We consider the problem of decentralized control of reactive power provided by distributed energy resources for voltage support in the distribution grid. We assume that the reactance matrix of the grid is unknown and potentially time-varying. We present a decentralized adaptive controller in which the reactive power at each inverter is set using a potentially heterogeneous droop curve and analyze the stability and the steady-state error of the resulting system. The effectiveness of the controller is validated in simulations using a modified version of the IEEE 13-bus and a 8500-node test system.
The penetration of wind power generation into the power grid has been accelerated in recent times due to the aggressive emission targets set by governments and other regulatory authorities. Although wind power has the advantage of being environment-friendly, wind as a resource is intermittent in nature. In addition, wind power contributes little inertia to the system as most wind turbines are connected to the grid via power electronic converters. These negative aspects of wind power pose serious challenges to the frequency security of power systems as penetration increases. In this work, an approach is proposed where an energy storage system (ESS) is used to mitigate frequency security issues of wind-integrated systems. ESSs are well equipped to supply virtual inertia to the grid due to their fast-acting nature, thus replenishing some of the energy storage capability of displaced inertial generation. In this work, a probabilistic approach is proposed to estimate the amount of inertia required by a system to ensure frequency security. Reduction in total system inertia due to the displacement of conventional synchronous generation by wind power generation is considered in this approach, while also taking into account the loss of inertia due to forced outages of conventional units. Monte Carlo simulation is employed for implementing the probabilistic estimation of system inertia. An ESS is then sized appropriately, using the system swing equation, to compensate for the lost inertia. The uncertainty associated with wind energy is modeled into the framework using an autoregressive moving average technique. Effects of increasing the system peak load and changing the wind profile on the expected system inertia are studied to illustrate various factors that might affect system frequency security. The proposed method is validated using the IEEE 39-bus test system.
Increase in the number and frequency of widespread outages in recent years has been directly linked to drastic climate change necessitating better preparedness for outage mitigation. Severe weather conditions are experienced more frequently and on larger scales, challenging system operation and recovery time after an outage. The impact is more evident and concerning than before, considering the increased dependency on electricity in all aspects of our lives.
Variable energy resources (VERs) like wind and solar are the future of electricity generation as we gradually phase out fossil fuel due to environmental concerns. Nations across the globe are also making significant strides in integrating VERs into their power grids as we strive toward a greener future. However, integration of VERs leads to several challenges due to their variable nature and low inertia characteristics. In this paper, we discuss the hurdles faced by the power grid due to high penetration of wind power generation and how energy storage system (ESSs) can be used at the grid-level to overcome these hurdles. We propose a new planning strategy using which ESSs can be sized appropriately to provide inertial support as well as aid in variability mitigation, thus minimizing load curtailment. A probabilistic framework is developed for this purpose, which takes into consideration the outage of generators and the replacement of conventional units with wind farms. Wind speed is modeled using an autoregressive moving average technique. The efficacy of the proposed methodology is demonstrated on the WSCC 9-bus test system.
This paper presents a literature review on current practices and trends on cyberphysical security of grid-connected battery energy storage systems (BESSs). Energy storage is critical to the operation of Smart Grids powered by intermittent renewable energy resources. To achieve this goal, utility-scale and consumer-scale BESS will have to be fully integrated into power systems operations, providing ancillary services and performing functions to improve grid reliability, balance power and demand, among others. This vision of the future power grid will only become a reality if BESS are able to operate in a coordinated way with other grid entities, thus requiring significant communication capabilities. The pervasive networking infrastructure necessary to fully leverage the potential of storage increases the attack surface for cyberthreats, and the unique characteristics of battery systems pose challenges for cyberphysical security. This paper discusses a number of such threats, their associated attack vectors, detection methods, protective measures, research gaps in the literature and future research trends.
