Mapping Energy Storage Physics to Application Economics

2016 ◽  
Author(s):  
Irene Berry ◽  
Glen Merfeld ◽  
Patrick Riley
Keyword(s):  
Energy Storage ◽  
Net Present Value ◽  
Financial Analysis ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Degradation Rates ◽  
Wide Range ◽  
Revenue Streams ◽  
Power Capability ◽  
Storage Type

The success of grid scale energy storage hinges on our ability to solve real problems economically. By mapping energy storage physics to application economics, this paper offers a technology neutral look at how energy storage can solve real problems. A value analytics methodology was developed that combines the physics of energy storage, application power commands, and market-specific economic constructs. This approach evaluates and optimizes the value of energy storage for specific projects by providing insight into the tradeoffs between the lifecycle costs and revenues. These analytics calculate the net present value (NPV) and internal rate of return (IRR) of select energy storage assets, markets, and applications by considering these key factors: • Duty profiles and control strategies • Market economics and revenue streams • Asset performance at cell, module, and system levels • Price projections including balance of plant (BOP) • Cycle and calendar life • Project length and financing terms The value analytics methodology combines three model streams. The first takes a high fidelity load profile (for example, the power output of a building, wind turbine, or solar farm), imposes a specific control strategy, and calculates revenue streams in a selected market. From this first model stream a storage power command is generated. This power command is fed into the second model stream that calculates the required size and price of a given storage type. Finally, a third model stream uses empirical life models to calculate degradation rates, replacement intervals, and maintenance costs. These are rolled up into a project specific financial analysis that forecasts project NPV and IRR. The underlying engine for this methodology is a large performance and price database of over 100 commercial and emerging energy storage assets that spans a wide range of technologies from ultracapacitors and flywheels to lead acid and lithium-ion batteries. The physics based performance of each asset is captured as an equivalent circuit model. These models are exercised to create performance envelops that describe the rate dependent power capability as a function of the type, amount, and age of installed storage. The energy storage value analytics described in this paper can be used to test key sensitivities. This methodology has been applied to standalone energy storage systems as well as the combination of energy storage with renewables and distributed power generation. As shown, the methodology is relevant for an even wider range of applications. Several solution maps will be shared that reveal, by market segment, the energy storage type, amount, and application that create the greatest customer value. This type of informed design and dispatch will solve real problems, create new value streams, and open new markets for grid scale energy storage.

Stacked value streams of hybrid energy storage systems in prosumer microgrids

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Azizat Olusola Gbadegesin ◽  
Yanxia Sun ◽  
Nnamdi I. Nwulu
Keyword(s):  
Energy Storage ◽  
Storage Systems ◽  
Lithium Ion ◽  
Payback Period ◽  
Solar Pv ◽  
Energy Storage Systems ◽  
Content Type ◽  
Hybrid Energy ◽  
Hybrid Energy Storage ◽  
Revenue Streams

Purpose Storage systems are deemed to be unable to provide revenue commensurate with the resources invested in them, thus discouraging their incorporation within power networks. In prosumer microgrids, storage systems can provide revenue from reduced grid consumption, energy arbitraging or when serving as back-up power. This study aims to examine stacking these revenue streams with the aim of making storage systems financially viable for inclusion in prosumer microgrids. Design/methodology/approach With the aim of reducing self-consumption and maximising revenue, the prosumer microgrid incorporating hybrid energy storage systems (HESS) and solar PV power is solved using the CPLEX solver of the Advanced Interactive Multidimensional Modeling Software (AIMMS). The financial analysis of the results is carried out to provide the payback periods of different system configurations of the prosumer microgrid. Findings The findings reveal that the payback period of the three HESS when minimising grid expenses during self-consumption alone and when compared with stacked revenue streams shows an improvement from 4.8–11.2 years to 2.4–6.6 years. With stacked HESS revenues, the supercapacitor-lithium ion battery HESS gave the shortest payback period of 2.31 years when solar PV power is at 75% penetration level. Originality/value Existing literature has considered revenue streams of storage systems at the electrical power transmission and distribution levels, but not for prosumer microgrids in particular. This study has captured these benefits and verified the profitability of stacking revenue from HESS to prosumer microgrids, using a case study.

