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This fire protection engineering technical report discusses and presents the properties, data, and safety of select lithium-ion batteries. Lithium-ion batteries have increased in usage and a fire scenario analysis must be created for each situation where they may be introduced in buildings to determine the risk associated if a battery failure were to occur.
The power systems have faced progressively more demanding operational requirements over the last two decades. Several factors contribute to these challenging operating conditions, including load growth, aging infrastructure, increasing penetrations of distributed energy resources (DERs), electrification of the economy, and policy initiatives such as decarbonization. The power system and its components must provide high operational flexibility to mitigate these challenges. For example, the proliferation of intermittent DERs such as wind and solar has increased the need for conventional generation assets like hydropower plants to respond to sudden load-generation imbalances. The higher flexibility requirements for hydropower plants cause more wear and tear, potentially shortening the useful lifespan of hydropower turbines. To reduce the need for hydropower plants to follow sudden changes in the dispatch signal, we investigate their combined operation with the energy storage systems (ESSs; “ESS-based hybridization”). Our analyses focuses on improving the lifespan of hydropower plants through ESS-based hybridization. Wear and tear on hydropower turbines (particularly Francis turbines) is modeled using a loss-of-life concept that is based on damage experienced by the turbine due to various cycles of operation. Then, we show that using ESSs to offset some of the high variation increases the remaining life of the hydropower plants. To demonstrate this, a few modeling tools were developed for this work: (1) a dynamic model for various components of the turbine and its governor; (2) a control strategy that assigns a slow-varying dispatch signal to a hydropower unit versus a fastmoving signal to ESS, such that the overall power request remains the same; and (3) models for the financial analysis to quantify the economic merits of such a framework. We used the models we developed to analyze the dispatch pattern of an actual hydropower plant with a power output of 50 MW and a head height of 152 m. This work showed that ESS-based hybridization could extend the life of the hydropower plant by 5% on average. This extension in life was then used to estimate the economic benefit in terms of cost deferrals associated with hydropower plant maintenance and replacement: on average, $3.6 million. Sensitivity analysis with respect to the size of ESS and cost of turbines was performed to show the variation in benefits over the range of turbine costs and ESS sizes. Crucially, stacking damage reduction and lifetime extension with other ESS value streams such as providing ancillary services could substantially increase the financial benefits of ESS-based hybridization. The higher costs associated with ESS of appropriate size would make more financial sense when multiple value streams are stacked and co-optimized to extract the maximum benefit. This dimension will be explored in future work.
In 2019, the United States installed 13.3 gigawatts of solar energy production capacity. This demand for solar will continually increase as the phasing out of fossil fuels continue. As the demand for solar energy grows, so does the demand to store this generated energy. It is projected that by 2035 the global demand for stationary energy storage will reach the terawatt scale. So, scalable solutions with suitable thermal management systems are required to meet future demand. Yotta Solar has developed an ESS system, the Yotta LEAF, that provides solar energy storage without increasing the footprint of solar arrays. This is particularly useful in applications with limited space (e.g., building roof) and where large scale batteries require strong requirements for fire suppression systems. As part of the Wells Fargo Innovation Incubator (IN2), the National Renewable Energy Laboratory (NREL) has conducted a third-party technology validation of Yotta's alpha prototype. The report includes the objectives, technology description, methodology, and results from experiments conducted at the Thermal Transfer Facility (TTF) at NREL.
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The penetration of wind energy has increased significantly in the power grid in recent times. Although wind is abundant, environment-friendly, and cheap, it is variable in nature and does not contribute to system inertia as much as conventional synchronous generators. Coupled with the low inertia contribution, the generation intermittency of wind power leads to reliability and stability issues in the power system. Energy storage systems (ESSs) are among the most prominent alternatives to alleviate these concerns associated with high wind penetration. This paper proposes a planning strategy to size ESS for the reliability and frequency security of wind-rich power grids. A probabilistic methodology for ESS sizing is developed utilizing a composite reliability-based framework with sequential Monte Carlo simulation (MCS). The MCS generates composite reliability indices for the power system, which are employed to obtain the capacity for a reliability energy storage system (RESS). Simultaneously, the MCS-derived probability of synchronization of conventional generators is integrated into an analytical approach for sizing a frequency support energy storage system (FESS). The effect of wind farm dispersion across geographical regions is incorporated in the framework to study possible reductions in the ESS size while maintaining the system reliability and frequency security. Furthermore, the efficacy of the proposed strategy is demonstrated on the RTS-GMLC test system.
