Earticle

최근 스마트 그리드와 관련된 프로젝트가 선진국을 중심으로 활발하게 연구되고 있다. 특히, 전력 문제의 장기적 안정 대책으로 분산전원이 주목받고 있다. 본 논문에서는 분산형 전원의 출력 예측을 위해서 물리모델과 통 계모델을 조합하여 예측 정보 오차율을 비교분석할 수 있는 3차원 기상 수치 모델을 제안한다. 제안 모델은 분산형 전원의 예측정보를 향상시킬 수 있어 안정적인 전력계통 연계를 위한 예측시스템을 가능하다. 성능평가 결과, 제안 모델은 발전량 예측 정확도가 4.6% 개선되었고, 온도보정 예측 정확도는 3.5% 향상되었다. 마지막으로 일사량 보정 정확도는 1.1% 향상되었다.

Recently, the project related to the smart grid are being actively studied around the developed world. In particular, the long-term stabilization measures distributed power supply problem has been highlighted. In this paper, we propose a three-dimensional numerical weather prediction models to compare the error rate information which combined with the physical models and statistical models to predict the output of distributed power. Proposed model can predict the system for a stable power grid-can improve the prediction information of the distributed power. In performance evaluation, proposed model was a generation forecasting accuracy improved by 4.6%, temperature compensated prediction accuracy was improved by 3.5%. Finally, the solar radiation correction accuracy is improved by 1.1%.

A distributed congestion control must be adaptable to varying target communication ranges as cellular V2X (C-V2X) is evolving to support flexible coverage suitable for various service scenarios. This study proposes range-adaptive distributed power control (Ra-DPC) based on deep reinforcement learning (DRL) with the Monte Carlo policy gradient algorithm. A key finding is that the agents learn Ra-DPC more effectively when the cumulative interference power of the subchannels is adopted as the state of the DRL model, rather than the channel busy ratio. The proposed Ra-DPC algorithm performs better in energy efficiency and packet delivery ratio than the existing technologies.

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.

이 논문에서는 무선 멀티홉 네트워크 환경에서 종단간 최적 전송률을 제공하기 위한 분산 송신전력제어 방안을 제안한다. 제안 방안은 멀티홉 구성 링크들의 전송률이 갖는 연대 특성과 멀티홉 종단간 전송률이 최소 링크 전송률에 의해 결정된다는 점을 고려하여, 멀티홉 구성 링크들의 전송률이 모두 같아지도록 송신전력을 제어함으로써 종단간 전송률을 최대화 한다. 또한 제안 방안은 이웃단말과의 정보 공유만을 가지고 단말 스스로 송신전력 값을 계산하는 분산 방식으로 송신전력 제어에 필요한 정보 교환 오버헤드를 줄인다. 시뮬레이션 결과 제안 방안은 고정된 최대 송신전력 값을 사용한 기존 방식 대비 종단간 전송률과 전력소비 측면에서 큰 성능이득을 보여준다.

In this paper, we propose a distributed transmit power control algorithm for optimal end-to-end throughput in wireless multihop networks. Considering a solidarity property of link rates consisting of a multihop link and the fact that the multihop end-to-end throughput is determined by the minimum link rate, the proposed scheme controls the transmit power to make all link rates be equal and so maximizes the end-to-end throughput of multihop link. In addition, in the proposed scheme the transmit node calculates its transmit power autonomously in a distributed manner just through the information sharing with its neighbor nodes and so decreases the information sharing overhead. Simulation results show that the proposed scheme achieves significant improvements in terms of end-to-end throughput and power consumption compared with the conventional maximum equal power allocation scheme.

The current paper proposes fast distributed constrained power control (FDCPC) with a non‐stationary relaxation factor as the next power update for CDMA cellular power control systems. A review is also given of unconstrained control algorithms: distributed power control (DPC), unconstrained second‐order power control (USOPC), and DPC with a stationary relaxation factor (DPCSRF). To improve the performance of outage probability convergence, DCPC with a non‐stationary relaxation factor (FDCPC) is proposed. Under constrained conditions, the convergence rate of FDCPC is shown to outperform that of DCPC and constrained second order power control(CSOPC).

