• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.11
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• pp.1554-1560
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• 2017

Prepare a lose of 765kV transmission route in power system operation condition, there are some Special Protection Scheme(SPS)s in Korean power system. These SPS can make some preselected generators are tripped to avoid generator overspeed. Because of many of the new large power plants are installed to existing power generation sites due to the siting problem, the number of generator tripped by SPS should be increased. But that can be a cause of system frequency change under the Under Frequency Relay(UFR) 1st pickup level 59.0Hz. Therefore generation constraint should be considered until new transmission lines are installed. In this paper, we propose the ESS application for generation constraint mitigation by frequency damping control of ESS. To analysis an effect of ESS application, we use PSS/E dynamic simulation tool, CBEST model and controller model. The proposed ESS application is applied to the empirical Korean power system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.1
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• pp.86-93
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• 2015

Globally, wind power development is experiencing dramatic growth and wind power penetration levels are increasing. Wind generation is highly variable in time and space and it doesn't guarantee the system reliability and secure system operation. As wind power capacity becomes a significant portion of total generation capacity, the reliability assessment for wind power are therefore needed. At present, this operational reliability assessment is focusing on a generation adequacy perspective and does not consider transmission reliability issues. In this paper, we propose the critical transmission operating constraint prediction(CTOCP) system with high wind power penetration to enhance transmission reliability.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.371-372
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• 2008

In this paper, we consider wireless sensor networks with hard energy constraint, where each node is powered by a small battery. Under this hard constraint, reducing energy consumption is the most important design consideration for wireless sensor networks. Energy saving and control is an important issue, involved in the design of most sensor nodes. In this context, we focus on physical layer design where energy constraint problem can be modeled as an optimization of transmission modulation scheme[1]. Specifically, our analyses are based on energy control schemes that are relative to physical layer design on upper bound SEP MPSK in AWGN channels.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2873-2892
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• 2019

Reducing the interference to the licensed mobile users and obtaining the energy efficiency are key issues in cognitive heterogeneous networks. A corresponding rate loss constraint is proposed to be used for the sensing-based spectrum sharing (SBSS) model in cognitive heterogeneous networks in this paper. Resource allocation optimization strategy is designed for the maximum energy efficiency under the proposed interference constraint together with average transmission power constraint. An efficiency algorithm is studied to maximize energy efficiency due to the nonconvex optimal problem. Furthermore, the relationship between the proposed protection criterion and the conventional interference constraint strategy under imperfect sensing condition for the SBSS model is also investigated, and we found that the conventional interference threshold can be regarded as the upper bound of the maximum rate loss that the primary user could tolerate. Simulation results have shown the effectiveness of the proposed protection criterion overcome the conventional interference power constraint.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.20-39
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• 2020

This paper considers a downlink multi-carrier cooperative non-orthogonal multiple access (NOMA) transmission, where no direct link exists between the far user and the base station (BS), and the communication between them only relies on the assist of the near user. Firstly, the BS sends a superimposed signal of the far and the near user to the near user, and then the near user adopts simultaneous wireless information and power transfer (SWIPT) to split the received superimposed signal into two portions for energy harvesting and information decoding respectively. Afterwards, the near user forwards the signal of the far user by utilizing the harvested energy. A minimum data is required to ensure the quality of service (QoS) of the far user. We jointly optimize power allocation, subcarrier allocation, time allocation, the power allocation (PA) coefficient and the power splitting (PS) ratio to maximize the number of data bits received at the near user under the energy causality constraint, the minimum data constraint and the transmission power constraint. The block-coordinate descent method and the Lagrange duality method are used to obtain a suboptimal solution of this optimization problem. In the final simulation results, the superiority of the proposed NOMA scheme is confirmed compared with the benchmark NOMA schemes and the orthogonal multiple access (OMA) scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.6
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• pp.1357-1378
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• 2013

Energy constraint of wireless sensor networks makes energy saving and prolonging the network lifetime become the most important goals of routing protocols. In this paper, we propose an Energy Efficient Chain-based Routing Protocol (EECRP) for wireless sensor networks to minimize energy consumption and transmission delay. EECRP organizes sensor nodes into a set of horizontal chains and a vertical chain. Chain heads are elected based on the residual energy of nodes and distance from the header of upper level. In each horizontal chain, sensor nodes transmit their data to their own chain head based on chain routing mechanism. EECRP also adopts a chain-based data transmission mechanism for sending data packets from the chain heads to the base station. The simulation results show that EECRP outperforms LEACH, PEGASIS and ECCP in terms of network lifetime, energy consumption, number of data messages received at the base station, transmission delay and especially energy${\times}$delay metric.

