Modeling, Simulation, and Analysis of Lithium-Ion Batteries for Grid-Scale Applications

Lithium-ion batteries have become universally present in daily life, being used across a wide range of portable consumer electronics. These batteries are advantageous compared to other forms of energy storage due to their high energy density and long cycle life. These characteristics make lithium-ion batteries advantageous for many new and developing applications that require large scale energy storage such as electric vehicles and the utility grid. Typical uses for lithium-ion batteries require consistent cycling patterns that are predictable and easy to approximate across all uses, but new large scale applications will have much more dynamic demands. The cycling patterns for electric vehicles will vary based on each individuals driving patterns and batteries used for energy storage in the grid must be flexible enough to account for continuous fluctuations in demand and generation with little advanced notice. Along with these requirements, large scale applications do not want to sacrifice on cycle life and need to know that adding batteries will make operational and economic sense in specific cases. It is not possible to experimentally validate every possible driving pattern or grid storage need because of the great expense of these large systems and the long timescale required for testing. Therefore modeling of these systems is advantageous to help study specific application constraints and understand how lithium-ion batteries operate under those constraints. A systems level model is developed to study lithium-ion battery systems for use with solar energy (in a solar-battery hybrid system) and electric vehicles. Electrochemical based battery models are used as a component within larger systems. To facilitate fast simulation a single step perturbation and switch method is outlined for increasing the speed and robustness of solving the systems of DAEs that result from the systems level model. Operational characteristics are studied for lithium-ion batteries used to store solar energy within the electric grid. Different grid demands are tested against the system model to better understand the best uses for the solar-battery hybrid system. Both generic site studies and site specific studies were conducted. Solar irradiance data from 2010-2014 was obtained from 10 US based sites and used as an input to the system model to understand how the same system will operate differently at various locations. Technological benefits such as system autonomy were simulated for each site as well as economic benefits based on a time-of-use pricing scenario. These models included the growth of the solid-electrolyte interface layer on the battery electrodes to measure capacity fade during operation. This capacity fade mechanism allowed tracking of the site specific effects on battery life. A systems level model for an electric vehicle was also developed to simulate the growth of the SEI layer caused from different types of driving cycles and charging patterns. Results from both system models are presented along with an optimization method for the solar-battery hybrid model. In addition to modeling, experimental tests of LiFePO4 lithium-ion battery cells were conducted to measure capacity fade associated with different types of cycling throughout a batterys life. Cycling protocols were tested to study traditional capacity fade and also to focus on increasing a cells lifetime benefit through application switching

Energy Storage Technologies for Smoothing Power Fluctuations in Marine Current Turbines

With regard to marine renewable energies, significant electrical power can be extracted from marine tidal current. However, the power harnessed by a marine current turbine varies due to the periodicity of the tidal phenomenon and could be highly fluctuant caused by swell effect. To improve the power quality and make the marine current generation system more reliable, energy storage systems will play a crucial role. In this paper, the power fluctuation phenomenon is described and the state of art of energy storage technologies is presented. Characteristics of various energy storage technologies are analyzed and compared for marine application. The omparison shows that high-energy batteries like sodiumsulphur battery and flow battery are favorable for smoothing the long-period power fluctuation due to the tide phenomenon while supercapacitors and flywheels are suitable for eliminating short-period power disturbances due to swell or turbulence phenomena. It means that hybrid storage technologies are needed for achieving optimal performance in marine current energy systems

Economic optimization of component sizing for residential battery storage systems

Battery energy storage systems (BESS) coupled with rooftop-mounted residential photovoltaic (PV) generation, designated as PV-BESS, draw increasing attention and market penetration as more and more such systems become available. The manifold BESS deployed to date rely on a variety of different battery technologies, show a great variation of battery size, and power electronics dimensioning. However, given today's high investment costs of BESS, a well-matched design and adequate sizing of the storage systems are prerequisites to allow profitability for the end-user. The economic viability of a PV-BESS depends also on the battery operation, storage technology, and aging of the system. In this paper, a general method for comprehensive PV-BESS techno-economic analysis and optimization is presented and applied to the state-of-art PV-BESS to determine its optimal parameters. Using a linear optimization method, a cost-optimal sizing of the battery and power electronics is derived based on solar energy availability and local demand. At the same time, the power flow optimization reveals the best storage operation patterns considering a trade-off between energy purchase, feed-in remuneration, and battery aging. Using up to date technology-specific aging information and the investment cost of battery and inverter systems, three mature battery chemistries are compared; a lead-acid (PbA) system and two lithium-ion systems, one with lithium-iron-phosphate (LFP) and another with lithium-nickel-manganese-cobalt (NMC) cathode. The results show that different storage technology and component sizing provide the best economic performances, depending on the scenario of load demand and PV generation.Web of Science107art. no. 83

Improving optimal control of grid-connected lithium-ion batteries through more accurate battery and degradation modelling

The increased deployment of intermittent renewable energy generators opens up opportunities for grid-connected energy storage. Batteries offer significant flexibility but are relatively expensive at present. Battery lifetime is a key factor in the business case, and it depends on usage, but most techno-economic analyses do not account for this. For the first time, this paper quantifies the annual benefits of grid-connected batteries including realistic physical dynamics and nonlinear electrochemical degradation. Three lithium-ion battery models of increasing realism are formulated, and the predicted degradation of each is compared with a large-scale experimental degradation data set (Mat4Bat). A respective improvement in RMS capacity prediction error from 11\% to 5\% is found by increasing the model accuracy. The three models are then used within an optimal control algorithm to perform price arbitrage over one year, including degradation. Results show that the revenue can be increased substantially while degradation can be reduced by using more realistic models. The estimated best case profit using a sophisticated model is a 175% improvement compared with the simplest model. This illustrates that using a simplistic battery model in a techno-economic assessment of grid-connected batteries might substantially underestimate the business case and lead to erroneous conclusions

Energy Storage Systems for Traction and Renewable Energy Applications

Energy storage systems are the set of technologies used to store various forms of energy, and by necessity, can be discharged. Energy storage technologies have a wide range of characteristics and specifications. Like any other technology, each type of energy storage has its pros and cons. Depending on the application, it is crucial to perform a tradeoff study between the various energy storage options to choose the optimal solution based on the key performance objectives and various aspects of those technologies. The purpose of this thesis is to present a thorough literature review of the various energy storage options highlighting the key tradeoffs involved. This thesis focuses on evaluating energy storage options for traction and renewable energy applicationsHybrid Electric Vehicles (HEVs) is one key application space driving breakthroughs in energy storage technologies. The focus though has been typically on using one type of energy storage systems. This thesis investigates the impact of combining several types of batteries with ultracapacitor. A case study of integrating two energy storage systems in a series-parallel hybrid electric vehicle is simulated by using MATLAB-SIMULINK software.The other key application space is renewable energy especially wind and solar. Due to the intermittent nature of renewable energy sources, energy storage is a must to achieve the required power quality. Therefore, this thesis aims to investigate different cases of combining different types of energy storage with wind and solar. Hybrid Optimization Model for Electric Renewables (HOMER) software is utilized to study the economic and sizing aspects in each case