Rechargeable alkaline Zn–MnO2 (RAM) batteries are a promising candidate for grid-scale energy storage owing to their high theoretical energy density rivaling lithium-ion systems (∼400 Wh/L), relatively safe aqueous electrolyte, established supply chain, and projected costs below $100/kWh at scale. In practice, however, many fundamental chemical and physical processes at both electrodes make it difficult to achieve commercially competitive energy density and cycle life. This review presents a detailed and timely analysis of the constituent materials, current commercial status, electrode processes, and performance-limiting factors of RAM batteries. We also examine recently reported strategies in RAM and related systems to address these issues through additives and modifications to the electrode materials and electrolyte, special ion-selective separators and/or coatings, and unconventional cycling protocols. We conclude with a critical summary of these developments and discussion of how future studies should be focused toward the goal of energy-dense, scalable, and cost-effective RAM systems.
Energy storage systems (ESSs) are being deployed widely due to numerous benefits including operational flexibility, high ramping capability, and decreasing costs. This study investigates the economic benefits provided by battery ESSs when they are deployed for market-related applications, considering the battery degradation cost. A comprehensive investment planning framework is presented, which estimates the maximum revenue that the ESS can generate over its lifetime and provides the necessary tools to investors for aiding the decision making process regarding an ESS project. The applications chosen for this study are energy arbitrage and frequency regulation. Lithium-ion batteries are considered due to their wide popularity arising from high efficiency, high energy density, and declining costs. A new degradation cost model based on energy throughput and cycle count is developed for Lithium-ion batteries participating in electricity markets. The lifetime revenue of ESS is calculated considering battery degradation and a cost-benefit analysis is performed to provide investors with an estimate of the net present value, return on investment and payback period. The effect of considering the degradation cost on the estimated revenue is also studied. The proposed approach is demonstrated on the IEEE Reliability Test System and historical data from PJM Interconnection.
Changes in the Demand Profile and a growing role for renewable and distributed generation are leading to rapid evolution in the electric grid. These changes are beginning to considerably strain the transmission and distribution infrastructure. Utilities are increasingly recognizing that the integration of energy storage in the grid infrastructure will help manage intermittency and improve grid reliability. This recognition, coupled with the proliferation of state-level renewable portfolio standards and rapidly declining lithium-ion (Li-ion) battery costs, has led to a surge in the deployment of battery energy storage systems (BESSs). Additionally, although BESSs represented less than 1% of grid-scale energy storage in the United States in 2019, they are the preferred technology to meet growing demand because they are modular, scalable, and easy to deploy across diverse use cases and geographic locations.
Large-scale integration of energy storage on the electric grid will be essential to enabling greater penetration of intermittent renewable energy sources, modernizing the grid for increased flexibility security, reliability, and resilience, and enabling cleaner forms of transportation. The purpose of this report is to summarize Sandia's research and capabilities in energy storage and to provide a preliminary roadmap for future efforts in this area that can address the ongoing program needs of DOE and the nation. Mission and vision statements are first presented followed by an overview of the organizational structure at Sandia that provides support and activities in energy storage. Then, a summary of Sandia's energy storage capabilities is presented by technology, including battery storage and materials, power conversion and electronics, subsurface-based energy storage, thermal/thermochemical energy storage, hydrogen storage, data analytics/systems optimization/controls, safety of energy storage systems, and testing/demonstrations/model validation. A summary of identified gaps and needs is also presented for each technology and capability.
Li-ion batteries currently dominate electrochemical energy storage for grid-scale applications, but there are promising aqueous battery technologies on the path to commercial adoption. Though aqueous batteries are considered lower risk, they can still undergo problematic degradation processes. This perspective details the degradation that aqueous batteries can experience during normal and abusive operation, and how these processes can even lead to cascading failure. We outline methods for studying these phenomena at the material and single-cell level. Considering reliability and safety studies early in technology development will facilitate translation of emerging aqueous batteries from the lab to the field.
Energy storage systems with Li-ion batteries are increasingly deployed to maintain a robust and resilient grid and facilitate the integration of renewable energy resources. However, appropriate selection of cells for different applications is difficult due to limited public data comparing the most commonly used off-the-shelf Li-ion chemistries under the same operating conditions. This article details a multi-year cycling study of commercial LiFePO4 (LFP), LiNixCoyAl1-x-yO2 (NCA), and LiNixMnyCo1-x-yO2 (NMC) cells, varying the discharge rate, depth of discharge (DOD), and environment temperature. The capacity and discharge energy retention, as well as the round-trip efficiency, were compared. Even when operated within manufacturer specifications, the range of cycling conditions had a profound effect on cell degradation, with time to reach 80% capacity varying by thousands of hours and cycle counts among cells of each chemistry. The degradation of cells in this study was compared to that of similar cells in previous studies to identify universal trends and to provide a standard deviation for performance. All cycling files have been made publicly available at batteryarchive.org, a recently developed repository for visualization and comparison of battery data, to facilitate future experimental and modeling efforts.