• Journal of Communications and Networks
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• v.18 no.2
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• pp.173-181
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• 2016

In this paper, we address a new robust optimization problem in a multiuser multiple-input single-output broadcasting system with simultaneous wireless information and power transmission, where a multi-antenna base station (BS) sends energy and information simultaneously to multiple users equipped with a single antenna. Assuming that perfect channel-state information (CSI) for all channels is not available at the BS, the uncertainty of the CSI is modeled by an Euclidean ball-shaped uncertainty set. To optimally design transmit beamforming weights and receive power splitting, an average total transmit power minimization problem is investigated subject to the individual harvested power constraint and the received signal-to-interference-plus-noise ratio constraint at each user. Due to the channel uncertainty, the original problem becomes a homogeneous quadratically constrained quadratic problem, which is NP-hard. The original design problem is reformulated to a relaxed semidefinite program, and then two different approaches based on convex programming are proposed, which can be solved efficiently by the interior point algorithm. Numerical results are provided to validate the robustness of the proposed algorithms.

• Smart Structures and Systems
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• v.14 no.4
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• pp.617-641
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• 2014

The energy constraint is still a common issue for the practical application of wireless sensors, since they are usually powered by batteries which limit their lifetime. In this paper, a practical compound energy efficiency strategy is proposed and realized in the implementation of a real time wireless sensor platform. The platform is intended for wireless structural monitoring applications and consists of three parts, wireless sensing unit, base station and data acquisition and configuration software running in a computer within the Matlab environment. The high energy efficiency of the wireless sensor platform is achieved by a proposed adaptive radio transmission power control algorithm, and some straightforward methods, including adopting low power ICs and high efficient power management circuits, low duty cycle radio polling and switching off radio between two adjacent data packets' transmission. The adaptive transmission power control algorithm is based on the statistical average of the path loss estimations using a moving average filter. The algorithm is implemented in the wireless node and relies on the received signal strength feedback piggybacked in the ACK packet from the base station node to estimate the path loss. Therefore, it does not need any control packet overheads. Several experiments are carried out to investigate the link quality of radio channels, validate and evaluate the proposed adaptive transmission power control algorithm, including static and dynamic experiments.

• Journal of Communications and Networks
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• v.14 no.2
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• pp.130-139
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• 2012

Energy harvesting has emerged as a powerful technology for complementing current battery-powered communication systems in order to extend their lifetime. In this paper a general framework is introduced for the optimization of communication systems in which the transmitter is able to harvest energy from its environment. Assuming that the energy arrival process is known non-causally at the transmitter, the structure of the optimal transmission scheme, which maximizes the amount of transmitted data by a given deadline, is identified. Our framework includes models with continuous energy arrival as well as battery constraints. A battery that suffers from energy leakage is studied further, and the optimal transmission scheme is characterized for a constant leakage rate.

• Journal of Communications and Networks
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• v.10 no.1
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• pp.28-37
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• 2008

In this paper, we investigate the problem of minimizing the average transmission power of users while guaranteeing the average delay constraints in time-varying uplink channels. We design a scheduler that selects a user for transmission and determines the transmission rate of the selected user based on the channel and backlog information of users. Since it requires prohibitively high computation complexity to determine an optimal scheduler for multi-user systems, we propose a low-complexity scheduling scheme that can achieve near-optimal performance. In this scheme, we reduce the complexity by decomposing the multiuser problem into multiple individual user problems. We arrange the probability of selecting each user such that it can be determined only by the information of the corresponding user and then optimize the transmission rate of each user independently. We solve the user problem by using a dynamic programming approach and analyze the upper and lower bounds of average transmission power and average delay, respectively. In addition, we investigate the effects of the user selection algorithm on the performance for different channel models. We show that a channel-adaptive user selection algorithm can improve the energy efficiency under uncorrelated channels but the gain is obtainable only for loose delay requirements in the case of correlated channels. Based on this, we propose a user selection algorithm that adapts itself to both the channel condition and the backlog level, which turns out to be energy-efficient over wide range of delay requirement regardless of the channel model.