and 78.91 mA h g−1 at 10 C, as well as long-term cycling stability, with 114.94 mA h g−1 at 2 C and retaining 92.09% capacity after 500 cycles. The ultralow carbon content feature will contribute to the commercialization of cathodes. This work provides a novel direction for the design and fabrication of new electrode materials.

Adsorption behavior of CuO doped GeS monolayer on the thermal runaway gas evolution in lithium battery energy storage systems

Considering that the thermal runaway failure of lithium battery energy storage system will cause serious safety accidents, and lithium battery thermal runaway will precipitate various detectable gases through the safety gas valve. Effective monitoring of the precipitated gas can ensure the safe operation of the energy storage system. In this study, the adsorption behavior of CuO-GeS towards the main precipitated gases CO, CO2, CH4, and C2H4 in Lithium battery before thermal runaway is systematically studied based on DFT. The adsorption structure, DOS, DCD, and ELF are analyzed to explore the interactions between CuO-GeS monolayer and the gases. The results show that CuO-GeS monolayer achieves strong adsorption of CO and C2H4 and highly sensitive monitoring of CO2 and CH4. Furthermore, the relative molecular mass ratios of CxHy and CxHy-1F (x = 1, 2 y=2, 4, 6) gases to doped CuO can satisfy Smoothing Spline with adsorption energy and charge transfer, which can be used to estimate the adsorption properties of the homologous gases. The potential application of CuO-GeS monolayer in lithium battery energy storage systems lays a theoretical research foundation for the adsorption and detection of thermal runaway gas in lithium battery energy storage systems.

Control Optimization Method for Ship Direct Current Microgrid Based on Impedance Reshaping

In response to the constant power negative impedance characteristics on the load side of a ship DC microgrid, leading to voltage oscillation issues in the DC bus, this paper proposes a control optimization method based on impedance reshaping using bus voltage feedback. First, a simplified small-signal diagram of a lithium battery energy storage system converter is analyzed. Combining active damping control technology, an impedance regulator is introduced, and its parameters are optimized to effectively reduce the output impedance magnitude on the power source side. Subsequently, a ship DC microgrid simulation model is constructed using MATLAB R2022a/Simulink for validation, and comparative analysis is conducted on the anti-interference ability of the DC bus voltage before and after impedance reshaping. Finally, a model is built on a semi-physical simulation platform to experimentally verify the proposed method. The research results indicate that the proposed control optimization method can effectively increase the system’s stability margin, suppress DC bus oscillations, and enhance the anti-interference ability of the ship DC microgrid’s bus voltage when facing significant power load variations.

The Cobalt Supply Chain and Environmental Life Cycle Impacts of Lithium-Ion Battery Energy Storage Systems

Lithium-ion batteries (LIBs) deployed in battery energy storage systems (BESS) can reduce the carbon intensity of the electricity-generating sector and improve environmental sustainability. The aim of this study is to use life cycle assessment (LCA) modeling, using data from peer-reviewed literature and public and private sources, to quantify environmental impacts along the supply chain for cobalt, a crucial component in many types of LIBs. The study seeks to understand where in the life cycle stage the environmental impacts are highest, thus highlighting actions that can be taken to improve sustainability of the LIB supply chain. The system boundary for this LCA is cradle-to-gate. Impact assessment follows ReCiPe Midpoint (H) 2016. We assume a 30-year modeling period, with augmentation occurring at the end of the 3rd, 7th, and 14th years of operations, before a complete replacement in the 21st year. Three refinery locations (China, Canada, and Finland), a range of ore grades, and five battery chemistries (NMC111, NMC532, NMC622, NMC811, and NCA) are used in scenarios to better estimate their effect on the life cycle impacts. Insights from the study are that impacts along nearly all pathways increase according to an inverse power-law relationship with ore grade; refining outside of China can reduce global warming potential (GWP) by over 12%; and GWP impacts for cobalt used in NCA and other NMC battery chemistries are 63% and 45–74% lower than in NMC111, respectively. When analyzed on a single-score basis, marine and freshwater ecotoxicity are prominent. For an ore grade of 0.3%, the GWP values for the Canada route decrease at a rate of 58% to 65%, and those for Finland route decrease by 71% to 76% from the base case. Statistical analysis shows that cobalt content in the battery is the highest predictor (R2 = 0.988), followed by the ore grade (R2 = 0.966) and refining location (R2 = 0.766), when assessed for correlation individually. The results presented here point to areas where environmental burdens of LIBs can be reduced, and thus they are helpful to policy and investment decision makers.