This paper takes a critical look at the materials aspects of thermal runaway of lithium-ion batteries and correlates contributions from individual cell components to thermal runaway trends. An accelerating rate calorimeter (ARC) was used to evaluate commercial lithium-ion cells based on LiCoO2 (LCO), LiFePO4 (LFP), and LiNixCoyAl1-x-yO2 (NCA) at various states of charge (SOC). Cells were disassembled and the component properties were evaluated by thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and temperature-resolved X-ray diffraction (TR-XRD). The whole cell thermal runaway onset temperature decreases and peak heating rate increases with SOC due to cathode destabilization. LCO and NCA cathodes are metastable, with NCA cells exhibiting the highest thermal runaway rates. By contrast, the LFP cathode is stable to >500 °C, even when charged. For anodes, the decomposition and whole cell self-heating onset temperature is generally independent of SOC. DSC exotherm onset temperatures of the anodes were generally within 10 °C of the onset of self-heating in whole cell ARC. However, onset temperatures of the cathodes were typically observed above the ARC onset of whole cell runaway. This systematic evaluation of component to whole cell degradation provides a scientific basis for future thermal modeling and design of safer cells.
In this paper, we study, analyze, and validate some important zero-dimensional physics-based models for vanadium redox batch cell (VRBC) systems and formulate an adequate physics-based model that can predict the battery performance accurately. In the model formulation process, a systems approach to multiple parameters estimation has been conducted using VRBC systems at low C-rates (~C/30). In this batch cell system, the effect of ions' crossover through the membrane is dominant, and therefore, the capacity loss phenomena can be explicitly observed. Paradoxically, this means that using the batch system might be a better approach for identifying a more suitable model describing the effect of ions transport. Next, we propose an efficient systems approach, which enables to help understand the battery performance quickly by estimating all parameters of the battery system. Finally, open source codes, executable files, and experimental data are provided to enable people's access to robust and accurate models and optimizers. In battery simulations, different models and optimizers describing the same systems produce different values of the estimated parameters. Providing an open access platform can accelerate the process to arrive at robust models and optimizers by continuous modification from the users' side.
A generic constant-efficiency energy flow model is commonly used in techno-economic analyses of grid energy storage systems. In practice, charge and discharge efficiencies of energy storage systems depend on state of charge, temperature, and charge/discharge powers. Furthermore, the operating characteristics of energy storage devices are technology specific. Therefore, generic constant-efficiency energy flow models do not accurately capture the system performance. In this work, we propose to use technology-specific nonlinear energy flow models based on nonlinear operating characteristics of the storage devices. These models are incorporated into an optimization problem to find the optimal market participation of energy storage systems. We develop a dynamic programming method to solve the optimization problem and perform two case studies for maximizing the revenue of a vanadium redox flow battery (VRFB) and a Li-ion battery system in Pennsylvania New Jersey Maryland (PJM) interconnection's energy and frequency regulation markets.
In this paper, we study, analyze, and validate some important zero-dimensional physics-based models for vanadium redox batch cell (VRBC) systems and formulate an adequate physics-based model that can predict the battery performance accurately. In the model formulation process, a systems approach to multiple parameters estimation has been conducted using VRBC systems at low C-rates (∼C/30). In this batch cell system, the effect of ions’ crossover through the membrane is dominant, and therefore, the capacity loss phenomena can be explicitly observed. Paradoxically, this means that using the batch system might be a better approach for identifying a more suitable model describing the effect of ions transport. Next, we propose an efficient systems approach, which enables to help understand the battery performance quickly by estimating all parameters of the battery system. Finally, open source codes, executable files, and experimental data are provided to enable people’s access to robust and accurate models and optimizers. In battery simulations, different models and optimizers describing the same systems produce different values of the estimated parameters. Providing an open access platform can accelerate the process to arrive at robust models and optimizers by continuous modification from the users’ side.