This paper presents a new 60 GHz amplifier design method using TSMC 90 nm CMOS technology. The proposed design scheme is based on the way of the distributed amplifier design with open gate & open drain. The proposed architecture is analyzed and we define the upper limit to adopt proposed method in designing 60 GHz amplifier. To verify the effectiveness of the proposed scheme, the 60 GHz power amplifier with three cascade structure is designed and measured. Thanks to the proposed design structure, the fabricated power amplifier shows 29 dB peak gain, 25 dB gain over the 56~65 GHz, 11.5 dBm OP1dB, 13 dBm saturation power and peak 18.8 % PAE(Power Added Efficiency) under 2V supply voltage. Judging from the measurement results, the suggested architecture is a promising way for the future millimeter wave CMOS amplifier.

본 연구에서 고찰되는 가상발전소(VPP; Virtual Power Plant) 솔루션 플랫폼은 전력회사가 발전・송전설비 등의 건설에 소요되는 비용과 이와 관련된 투자리스크를 최소화 한다. 또한, 소비자의 전력 수요를 충족할 수 있도록 수요대응(DR; Demand Response) 프로그램운영 기능을 포함시켜 VPP도입으로 발전 및 송・배전부문에 대한 대규모 설비투자 없이 현존하는 발전기와 DR 프로그램 등을 통해서 소비자의 부하변화에 실시간으로 대처하여 보다 친환경적 이고 효율적인 전력공급이 가능하도록 한다. 태양광 및 ESS 연동 장치에 통신 Device를 연동하기 위해서는 Device 장치와 Edge System간 제어・상태에서 데이터를 전달하고 IoT Device 및 연동 플랫폼 개발(OneM2M)이 필요하다.

In this study, The Virtual Power Plant (VPP) solution platform considered in this study minimizes the cost and investment risk associated with the construction of power generation and transmission facilities. In addition, it includes a Demand Response (DR) program operation function to meet consumers' electricity demand. With the introduction of VPP, it is possible to provide more eco-friendly and efficient power by responding to changes in consumer load in real time through existing generators and DR programs without large-scale facility investment in power generation and transmission/distribution sectors. In order to link the communication device to the solar power and ESS linkage device, it is necessary to transmit data in the control/state between the device device and the edge system and develop an IoT device and interworking platform (OneM2M).

At present, the technology of the distributed power grid gradually become mature. The focus of the study is from controlling power quality to reducing the loss of power grid, improving the network efficiency and reducing the cost. In the link of distributed generation grid connected power generation, the loss of the switching device is an important factor affecting the efficiency of grid connection. This paper puts forward a systematic solution to this problem. Firstly, as for topology structure of grid connected controller, aiming at the research on NPC, a traditional topology which is energy-saving and low loss, we present an improved NPC topology with a more continuous flow state. At the same time for this topology, the corresponding control strategies are designed in this paper. It makes the switching device of the grid connected controller have more freedom of switch and make the system can achieve the precise control of the switch tube ,which can achieve the balance of system device lose heat so as to solve the problem of local high temperature from inverter. The system is verified by grid connected test, the power adjustable PWM strategy can be used to achieve different working states without affecting the output current of the system. Through the comparison between light and heat sensors finds that the topology and control strategy proposed in this paper are successfully completed by the new hardware topology and control strategy to achieve the loss balance of the system switching devices.