Maximum Power Estimation of Lithium-Ion Batteries Accounting for Thermal and Electrical Constraints

2013 ◽  
Author(s):  
Youngki Kim ◽  
Shankar Mohan ◽  
Jason B. Siegel ◽  
Anna G. Stefanopoulou
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion ◽  
Operating Conditions ◽  
Thermal Systems ◽  
Model Inversion ◽  
Dynamic Constraints ◽  
Time Scale Separation ◽  
Wide Range ◽  
Temperature Constraint ◽  
Power Capability

Enforcement of constraints on the maximum deliverable power is essential to protect lithium-ion batteries from over-charge/discharge and overheating. This paper develops an algorithm to address the often overlooked temperature constraint in determining the power capability of battery systems. A prior knowledge of power capability provides dynamic constraints on currents and affords an additional control authority on the temperature of batteries. Power capability is estimated using a lumped electro-thermal model for cylindrical cells that has been validated over a wide range of operating conditions. The time scale separation between electrical and thermal systems is exploited in addressing the temperature constraint independent of voltage and state-of-charge (SOC) limits. Limiting currents and hence power capability are determined by a model-inversion technique, termed Algebraic Propagation (AP). Simulations are performed using realistic depleting currents to demonstrate the effectiveness of the proposed method.

scholarly journals Direct X-Ray Imaging as a Tool for Understanding Multiphysics Phenomena in Energy Storage

2016 ◽  
Vol 13 (3) ◽  
Author(s):  
George J. Nelson ◽  
Zachary K. van Zandt ◽  
Piyush D. Jibhakate
Keyword(s):  
Energy Storage ◽  
Lithium Ion ◽  
Ex Situ ◽  
Storage Device ◽  
Li Ion Batteries ◽  
X Ray ◽  
X Ray Imaging ◽  
Wide Range ◽  
Li Ion ◽  
Insight Into

The lithium-ion battery (LIB) has emerged as a key energy storage device for a wide range of applications, from consumer electronics to transportation. While LIBs have made key advancements in these areas, limitations remain for Li-ion batteries with respect to affordability, performance, and reliability. These challenges have encouraged the exploration for more advanced materials and novel chemistries to mitigate these limitations. The continued development of Li-ion and other advanced batteries is an inherently multiscale problem that couples electrochemistry, transport phenomena, mechanics, microstructural morphology, and device architecture. Observing the internal structure of batteries, both ex situ and during operation, provides a critical capability for further advancement of energy storage technology. X-ray imaging has been implemented to provide further insight into the mechanisms governing Li-ion batteries through several 2D and 3D techniques. Ex situ imaging has yielded microstructural data from both anode and cathode materials, providing insight into mesoscale structure and composition. Furthermore, since X-ray imaging is a nondestructive process studies have been conducted in situ and in operando to observe the mechanisms of operation as they occur. Data obtained with these methods has also been integrated into multiphysics models to predict and analyze electrode behavior. The following paper provides a brief review of X-ray imaging work related to Li-ion batteries and the opportunities these methods provide for the direct observation and analysis of the multiphysics behavior of battery materials.

scholarly journals Special Section on Mechanics of Electrochemical Energy Storage and Conversion

2021 ◽  
pp. 1-2
Author(s):  
Dibakar Datta ◽  
Partha Mukherjee ◽  
Wilson K. S. Chiu
Keyword(s):  
Fuel Cells ◽  
Energy Storage ◽  
Structural Parameters ◽  
Critical Role ◽  
Lithium Ion ◽  
Stress Generation ◽  
Electrochemical Energy Storage ◽  
Energy Storage And Conversion ◽  
Wide Range ◽  
Electrochemical Energy

Abstract The increasing population growth, depletion of natural resources, and rising energy demand have sparked enormous research endeavors in electrochemical energy storage and conversion. For example, rechargeable lithium-ion batteries are ubiquitous in everyday life. Mechanics plays a critical role in designing a wide range of energy technologies. The emerging field of electro-chemo-mechanics, the interplay of mechanics and electrochemistry, is crucial for understanding the coupled physiochemical processes. The electrochemical phenomena can govern the mechanical response such as stress generation, deformation, fracture initiation/propagation, elasticity, plasticity, etc. Similarly, mechanical phenomena also influence the electrochemical properties such as device reliability, durability, etc. Therefore, the in-depth mechanical study of electrochemical systems is urgently necessary for fundamental science and technological applications. Over the past few years, there has been significant progress in modeling, theories, and experimental characterizations of mechanical aspects of energy storage and conversion. This timely special issue addressed some recent advances in electro-chemo-mechanics. We have selected eight papers covering a wide range of issues in batteries and fuel cells such as (i) deformation, microstructural changes, creep, overcharge detection and prevention, optimization of structural parameters in batteries, (ii) temperature and load variations, metal-free cathode catalyst in fuel cells. The selected papers cover a gamut of electrochemical-mechanics centric research in energy storage and conversion.