Reliable engineering quality, safety, and performance are essential for a successful energy-storage project. The commercial energy-storage industry is entering its most formative period, which will impact the arc of the industry's development for years to come. Project announcements are increasing in both frequency and scale. Energy-storage systems (ESSs) are establishing themselves as a viable option for deployment across the entire electricity infrastructure as grid-connected energy-storage assets or in combination with other grid assets, such as hybrid generators. How the industry will evolve-in direction and degree-will depend largely on building a firm foundation of sound engineering requirements into project expectations.
The role of power electronics in the utility grid is continually expanding. As converter design processes mature and new advanced materials become available, the pace of industry adoption is poised to accelerate. Looking forward, we can envision a future in which power electronics are as integral to grid functionality as the transformer is today. The Enabling Advanced Power Electronics Technologies for the Next Generation Electric Utility Grid Workshop was organized by Sandia National Laboratories and held in Albuquerque, New Mexico, July 17 - 18, 2018 . The workshop helped attendees to gain a broader understanding of power electronics R&D needs—from materials to systems—for the next generation electric utility grid. This report summarizes discussions and presentations from the workshop and identifies opportunities for future efforts.
Techno-economic analyses of energy storage currently use constant-efficiency energy flow models. In practice, charge/discharge efficiency of energy storage varies as a function of state-of-charge, temperature, charge/discharge power. Therefore, using the constant-efficiency energy flow models will cause suboptimal results. This work focuses on incorporating nonlinear energy flow models based on nonlinear efficiency models in the revenue maximization problem of energy storage. Dynamic programming is used to solve the optimization problem. A case studies is conducted to maximize the revenue of a Vanadium Redox Flow Battery (VRFB) system in PJM's energy and frequency regulation market.
Mathematical models of Redox Flow Batteries (RFBs) can be used to analyze cell performance, optimize battery operation, and control the energy storage system efficiently. Among many other models, physics-based electrochemical models are capable of predicting internal states of the battery, such as temperature, state-of-charge, and state-of-health. In the models, estimating parameters is an important step that can study, analyze, and validate the models using experimental data. A common practice is to determine these parameters either through conducting experiments or based on the information available in the literature. However, it is not easy to investigate all proper parameters for the models through this way, and there are occasions when important information, such as diffusion coefficients and rate constants of ions, has not been studied. Also, the parameters needed for modeling charge-discharge are not always available. In this paper, an efficient way to estimate parameters of physics-based redox battery models will be proposed. This paper also demonstrates that the proposed approach can study and analyze aspects of capacity loss/fade, kinetics, and transport phenomena of the RFB system.
At a low depth of discharge, the performance of rechargeable alkaline Zn/MnO2 batteries is determined by the concomitant processes of hydrogen ion insertion and electro-reduction in the solid phase of γ-MnO2. Ab initio computational methods based on density functional theory (DFT) were applied to study the mechanism of hydrogen ion insertion into the pyrolusite (β), ramsdellite (R), and nsutite (γ) MnO2 polymorphs. It was found that hydrogen ion insertion induced significant distortion in the crystal structures of MnO2 polymorphs. Calculations demonstrated that the hydrogen ions inserted into γ-MnO2 initially occupied the larger 2×1 ramsdellite tunnels. The protonated form of γ-MnO2 was found to be stable over the discharge range during which up to two hydrogen ions were inserted into each 2×1 tunnel. At the same time, the study showed that the insertion of hydrogen ions into the 1×1 pyrolusite tunnels of γ-MnO2 created instability leading to the structural breakdown of γ-MnO2. The results of this study explain the presence of groutite (α-MnOOH) and the absence of manganite (γ-MnOOH) among the reaction products of partially reduced γ-MnO2
For nearly a century, global power systems have focused on three key functions: Generating, transmitting, and distributing electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load-despite variability in load on time scales ranging from subsecond disturbances to multiyear trends. With the increasing role of variable generation from wind and solar, the retirement of fossil-fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.