Jurisdictions around the world are enacting and enforcing an increasing number of policies to fight climate change, leading to higher penetration of variable renewable energy (VRE) and energy storage systems (ESSs) in the power grid. One of the biggest challenges associated with this process is the evaluation of the appropriate amount of ESS required to mitigate the variability of the VREs and achieve decarbonization goals of a particular jurisdiction. This report presents methodologies developed and results obtained for determining the minimum amount of ESS required to adequately serve load in a system where fossil fueled generators are being replaced by VREs over the next two decades. This technical analysis is performed by Sandia National Laboratories for the DOE Office of Electricity Energy Storage Program in collaboration with the Illinois Commerce Commission (ICC). The Illinois MISO Zone 4 is used as a case study. Several boundary conditions are investigated in this analysis including capacity adequacy and energy adequacy to determine the quantity of ESS required for MISO Zone 4. Multiple scenarios are designed and evaluated to incorporate the impact of varying capacity values of VREs and on the resource adequacy of the system. Several retirement scenarios involving fossil-fueled assets are also considered. Based on the current plans of new additions and retirements of generating assets, the results of the technical analysis indicate that Illinois MISO Zone 4 will require a significant quantity of ESS to satisfy their electricity demand over the next two decades.
The role of energy storage systems (ESSs) is becoming increasingly important for today’s electric power systems. Unavailability of an ESS assigned to critical grid services may cause unwanted disruption of those services and hence, may have a significant techno-economic impact. Like any physical equipment, an ESS is vulnerable to various types of faults. Failure of one or more strings in a multistring ESS does not have to be the cause of shutting down the entire ESS. It can still operate with a partial number of strings and continue providing critical services to the grid, if there are no reliability or safety issues and is acceptable under applicable standards. However, it is important to make sure that the control strategies are adaptable to the changes in ESS capacity caused by failed strings. Also, depending on the previous operation and type of failure, the reallocation of duty cycle burden among available strings could be non-uniform. These complexities suggest that mitigation of the impact of partial failure in multistring ESSs is not trivial and needs careful consideration. This is the topic of this paper. The proposed work investigates the impact of partial failure of a large multistring ESS on the assigned service and develops strategies to adjust the ESS control duty cycles for reducing such impacts. In doing so, the paper proposes a novel two-stage framework that plans for the multistring failure using robust optimization theory and then adjusts in real-time using a rule-based algorithm, based on the real-time information on the power availability of the string. Illustrations provided in this work are based on frequency regulation use-case, which is a common application for many utility-scale ESSs. A 750 kilowatt (kW)/1500 kilowatt-hour (kWh) 3-string ESS is used for the demonstration in this work and the efficacy of the proposed method is demonstrated and compared against methods that do not incorporate string failure in their strategy. In particular, here we show that revenue loss of 93% can be incurred when partial string failure is not included in operation and planning. These losses in revenue are reduced by 60% with the proposed method.