Applications of Lithium-Ion Batteries in Offshore Oil & Gas: The Journey to Building a Low-Emissions Drilling Rig

2021 ◽  
Author(s):  
Stig Settemsdal
Keyword(s):  
Energy Storage ◽  
Lithium Ion Batteries ◽  
Electric Power ◽  
Power Plants ◽  
Oil And Gas ◽  
Lithium Ion ◽  
Combustion Efficiency ◽  
Drilling Rig ◽  
Wide Range ◽  
Offshore Oil

Abstract This paper discusses applications for lithium-ion batteries in an offshore oil and gas environment and describes how battery packs/energy storage can be applied in hybrid, diesel-electric power plants to create low-emissions drilling rigs. The incorporation of energy storage, particularly in direct current (DC) based power plants, can provide a wide range of benefits for operators, allowing them to reduce the runtime of onboard diesel engines and optimize combustion efficiency, thereby maximizing fuel utilization and reducing emissions. Batteries can also be used to create new redundancy schemes, as well as for peak shaving and blackout prevention. The West Mira semisubmersible installation in the North Sea was the world's first modern drilling rig to operate a low-emission hybrid (diesel-electric) power plant with lithium-ion batteries connected to the main power grid. The paper describes the energy storage solution that was implemented on the facility and discusses how considerations for safety and reliability were addressed.

Performance Analysis of Li-ion Battery Under Various Thermal and Load Conditions

2018 ◽  
Vol 16 (2) ◽  
Author(s):  
Krishnashis Chatterjee ◽  
Pradip Majumdar ◽  
David Schroeder ◽  
S. Rao Kilaparti
Keyword(s):  
Energy Storage ◽  
Internal Heat ◽  
Lithium Ion ◽  
Operating Conditions ◽  
Li Ion Battery ◽  
Discharge Rates ◽  
Wide Range ◽  
Li Ion ◽  
Load Conditions ◽  
Charge Discharge

In the recent years, with the rapid advancements made in the technologies of electric and hybrid electric vehicles, selecting suitable batteries has become a major factor. Among the batteries currently used for these types of vehicles, the lithium-ion battery leads the race. Apart from that, the energy gained from regenerative braking in locomotives and vehicles can be stored in batteries for later use for propulsion thus improving the fuel consumption and efficiency. But batteries can be subjected to a wide range of temperatures depending upon the operating conditions. Thus, a thorough knowledge of the battery performance over a wide range of temperatures and different load conditions is necessary for their successful employment in future technologies. In this context, this study aims to experimentally analyze the performance of Li-ion batteries by monitoring the charge–discharge rates, efficiencies, and energy storage capabilities under different environmental and load conditions. Sensors and thermal imaging camera were used to track the environment and battery temperatures, whereas the charge–discharge characteristics were analyzed using CADEX analyzer. The results show that the battery performance is inversely proportional to charge–discharge rates. This is because, at higher charge–discharge rates, the polarization losses increase thus increasing internal heat generation and battery temperature. Also, based on the efficiency and energy storage ability, the optimum performing conditions of the Li-ion battery are 30–40 °C (temperature) and 0.5 C (C-rate).

scholarly journals Net Present Value Analysis of a Hybrid Gas Engine-Energy Storage System in the Balancing Mechanism

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3816
Author(s):  
Farhad Anvari-Azar ◽  
Dani Strickland ◽  
Neil Filkin ◽  
Harry Townshend
Keyword(s):  
Energy Storage ◽  
Interest Rates ◽  
Hybrid System ◽  
Net Present Value ◽  
Lithium Ion ◽  
Present Value ◽  
Value Analysis ◽  
Gas Engine ◽  
Run Time ◽  
Pumped Storage

There is the potential for hybridised gas engine-energy storage systems to participate in the Balancing Mechanism (BM) by offering a product that marries the advantages of both units. The higher price offerings are currently dominated by pumped storage (PS) assets. Given their high-flexibility, PS plants mostly offer at higher prices, but respond quicker and can run for a smaller minimum run time than a gas engine on its own. The operation of the hybrid system must match the operation of the pumped storage plants, to be able to claim a space in this part of the BM market including meeting a minimum run time and minimum start time. The business case is dependent on battery costs which in turn depend on size and operational strategy. This paper uses a case study approach to estimate Net Present Value of a hybrid system. The paper uses a mixture of publicly available data and industrially provided data within its analysis. The paper concludes that battery cost and lifespan are still issues and that battery-engine hybrids are not economic at present. There is indication in the modelling that under very favorable conditions such as low compound interest rates, an acceptance of offers above 7 times/day and low gas price, it is possible to see a return on investment of a lithium ion-based battery-gas engine hybrid.

scholarly journals A Consensus Algorithm for Multi-Objective Battery Balancing

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4279
Author(s):  
Jorge Varela Barreras ◽  
Ricardo de Castro ◽  
Yihao Wan ◽  
Tomislav Dragicevic
Keyword(s):  
Decentralized Control ◽  
Low Voltage ◽  
Lithium Ion ◽  
Operating Conditions ◽  
Consensus Algorithm ◽  
Dissipative Systems ◽  
Multi Objective ◽  
Active Balancing ◽  
Degradation Rates ◽  
Power Capability

