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Relevant bibliographies by topics / Battery storage

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Academic literature on the topic 'Battery storage'

Author: Grafiati

Published: 4 June 2021

Last updated: 23 August 2023

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Journal articles on the topic "Battery storage"

1

Ueda, T. "Alkaline storage battery." Journal of Power Sources 70, no. 1 (January 30, 1998): 169. http://dx.doi.org/10.1016/s0378-7753(97)84138-9.

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Zainurin, N. A., S. A. B. Anas, and R. S. S. Singh. "A Review of Battery Charging - Discharging Management Controller: A Proposed Conceptual Battery Storage Charging – Discharging Centralized Controller." Engineering, Technology & Applied Science Research 11, no. 4 (August 21, 2021): 7515–21. http://dx.doi.org/10.48084/etasr.4217.

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This paper describes the development of a centralized controller to charge or discharge the battery storages that are connected to renewable energy sources. The centralized controller is able to assist, control, and manage the battery storage charging when excessive power is available from renewable energy sources. At the same time, the centralized controller also performs battery storage discharging when the connected load requires a power source, especially when the renewable energy sources are unavailable. Background studies regarding battery storage charging-discharging are presented in the introduction section. Also, generally developed charging-discharging methods or techniques were applied at the system level and not specifically to the battery storage system level. Due to the limited study on battery storage system charging-discharging, this paper reviews some of the similar studies in order to understand the battery storage charging–discharging characteristics as well as to propose a new conceptual methodology for the proposed centralized controller. The battery storage State-of-Charge (SoC) is used as the criterion to develop the conceptual centralized controller, which is also used as a switching characteristic between charging or discharging when only the battery energy storages are supplying the output power to the connected load. Therefore, this paper mainly focuses on the conceptual methodology as well as explaining the functionality and operationality of the proposed centralized controller. A summarized comparison based on the studied charging–discharging systems with the proposed centralized controller is presented to indicate the validity of the proposed centralized controller.

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Praphun Pikultong, Sahataya Thongsan, and Somchai Jiajitsawat. "The Study of Usable Capacity Efficiency and Lifespan of Hybrid Energy Storage (Lead-Acid with Lithium-ion Battery) Under Office Building Load Pattern." Journal of Advanced Research in Fluid Mechanics and Thermal Sciences 98, no. 2 (September 29, 2022): 67–79. http://dx.doi.org/10.37934/arfmts.98.2.6779.

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One of the greatest practices in energy management is the Energy Storage System (ESS). ESS can be used for renewable energy control as well as peak shaving in the build-up of a Smart Grid. The cost of a lithium ion battery is more than 200 percent greater than that of a lead-acid battery, which is a significant barrier to project start-up. This paper focuses on the use of a hybrid energy storage system that includes a lithium-ion battery and a lead-acid battery. This work presents the hybrid energy storage using lithium-ion battery and lead-acid battery to reduce costs of the project. However, usability that requires high current power supply considerably affects the usable capacity of a lead-acid battery. Results showed that the ratio 68.63: 31.37 was the most suitable among 7 ratios, compared to the model building installed a 50kW solar power generator on the rooftop, in the worst case scenario when the batter have 85% DoD per cycle. The EOL for hybrid energy storage is about 4 years lifespan with the 0.5C and 0.2C for LFP and AGM respectively. In terms of economic evaluation, hybrid energy storage could initially reduce the project cost by 47.5%.

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Kennelly, A. E. "THE EDISON STORAGE BATTERY." Journal of the American Society for Naval Engineers 13, no. 3 (March 18, 2009): 669–77. http://dx.doi.org/10.1111/j.1559-3584.1901.tb04148.x.

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Wedlake, R. "High temperature storage battery." Journal of Power Sources 70, no. 1 (January 30, 1998): 168. http://dx.doi.org/10.1016/s0378-7753(97)84133-x.

