Earticle

최근 풍력에너지는 풍력터빈의 지능화뿐만 아니라 풍력 발전량 예측 부분에서 컴퓨팅과의 결합이 확대되고 있다. 풍력 발전은 기상상태에 따라 출력변동이 심하고 출력 예측이 어려워 효율적인 전력 생산을 위해서 신재생에너지를 전력계통에 안정적으로 연계할 수 있는 기술이 필요하다. 본 논문에서는 분산형 전원의 예측정보를 향상시켜 예측한 발전량과 실제 발전량의 차이를 최소화하기 위한 분산형 전원전력의 단기예측 모델을 설계한다. 제안된 모델은 단기 예측을 위해서 물리모델과 통계모델을 결합하였으며, 물리모델에서 생산된 격자별 예측값 중 예측 지점내 예측지점의 값을 추출하고, 물리 모델 예측값에 통계모델을 적용하여 발전량 산정을 위한 최종 기상 예측값을 생성한다. 또한, 제안 모델에서는 실시간 기상청 관측자료와 실시간 중기 예측 자료를 입력 자료로 사용하여 단기 예측 모델을 수행한다.

Recently, wind energy is expanding to combination of computing to forecast of wind power generation as well as intelligent of wind powerturbine. Wind power is rise and fall depending on weather conditions and difficult to predict the output for efficient power production. Wind power is need to reliably linked technology in order to efficient power generation. In this paper, distributed power generation forecasts to enhance the predicted and actual power generation in order to minimize the difference between the power of distributed power short-term prediction model is designed. The proposed model for prediction of short-term combining the physical models and statistical models were produced in a physical model of the predicted value predicted by the lattice points within the branch prediction to extract the value of a physical model by applying the estimated value of a statistical model for estimating power generation final gas phase produces a predicted value. Also, the proposed model in real-time National Weather Service forecast for medium-term and real-time observations used as input data to perform the short-term prediction models.

최근 정부의 녹색성장 정책에 의해 배전계통에 태양광, 풍력발전 등과 같은 분산전원의 보급률이 지속적 으로 증가되고 있는 실정이다. 이러한 분산전원의 설치가 급증함에 따라 기존 배전계통의 조류흐름은 단방향(Onedirection) 에서 양방향(Bi-direction)으로 변화되고 고장전류의 증·감이 발생하는 등, 다양한 변화가 생겨 배전계통 의 운용상에 여러 가지 문제점들이 발생할 가능성이 커지고 있다. 따라서 본 논문에서는 분산전원의 배전계통 연계 에 따른 보호기기의 정정 및 양방향 보호협조검토가 가능한 보호협조 평가알고리즘을 제안하고, 그 알고리즘을 바 탕으로 양방향 보호협조 평가시스템을 제작하였다. 또한 평가시스템을 이용하여 배전계통을 모델링하고 분산전원 연계 시 보호기기들 사이의 보호협조를 검토하여, 분산전원이 연계된 경우 배전계통에 발생할 수 있는 기술적인 문제점들을 분석하여 그 방안을 제시하였다.

Recently, with the increasement of the interest about global warming, pollutions, and so on, a number of distributed generations(DGs) such as photovoltaic(PV) and wind power(WP), are interconnected with distribution systems. However, installing of DGs makes power flow changes such as directions, one-direction to bi-direction, and increasing/decreasing of fault current. Therefore, it may cause the critical problems. This paper proposes an evaluation algorithm for bi-directional protection coordination and presents an evaluation system for protection coordination based on this algorithm. Additionally, the result shows that the existing method may cause critical problems, and also the effectiveness of proposed method is verified.

본 논문은 분산 시스템에서의 표준합성환경 기반 수중 교전 시뮬레이션을 위한 방법론이다. 수 중 교전 시뮬레이션의 경우 염분과 수온 등의 수중 환경 데이터를 시뮬레이션에 반영하는 것이 중요 하다. 분산 시뮬레이션 시스템에서 이러한 환경 데이터의 재사용성과 상호운용성 향상을 위해 합성 환 경 표현 및 교환 표준(Synthetic Environmental Data Representation and Interchange Specification, SEDRIS(ISO standard for environmental data))이 개발되었고, 본 논문에서는 SEDRIS 를 활용하여 수중 합성환경을 구축한다. 본 논문을 통해 SEDRIS가 합성환경 데이터의 국제 표준이 지만 그 방대함과 복잡함으로 인하여 사용이 저해된 문제점을 대기/해양 환경에 대해 효율적인 SEDRIS 기술 활용 방법을 제시하여 해결한다. 본 논문의 최종 목적은 대기/해양 환경 표현을 위한 다차원 격자 기반의 SEDRIS 구조를 구축하고, High Level Architecture (HLA)/Run-Time Infrastructure (RTI) 기반의 분산 시스템에서 대기/해양 합성전장환경 구축에 SEDRIS 적용 방법을 제시한다.

