• 한국지능시스템학회논문지
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• 제25권3호
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• pp.299-305
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• 2015

Global environmental concerns and the ever increasing need of energy, coupled with steady progress in renewable energy technologies, are opening up new opportunities for utilization of renewable energy resources. Distributed electricity generation is a suitable option for sustainable development thanks to the load management benefits and the opportunity to provide electricity to remote areas. Solar energy being easy to harness, non-polluting and never ending is one of the best renewable energy sources for electricity generation in present and future time. Due to the random and intermittent nature of solar source, PV plants require the adoption of an energy storage and management system to compensate fluctuations and to meet the energy demand during night hours. This paper presents an efficient, economic and technical model for the design of a MPPT based grid connected PV with battery storage and management system. This system satisfies the energy demand through the PV based battery energy storage system. The aim is to present PV-BES system design and management strategy to maximize the system performance and economic profitability. PV-BES (photovoltaic based battery energy storage) system is operated in different modes to verify the system feasibility. In case of excess energy (mode 1), Li-ion batteries are charged using CC-CV mechanism effectively controlled by fuzzy logic based PID control system whereas during the time of insufficient power from PV system (mode 2), batteries are used as backup to compensate the power shortage at load and likewise other modes for different scenarios. This operational mode change in PV-BES system is implemented by State flow chart technique based on SOC, DC bus voltages and solar Irradiance. Performance of the proposed PV-BES system is verified by some simulations study. Simulation results showed that proposed system can overcome the disturbance of external environmental changes, and controls the energy flow in efficient and economical way.

• 상하수도학회지
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• 제12권2호
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• pp.90-98
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• 1998

The optimal rechlorination in water distribution systems was investigated by incorporating optimization techniques into a numerical water quality model. For a hypothetical system that consists of 10 junctions including a storage tank and 12 links, the bulk ($k_b$) and pipe-wall ($k_w$) decay-rate constants of chlorine residual are assumed to be 2.0 1/day and 1.5 m/day, respectively. It was also assumed that the lower and upper limits of chlorine residual in the network are 0.2 mg/L and 0.6 mg/L. When the chlorine source is only the storage tank (without rechlorination), the high levels of chlorine residual appear near the storage tank to maintain the chlorine residuals above the lower limit over the junctions. On the other hand, the chlorine residuals in the network are distribute within the desirable range (0.2 - 0.6 mg/L) after the optimal rechlorination through five injection sites including the storage tank. In case of a real water distribution system that comprises 28 junctions including a clear well and 27 links, the bulk and pipe-wall decay-rate constants are 0.3 1/day and 0.2 m/day, respectively. Before rechlorination, the required chlorine residual at the clearwell is 5.1 mg/L to keep the chlorine residuals above the minimum level (0.6 mg/L) over the junctions. By the optimal rechlorination at five injection sites, the chlorine residuals are distributed within a desirable range of 0.6 mg/L through 2.0 mg/L, which can avoid the excess of chlorine residuals near the clear well. Consequently, total chlirine doses are decreased by 81% in the hypothetical distribution network and 69 % in the real distribution network for satisfying the minimum chlorine residuals.

• 디지털콘텐츠학회 논문지
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• 제18권1호
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• pp.149-158
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• 2017

빅데이터는 경제개발에서 흥미로운 기회와 도전을 보여왔다. 예를 들어, 농업 분야에서 날씨 데이터 및 토양데이터와 같은 복합데이터의 조합과 이들의 분석 결과는 농업종사자 및 농업경영체들에게 귀중하고 도움되는 정보를 제공한다. 그러나 농업 데이터는 센서들과 농업 웹 마켓 등의 다양한 형태의 장치 및 서비스들을 통해 매 분마다 대규모로 생성된다. 이는 데이터 수집, 저장, 분석과 같은 빅데이터 이슈들을 발생시킨다. 비록 몇몇 시스템들이 이 문제를 해결하기 위해 제안되었으나, 이들은 다루는 데이터 종류의 제약, 저장 방식의 제약, 데이터 크기의 제약 등의 문제를 여전히 가지고 있다. 이 논문에서는 농업데이터의 수집과 분석 플랫폼의 새로운 설계를 제안한다. 제안하는 플랫폼은 (1) Flume과 MapReduce를 이용한 다양한 데이터 소스들로부터의 데이터 수집 방법, (2) HDFS, HBase, 그리고 Hive를 이용한 다양한 데이터 저장 방법, (3) Spark와 Hadoop을 이용한 빅데이터 분석 모듈들을 제공한다.