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Green, Sidney, John McLennan, Palash Panja, Kevin Kitz, Richard Allis, and Joseph Moore. "Geothermal battery energy storage." Renewable Energy 164 (February 2021): 777–90. http://dx.doi.org/10.1016/j.renene.2020.09.083.

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Anderson, M. D., and D. S. Carr. "Battery energy storage technologies." Proceedings of the IEEE 81, no. 3 (March 1993): 475–79. http://dx.doi.org/10.1109/5.241482.

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Kumar, K. Pandu. "Battery Storage Management System." International Journal of Electrical Engineering 16, no. 1 (July 6, 2023): 17–25. http://dx.doi.org/10.37624/ijee/16.1.2023.17-25.

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Leung, K. K., and D. Sutanto. "Storage power flow controller using battery storage." IEE Proceedings - Generation, Transmission and Distribution 150, no. 6 (2003): 727. http://dx.doi.org/10.1049/ip-gtd:20030754.

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Jiang, Minglei. "Selection of Electrochemical Energy Storage Types Based on Renewable Energy Storage Technology." Journal of Physics: Conference Series 2186, no. 1 (February 1, 2022): 012010. http://dx.doi.org/10.1088/1742-6596/2186/1/012010.

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Abstract With the strong support of the national new energy policy, higher requirements are put forward for the flexible regulation ability base on the power system. It is the key factor of the flexible regulation ability of the system. How to achieve better new energy consumption through reasonable selection of energy storage types has become an urgent problem to be solved. In view of this, this paper establishes an energy storage type selection model and analyzes a numerical example. The conclusion is that lead-carbon battery and lithium-ion battery have different advantages: lead battery is more suitable for small-scale new energy consumption. Although lithium-ion battery is superior to lead-carbon battery in construction, operation and maintenance, it has more cycles, avoids frequent replacement, and has high battery conversion efficiency. With the further decline of battery manufacturing cost, the benefit of investing in energy storage system will be further improved. The conclusion can provide a basis for formulating relevant policies

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Dissertations / Theses on the topic "Battery storage"

1

Kerr, John C. H. "Polymer battery studies." Thesis, University of Oxford, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.236224.

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Rydberg, Lova. "RTDS modelling of battery energy storage system." Thesis, Uppsala universitet, Elektricitetslära, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-155960.

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This thesis describes the development of a simplified model of a battery energy storage. The battery energy storage is part of the ABB energy storage system DynaPeaQ®. The model has been built to be run in RTDS, a real time digital simulator. Batteries can be represented by equivalent electric circuits, built up of e.g voltage sources and resistances. The magnitude of the components in an equivalent circuit varies with a number of parameters, e.g. state of charge of the battery and current flow through the battery. In order to get a model of how the resistive behaviour of the batteries is influenced by various parameters, a number of simulations have been run on a Matlab/Simulink model provided by the battery manufacturer. This model is implemented as a black box with certain inputs and outputs, and simulates the battery behaviour. From the simulation results a set of equations have been derived, which approximately give the battery resistance under different operational conditions. The equations have been integrated in the RTDS model, together with a number of controls to calculate e.g. state of charge of the batteries and battery temperature. Results from the RTDS model have been compared with results from the Simulink model. The results coincide reasonably well for the conditions tested. However, further testing is needed to ensure that the RTDS model produces results similar enough to the ones from the Simulink model, over the entire operational range.

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Kromlidis, S. "Battery energy storage for power quality improvement." Thesis, University of Manchester, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.556320.

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Maskey, Anuj. "Battery energy storage system control algorithm design." Thesis, Maskey, Anuj (2019) Battery energy storage system control algorithm design. Honours thesis, Murdoch University, 2019. https://researchrepository.murdoch.edu.au/id/eprint/52653/.