Many developing countries suffer from a shortage of clean energy-water production, causing significant dependency on imported fossil fuel to meet the local energy and freshwater demands. Furthermore, when planning a 100 % renewable energy system (RES) to match the energy demand on an hourly basis, the RES is usually oversized. Hence, unavoidable large amounts of excess energy would be generated during hours of high production, low demand, and fully charged energy storage systems (ESSs). Hence, using Jordan as a case study, this work proposes a novel integrated system of wind, solar photovoltaic (PV), and lithium-ion ESS to match 100 % of the country's energy demand while using the excess generated power to drive reverse osmosis water desalination plants to match the demand of freshwater as well. Furthermore, the remaining excess energy is used for producing green hydrogen. A techno-economic optimizer was developed to show that this concept is indeed feasible. Here, the model was used to scan Jordan for the fitting sites of the highest demand-supply matching and the lowest levelized cost of electricity (LCOE), simultaneously. Three different integration scenarios are presented, namely PV-ESS, wind-ESS, and hybrid PV-wind-ESS RESs. The hybrid system showed the best performance, especially compared to the wind-ESS RES, in terms of total installed capacity (33.37 GW), LCOE (0.0492 USD/kWh), specific water cost (0.3629 USD/m 3 ), and energy and water demand-supply fractions (99.47 and 96.16 %, respectively). Storing desalinated water in natural aquifers was found to be a favorable option to enhance the performance of the three systems, where stored water by the end of the year was sufficient to cover the freshwater requirements for several following years. Finally, the remaining excess energy is used to produce green hydrogen with an annual production of up to 1.37 million tons and a specific cost down to 1.08 USD/kg.
The ever-growing higher penetration of distributed energy resources (DERs) in low-voltage (LV) distribution systems brings both opportunities and challenges to voltage support and regulation. This paper proposes a deep reinforcement learning (DRL)-based scheduling scheme of energy storage systems (ESSs) to mitigate system voltage deviations in unbalanced LV distribution networks. The ESS-based voltage regulation problem is formulated as a multi-stage quadratic stochastic program, with the objective of minimizing the expected total daily voltage regulation cost while satisfying operational constraints. While existing voltage regulation methods are mostly focused on onetime- step control, this paper explores a day-horizon systemwide voltage regulation problem. In other words, the size of action and state spaces are extremely high-dimensional and need to be delicately handled. Furthermore, in order to overcome the difficulty of modeling uncertainties and develop a realtime solution, a learn-to-schedule feedback control framework is proposed by adapting the problem to a model-free DRL setting. The proposed algorithm is tested on a customized 6-bus system and a modified IEEE 34-bus system. Simulation results validate the effectiveness and near-optimality of voltage regulation by ESS in comparison with a deterministic quadratic program solution.
An improved PV system control method is proposed to reduce nanogrid operation costs in this paper. A model including it various components such as photovoltaic (PV) systems, energy storage systems (ESSs), gateways, and household loads is considered with the constraints of the ESS, PV irradiance from real data, and household load. We designed an optimal economic dispatch strategy with an improved PV system control method. Combining the proposed optimal economic dispatch and PV system control strategies, it can improve the control performance for both transient and steady-state responses thereby enabling the maximum power to be extracted from the PV. Consequently, the PV power is maximized, which allows the ESS to use less power and sell the surplus to external power sources, which means the proposed method decreases the nanogrid operation costs. Furthermore, this performance is verified via nanogrid simulations and PV experimental kit.
Most existing coal-fired power plants were designed for sustained operation at full load to maximize efficiency, reliability, and revenues. Depending on plant type and design, these plants can adjust output within a fixed range in response to plant or market conditions. The need for flexibility driven by increased penetration of variable and non-dispatchable power generation such as wind and solar is shifting traditional mission profile of thermoelectric power plants in three ways: more frequent shutdowns when market or grid conditions warrant, more aggressive load ramp rates (rate of output change), and lower minimum sustainable load, which provides a wider operating range and helps avoid costly plant shutdowns. The recent studies have shown that flexibility of a coal-fired power plant can be improved by the energy storage. The objective of this project was to analyze a set of energy storage options (technologies) and determine their impact on flexibility and economics of a representative coal-fired power plant. The effect of five Energy Storage Systems (ESSs) integrated with a coal power plant on plant flexibility and economics was investigated in this study. The results obtained in this project and presented in this report showed that ESS integrated with a thermal power plant improves plant flexibility and participation in the Energy and Ancillary Services markets and also improves plant financial performance.