With the continuous expansion of the scale of distributed power generation，multi grid connected converters often prone to oscillation problems when parallel operation.In this paper,we study the equivalent circuit of parallel connection of multi grid connected converters , system response characteristics of voltage source and in-depth analysis of the causes of the parallel oscillation of the converters.This paper analyzes converter’s parallel complex vector model by complex vector and comes to a conclusion that power grid voltage feed-forward will produce strong coupling between converter so that cause oscillation parallel converters. In view of the above problems and the flow of the converter starting or the voltage fluctuation of the grid, we design a low feed forward method, that is to make the fundamental and the main sub components of the grid voltage forward without delay and for the relative high frequency components, the filter technology is used to attenuate, so as to achieve the maximum elimination of the feed-forward coupling between the converter, to prevent the occurrence of system oscillation. In order to verify the use of this paper, the theory of the parallel converter is applied in the field of MW level wind field. The experimental results prove the correctness of the theory.

This work aims to study a variety of distributed power access based on the theory of operation microgrid control. It provided a theoretical reference and reference for the development of micro-engineering application grid technology. In this paper, the risk characteristics of grid operations management side under the background of the smart grid, from project investment, load forecasting, renewable energy power purchase access, economic dispatch, information security, and constructed investment project set risk transfer model, load forecasting risk transfer model, considering the economic dispatch model smart grid element of risk transfer. It takes into account price and load uncertainties purchase risk transfer element optimization model, smart grid information security risk assessment element transfer model to study the dynamics of the smart grid from a risk point of view under the grid-side operational risk management.

The design of an automatic voltage regulator (AVR) microcontroller-based distributed DC power supply is presented. The system includes a photovoltaic (PV) power generation, commercial hardware drive power system, and a battery booster circuit. A software control technology is used for storage battery charging and discharging. The PID control algorithm is used to control AVR microcontroller to achieve maximum power point tracking (MPPT) and to improve system stability. In addition to the traditional battery power, the system can make full use of solar system for energy sustainability. Experiment results show that the proposed system outperforms the traditional system with respect to the function of track, monitor and fine-tune for system steady state.

A large number of distributed photovoltaic power grid, islanding problems become more prominent. This paper first analyzes some existing anti-islanding scheme, and analyzes its advantages and disadvantages. Then, this paper proposes adaptive anti-islanding scheme by using the load, i.e. load automatic switching, changing the characteristics of the whole load, make the passive anti-islanding without dead-zone. Then using PSCAD simulation of the program, to verify the usefulness of the proposed scheme. To minimize the distributed photovoltaic power grid investment, saving the scheme relies on a new generation of distributed photovoltaic (pv) grid interface device. Then the paper introduces the overall structure and function of the device configuration, the device not only can solve the problem of area of backup protection, also save on investment, convenient for on-site equipment installation and maintenance, for the widespread promotion of distributed photovoltaic power grid to lay a solid foundation.

In this paper, the transmit power minimization for Poisson distributed wireless ad-hoc relay networks in Rayleigh fading channels is considered. We investigate two power allocation methods one is a minimum power allocation (MPA) strategy and the other is an equal outage power allocation (EOPA) strategy. We analyze the total transmit power of two allocation methods under the given end-to-end outage probabilityconstraint. Our results show that the MPA achieves more power saving than EOPA, and the power saving is more significant as the number of relay nodes increases.

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 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.

본 논문은 분산형 전력 시스템에서 심층강화학습 기반의 전력 생산 환경 및 수요와 공급을 예측하며 자원 할당 알고리즘을 적용해 전력거래 시스템 연구의 최적화된 결과를 보여준다. 전력 거래시스템에 있어서 기존의 중앙집중식 전력 시스템에서 분산형 전력 시스템으로의 패러다임 변화에 맞추어 전력거래에 있어서 공동의 이익을 추구하며 장기적 인 거래의 효율을 증가시키는 전력 거래시스템의 구축을 목표로 한다. 심층강화학습의 현실적인 에너지 모델과 환경을 만들고 학습을 시키기 위해 날씨와 매달의 패턴을 분석하여 데이터를 생성하며 시뮬레이션을 진행하는 데 있어서 가우시 안 잡음을 추가해 에너지 시장 모델을 구축하였다. 모의실험 결과 제안된 전력 거래시스템은 서로 협조적이며 공동의 이익을 추구하며 장기적으로 이익을 증가시킨 것을 확인하였다.