Presented in the paper is a methodology for the distributed simulation of underwater warfare based on standard synthetic environment. In the case of underwater warfare simulation, it is very important to reflect environmental data, such as salinity and temperature. For the reusability and interoperability of environmental data, this paper adopts Synthetic Environmental Data Representation and Interchange Specification (SEDRIS(ISO standard for environmental data)). Although SEDRIS provides various merits as an international standard, applying of SEDRIS has been hindered by its broadness and heaviness. To relieve the difficulties, this paper proposes an efficient procedure to utilize SEDRIS technology for the atmosphere and underwater environment. This paper identifies SEDRIS structure for the atmosphere/underwater structured dimensional grid-based and implements the proposed procedure on the High Level Architecture (HLA) / Run-Time Infrastructure (RTI) to explain the generation of the battlefield in a distributed simulation system.

In order to minimize power losses caused by high current and improve the voltage profile in the network distribution, the introduction of dispersed generations also called productions decentralized in distribution network (DG) plays an important role. The installation of DGs directly affects the power requested or purchased. The sizing and placement of DGs in the system must be optimal because a wrong choice has a negative impact on the system behavior. To solve this combinatorial problem, an algorithm known as Firefly algorithm is proposed in this paper. This is a meta-heuristic algorithm inspired by the behavior of fireflies flashing. The main objective of firefly flash is to act as a signaling system to attract other fireflies. Networks tested IEEE69-bus and IEEE33-bus are used to evaluate the effectiveness of this method. The results are compared with those obtained by genetic algorithm (GA) to IEEE69-bus, and Shuffled frog leaping algorithm (SFLA) for IEEE 33-bus.

Protection system is used to protect components against fault as fast as possible and also to minimize the area around it from fault. Nowadays because of the existence of Distributed Generation in power system, a change is needed to be implemented for protection system at distribution network in order to ensure the electricity can be supplied to the consumer safely. With the presence of distributed generation (DG) units in distribution systems, the function of relay protection is generally going to be changed. In this paper the impact of installing Dis-tributed Generation in radial system on the directional over-current protection relay, in pres-ence of a Thyristor Controlled Series Capacitor on fault courant is investigated. The relays coordination scheme was developed through analysis for three fault location scenarios. A realistic feeder system for a case study with its scheme protection is developed in Matlab software environment.

Distributed generation is a form of electric power privatization. Consumers install their own power station to supply the local loads and/or share in the utility loads. Many protective problems have been developed due to the existence of these distributed generations. However, a protective strategy should be developed to protect the system and the generator itself from different hazards. One problem with such generators is an unwanted islanding phenomenon. This paper introduces a hybrid passive method for islanding detection to minimize the non-detective zone. This method based on composed of rate of change of frequency over power under each event and rate of change of DG reactive power under each event (ROCORP). Simulation results which are carried out on software PSCAD/EMTDC shows good performance of this method.

In this paper, network reconfiguration has been conducted to improve the power quality and reliability of distribution systems in presence of distributed generations. In this case, network reconfiguration is analyzed for different indices. The most important indices are the number of propagated voltage sags (N sag), sustained average interruption frequency index, average system interruption frequency index and momentary average interruption frequency index. The Imperialist competitive algorithm (ICA) is hired to find the optimal configuration of the distribution system in order to minimize the mentioned indices. Simulation result is discussed with and without distributed generation.

In today’s trend, the importance of Distributed Generation (DG) implementation in the distribution system (DS) becomes more significant with respect to proper location, sizing and reduction of losses. In this paper the location and size of DG were discussed based on Voltage Limitation Index (VLI). This index is used to ensure that all the buses in the network have acceptable voltage profile according to the distribution permissible limits. After determining the DG size and location a comprehensive analysis on cost of DG, energy loss occurred and savings obtained in the network were listed. The significance of VLI was tested on IEEE 33 and 69 bus DS under initial configuration state as well as in feeder reconfigured state also.