Transfer operation ride though control strategy of the aircraft power supply system with lithium battery energy storage

The aircraft power supply system turns towards multi-source, and transfer operation will likely happen during flight missions and fault conditions. The transfer may lead to voltage interruptions and current surges, adversely affecting power quality. This paper proposes incorporating a lithium battery energy storage system (ESS) into the aircraft high-voltage direct current (HVDC) power system. The ESS employs a voltage control model with a lower voltage reference base, facilitating a smooth transfer operation during power interruptions. This approach reduces voltage fluctuations in the power supply system, enhances power quality, and enables seamless power transfer during the transfer operation.

Techno-economic analysis of renewable energy generation at the South Pole

Transitioning from fossil-fuel power generation to renewable energy generation and energy storage in remote locations has the potential to reduce both carbon emissions and cost. This study presents a techno-economic analysis for implementation of a hybrid renewable energy system at the South Pole in Antarctica, which currently hosts several high-energy physics experiments with nontrivial power needs. A tailored model of resource availability and economics for solar photovoltaics, wind turbine generators, lithium-ion energy storage, and long-duration energy storage at this site is explored in different combinations with and without existing diesel energy generation. The Renewable Energy Integration and Optimization (REopt) platform is used to determine the optimal system component sizing and the associated system economics and environmental benefit. We find that the least-cost system includes all three energy generation sources and lithium-ion energy storage. For an example steady-state load of 170 kW, this hybrid system includes 180 kW-DC of photovoltaic panels, 570 kW of wind turbines, and a 3.4 MWh lithium-ion battery energy storage system. This system reduces diesel consumption by 95% compared to an all-diesel configuration, resulting in approximately 1200 metric tons of carbon footprint avoided annually. Over the course of a 15-year analysis period the reduced diesel usage leads to a net savings of 57 million United States dollars, with a time to payback of approximately two years. All the scenarios modeled show that the transition to renewables is highly cost effective under the unique economics and constraints of this extremely remote site.

Physics-Aware Degradation Model of Lithium-ion Battery Energy Storage for Techno-Economic Studies in Power Systems

Power system operation and planning decisions for lithium-ion battery energy storage systems are mainly derived using their simplified linear models. While these models are computationally simple, they have limitations in how they estimate battery degradation, either using the energy throughput or the Rainflow method. This paper proposes a hybrid approach for lithium-ion battery system modeling suitable for use in power system studies that enhances representation of battery degradation at a reasonable computational cost. The proposed hybrid model combines a physics-based model for improved degradation estimates with a simple and linear energy reservoir model commonly used to represent a battery storage system. The advantage of constructing the battery model with this vision is that it allows its smooth integration into the mixed-integer optimization frameworks. The proposed model is evaluated using both power- and energy-based use cases from the electrical grid. The simulations demonstrate that degradation could be reduced by 45% compared to other modeling strategies while generating the same level of operation profits. The net result of using the proposed hybrid model could be an extended lifespan through better informed planning and operating decisions for energy storage assets.

Inertia Emulation-Oriented Evaluation Method of Sustaining Power Boundary for Lithium-Ion Battery Energy Storage System

Inertia Emulation-Oriented Evaluation Method of Sustaining Power Boundary for Lithium-Ion Battery Energy Storage System

Diagnostics of Safety Hazardous Ageing Conditions for Commercial Lithium-Ion Pouch Cells

It is well-known that Lithium-ion cells can have safety issues. A large number of battery fire incidents have been reported the last years within e.g. battery energy storage systems [1], electric and hybrid-electric ships [2], electric vehicles and mobile phones [3]. The causes for these incidents are numerous and can include internal shortage of the Li-ion cell, external shortage of the battery system, over-heating or over-charging. All these causes result in overheating which can lead to an eventual thermal runaway which again could lead to a severe fire and explosion. We report on changes in thermal stability due to different ageing mechanisms in abstract Lian (#176439) and in Lian [4]. A decrease in thermal stability due to battery ageing could be hazardous and might be an end-of-life criteria. It is thus of vital importance to develop diagnostic tools capable of detecting a potentially hazardous drop in thermal stability for aged lithium-ion cells.This study is based on results from a battery life study performed on a large renowned Li-ion pouch cell with an initial capacity of 64 Ah. More than 100 cells were tested following a selected test matrix including different temperatures, currents, and State-of-Charge windows. All cells were tested until they reached a remaining capacity of between 60 to 80 % State-of-Health. A large dataset with diagnostic data was recorded during ageing, including e.g., dQ/dV (incremental capacity analysis) and DC resistances. Thermal properties of selected new and aged cells were studied in an Accelerated Rate Calorimeter (ARC), see Lian (abstract #176439). A post-mortem study of selected new and aged cells was performed to relate the collected diagnostics data to different ageing paths and safety properties. Based on detailed cell characterization, an experimental parameter set for an electrochemical pseudo-two-dimensional (P2D) model was established.Based on the dQ/dV (ICA) analysis, a distinct change in diagnostic patterns was observed for cells aged and cycled at low temperature (5-15 °C) compared to cells cycled at higher temperatures (35 -45 °C). This correlates to the observed differences in thermal stability reported by Lian (abstract #176439). To verify the observed ageing mechanisms from the post-mortem studies, emulated ageing modelling was performed both based on the Alawa tool [5], as well as the P2D model coupled with different ageing mechanisms. References McKinnon, M.B., S. DeCrance, and S. Kerber, Four Firefigheters Injured In Lithium-Ion Battery Energy Storage System Explosion - Arizona, U. Laboratories, Editor. 2020, Underwriters Laboratories: Columbia, MD. p. 66.Norwegian Maritime Authority, Supporting preliminary findings after battery incident. 2019: Norwegian Maritime Authority.BBC, Samsung confirms battery faults as cause of Note 7 fires, in BBC. 2017, BBC.Lian, T., et al., (Invited) Changes in Thermal Stability of Cyclic Aged Commercial Lithium-Ion Cells. ECS Transactions, 2019. 89(1): p. 73-81.Dubarry, M., et al., State of health battery estimator enabling degradation diagnosis: Model and algorithm description. Journal of Power Sources, 2017. 360: p. 59-69.

