Publications

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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.

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Battery energy storage systems are often controlled through an energy management system (EMS), which may not have access to detailed models developed by battery manu-facturers. The EMS contains a model of the battery system's performance capabilities that enables it to optimize charge and discharge decisions. In this paper, we develop a process for the EMS to calculate and improve the accuracy of its control model using the operational data produced by the battery system. This process checks for data salience and quality, identifies candidate parameters, and then calculates their accuracy. The process then updates its model of the battery based on the candidate parameters and their accuracy. We use a charge reservoir model with a first order equivalent circuit to represent the battery and a flexible open-circuit-voltage function. The process is applied to one year of operational data from two lithium-ion batteries in a battery system located in Sterling, MA USA. Results show that the process quickly learns the optimal model parameters and significantly reduces modeling uncertainty. Applying this process to an EMS can improve control performance and enable risk-averse control by accounting for variations in capacity and efficiency.

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Energy storage technologies are positioned to play a substantial role in power delivery systems. They are being touted as an effective new resource to maintain reliability and allow for increased penetration of renewable energy. However, due to their relative infancy, there is a lack of knowledge on how these resources truly operate over time. Data analysis can help ascertain the operational and performance characteristics of these emerging technologies. Rigorous testing and data analysis are important for all stakeholders to ensure a safe, reliable system that performs predictably on a macro level. Standardizing testing and analysis approaches to verifying the performance of energy storage devices, equipment, and systems when integrating them into the grid will improve the understanding and benefit of energy storage over time from technical and economic vantage points. Demonstrating the life-cycle value and capabilities of energy storage systems begins with the data the provider supplies for analysis. After review of energy storage data received from several providers, it has become clear that some of these data are inconsistent and incomplete, raising the question of their efficacy for robust analysis. This report reviews and proposes general guidelines such as sampling rates and data points that providers must supply for robust data analysis to take place. Consistent guidelines are the basis of the proper protocol and ensuing standards to (a) reduce the time it takes data to reach those who are providing analysis; (b) allow them to better understand the energy storage installations; and (c) enable them to provide high-quality analysis of the installations. This report is intended to serve as a starting point for what data points should be provided when monitoring. As battery technologies continue to advance and the industry expands, this report will be updated to remain current.

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The Natural Energy Laboratory of Hawaii Authority's (NELHA) campus on The Island of Hawai'i supplies resources for a number of renewable energy and aquaculture research projects. There is a growing interest at NELHA to convert the research campus to a 100% renewable, islanded microgrid to improve the resiliency of the campus for critical ocean water pumping loads and to limit the increase in the long-term cost of operations. Currently, the campus has solar array to cover some electricity needs but scaling up this system to fully meet the needs of the entire research campus will require significant changes and careful planning to minimize costs. This study will investigate least-cost solar and energy storage system sizes capable of meeting the needs of the campus. The campus is split into two major load centers that are electrically isolated and have different amounts of available land for solar installations. The value of adding an electrical transmission line if NELHA converts to a self-contained microgrid is explored by estimating the cost of resources for each load center individually and combined. Energy storage using lithium-ion and hydrogen-based technologies is investigated. For the hydrogen-based storage system, a variable efficiency and fixed efficiency representation of the electrolysis and fuel cell systems are used. Results using these two models show the importance of considering the changing performance of hydrogen systems for sizing algorithms.

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In order to consider and understand emerging energy storage technologies, data analysis can be executed to ascertain proper operation and performance. The technical benefits of rigorous testing and data analysis are important for the customer, the planner, developer, and system operator: the end-user has a safe, reliable system that performs predictably on a macro level. The test-and-analyze approach to verifying performance of energy storage devices, equipment, and systems integration into the grid improves the understanding of the value of energy storage over time from the economic vantage point. Demonstrating the lifecycle value of energy storage begins with the data the provider supplies for analysis. After review of energy storage data received from several providers, it has become clear that some ESS data is inconsistent and incomplete - thus leading to a question of the inefficacy of the data when it comes time to analyze it. This paper will review and propose general guidelines such as sampling rates and data points that providers must supply in order for robust data analysis to take place. Consistent guidelines are the basis of the proper protocol to (a) reduce time it takes data to reach those who are providing analyses; (b) allow them to better understand the energy storage installations; and (c) provide high quality analysis of the installation. This paper intends to serve as a starting point for what data points should be provided when monitoring. As battery technologies continue to advance and the industry expands, this paper will be updated to remain current.

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This paper investigates the suitability of sizing the electrical export cable based on the rating of the contributing WECs within a farm. These investigations have produced a new methodology to evaluate the probabilities associated with peak power values on an annual basis. It has been shown that the peaks in pneumatic power production will follow an exponential probability function for a linear model. A methodology to combine all the individual probability functions into an annual view has been demonstrated on pneumatic power production by a Backward Bent Duct Buoy (BBDB). These investigations have also resulted in a highly simplified and perfunctory model of installed cable cost as a function of voltage and conductor cross-section. This work solidifies the need to determine electrical export cable rating based on expected energy delivery as opposed to device rating as small decreases in energy delivery can result in cost savings.

This paper presents a review of the main electrical components that are expected to be present in marine renewable energy arrays. The review is put in context by appraising the current needs of the industry and identifying the key components required in both device and array-scale developments. For each component, electrical, mechanical and cost considerations are discussed; with quantitative data collected during the review made freely available for use by the community via an open access online repository. This data collection updates previous research and addresses gaps specific to emerging offshore technologies, such as marine and floating wind, and provides a comprehensive resource for the techno-economic assessment of offshore energy arrays.

The community of Cordova, Alaska currently uses diesel and run-of-river hydro generation for its electricity needs. In the past, 60% of the Cordova summer load was supplied by the run-of-river generation. The majority of the time, the load was supplied only by the run-of-river generation. The bulk of generated electricity is delivered to Cordova's industrial fish processing plants and to other industrial loads. With the expansion of Cordova's fishing industry, the run-of-river generation is less often able to supply 100% of the load demand. When the run-of-river generation is not able to supply 100% of the load demand it has to be supplemented by diesel generation. There are also many times when the load demand is low and the available run-of-river generation has to be curtailed by spilling water which could be stored in an energy storage system. Sandia National Laboratories and Alaska Center for Energy and Power collaborated to evaluate how an energy storage system can be used to capture the spilled water and how it can economically and technically benefit Cordova during the fishing season and other times throughout the year. Results from this study are summarized in this report.