• Asia pacific journal of information systems
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• v.27 no.2
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• pp.99-125
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• 2017

In this study, we propose an operations model to automate a home energy management system (HEMS) that utilizes an energy storage system (ESS) in consideration of consumer utility. Most previous studies focused on the system for the profits obtained from trading charged energy using large-scale ESS. By contrast, the present study focuses on constructing a home-level energy management system that considers consumer's utility over energy consumption. Depending on personal preference, some residential consumers may prefer consuming additional energy to earn increased profits through price arbitrage and vice versa. However, the current system could not yet reflect on this aspect. Thus, we develop an operations model for HEMS that could automatically control energy consumption while considering the level of consumer's preference and the economic benefits of using an ESS. The results of simulations using a dataset of the Korean market show that an operations policy of charging and discharging can be changed depending on consumer's utility. The impact of this policy is not ignorable. Moreover, the technical specifications of ESS, such as self-discharge rate and round-trip efficiency, can affect the operations policy and automation of HEMS.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2791-2798
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• 2015

The purpose of this study is to suggest Process Reference Model(PRM) for BIM/GIS-based Energy Information Modeling(BG-EIM) efficiently. Through the study, the detail process and consideration were derived to design EIM for the purpose of energy analysis depending on specific use-cases. To do this, we survey related studies and analyze the detailed EIM process. By using the results, BIM/GIS-based energy analysis consideration is defined and BG-EIM PRM is proposed.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.2043-2050
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• 2017

This paper presents two MPC (Model Predictive Control) based charging and discharging algorithms of BESS (Battery Energy Storage System) for capacity firming of wind generation. To deal with the intermittency of the output of wind generation, a single BESS is employed. The proposed algorithms not only make the output of combined systems of wind generation and BESS track the predefined reference, but also keep the SoC (State of Charge) of BESS within its physical limitation. Since the proposed algorithms are both presented in simple if-then statements which are the optimal solutions of related optimization problems, they are both easy to implement in a real-time system. Finally, simulations of the two strategies are done using a realistic wind farm library and a BESS model. The results on both simulations show that the proposed algorithms effectively achieve capacity firming while fulfilling all physical constraints.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.2
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• pp.129-142
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• 2014

We propose a variational segmentation model based on statistical information of intensities in an image. The model consists of both a local region-based energy and a global region-based energy in order to handle misclassification which happens in a typical statistical variational model with an assumption that an image is a mixture of two Gaussian distributions. We find local ambiguous regions where misclassification might happen due to a small difference between two Gaussian distributions. Based on statistical information restricted to the local ambiguous regions, we design a local region-based energy in order to reduce the misclassification. We suggest an algorithm to avoid the difficulty of the Euler-Lagrange equations of the proposed variational model.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.53-54
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• 2006

In this paper, we analytically evaluate packet delay and energy consumption of S-MAC protocol with a modified Markov chain model. Although some models, based on IEEE 802.11 MAC protocol, to analyze the S-MAC protocol in wireless sensor network (WSN) have been proposed, they fail to consider the differences in architecture between the S-MAC and the 802.11 MAC. Therefore, by reflecting the significant features in the S-MAC function, we model the operation of S-MAC protocol, and derive its packet delay and energy consumption in single-hop WSN. Numerical results show the delay and the dissipated energy at various duty cycle values according to offered load, where a practical mote is used.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2302-2324
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• 2014

Cluster-based wireless sensor network (WSN) can significantly reduce the energy consumption by data aggregation and has been widely used in WSN applications. However, due to the intrinsic many-to-one traffic pattern in WSN, the network lifetime is generally deteriorated by the unbalanced energy consumption in a cluster-based WSN. Therefore, energy efficiency and network lifetime improvement are two crucial and challenging issues in cluster-based WSNs. In this paper, we propose a Non-Uniform Node Distribution (NUND) scheme to improve the energy efficiency and network lifetime in cluster-based WSNs. Specifically, we first propose an analytic model to analyze the energy consumption and the network lifetime of the cluster-based WSNs. Based on the analysis results, we propose a node distribution algorithm to maximize the network lifetime with a fixed number of sensor nodes in cluster-based WSNs. Extensive simulations demonstrate that the theoretical analysis results determined by the proposed analytic model are consistent with the simulation results, and the NUND can significantly improve the energy efficiency and network lifetime.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.7-21
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• 2019

In order to improve the edge segmentation effect of the level set image segmentation and avoid the influence of the initial contour on the level set method, a saliency level set image segmentation model based on local Renyi entropy is proposed. Firstly, the saliency map of the original image is extracted by using saliency detection algorithm. And the outline of the saliency map can be used to initialize the level set. Secondly, the local energy and edge energy of the image are obtained by using local Renyi entropy and Canny operator respectively. At the same time, new adaptive weight coefficient and boundary indication function are constructed. Finally, the local binary fitting energy model (LBF) as an external energy term is introduced. In this paper, the contrast experiments are implemented in different image database. The robustness of the proposed model for segmentation of images with intensity inhomogeneity and complicated edges is verified.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.1
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• pp.181-193
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• 2014

The environment of supply chains is rapidly changed to global and eco-freindly work process. However, at current environment, it is not easy to grasp work flow and to analyze energy efficiency. Improving energy efficiency and visibility for goods flow can contribute to increases in customer attitudes and reductions in overall production costs Additionally, it can lead to increases in work efficiency and reductions in overall production costs. Until recently, efforts to improve energy performance focused on manufacturing industry. Those efforts have expanded to the supply chain. In this paper, we perform business process modeling about supply chain for visibility and sustainability - information and component flows - from assembly plants to logistics. This paper defines the work and information flows by modeling the underlying logical structures of the supply chain and the business processes that determine impact of visibility and sustainability. We model processes using the modeling methodology specified by UN/CEFACT. This methodology explains business process functionality and business transactions by UML diagram. The output of this paper would be useful in grasping work flow and capturing the used energy.

• Korean System Dynamics Review
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• v.6 no.2
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• pp.95-116
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• 2005

The purpose of this study is to analyze the structure of renewable energy market in order to deploy more renewable energy in Korea on the basis of information asymmetry between suppliers and demanders. To attain this purpose we develop the model to analyze and simulate the renewable market using system dynamics. This model is developed not to forecast the accurate size of market but to learn more structure of market using our limited data, mental model and knowledge of market.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.156-162
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• 2020

Wireless Sensor Network (WSN) field is mainly studied to monitor and characterize large-scale physical environments to track various environmental or physical conditions, such as temperature, pressure, wind speed and humidity. WSN can be used in various applications such as wild surveillance, military target tracking and monitoring, dangerous environmental exploration and natural disaster relief. We design probabilistic mobile models that apply to mobile ad hoc network mobile environments. A probabilistic shift model proposed by dividing the number of moving nodes and the distance of travel into two categories to express node movement characteristics. The proposed model of movement through simulation was compared with the existing random movement model, ensuring that the width and variation rate of the first node node node node (FND) was stable regardless of the node movement rate. In addition, when the proposed mobile model is applied to the routing protocol, the superiority of network life can be verified from measured FND values. We overcame the limitations of the existing random movement model, showing excellent characteristics in terms of energy efficiency and stable in terms of changes in node movement.