An Open-Source Energy Arbitrage Model Involving Price Bands for Risk Hedging with Imperfect Price Signals

The increased uptake of variable renewable energy sources has increased electricity price volatility in many energy pool markets, providing an opportunity for storage systems to profit through energy arbitrage. Comparison between the cost or value of storage systems engaging in energy arbitrage should be performed on a levelised basis due to differences in system lifetime. Existing energy arbitrage models with bid/offer curves and imperfect forecasting are typically computationally expensive and are impractical for calculating lifetime levelised cost metrics. In this work, an open-source modular energy arbitrage model with bid and offer curve inputs was developed for a lithium-ion battery energy storage system (BESS) and pumped hydro system (PHS) to analyse lifetime levelised cost and revenue. The mixed integer linear program scheduling module included a new piece-wise linearised description of PHS charging behaviour for rapid optimisation. A one-at-a-time sensitivity analysis indicated that levelised cost and revenue were highly sensitive to discharging efficiency. In a case study based on Australia’s National Electricity Market, imperfect forecasting with no risk hedging was found to increase levelised costs by up to 24% and decrease levelised revenue by up to 50% relative to perfect price forecasting, despite 95% of prices being forecast to be within $35/MWh of the actual trading price. BESS levelised costs were more significantly correlated with consistent low risk bids (Kendall Tau-b of 0.75), since the undiscounted capital costs contribute to a larger proportion of the overall costs than in the PHS systems.

Grid-connected lithium-ion battery energy storage system towards sustainable energy: A patent landscape analysis and technology updates

Presently, as the world advances rapidly towards achieving net-zero emissions, lithium-ion battery (LIB) energy storage systems (ESS) have emerged as a critical component in the transition away from fossil fuel-based energy generation, offering immense potential in achieving a sustainable environment. This study conducts an in-depth analysis of grid-connected LIB ESS patents published from 1998 to 2022, aiming to comprehend essential developments and trends in the technology landscape while identifying key players and inventors. Employing extensive keyword searches within the Lens database, 95 patent documents were extracted along with the bibliometric data. The research highlights two prominent factors in the field of grid-connected LIB ESS patents. Firstly, a detailed patent bibliometric analysis including patent growth trends, keyword analysis, patent distribution over jurisdiction, and subject categories was presented. Moreover, the research identifies key owners, inventors and hierarchical jurisdiction in patent document publishing and evaluates the possibilities for future research sustainability. Secondly, detailed updates regarding technological advancements that are driving sustainable grid-connected LIB ESS development in various sectors such as; gird connected ESS, power conversion system (PCS), energy management system (EMS) and transportation sector are provided. The study concluded that the patents related to grid-connected ESS, minimizing voltage and frequency regulation to achieve grid stability and EMS of LIB are the key trending topics in the field of grid-connected LIB ESS. The comprehensive analysis not only illuminates crucial trends but also provides valuable guidance to future researchers and industry stakeholders, facilitating the path towards sustainable grid-connected LIB ESS and paving the way for a more environmentally conscious energy landscape.