• 한국통신학회논문지
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• 제41권12호
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• pp.1684-1691
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• 2016

최근 분산 저장 시스템에 erasure code를 활용하여 저장소 효율성을 높이려는 연구가 활발히 진행되고 있다. 재생 부호(regenerating codes)는 erasure code의 일종으로, 높은 저장소 효율성과 네트워크 효율성을 가지는 코드이다. (n,k,d)-재생 부호는 n개의 저장소 노드를 가지며, 손실된 노드가 발생하였을 때, 해당 노드는 d개의 살아남은 노드로부터 정보를 다운로드받아 복구될 수 있다. 하지만 일반적인 재생 부호는 노드 복구 시 정확히 d개의 도움 노드들을 사용해야 하며, 노드 손실이 빈번하거나, 노드 간 접속이 불안정한 환경에서, d개 이하의 노드들에만 접속 가능할 경우에 유연하게 대처할 수 없다. 본 논문에서는 약간의 복구 대역폭의 희생을 통하여, $$k{\leq_-}{\bar{d}}{\leq_-}d$$의 다양한 도움 노드의 수 ${\bar{d}}$개로 노드를 복구할 수 있는 유연한 코드 운용 방식을 제안하였다.

• Journal of Information Processing Systems
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• 제14권4호
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• pp.989-1009
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• 2018

Rapid advances in science and technology with exponential development of smart mobile devices, workstations, supercomputers, smart gadgets and network servers has been witnessed over the past few years. The sudden increase in the Internet population and manifold growth in internet speeds has occasioned the generation of an enormous amount of data, now termed 'big data'. Given this scenario, storage of data on local servers or a personal computer is an issue, which can be resolved by utilizing cloud computing. At present, there are several cloud computing service providers available to resolve the big data issues. This paper establishes a framework that builds Hadoop clusters on the new single-board computer (SBC) Mobile Raspberry Pi. Moreover, these clusters offer facilities for storage as well as computing. Besides the fact that the regular data centers require large amounts of energy for operation, they also need cooling equipment and occupy prime real estate. However, this energy consumption scenario and the physical space constraints can be solved by employing a Mobile Raspberry Pi with Hadoop clusters that provides a cost-effective, low-power, high-speed solution along with micro-data center support for big data. Hadoop provides the required modules for the distributed processing of big data by deploying map-reduce programming approaches. In this work, the performance of SBC clusters and a single computer were compared. It can be observed from the experimental data that the SBC clusters exemplify superior performance to a single computer, by around 20%. Furthermore, the cluster processing speed for large volumes of data can be enhanced by escalating the number of SBC nodes. Data storage is accomplished by using a Hadoop Distributed File System (HDFS), which offers more flexibility and greater scalability than a single computer system.

• Steel and Composite Structures
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• 제23권6호
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• pp.683-690
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• 2017

In the stability and sensitivity design and diagnosis approaches, there are various methodologies available. Bond graph modeling by lumping technique is one of the universal methodologies in methodical analysis used by many researchers in all over the world. The accuracy of the method is validated in different arenas. Bond graphs are a concise, pictorial representation of the energy storage, dissipation and exchange mechanisms of interacting dynamic systems, subsystems and components. This paper proposes a bond graph modeling for distributed parameter systems using lumping techniques. Therefore, a steel frame structure was modeled to analyze employing bond graph modeling of distributed system using lumping technique. In the analytical part, the effectiveness of bond graphs to model this system is demonstrated. The dynamic responses of the system were computed and compared with those computed from the finite element analysis. The calculated maximum deflection time histories were found to be comparable. The sensitivity and the stability of the steel frame structure was also studied in different aspects. Thus, the proposed methodology, with its simplicity, can be used for stability and sensitivity analyses as alternative to finite element method for steel structures. The major value brought in the practical design is the simplicity of the proposed method for steel structures.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.640-643
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• 2003