Batteries stacks are made of cells in certain series-parallel arrangements. Unfortunately, cell performance degrades over time in terms of capacity, internal resistance, or self-discharge rate. In addition, degradation rates are heterogeneous, leading to cell-to-cell variations. Balancing systems can be used to equalize those differences. Dissipative or non-dissipative systems, so-called passive or active balancing, can be used to equalize either voltage at end-of-charge, or state-of-charge (SOC) at all times. While passive balancing is broadly adopted by industry, active balancing has been mostly studied in academia. Beyond that, an emerging research field is multi-functional balancing, i.e., active balancing systems that pursue additional goals on top of SOC equalization, such as equalization of temperature, power capability, degradation rates, or losses minimization. Regardless of their functionality, balancing circuits are based either on centralized or decentralized control systems. Centralized control entails difficult expandability and single point of failure issues, while decentralized control has severe controllability limitations. As a shift in this paradigm, here we present for the first time a distributed multi-objective control algorithm, based on a multi-agent consensus algorithm. We implement and validate the control in simulations, considering an electro-thermal lithium-ion battery model and an electric vehicle model parameterized with experimental data. Our results show that our novel multi-functional balancing can enhance the performance of batteries with substantial cell-to-cell differences under the most demanding operating conditions, i.e., aggressive driving and DC fast charging (2C). Driving times are extended (>10%), charging times are reduced (>20%), maximum cell temperatures are decreased (>10 °C), temperature differences are lowered (~3 °C rms), and the occurrence of low voltage violations during driving is reduced (>5×), minimizing the need for power derating and enhancing the user experience. The algorithm is effective, scalable, flexible, and requires low implementation and tuning effort, resulting in an ideal candidate for industry adoption.

Charge Transport in Energy Storage and Conversion Devices

2018 ◽  
Vol 19 ◽  
pp. 1-17
Author(s):  
Volker Döge ◽  
Árpád W. Imre
Keyword(s):  
Energy Storage ◽  
Charge Transport ◽  
Specific Energy ◽  
High Power ◽  
Lithium Ion ◽  
High Energy ◽  
Transport Processes ◽  
Power Load ◽  
Power Capability ◽  
Electrical Loss

Charge transport is one of the most important phenomena, which directly influences the performance of the energy storage and conversation devices. In this work, the authors provide an overview of various rechargeable energy storage battery chemistries and designs, and discuss the charge transport processes related to power capability of the lithium-ion technology. The load distribution by parallel connection of high power batteries or supercapacitor and high-energy cells is discussed and general conclusions are provided. Thus, the reduced peak power load on the high-energy cells are approved by simulation and experiment in passive parallel circuitry of high power and a high energy lithium-ion cells. The definition and advantages of the earlier deduced electrical loss time are explained. It is shown, that at a constant C-rate, defined as the ratio of the applied current and the rated cell capacity in Ah, the electrical loss time has a direct linear correlation to efficiency, and that the electrical loss time allows a direct power capability comparison of various battery cell chemistries and systems. The power capability, specific energy, and energy density of the industry relevant Li-ion battery cells based on electrical loss time approach are summarized and the following conclusions made. Today prismatic cells reach the maximum specific energy of small cylindrical cells, at the same time showing a little bit better power capability, than the investigated high energy cylindrical cells.

scholarly journals Experimental Data Comparison of an Electric Minibus Equipped with Different Energy Storage Systems

Batteries ◽  
2020 ◽  
Vol 6 (2) ◽  
pp. 26
Author(s):  
Fabio Cignini ◽  
Antonino Genovese ◽  
Fernando Ortenzi ◽  
Adriano Alessandrini ◽  
Lorenzo Berzi ◽  
...  
Keyword(s):  
Energy Storage ◽  
Lithium Ion Batteries ◽  
Net Present Value ◽  
Storage Systems ◽  
Discharge Rate ◽  
Dynamic Performance ◽  
Lithium Ion ◽  
Real Data ◽  
Maximum Speed ◽  
Energy Storage Systems

As electric mobility becomes more important every day, scientific research brings us new solutions that increase performance, reduce financial and economic impacts and increase the market share of electric vehicles. Therefore, there is a necessity to compare technical and economic aspects of different technologies for each transport application. This article presents a comparison of three bus prototypes in terms of dynamic performance. The analysis is based on the collection of real data (acceleration, maximum speed and energy consumption) under different settings. Each developed prototype uses the same bus chassis but relies on different energy storage systems. Results show that the dynamic bus performance is independent on the three energy storage technologies, whereas technologies affect the management costs, charging time and available range. An extensive experimental analysis reveals that the bus equipped with a hybrid storage (lithium-ion batteries and supercapacitors) had the most favorable net present value, in comparison with storage composed of only lead–acid or lithium-ion batteries. This result is due to the greater life of lithium-ion batteries and to the capability of supercapacitors, which reduce both batteries depth of discharge and discharge rate.

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