Techno-economic assessment of small-size residential solar PV + battery systems under different tariff structures in Brazil

This paper proposes a methodology to assess the energy and economic impact of adopting small-scale residential photovoltaic (PV) systems paired with lithium-ion battery energy storage (BESS) systems in single-family homes, under the current energy feed-in legislation. The suggested methodology was applied to a case study of a prosumer unit (PU) in Brazil. Data from energy bills, measured PV generation, BESS behaviour, and energy consumption were analysed to compare different viewpoints and estimate key economic indicators. As a result, the PV + BESS combination increases residential users' energy self-consumption and self-sufficiency, resulting in respective increases of 15 % and 2 %. Under the conventional tariff, adopting the PV + BESS system led to an average 29 % reduction in electricity costs compared to scenarios without PV + BESS. Furthermore, by transitioning to the white tariff mode in conjunction with PV + BESS, the PU achieved a 49 % reduction. This result emphasizes the advantages of time-of-use adoption for PV + BESS consumers. A greater discrepancy between tariff periods enhances the feasibility of storing off-peak energy for use during peak periods. Currently, BESS implementation costs impede competitiveness, with attractive LCOS metrics achieved only at costs below $600.00/kWh and MRAs below 9 %. BESS + PV lowers generation costs compared to off-peak rates, increasing the viability of shared usage. Integrating PV + BESS systems with rate switching significantly diminishes electricity expenses. The substantial BESS implementation cost necessitates a noteworthy rate differential for viability, which could potentially impact non-PV and non-BESS consumers.

Smart Lithium-Ion Battery Monitoring in Electric Vehicles: An AI-Empowered Digital Twin Approach

This paper presents a transformative methodology that harnesses the power of digital twin (DT) technology for the advanced condition monitoring of lithium-ion batteries (LIBs) in electric vehicles (EVs). In contrast to conventional solutions, our approach eliminates the need to calibrate sensors or add additional hardware circuits. The digital replica works seamlessly alongside the embedded battery management system (BMS) in an EV, delivering real-time signals for monitoring. Our system is a significant step forward in ensuring the efficiency and sustainability of EVs, which play an essential role in reducing carbon emissions. A core innovation lies in the integration of the digital twin into the battery monitoring process, reshaping the landscape of energy storage and alternative power sources such as lithium-ion batteries. Our comprehensive system leverages a cloud-based IoT network and combines both physical and digital components to provide a holistic solution. The physical side encompasses offline modeling, where a long short-term memory (LSTM) algorithm trained with various learning rates (LRs) and optimized by three types of optimizers ensures precise state-of-charge (SOC) predictions. On the digital side, the digital twin takes center stage, enabling the real-time monitoring and prediction of battery activity. A particularly innovative aspect of our approach is the utilization of a time-series generative adversarial network (TS-GAN) to generate synthetic data that seamlessly complement the monitoring process. This pioneering use of a TS-GAN offers an effective solution to the challenge of limited real-time data availability, thus enhancing the system’s predictive capabilities. By seamlessly integrating these physical and digital elements, our system enables the precise analysis and prediction of battery behavior. This innovation—particularly the application of a TS-GAN for data generation—significantly contributes to optimizing battery performance, enhancing safety, and extending the longevity of lithium-ion batteries in EVs. Furthermore, the model developed in this research serves as a benchmark for future digital energy storage in lithium-ion batteries and comprehensive energy utilization. According to statistical tests, the model has a high level of precision. Its exceptional safety performance and reduced energy consumption offer promising prospects for sustainable and efficient energy solutions. This paper signifies a pivotal step towards realizing a cleaner and more sustainable future through advanced EV battery management.

Health-aware coordinate long-term and short-term operation for BESS in energy and frequency regulation markets

The penetration of renewable energy in modern power systems is still increasing. Battery energy storage can rapidly respond to a dispatch order and is expected to provide multiple auxiliary services. However, deep charging cycles have negative impacts on battery health. This paper presents a health-aware long-term operation strategy for lithium-ion battery energy storage participating in the energy and frequency regulation markets. The strategy determines the capacity bounds that can be bid in the energy and frequency regulation markets and updates these bounds every three months, aiming to preserve battery health and increase market revenue. A long-term operational modeling framework is proposed to address the multi-timescale nature, integrating frequency control, energy arbitrage, and the evolution of battery degradation in a holistic model. A nonlinear degradation model is developed to approximate the health impact of main stress factors, which captures the nonlinearity of three-stage capacity degradation process caused by the formation of solid electrolyte interphase film and lithium plating. For intraday operation, a two-scale stochastic programming model is proposed, in which the market bidding and automatic generation control response are simulated in the timescales of one hour and two seconds, respectively. This simulation based method is closer to industrial practice, as it accounts for various factors in BESS operation. For the seasonal update of the capacity allocation strategy, a dynamic programming problem is established and solved based on the nonlinear degradation model and the daily revenue obtained from simulation of intraday operation; the capacity allocation strategy is determined from the renowned Principle of Optimality by Bellman. This two timescale modeling framework captures the interaction between short-term operation strategy and long-term degradation process. Numerical simulations validate that the proposed method can slow down battery degradation and increase lifetime revenue.