Today, the stability of the electric power grid is maintained through real time balancing of generation and demand. Grid scale energy storage systems are increasingly being deployed to provide grid operators the flexibility needed to maintain this balance. Energy storage also imparts resiliency and robustness to the grid infrastructure. Over the last few years, there has been a significant increase in the deployment of large scale energy storage systems. This growth has been driven by improvements in the cost and performance of energy storage technologies and the need to accommodate distributed generation, as well as incentives and government mandates. Energy management systems (EMSs) and optimization methods are required to effectively and safely utilize energy storage as a flexible grid asset that can provide multiple grid services. The EMS needs to be able to accommodate a variety of use cases and regulatory environments. In this paper, we provide a brief history of grid-scale energy storage, an overview of EMS architectures, and a summary of the leading applications for storage. These serve as a foundation for a discussion of EMS optimization methods and design.
While the low cost and strong safety record of lead-acid batteries make them an appealing option compared to lithium-ion technologies for stationary storage, they can be rapidly degraded by the extended periods of high rate, partial state-of-charge operation required in such applications. Degradation occurs primarily through a process called hard sulfation, where large PbSO4 crystals are formed on the negative battery plates, hindering charge acceptance and reducing battery capacity. Various researchers have found that the addition of some forms of excess carbon to the negative active mass in lead-acid batteries can mitigate hard sulfation, but the mechanism through which this is accomplished is unclear. In this work, the effect of carbon composition and morphology was explored by characterizing four discrete types of carbon additives, then evaluating their effect when added to the negative electrodes within a traditional valve-regulated lead-acid battery design. The cycle life for the carbon modified cells was significantly larger than an unmodified control, with cells containing a mixture of graphitic carbon and carbon black yielding the greatest improvement. The carbons also impacted other electrochemical aspects of the battery (e.g., float current, capacity, etc.) as well as physical characteristics of the negative active mass, such as the specific surface area.
Lithium-ion batteries are a central technology to our daily lives with widespread use in mobile devices and electric vehicles. These batteries are also beginning to be widely used in electric grid infrastructure support applications which have stringent safety and reliability requirements. Typically, electrochemical performance data is not available for modelers to validate their simulations, mechanisms, and algorithms for lithium-ion battery performance and lifetime. In this paper, we report on the electrochemical performance of commercial 18650 cells at a variety of temperatures and discharge currents. We found that LiFePO4 is temperature tolerant for discharge currents at or below 10 A whereas LiCoO2, LiNixCoyAl1-x-yO2, and LiNi0.80Mn0.15Co0.05O2 exhibited optimal electrochemical performance when the temperature is maintained at 15◦C. LiNixCoyAl1-x-yO2 showed signs of lithium plating at lower temperatures, evidenced by irreversible capacity loss and emergence of a high-voltage differential capacity peak. Furthermore, all cells need to be monitored for self-heating, as environment temperature and high discharge currents may elicit an unintended abuse condition. Overall, this study shows that lithium-ion batteries are highly application-specific and electrochemical behavior must be well understood for safe and reliable operation. Additionally, data collected in this study is available for anyone to download for further analysis and model validation.
We report a simple method to synthesize V 4+ (VO 2+ ) electrolytes as feedstock for all- vanadium redox flow batteries (RFB). By dissolving V 2 O 5 in aqueous HCl and H 2 SO 4 , subsequently adding glycerol as a reducing agent, we have demonstrated an inexpensive route for electrolyte synthesis to concentrations >2.5 M V 4+ (VO 2+ ). Electrochemical analysis and testing of laboratory scale RFB demonstrate improved thermal stability across a wider temperature range (-10-65 degC) for V 4+ (VO 2+ ) electrolytes in HCl compared to in H 2 SO 4 electrolytes.
Here, we report a simple method to synthesize V4+(VO2+) electrolytes as feedstock for all vanadium redox flow batteries (RFB). By dissolving V2O5 in aqueous HCl and subsequently adding glycerol as a reducing agent, we have demonstrated an inexpensive route for electrolyte synthesis to concentrations >2.5 M V4+ (VO2+). Electrochemical analysis and testing of laboratory scale RFB demonstrate improved thermal stability across a wider temperature range (-10-65°C) for V4+(VO2+) electrolytes in HCl compared to in H2SO4 electrolytes.
