• Korean Journal of Artificial Intelligence
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• v.12 no.1
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• pp.17-24
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• 2024

This paper introduces a novel approach to time-series estimation for energy load forecasting within Virtual Power Plant (VPP) systems, leveraging advanced artificial intelligence (AI) algorithms, namely Long Short-Term Memory (LSTM) and Seasonal Autoregressive Integrated Moving Average (SARIMA). Virtual power plants, which integrate diverse microgrids managed by Energy Management Systems (EMS), require precise forecasting techniques to balance energy supply and demand efficiently. The paper introduces a hybrid-method forecasting model combining a parametric-based statistical technique and an AI algorithm. The LSTM algorithm is particularly employed to discern pattern correlations over fixed intervals, crucial for predicting accurate future energy loads. SARIMA is applied to generate time-series forecasts, accounting for non-stationary and seasonal variations. The forecasting model incorporates a broad spectrum of distributed energy resources, including renewable energy sources and conventional power plants. Data spanning a decade, sourced from the Korea Power Exchange (KPX) Electrical Power Statistical Information System (EPSIS), were utilized to validate the model. The proposed hybrid LSTM-SARIMA model with parameter sets (1, 1, 1, 12) and (2, 1, 1, 12) demonstrated a high fidelity to the actual observed data. Thus, it is concluded that the optimized system notably surpasses traditional forecasting methods, indicating that this model offers a viable solution for EMS to enhance short-term load forecasting.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.178-188
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• 2022

The introduction of virtual power plants is actively being discussed to solve the problem of grid acceptability caused by the spread of distributed renewable energy, which is the key to achieving carbon neutrality. However, a new business such as virtual power plants is difficult to secure economic feasibility at the initial stage of introduction because it is common that there is no compensation mechanism. Therefore, appropriate support including subsidy is required at the early stage. But, it is generally difficult to obtain the cost model to determine the subsidy level because of the lack of enough data for the new business model. In this study, a survey of domestic experts on the requirements, appropriate scale, and cost required for the introduction of virtual power plants is conducted. First, resource composition scenarios are designed from the survey results to consider the impact of the resource composition on the cost. Then, the cost estimation model is obtained using the individual cost estimation data for their resource compositions using logistic regression analysis. In the case study, appropriate initial subsidy levels are analyzed and compared for the virtual power plants on the scale of 20-500MW. The results show that mid-to-large resource composition cases show 29-51% lower cost than small-to-large resource composition cases.

• Journal of IKEEE
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• v.22 no.1
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• pp.6-13
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• 2018

To develop highly dependable CPS, M&S(modeling and simulation) is very important. It is not easy to model any CPS whole system in a single simulation tool because each simulation tool is optimized for modeling each different part of the CPS. The FMI is the standard for M&S between different simulation tools. The DDS is a communication middleware suitable for large-scale real-time data transmission. In this paper, we proposed FMI based CPS real-time distributed simulaton framework using DDS. To evaluate the performance of the proposed framework, we performed distributed simulation using IEEE HLA/RTI and OMG DDS middleware and measured and compared the execution time of the entire simulation. From the simulation results, we can confirm that the simulation execution time using DDS is at least 1.14 times faster compared to execution time using HLA/RTI.

• Journal of Communications and Networks
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• v.14 no.2
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• pp.188-194
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• 2012

Cognitive networks (CNs) are capable of enabling dynamic spectrum allocation, and thus constitute a promising technology for future wireless communication. Whereas, the implementation of CN will lead to the requirement of an increased energy-arrival rate, which is a significant parameter in energy harvesting design of a cognitive user (CU) device. A well-designed spectrum-sensing scheme will lower the energy-arrival rate that is required and enable CNs to self-sustain, which will also help alleviate global warming. In this paper, spectrum sensing in a multi-user cognitive ad hoc network with a wide-band spectrum is considered. Based on the prospective spectrum sensing, we classify CN operation into two modes: Distributed and centralized. In a distributed network, each CU conducts spectrum sensing for its own data transmission, while in a centralized network, there is only one cognitive cluster header which performs spectrum sensing and broadcasts its sensing results to other CUs. Thus, a wide-band spectrum that is divided into multiple sub-channels can be sensed simultaneously in a distributed manner or sequentially in a centralized manner. We consider the energy consumption for spectrum sensing only of an analog-to-digital convertor (ADC). By formulating energy consumption for spectrum sensing in terms of the sub-channel sampling rate and whole-band sensing time, the sampling rate and whole-band sensing time that are optimal for minimizing the total energy consumption within sensing reliability constraints are obtained. A power dissipation model of an ADC, which plays an important role in formulating the energy efficiency problem, is presented. Using AD9051 as an ADC example, our numerical results show that the optimal sensing parameters will achieve a reduction in the energy-arrival rate of up to 97.7% and 50% in a distributed and a centralized network, respectively, when comparing the optimal and worst-case energy consumption for given system settings.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.6
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• pp.115-125
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• 2001

Authentication and access control are essential requirements for the information security of distributed environment. Delegation is process whereby an initiator principal in a distributed environment authorizes another principal to carry out some functions on behalf of the former. Delegation of access rights also increases the availability of services offer safety in distributed environments. A delegation easily provides principal to grant privileges in the single domain with Role-Based Access Control(RBAC). But in the multi-domain, initiators who request delegation may require to limit the access right of their delegates with restrictions that are called delegate restriction to protect the abuse of privilege. In this paper, we propose the delegation view as function of delegation restrictions. Proposed delegation view model not only prevent over-exposure of documents from granting multiple step delegation to document sharing in multi-domain with RBAC infrastructure but also reduce overload of security administrator and communication.