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Microgrid is based on smaller decentralised low voltage system with the use of modern power technology puts different types of Distributed Energy sources solar power, wind power, and energy storage devices together, improving the electrical supply reliability, reducing the feeder loss and ensures the stability of the voltage. The current trend of incorporating energy storage devices in the microgrid is aimed to mitigate the power imbalance and improve the electrical supply reliability. The thesis uses Kalbarri, Western Australia as a case study site with an aim to investigate the appropriate battery technology and formulate control algorithm for the microgrid. The thesis starts by examining the Australian electrical market including the: socio‐economic, political, and regulatory environment and presents the rationale of having an Energy Storage System in rural Australia. The thesis investigates the various available BESS battery technology options and suggests the most appropriate options for the BESS comprised Kalbarri microgrid model. The MATLAB/Simulink BESS control algorithm design model is presented with an aim to test voltage and frequency regulation under different load condition, including the process of seamless transition from the grid‐connected operation to a grid‐disconnected operation of the microgrid. The research presents a theoretical control model based on the Power Control theory and existing academic literature on the topic. The thesis examines the control algorithm design to regulate the frequency and voltage using the BESS system to connect to the main three phase AC grid. The overall site model includes a power conversion of two DC sources: BESS and PV system. The BESS control algorithm model comprises of a Power Conversion system that use three‐phase full bridge Insulated Gate Bipolar Transistors (IGBTs) with LCL filter and a Power Control System based on Phased Lock Loop to synchronise with the grid frequency. The Power Control system uses a three‐phase sinusoidal abc frame conversion to a DC reference signal dq0 frame to incorporate PI controller with an aim that the intermittence of the renewable energy generation Wind and PV system can be maintained to a balanced state in the grid within a short frame of time. The BESS control algorithm model uses a Current Controlled Voltage Source Converter for its simple controller design, better performance during grid fault and the overall cost saving of the system. The thesis simulation utilized CCVSC for its tight regulation of the line current, mainly VSC protection against overcurrent and a high accuracy instantaneous current control. However, the author acknowledges the simulation result indicate an anomaly with voltage control while using CCVSC in the control algorithm model in power source transition test condition. Hence, as a part of future improvement with a focus on the overcurrent, the author concludes possible testing with the VCVSC based control algorithm model for rapid and continuous response for smooth dynamic control and automated P and Q power control in both steady‐state and dynamic system conditions. Finally, the impact on the microgrid is presented with an in‐depth analysis of the results, including the achievements, innovations, challenges and the suggestion for future improvement in the discussion section of the report.

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Börjesson, Philip, and Patrik Larsson. "Cost models for battery energy storage systems." Thesis, KTH, Energiteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-245187.

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The aim of this study is to identify existing models for estimating costs of battery energy storage systems(BESS) for both behind the meter and in-front of the meter applications. The study will, from available literature, analyse and project future BESS cost development. The study presents mean values on the levelized cost of storage (LCOS) metric based on several existing cost estimations and market data on energy storage regarding three different battery technologies: lithium ion, lead-acid and vanadium flow. These values are intended to serve as benchmarks for BESS costs of today. The results show that for in-front of the meter applications, the LCOS for a lithium ion battery is 30 USDc/kWh and 34 USDc/kWh for a vanadium flow battery. For behind the meter applications, the LCOS for a lithium ion battery is 43 USD/kWh and 41 USD/kWh for a lead-acid battery. A sensitivity analysis is conducted on the LCOS in order to identify key factors to cost development of battery storage. The mean values and the results from the sensitivity analysis, combined with data on future cost development of battery storage, are then used to project a LCOS for year 2030. The results from the sensitivity analysis show that capex, cycles and discount rate have the biggest impact on the LCOS formula. The projection conducted in this study indicates that LCOS will decrease significantly by 2030. The results show that for in-front of the meter applications, the LCOS for a lithium ion battery will drop 60 % and 68 % for a vanadium flow battery. For behind the meter applications, the LCOS for a lithium ion battery will drop 60 % and 49 % for a lead-acid battery.
Denna studie syftar till att identifiera befintliga modeller för att estimera kostnader för batterilagringssystem för både små och storskaliga applikationer samt att från tillgänglig litteratur, analysera och estimera framtida kostnader för batterilagringsystem. Studien presenterar medelvärden på ”levelized cost of storage (LCOS)” baserat på befintliga kostnadsberäkningar och marknadsdata för tre olika batteriteknologier: litiumjon, bly och vanadin-flödesbatteri. Dessa medelvärden kan ses som riktmärken för kostnader av batterilagringssystem idag. Resultaten visar att LCOS för ett litiumjonbatteri är 30 USDc/kWh och att LCOS för ett vanadin-flödesbatteri i storskaliga applikationer är 34 USDc/kWh. För småskaliga applikationer visar resultaten att LCOS för ett litiumjonbatteri är 43 USD/kWh och 41 USD/kWh för ett blybatteri. Studien genomförde även en känslighetsanalys på LCOS för att identifiera vilka parametrar som har störst påverkan på LCOS. Medelvärdena och resultatet från känslighetsanalysen, kombinerat med marknadsdata om framtidens kostnadsutveckling för batterilagring, användes för att estimera LCOS för år 2030. Resultatet från känslighetsanalysen visar att capex, cykler och diskonteringsräntan har störst inverkan på LCOS-formeln. Estimeringen av LCOS för 2030 indikerar att kostnader för batterilagring kommer minska avsevärt. Resultatet visar att för storskaliga applikationer kommer LCOS för ett system med ett litiumjonbatteri minska med 60 % och 68 % för ett med vanadin-flödesbatteri. För småskaliga applikationer minskar LCOS för ett system med litiumjonbatteri med 60 % och 49 % för ett med blybatteri.