In this paper, the energy transaction system was optimized by applying a resource allocation algorithm and deep reinforcement learning in the distributed power system. The power demand and supply environment were predicted by deep reinforcement learning. We propose a system that pursues common interests in power trading and increases the efficiency of long-term power transactions in the paradigm shift from conventional centralized to distributed power systems in the power trading system. For a realistic energy simulation model and environment, we construct the energy market by learning weather and monthly patterns adding Gaussian noise. In simulation results, we confirm that the proposed power trading systems are cooperative with each other, seek common interests, and increase profits in the prolonged energy transaction.

본 논문에서 제안하는 이동에이전트를 이용한 분산형 절전제어 방법은 다수의 센서와 이동에이전트를 이용 하여 능동적 지능적으로 조명장치의 제어(on/off 및 디밍 조절 등)를 가능하게 하여 에너지 절감에 효과적이며, 다양 한 능동규칙들의 적용에 의한 원격감시 및 제어기능 추가가 용이하므로 효율적 절전제어시스템 설계 및 구축에 따른 비용절감 등의 효과를 유도한다. 또한, 이동에이전트 기반의 센서네트워크 미들웨어의 기능을 통하여 상황정보나 사 용자의 감성 등을 규칙화하여 실시간으로 이벤트 처리 및 제어함으로써 센싱 데이터의 효용성을 향상시킨다. 본 논문 의 결과는 다양한 능동적 센서네트워크 응용들의 개발에 있어 제안한 이동에이전트를 이용한 제어시스템의 활용가능 성을 제시한다.

In this paper, we propose the Distributed Power Saving Control System that enables the active and intelligent control(on/off and/or dimming control) of the lightning device using sensors and mobile agents. The proposed system is effective for energy saving and induces cost reductions in design and development of power saving control system as adding remote-monitoring or controlling functions is easier with the application of a variety of active rules. Moreover, the system improves the effectiveness of the acquired sensing data by real-time event handling and device controlling using a mobile agent based sensor network middleware that regularize the contextual information or a user’s emotion. The results of this paper present the potential applicability of the proposed distributed control system using mobile agent in various active sensor network applications.

To address the convergence issue of power control algorithms, a number of algorithms have been developed hat shape the dynamics of up-link power control for cellular network. Power algorithms based on fixed point iterations can be accelerated by the use of various methods, one of the simplest being the use of Newton iterations, however, this method has the disadvantage which not only needs derivatives of the cost function but also may be weak to noisy nvironment. we showed performance of the power control schemes to solve the fixed point problem under static or stationary channel. They proved goof performance to solve the fixed point problem due to their predictor based optimal control and quadratic convergence rate. Here, we apply the proposed power control schemes to the problem of the dynamic channel or to dynamic time varying link gains. The rigorous simulation results demonstrated the validity of our approach.

In this paper, a multi-agent control system for DC-coupled photovoltaic (PV), fuel cell (FC), ultracapacitor(UC) and battery hybrid power system is studied for commercial buildings & apartment buildings microgrid. In this proposed system, the PV system provides electric energy to the electrolyzer to produce hydrogen for future use and transfer to the load side, if possible. Whenever the PV system cannot completely meet load demands, the FC system provides power to meet the remaining load. A multi-agent system based-power management and control algorithm is proposed for the hybrid power system by taking into account the characteristics of each power source. The main works of this paper are hybridization of alternate energy sources with FC systems using long and short storage strategies to build the multi-agent control system with pragmatic design, and a dynamic model proposed for a PV/FC/UC/battery bank hybrid power generation system. A dynamic simulation model for the hybrid power system has been developed using Matlab/Simulink, SimPowerSystems and Stateflow. Simulation results are also presented to demonstrate the effectiveness of the proposed multi-agent control and management system for building microgrid.