Optimal allocation of distributed generations (DGs) integrated into micro grids can significantly improve the stability and benefit the economy of micro grid operation. However, optimal micro grid planning is a kind of multi-dimensional and non-linear optimization problem. In this study, a multi-objective model is established by adopting the objective function which minimizes network loss, electricity price and operation cost; an improved particle swarm optimization (IPSO) algorithm with better optimizing performance is proposed by improving the initializing method and parameter control as well as average minimum and mutation factor are introduced. The proposed IPSO algorithm is then applied to a 29-node micro grid network structure. The comparison between different optimization schemes demonstrates the significance of optimal placement of DGs in micro grids. And it is also clear that the IPSO algorithm proposed in this study can effectively solve such problems.

Distributed computing systems have evolved over decades to support various types of scientific applications and overall computing paradigms have been categorized into HTC (High-Throughput Computing) to support bags of tasks which are usually long running, HPC (High-Performance Computing) for processing tightly-coupled communication-intensive tasks on top of dedicated clusters of workstations or Supercomputers, and Data-intensive Computing leveraging distributed storage systems and parallel processing frameworks. Many-Task Computing (MTC) aims to bridge the gap between traditional HTC and HPC by building efficient middleware systems throughout employing lightweight task dispatching mechanisms, minimizing data movements, leveraging data-aware scheduling, and proposing of next generation Exascale storage systems. Recent emerging applications requiring millions or even billions of tasks to be processed with relatively short per task execution times have driven this new computing paradigm. In this paper, we investigate concepts and technologies of MTC and propose guidelines for building an efficient and effective middleware system to fully support MTC applications. Throughout our short survey about challenges, systems and applications of MTC, we argue that a next generation distributed middleware system must effectively leverage distributed file systems, parallel processing frameworks, decentralized data/compute management systems, and dynamic load balancing techniques to solve the most challenging and complex scientific problems.

Renewable sources integration is gaining importance in electrical utilities all over the world. The liberization of power sector in competitive regime, the share of renewable energy sources is increasing and it is essential to carry out the impact of clean energy on the system performance In this paper, analysis has been carried out with the PV-based distribution generation in the power system network. A Mixed Integer Nonlinear Programming (MINLP) approach has been utilized for determining optimal location and number of distributed generators considering minimization of fuel cost of conventional and solar PV power. The pattern of nodal real and reactive power prices have been obtained with and without PV integration. The results are also obtained for, loss reduction, fuel cost saving and voltage profile. The impact of different load models as PQ load and Zip load model has been studied. The proposed MINLP based optimization approach has been applied for IEEE24 bus reliability test system.

The system of distribution network with distributed generation is analyzed, and dynamic optimization based on an improved genetic algorithm is presented in this paper. First, the mathematical model of distribution network can be established by using constraints and objective function, which contains the network loss, the DGs investment and reliability of power supply. Then, according the construction of distribution network, this paper presents a design of improved genetic algorithm. Finally, IEEE 14 nodes system is adopted to realize the design of the algorithm.

With the continuous development of economy and social progress, the social requirement of power network is more and more high. This paper, as a basis research of distributed generation, proceed mainly from the impact of distributed generation on power grid, detailed fine analysis of the influence of all kinds of distributed generation on power network adverse, including power system stability, power quality, power supply reliability effect. In order to avoid these adverse effects, we combining the distributed grid technology and smart micro grid, put distributed generation as a branch of the micro grid that can be ideal to connect grid and can avoid most of the problems mentioned above. Distributed intelligent micro grid system uses variety of new energy supply, it is a comprehensive model of power electronic technology, distributed generation, renewable energy power technology and energy storage technology .The paper provides a reference for the use of future distributed power generation.

Due to the complexity of the smart grid and the uncertainty of the distributed generation, there is a lot of uncertain information in smart grid. The theory of rough intuitionist fuzzy set is proposed in this article to deal with the fault diagnosis in the case of uncertain information. Fault position and the fault device can be judged based on current, voltage and the action of protection device and circuit breakers under failure state, including error and incomplete fault signal caused by malfunction, bit error in signal propagation. Diagnosis rules can be extracted from the set of fault samples. Diagnosis rules obtained by this method can be used to establish the fault diagnosis knowledge base, thus provides a feasible method for the fault diagnosis of smart grid.