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Larsson, Patrik, and Philip Börjesson. "Cost models for battery energy storage systems." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-235914.

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The aim of this study is to identify existing models for estimating costs of battery energy storage systems (BESS) for both behind the meter and in-front of the meter applications. The study will, from available literature, analyse and project future BESS cost development. The study presents mean values on the levelized cost of storage (LCOS) metric based on several existing cost estimations and market data on energy storage regarding three different battery technologies: lithium ion, lead-acid and vanadium flow. These values are intended to serve as benchmarks for BESS costs of today. The results show that for in-front of the meter applications, the LCOS for a lithium ion battery is 30 USDc/kWh and 34 USDc/kWh for avanadium flow battery. For behind the meter applications, the LCOS for a lithium ion batteryis 43 USD/kWh and 41 USD/kWh for a lead-acid battery. A sensitivity analysis is conducted on the LCOS in order to identify key factors to cost development of battery storage. The mean values and the results from the sensitivity analysis, combined with data on future cost development of battery storage, are then used to project a LCOS for year 2030. The results from the sensitivity analysis show that capex, cycles and discount rate have the biggest impacton the LCOS formula. The projection conducted in this study indicates that LCOS will decreases ignificantly by 2030. The results show that for in-front of the meter applications, the LCOS for a lithium ion battery will drop 60 % and 68 % for a vanadium flow battery. For behind the meter applications, the LCOS for a lithium ion battery will drop 60 % and 49 % for a lead-acid battery.
Denna studie syftar till att identifiera befintliga modeller för att estimera kostnader för batterilagringssystem för både små och storskaliga applikationer samt att från tillgänglig litteratur, analysera och estimera framtida kostnader för batterilagringsystem. Studien presenterar medelvärden på ”levelized cost of storage (LCOS)” baserat på befintliga kostnadsberäkningar och marknadsdata för tre olika batteriteknologier: litiumjon, bly och vanadin-flödesbatteri. Dessa medelvärden kan ses som riktmärken för kostnader av batterilagringssystem idag. Resultaten visar att LCOS för ett litiumjonbatteri är 30 USDc/kWh och att LCOS för ett vanadin-flödesbatteri i storskaliga applikationer är 34 USDc/kWh. För småskaliga applikationer visar resultaten att LCOS för ett litiumjonbatteri är 43 USD/kWh och 41 USD/kWh för ett blybatteri. Studien genomförde även en känslighetsanalys på LCOS för att identifiera vilka parametrar som har störst påverkan på LCOS. Medelvärdena och resultatet från känslighetsanalysen, kombinerat med marknadsdata om framtidens kostnadsutveckling för batterilagring, användes för att estimera LCOS för år 2030. Resultatet från känslighetsanalysen visar att capex, cykler och diskonteringsräntan har störst inverkan påLCOS-formeln. Estimeringen av LCOS för 2030 indikerar att kostnader för batterilagring kommer minska avsevärt. Resultatet visar att för storskaliga applikationer kommer LCOS för ett system med ett litiumjonbatteri minska med 60 % och 68 % för ett med vanadinflödesbatteri. För småskaliga applikationer minskar LCOS för ett system med litiumjonbatteri med 60 % och 49 % för ett med blybatteri.