A Walsh function based associative memory is capable of storing m patterns in a single pattern storage space with Walsh encoding of each pattern. Furthermore, each stored pattern can be matched against the stored patterns extremely fast using algorithmic parallel processing. As such, this special type of memory is ideal for real-time processing of large scale information. However this incredible efficiency generates large amount of crosstalk between stored patterns that incurs mis-recognition. This crosstalk is a function of the set of different sequencies [number of zero crossings] of the Walsh function associated with each pattern to be stored. This sequency set is thus optimized in this paper to minimize mis-recognition, as well as to maximize memory saying. In this paper, this Walsh memory has been applied to the problem of face recognition, where PCA is applied to dimensionality reduction. The maximum Walsh spectral component and genetic algorithm (GA) are applied to determine the optimal Walsh function set to be associated with the data to be stored. The experimental results indicate that the proposed methods provide a novel and robust technology to achieve an error-free, real-time, and memory-saving recognition of large scale patterns.

• 한국산업융합학회 논문집
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• 제21권5호
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• pp.207-217
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• 2018

Recently, the importance of energy demand management, particularly peak load control, has been increasing due to the policy changes of the Second Energy Basic Plan. Even though the installation of distributed generation systems such as Photovoltaic and energy storage systems (ESS) are encouraged, high initial installation costs make it difficult to expand their supply. In this study, the power consumption of a university building was measured in real time and the measured power consumption data was used to calculate the optimal installation capacity of the Photovoltaic and ESS, respectively. In order to calculate the optimal capacity, it is necessary to analyze the operation methods of the Photovoltaic and ESS while considering the KEPCO electricity billing system, power consumption patterns of the building, installation costs of the Photovoltaic and ESS, estimated savings on electric charges, and life time. In this study, the power consumption of the university building with a daily power consumption of approximately 200kWh and a peak power of approximately 20kW was measured per minute. An economic analysis conducted using these measured data showed that the optimal capacity was approximately 30kW for Photovoltaic and approximately 7kWh for ESS.

• Journal of Electrical Engineering and Technology
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• 제13권4호
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• pp.1459-1473
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• 2018

This paper focuses on voltage control schemes for multi-terminal low-voltage direct current (LVDC) distribution systems. In a multi-terminal LVDC distribution system, there can be multiple AC/DC converters that connect the LVDC distribution system to the AC grids. This configuration can provide enhanced reliability, grid-supporting functionality, and higher efficiency. The main applications of multi-terminal LVDC distribution systems include flexible power exchange between multiple power grids and integration of distributed energy resources (DERs) using DC voltages such as photovoltaics (PVs) and battery energy storage systems (BESSs). In multi-terminal LVDC distribution systems, voltage regulation is one of the most important issues for maintaining the electric power balance between demand and supply and providing high power quality to end customers. This paper focuses on a voltage control method for multi-terminal LVDC distribution system that can efficiently coordinate multiple control units, such as AC/DC converters, PVs and BESSs. In this paper, a control hierarchy is defined for undervoltage (UV) and overvoltage (OV) problems in LVDC distribution systems based on the control priority between the control units. This paper also proposes methods to determine accurate control commands for AC/DC converters and DERs. By using the proposed method, we can effectively maintain the line voltages in multi-terminal LVDC distribution systems in the normal range. The performance of the proposed voltage control method is evaluated by case studies.

• 한국정보처리학회논문지
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• 제7권2S호
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• pp.577-593
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• 2000

A distributed video-on-demand (VoD) system is one where collection of video data is located at dispersed sites across a computer network. In a single site environment, a local video server retrieves video data from its local storage device. However, in the setting of a distributed VoD system, when a customer requests a movie from the local server, the server may need to interact with other servers located across the network. In this paper, we present three types of presentation plans that a local server must construct in order to satisfy the customer request. Informally speaking, a presentation plan is a temporally synchronized detailed sequence of steps that the local server must perform for presenting the requested movie to the customer. This involves obtaining commitments from other video servers, obtaining commitments from the network service provider, as well as making commitments of local resources, within the limitations of available bandwidth, available buffer, and customer data consumption rates. Furthermore, for evaluating the goodness of a presentation plan, we introduce two measures of optimality for presentation plans: minimizing wait time for a customer, and minimizing access bandwidth is used. We develop algorithms to compute optimal presentation plans for all three types, and carry out extensive experiments to compare their performance. We have also mathematically proved certain results for the presentation plans that had previously been verified experimentally in the literature.