Distributed renewable energy generation is lack of intelligent information processing and decision-making section. The above problems can be solved effectively by the means of intelligent information processing technology based on the dynamic structure of multi-agent for distributed renewable energy. In order to solve the problems of less data and poor information, this paper puts forward fuzzy hyperbolic model and attempts to use dynamic intelligent information processing technology based on multi-agent to change the unreliable, inaccurate information into be full, reliable and accurate. And then the information we have obtained could be intelligent fitted, filtered and decided. The self-organizing self-learning and reasoning ability of multi-agent are considered when the information processing. The intelligent information processing section is comprised of three layers and two kinds of agents. The two kinds of agents are Bus Agents and Coordination Agents, and the three structural layers are the data layer, the filter layer and the policy making layer. Moreover the information have been processed could be utilized.

Suitable location and optimal sizing are impact on voltage stability margin of the distributed system. It is important to accurately simulate the random output active power of Distributed Generation (DG). In order to model uncertainties of intermittent distributed generation and load, this paper proposes a multi-scenario tree model of wind-photovoltaic-load using multiple scenarios technique based on the Wasserstein distance metrics, which generates asymptotically optimal scenario. And in this paper, a multi-objective optimizes control model with scenario tree is presented, which including objectives that are the total active power losses and the voltage deviations of the bus. Moreover, a new hybrid Honey Bee Mating Optimization and Particle Swarm Optimization (HBMO-PSO) algorithm is proposed to solved the problems. In the HBMO-PSO algorithm, the mating process is corrected, which the PSO algorithm is combined with the HBMO algorithm to improve the performance of HBMO. Finally, a typical IEEE 33-bus distribution test system is used to investigate the feasibility and effectiveness of the proposed method. Simulation results illustrate the correctness and adaptability of the proposed model and the improved algorithm.

Single-phase grid-connected inverters play an important role in small distributed generation (DG) systems. This paper illustrates the circuit configuration and operation principle of a novel single-phase, single-stage, three-switch, fly-back, buck-boost inverter. The equivalent circuits associated with the four operation modes are established for the charging and discharging process. The inverter can operate in both continuous conduction mode (CCM) and discontinuous conduction mode (DCM). Most importantly, a new pulse generation method called pulse energy modulation (PEM) is proposed and applied to the three-switch buck-boost inverter in this paper. PEM signals for controlling the power switches are generated by meeting the output energy demand in each switching period with the stored energy in the coupled fly-back inductors. The duty ratio of PEM is thus determined by the energy demand and dc input voltage. The efficiency of the inverter used PEM is analyzed. A 400W experimental prototype is built in the laboratory to verify the operation of the proposed pulse energy modulation method. The inverter controller employs DSP dsPIC33FJ64MC506 for controlling, detecting and protecting functions. Experimental results have shown that PEM provides a new modulation mechanism for controlling the three-switch buck-boost inverter to inject a sinusoidal current into the grid under a wide range of operating conditions.

GAN(Generative Adversarial Networks)이 합성 이미지 생성 및 기타 다양한 응용 프로그램에 현재 사용되고 있지만, 생성 모델을 제어하기가 어렵다. 문제는 생성 모델의 잠재 공간에 있는데, 이미지 생성과 관련하여 입력된 잠재 코드를 받아 특정 텍스트 및 신호에 따라 지정된 대상 속성이 향상되도록 하고 다른 속성은 크게 영향을 받지 않도록 하기 위해서는 상당한 제약이 요구된다. 본 연구에서는 이미지 생성 및 조작과 관련하여 변동 자동 인코더의 잠재 벡터 에 관해 특정 제약을 수반한 모델을 제안한다. 제안된 모델에 관해 TensorFlow의 변동 자동 인코더를 통해 실험한 결과 이미지의 생성 및 조작과 관련하여 비교적 우수한 성능을 갖는 것으로 확인된다.

Recent research shows that latent directions can be used to image process towards certain attributes. However, controlling the generation process of generative model is very difficult. Though the latent directions are used to image process for certain attributes, many restrictions are required to enhance the attributes received the latent vectors according to certain text and prompts and other attributes largely unaffected. This study presents a generative model having certain restriction to the latent vectors for image generation and manipulation. The suggested method requires only few minutes per manipulation, and the simulation results through Tensorflow Variational Auto-encoder show the effectiveness of the suggested approach with extensive results.