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Svensson, Henrik. "Pre-Study for a Battery Storage for a Kinetic Energy Storage System." Thesis, Uppsala universitet, Elektricitetslära, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-249173.

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This bachelor thesis investigates what kind of battery system that is suitable for an electric driveline equipped with a mechanical fly wheel, focusing on a battery with high specific energy capacity. Basic battery theory such as the principle of an electrochemical cell, limitations and C-rate is explained as well as the different major battery systems that are available. Primary and secondary cells are discussed, including the major secondary chemistries such as lead acid, nickel cadmium (NiCd), nickel metal hydride (NiMH) and lithium ion (Li-ion). The different types of Li-ion chemistries are investigated, explained and compared against each other as well as other battery technologies. The need for more complex protection circuitry for Li-ion batteries is included in the comparison. Request for quotations are made to battery system manufacturers and evaluated. The result of the research is that the Li-ion NMC energy cell is the best alternative, even if the cost per cell is the most expensive compared to other major technologies. Due to the budget, the LiFeMnPO4 chemistry is used in the realisation of the final system, which is scaled down with consideration to the power requirement.

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Murray-Jones, Peter J. "Aspects of the lead acid battery." Thesis, Loughborough University, 1992. https://dspace.lboro.ac.uk/2134/27055.

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Two aspects of the lead acid battery have been researched in this work. The first investigates some of the complex questions concerning the nature, composition and chemistry of lead sulphate membranes using scanning electron microscopy (SEM), impedance spectroscopy (IS) and inorganic chemistry techniques. A review of the literature on lead sulphate and precipitate impregnated membranes together with their role in the lead acid battery is presented.

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Gonsalves, Valerie Clare. "Studies on the sodium-sulphur battery." Thesis, University of Southampton, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.236343.

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Protogeropoulos, Christos I. "Autonomous wind/solar power systems with battery storage." Thesis, Cardiff University, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.320875.

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Books on the topic "Battery storage"

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Crompton, T. R. Battery reference book. London: Butterworths, 1990.

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Battery reference book. 3rd ed. Oxford, England: Newnes, 2000.

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Crompton, T. R. Battery reference book. 2nd ed. Oxford [England]: Boston, 1995.

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Battery reference book. 2nd ed. [S.l.]: SAE International, 1996.

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Stonfer, David. The storage battery market: Profiles and trade opportunities. [Washinton, D.C.?]: Nonferrous Metals Division, Basic Industries Sector, International Trade Administration, U.S. Dept. of Commerce, 1985.

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Raymond, Michele, and Dinesh Kumar. Battery recovery laws worldwide. College Park, MD: Raymond Communications (5111 Berwyn Rd., College Park), 1999.

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Valer, Pop, ed. Battery management systems: Accurate state-of-charge indication for battery powered applications. [Dordrecht]: Springer, 2008.

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Battery management systems for large lithium-ion battery packs. Boston: Artech House, 2010.

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M, Lewis Norma, National Risk Management Research Laboratory (U.S.), California Environmental Protection Agency. Dept. of Toxic Substances Control, and United States. Environmental Protection Agency, eds. Rechargeable alkaline household battery system, Rayovac Corporation, Renewal. Cincinnati, Ohio: U.S. Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, 1999.