Energy Storage Systems (ESSs) are gaining great attention, as they can help operate grid power grids more reliably. The ESS acquisition and operation is motivated by the economics revolving around its provided services and revenue streams. These economics are greatly impacted by uncertainties in predicting the parameters which influence the ESS operation. The main goal of this paper is in addressing these uncertainties. We organize sources of uncertainties which directly impact the value-driven operation of the ESS and propose a framework which combines the uncertain requirements from processes both internal and external to ESS.
A common solution to deal with the stochasticity introduced by fast-ramping wind power integration is to equip wind farms (WFs) with energy storage systems (ESSs) to formulate hybrid WF-ESSs. In addition to leveling off wind power fluctuations during normal operations, a hybrid WF-ESS can be a flexible power source to accumulate the power system restoration. In this paper, we propose a rolling optimization model for transmission network recovery and load restoration considering the contributions of WF-ESSs. The proposed model is formulated as a mixed integer linear programming problem that simultaneously optimizes the amount and location of restorable load blocks as well as the restoration lines. The cold load pickup features of interrupted loads considering the outage duration are modeled in detail. A chance-constrained method is employed to deal with the uncertainty of wind power, and a rolling horizon-based framework is adopted to reduce the influence of forecast error. Case studies are conducted on both New England 39-bus system and part of a provincial power system in China. The results show that the load restoration process can be significantly accelerated by employing the proposed method and contributions of hybrid WF-ESSs to power system restoration are validated.
In this study, a novel three-phase Oak Ridge ac to ac converter is introduced for wireless mobility energy storage system (WMESS) applications for grid support or ancillary service applications. The proposed topology can be used in bidirectional operation between ac grid and ac terminals of energy storage (output of the ESS inverter) by accomplishing unity power factor. Inherent merit of the technology is that it can directly merge ac input 60 Hz grid frequency with the high frequency by superimposing them with the Oak Ridge Converter (ORC) and through the wireless coils. Theoretical and simulation results are provided for 10 kW output power. The functionality of the proposed three-phase system is demonstrated with the coupling coils separated by 6 inches of air gap with the input / output of 277 V AC,RMS . The system overall design is presented, and simulation results demonstrate achieving 3% current total harmonic distortion (THD) and 0.99 power factor (PF) at full load of 10 kW wireless power transfer.
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The severity of the economic impact caused by grid outages has been the driving factor for creating innovative solutions that increases interest for the deployment of distributed energy resources to reduce the impact of grid outages. This study presents a novel way of providing export power using bi-directional wireless power transfer (WPT) systems for ac grid side power and mobile energy storage systems (ESSs) connectivity. The proposed concept here interfaces the EV batteries to the AC grid and also can redirect the power from the stationary ESS to grid, to EV batteries, or both simultaneously; providing the capabilities of an uninterrupted power supply (UPS). Results demonstrate the performance and the functionality of the system with overall efficiencies 93% to 97%, depending on the operating mode.
To increase inertia and improve primary frequency response of future grids, grid-forming inverters connecting PV to grid and energy storage systems (ESSs) are likely to play an important role. Moreover, high-voltage direct current (HVdc) links will also be an enabler to transfer remote PV generation and for improved grid stability. That is, with increased penetration of PV, discrete development of PV and ESS connecting to transmission ac grid and HVdc links is one of the solutions for stable operation of grid. Here, an integrated concept for integration of PV and ESS to transmission ac grid and HVdc links is proposed that is named as multi-port autonomous reconfigurable solar power plant (MARS). The proposed integrated development reduces the cost associated with respect to discrete development of PV-ESS systems connecting to transmission ac grid and HVdc links. The integrated development incorporates advanced control methods to provide inertial and primary frequency response, reactive power support, and transient stability to manage PV and ESS resources. In this paper, high-fidelity switched system model of the integrated system and grids are developed and detailed simulation results are provided to showcase the stable operation of the integrated system and provision of grid support functions.
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.