• Journal of Elementary Mathematics Education in Korea
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• v.12 no.2
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• pp.165-183
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• 2008

This study is to help to understand the influence of exchange writing activity in the elementary mathematics on students' mathematical communication skill. Various technical activities had been implemented during the classes and the ideas from those activities had been interpreted into writings in the final stage of the classes. Those writings, then, were distributed to other students or teachers in order to devise a teaching model for exchange writing, which is to be applied to the 3rd grade classes and to identify the influence on the in mathematical communication skill. From this study, we could get such conclusions as follows: First, there was considerable difference between experimental group practicing exchange writing and control group engaging in normal learning activities in the progress of their mathematical communication skill (group discussion), writing skill and expressivity when examining their average communication skill using t-method. Similar trend had been witnessed when self-evaluating their mathematical communication skill. Second, when it comes to the mathematical tendency, experimental group showed a higher tendency in positiveness compared to the control group. Therefore, we might conclude that the exchange writing has a positive influence on the students' mathematical tendency, especially on their curiosity or interest in teaming, willingness to study and their comprehension of its importance.

• Journal of Computing Science and Engineering
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• v.11 no.4
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• pp.152-159
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• 2017

Three-dimensional (3D) printing is applied to many areas of life, but 3D printing models are stolen by pirates and distributed without any permission from the original providers. Moreover, some special models and anti-weapon models in 3D printing must be secured from the unauthorized user. Therefore, 3D printing models must be encrypted before being stored and transmitted to ensure access and to prevent illegal copying. This paper presents a selective encryption algorithm for 3D printing models based on clustering and the frequency domain of discrete cosine transform. All facets are extracted from 3D printing model, divided into groups by the clustering algorithm, and all vertices of facets in each group are transformed to the frequency domain of a discrete cosine transform. The proposed algorithm is based on encrypting the selected coefficients in the frequency domain of discrete cosine transform to generate the encrypted 3D printing model. Experimental results verified that the proposed algorithm is very effective for 3D printing models. The entire 3D printing model is altered after the encryption process. The decrypting error is approximated to be zero. The proposed algorithm provides a better method and more security than previous methods.

• Korea Journal of Hospital Management
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• v.20 no.2
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• pp.28-38
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• 2015

This study was conducted by extending Ajzen's Theory of Planned Behavior(TPB) model in analyzing physician's observance behavior of National Health Insurance review standards. An extended TPB model was proposed by including 'background knowledge'and 'dorganizational commitment'in original model to predict physician's review standards observance behavior. Surveys for data collection were carried out on the physicians who were working in a general hospital, clinics, specialized hospitals, local medical centers and long term care hospitals located in Daegu and Kyoung-Buk province in Korea. Two hundreds twenty copies of questionnaires were distributed and 166 physicians responded. Data were analyzed using a structural equation model. The results show that an affirmative attitude and subjective norms have significant positive effects on physicians' behavior of observing review standards. However, the effect of perceived behavioral control on intention to behavior is not significant. The organizational commitment and background knowledge have a positive effect on the intention of observance of review standards. In conclusion, because physician's observance behaviors are affected by background knowledge and organizational commitment as well as attitudes, subjective norms, hospital managements should establish a communication system to share information on the review standards among physicians and provide appropriate measures to increase physician's organizational commitment.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.2
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• pp.184-189
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• 2013

In this paper, we propose the injurious moving picture filtering system using certain sounds contained in the injurious moving picture to filter injurious moving picture which is distributed without limitation in internet and internet storage space. For this purpose, the Gaussian Mixture Model which can well represent the characteristics of the sound, is used and frame level likelihood estimation is used to calculate the likelihood between filtering target data and the sound models. Also, the pruning method which can real-time proceed by reducing the comparing number of data, is applied for real-time processing, and MWMR method which showed good performance from existing speaker identification, is applied for the distinguish performance of high precision. In the identification experiment result, in case of the frame rate which is the proportion of total frame to high likelihood frame, is set to 50%, identification error rate is 6.06%, and in case of frame rate is set to 60%, error rate is 3.03%. As the result, the proposed system can distinguish between general and injurious moving picture effectively.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.2
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• pp.31-39
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• 1998

In this paper, we have presented a quantitative performance effect of CCP(Call Control Processor) when SAAL(Signalling ATM Adaptation Layer) function is distributed from CCP to SIMs(Subscriber Interface Modules) in an ATM switching system with distributed architecutre. For the performance analysis, SLAM II simulation language is used and subscriber signalling messageand inter-processor communication messages according to Q.2931 based local call processing procedure are taken into consideration in the proposed queuing network model. The results of simulation are compared with in case of processing SAAL function on CCP. It is observed that the processing utilization of CCP reach 24,000 BHCA and 25,700 BHCAwhen SAAL function load amounts to 10% and 20% of the processing time of the total message, respectively. These values shows that the processing utilization of CCP is alleviated about 7% in comparison with 2,000 BHCA in case that SAAL function is carried out on CCP. Consquently, it is shown that we have to consider seriously how to distribute the functions concerning call processing in a large cale ATM switching system architecture accomodating a number of SIMs.