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Arnold, Karen. Household battery recycling and disposal study. St. Paul, MN: Minnesota Pollution Control Agency, 1991.

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Book chapters on the topic "Battery storage"

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Fabjan, Christoph, and Josef Drobits. "Bromine-Storage Materials." In Handbook of Battery Materials, 197–217. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2011. http://dx.doi.org/10.1002/9783527637188.ch7.

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Yang, Wen-Jei. "Electrical Energy Storage Battery." In Energy Storage Systems, 599–603. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-2350-8_27.

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Sedghi, Mahdi, Ali Ahmadian, Ali Elkamel, Masoud Aliakbar Golkar, and Michael Fowler. "Battery Energy Storage Planning." In Electric Distribution Network Planning, 185–214. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7056-3_7.

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Atcitty, Stan, Jason Neely, David Ingersoll, Abbas Akhil, and Karen Waldrip. "Battery Energy Storage System." In Power Electronics for Renewable and Distributed Energy Systems, 333–66. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5104-3_9.

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Yanga, Jie, Jie Yanga, Zhenghui Pana, Zhenghui Pana, Yuegang Zhang, Yongcai Qiu, and Yongcai Qiu. "Doped Graphene for Electrochemical Energy Storage Systems." In Advanced Battery Materials, 511–612. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2019. http://dx.doi.org/10.1002/9781119407713.ch11.

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Khalilpour, Kaveh Rajab, and Anthony Vassallo. "PV-Battery Nanogrid Systems." In Community Energy Networks With Storage, 61–82. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-287-652-2_4.

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Jung, Joey. "Lead-Acid Battery." In Electrochemical Technologies for Energy Storage and Conversion, 111–74. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2012. http://dx.doi.org/10.1002/9783527639496.ch4.

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Akhtar, Mainul, and S. B. Majumder. "Hybrid Supercapacitor-Battery Energy Storage." In Handbook of Advanced Ceramics and Composites, 1259–96. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-16347-1_43.

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Akhtar, Mainul, and S. B. Majumder. "Hybrid Supercapacitor-Battery Energy Storage." In Handbook of Advanced Ceramics and Composites, 1–39. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-73255-8_43-1.

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Noussan, Michel. "Economics of Electricity Battery Storage." In The Palgrave Handbook of International Energy Economics, 235–53. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-86884-0_14.

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AbstractThis chapter deals with the challenges and opportunities of energy storage, with a specific focus on the economics of batteries for storing electricity in the framework of the current energy transition. Storage technologies include a variety of solutions that have been used for different grid services, including frequency control, load following, and uninterrupted power supply. A recent interest is being triggered by the increasing grid balance requirements to integrate variable renewable sources and distributed generation. In parallel, lithium-ion batteries are experiencing a strong market expansion driven by an uptake of electric vehicles worldwide, which is leading to a strong decrease of production costs, making Li-ion batteries an attractive solution also for stationary storage applications.

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Conference papers on the topic "Battery storage"

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Wu, Hongjie. "Hardware-in-loop verification of battery management system." In Energy Storage. IEEE, 2011. http://dx.doi.org/10.1109/pesa.2011.5982950.

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Pathak, Prashant Kumar, and Atma Ram Gupta. "Battery Energy Storage System." In 2018 4th International Conference on Computational Intelligence & Communication Technology (CICT). IEEE, 2018. http://dx.doi.org/10.1109/ciact.2018.8480377.

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Zagoras, Nikitas, Karthikeyan Balasubramaniam, Iordanis Karagiannidis, and Elham B. Makram. "Battery Energy Storage Systems." In 2015 North American Power Symposium (NAPS). IEEE, 2015. http://dx.doi.org/10.1109/naps.2015.7335215.

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Chalamala, Babu. "Battery Energy Storage Technologies." In Proposed for presentation at the ESIG 2020 Fall Technical Workshop, November 12, 2020 (virtual) held November 12, 2020. US DOE, 2020. http://dx.doi.org/10.2172/1831370.

