• Journal of Electrochemical Science and Technology
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• v.15 no.1
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• pp.1-13
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• 2024

This paper presents applications of lithium-sulfur (Li-S) energy storage batteries, while showing merits and demerits of several techniques to mitigate their electrochemical challenges. Unmanned aerial vehicles, electric cars, and grid-scale energy storage systems represent main applications of Li-S batteries due to their low cost, high specific capacity, and light weight. However, polysulfide shuttle effects, low conductivities, and low coulombic efficiencies signify key challenges of Li-S batteries, causing high volumetric changes, dendritic growths, and limited cycling performances. Solid-state electrolytes, interfacial interlayers, and electrocatalysts denote promising methods to mitigate such challenges. Moreover, nanomaterials have capability to improve kinetic reactions of Li-S batteries based on several properties of nanoparticles to immobilize sulfur in cathodes, stabilizing lithium in anodes while controlling volumetric growths. Li-S energy storage technologies are able to satisfy requirements of future markets for advanced rechargeable batteries with high-power densities and low costs, considering environmentally friendly systems based on renewable energy sources.

• Journal of the Korean Solar Energy Society
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• v.22 no.1
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• pp.31-42
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• 2002

This study has been carried out to design a number of storage units which could improve the utilizability of solar energy by offering convenient means to store it. The proposed units are systematically tested to establish their reliability in actual operations. One of the prominent features of the present storage units is that each design is meant to drastically improve the thermal response of solar systems which would definitely offer extreme convenience to whoever uses it. Also sought in the present study is to elicit ideal operating conditions during the storage and extraction phases of solar energy once it is delivered to the storage unit. The present study has confirmed the potential use of the proposed units with their applicability in capitalizing the sun's energy.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.87-106
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• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.1
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• pp.1211-1217
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• 2001

This paper presnts a controller for the heat capacity of thermal storage systems using off-peak electricity which is composed of an identifier using neural networks and a storage time adjuster in order to store exactly the required thermal energy without loss. Since thermal storage systems have nonlinear characteristics and large time constant, even if we predict the heating load accurately, it is very difficult to store exactly the required thermal energy. Thus, in the neural network for the identifier, the adaptive learning rate for high learning speed and bit inputs based on state changes of thermal storage power source are used. Also a hardware for the controller using a microprocessor is developed. The performance of the proposed controller is shown by experiment.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.879-884
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• 2007

Flywheel energy storage systems have advantages over other types of energy storage devices in such aspects as unlimited charge/discharge cycles and environmental friendliness. In this paper we propose a millimeter scale flywheel energy storage device. The flywheel is supported by a pair of passive magnetic bearings and rotated by a toroidally wound electric motor/generator. The geometry of the bearings is optimized for the maximum dynamic performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2134-2153
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• 2013

A network-coding-based scheme is proposed to improve the energy efficiency of distributed storage systems in WSNs (Wireless Sensor Networks). We mainly focus on two problems: firstly, consideration is given to effective distributed storage technology; secondly, we address how to effectively repair the data in failed storage nodes. For the first problem, we propose a method to obtain a sparse generator matrix to construct network codes, and this sparse generator matrix is proven to be the sparsest. Benefiting from this matrix, the energy consumption required to implement distributed storage is reduced. For the second problem, we designed a network-coding-based iterative repair method, which adequately utilizes the idea of re-encoding at intermediate nodes from network coding theory. Benefiting from the re-encoding, the energy consumption required by data repair is significantly reduced. Moreover, we provide an explicit lower bound of field size required by this scheme, which implies that it can work over a small field and the required computation overhead is very low. The simulation result verifies that the proposed scheme not only reduces the total energy consumption required to implement distributed storage system in WSNs, but also balances energy consumption of the networks.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.1
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• pp.11-25
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• 2024

Lithium-ion batteries (LIBs) have attracted great attention as the common power source in energy storage fields of large-scale applications such as electrical vehicles (EVs), industries, power plants, and grid-scale energy storage systems (ESSs). Insertion, alloying, and conversion reactions are the main electrochemical energy storage mechanisms in LIBs, which determine their electrochemical properties and performances. The electrochemical reaction mechanisms are determined by several factors including crystal structure, components, and composition of electrode materials. This article reviews a new strategy to compensate for the intrinsic shortcomings of each reaction mechanism by introducing the material systems to form a single compound with different types of reaction mechanisms and to allow the simultaneous hybrid electrochemical reaction of two different mechanisms in a single solid solution phase.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.4
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• pp.305-312
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• 2014

This paper discusses real-time peak shaving algorithms for a large-scale battery energy storage system (BESS). Although several transmission and distribution functions could be implemented for diverse purposes in BESS applications, this paper focuses on a real-time peak shaving algorithm for an energy time shift, considering wind power generation. In a high wind penetration environment, the effective load levels obtained by subtracting the wind generation from the load time series at each long-term cycle time unit are needed for efficient peak shaving. However, errors can exist in the forecast load and wind generation levels, and the real-time peak shaving operation might require a method for wind generation that includes comparatively large forecasting errors. To effectively deal with the errors of wind generation forecasting, this paper proposes a real-time peak shaving algorithm for threshold value-based peak shaving that considers fuzzy wind power generation.

• Proceedings of the KIPE Conference
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• 2016.07a
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• pp.345-346
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• 2016

The grid-connected energy storage systems, which could increase the reliability, efficiency, and cleanliness of the grid is presently restricted by the high cost of batteries. This problems could be solved by batteries retired from automotive services. These batteries can provide a low-cost system for energy storage and other applications such as residential applications and renewable energy integration. This paper gives an overview of technical requirements for the re-use of the electric vehicle batteries in energy storage systems.Firstly, the motivation of research is introduced. Secondly, the technologies needed for the re-use of the battery are introduced such asidentification of the battery characteristics, grading of the aged batteries, identification of the state-of-charge and state-of-health of the battery and suitable power electronic converter topologies. In addition the control strategy to maximize the battery lifespan and bypass the faulty batteries is presented and one-stop solution to implement the above mentioned technologies are also given.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.754-760
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• 2011

In the DC traction system, a large load current of electric railcar leads to a voltage drop when a vehicle starts, and the regenerative power generated by brake system increases the catenary voltage. To minimize the voltage fluctuation during the train operation and make use of the regenerative power, several types of energy storage systems are being studied. The energy storage system that is being recently introduced consists of the supercapacitors for energy storage and the bi-direction DC/DC converter for charge/discharge control. The efficiency of the energy storage system depends on the train operation pattern. In this paper, the operation efficiency of the energy storage system was quantitatively analyzed via simulation study taking consideration of the train operation patterns. The simulation was conducted changing the headway of trains with the energy storage system that uses the bi-direction DC/DC converter and supercapacitor. The simulation results showed that the operation efficiency of the energy storage system increases as the headway increase.