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Chotia, I., and S. Chowdhury. "Battery storage and hybrid battery supercapacitor storage systems: A comparative critical review." In 2015 IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA). IEEE, 2015. http://dx.doi.org/10.1109/isgt-asia.2015.7387080.

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Yiu, Kevin. "Battery technologies for electric vehicles and other green industrial projects." In Energy Storage. IEEE, 2011. http://dx.doi.org/10.1109/pesa.2011.5982908.

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Maiser, Eric. "Battery packaging - Technology review." In REVIEW ON ELECTROCHEMICAL STORAGE MATERIALS AND TECHNOLOGY: Proceedings of the 1st International Freiberg Conference on Electrochemical Storage Materials. AIP Publishing LLC, 2014. http://dx.doi.org/10.1063/1.4878489.

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Li, Chen, Hongzhong Ma, Chunning Wang, and Xiaohan Peng. "Summay of Gas Evolution Behaviours for Storage Battery: Gas evolution behaviours for storage battery." In 2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE). IEEE, 2020. http://dx.doi.org/10.1109/icmcce51767.2020.00073.

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Zich, Jan, and Jan Jandik. "Active Battery Management System for Home Battery Energy Storage." In 2020 21st International Scientific Conference on Electric Power Engineering (EPE). IEEE, 2020. http://dx.doi.org/10.1109/epe51172.2020.9269172.

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Leung, K. K., and D. Sutanto. "A storage power flow controller (SPFC) using battery storage." In Proceedings of the IEEE 1999 International Conference on Power Electronics and Drive Systems. PEDS'99 (Cat. No.99TH8475). IEEE, 1999. http://dx.doi.org/10.1109/peds.1999.792813.

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Reports on the topic "Battery storage"

1

Elgqvist, Emma. Battery Storage for Resilience. Office of Scientific and Technical Information (OSTI), June 2021. http://dx.doi.org/10.2172/1788427.

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2

Kraft, S., and A. Akhil. Battery energy storage market feasibility study. Office of Scientific and Technical Information (OSTI), July 1997. http://dx.doi.org/10.2172/510377.

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Ericson, Sean J., and Patricia Statwick. Opportunities for Battery Storage Technologies in Mexico. Office of Scientific and Technical Information (OSTI), October 2018. http://dx.doi.org/10.2172/1476985.

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Author, Not Given. Battery storage for supplementing renewable energy systems. Office of Scientific and Technical Information (OSTI), January 2009. http://dx.doi.org/10.2172/1216656.

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COREY, GARTH P., LARRY E. STODDARD, and RYAN M. KERSCHEN. Boulder City Battery Energy Storage Feasibility Study. Office of Scientific and Technical Information (OSTI), March 2002. http://dx.doi.org/10.2172/793408.

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Cole, Wesley J., and Allister Frazier. Cost Projections for Utility-Scale Battery Storage. Office of Scientific and Technical Information (OSTI), June 2019. http://dx.doi.org/10.2172/1529218.

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Bowen, Thomas, Ilya Chernyakhovskiy, and Paul L. Denholm. Grid-Scale Battery Storage: Frequently Asked Questions. Office of Scientific and Technical Information (OSTI), September 2019. http://dx.doi.org/10.2172/1561843.

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Brown, D. R., and J. A. Russell. Review of storage battery system cost estimates. Office of Scientific and Technical Information (OSTI), April 1986. http://dx.doi.org/10.2172/5858818.

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Lu, Ning, Mark R. Weimar, Yuri V. Makarov, Jian Ma, and Vilayanur V. Viswanathan. The Wide-Area Energy Storage and Management System ? Battery Storage Evaluation. Office of Scientific and Technical Information (OSTI), July 2009. http://dx.doi.org/10.2172/969906.

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DiOrio, Nicholas, Aron Dobos, Steven Janzou, Austin Nelson, and Blake Lundstrom. Technoeconomic Modeling of Battery Energy Storage in SAM. Office of Scientific and Technical Information (OSTI), September 2015. http://dx.doi.org/10.2172/1225314.

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