• Title/Summary/Keyword: Smart Photovoltaic System

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A Development of Smart Monitoring Technique for Photovoltaic Power Systems (태양광 발전 시스템의 스마트 모니터링 기술개발)

  • Cho, Hyun Cheol;Sim, Kwang Yeal
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.64 no.2
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    • pp.50-56
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    • 2015
  • This paper presents a smart monitoring technique for photovoltaic power systems by using wire and wireless communication networks in which the RS-232/484 and the Zigbee communication networks are inherently established respectively. In the proposed monitoring systems, environmental data sequences and the output power measured by sensors in photovoltaic systems are transferred to PC systems via two communication networks. We made electronic hardware boards for sensors and communication networks to construct its real-time monitoring system and carry out experiments for demonstrating reliability of the proposed monitoring system.

Renewable Source and Hybrid System Modeling for Smart Grid (스마트그리드를 위한 신재생에너지원과 하이브리드시스템 모델링)

  • Cho, Jae-Hoon;Hong, Won-Pyo;Chun, Myung-Geun
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.24 no.12
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    • pp.109-121
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    • 2010
  • Recently, smart grid for solving energy problems have been receiving growing attention. Also, renewable energy sources such as photovoltaic and fuel cell as future energy for realizing smart grid have been widely studied. On the other hand, hybrid structures have been proposed since the output power of these renewable energy sources is usually dependent on weather conditions. This paper proposes a hybrid system involving a proper photovoltaic in the hybrid system, Polymer Elecrolyte Membrane Fuel Cell with water electrolyzer and ultracapacitor. The results of simulation and output of the proposed model are established and analysed by Matlab/Simulink and SimPowerSystems.

Development of Self-Consumption Smart Home System (에너지 자립형 스마트 홈 시스템 개발)

  • Lee, Sanghak
    • Journal of Satellite, Information and Communications
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    • v.11 no.2
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    • pp.42-47
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    • 2016
  • Due to advances such as photovoltaic power generation and energy storage system, energy self-consumption smart home system in which energy management system is built and energy is generated in house has been actively researched. In particular, due to the instability of the grid after the Fukushima nuclear accident, home system in which generating electricity from photovoltaic, storing and using it in energy storage system was commercialized in Japan. While subsidizing renewable energy projects through a combination of solar and energy storage systems in North America and Europe has expanded home installation. In this paper, we describe development of self-consumption smart home system which is connecting photovoltaic system and energy storage system in home area network and operating it based on real-time price. We implemented automated self-consumption home in which optimizing the use of energy from the power grid with minimal user's intervention.

A Study on the Optimization of Power Consumption Pattern using Building Smart Microgrid Test-Bed (Building Smart Microgrid Test-Bed를 이용한 전력사용량 패턴 최적화방안 연구)

  • Lee, Sang-Woo;Kang, Jin-Kyu;Lee, Dong-Ha
    • Journal of the Korean Solar Energy Society
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    • v.34 no.4
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    • pp.1-7
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    • 2014
  • The microgrid system is the combination of photovoltaic(PV) array, load, and battery energy storage system. The control strategies were defined as multi-modes of operation, including rest operation without use of battery, power charging, and power discharging, which enables grid connected mode or islanded mode. Photovoltaic power is a problem of the uniformity of power quality because the power generated from solar light is very sensitive to variation of insolation and duration of sunshine. As a solution to the above problem, energy storage system(ESS) is considered generally. There fore, in this study, we did basic research activities about optimization method of the amount of energy used, using a smart microgrid test-bed constructed in building. First, we analyzed the daily, monthly and period energy pattern amount of power energy used, and analyzed PV power generation level which is built on the roof. Utilizing building energy pattern analysis data, we was studied an efficient method of employing the ESS about building power consumption pattern and PV generation.

Analysis and Performance Test of Hybrid Transformer used in the Grid-Connected Photovoltaic Generation System (태양광 계통연계형 하이브리드 변압기의 해석 및 성능시험)

  • Kim, Ji-Ho;Park, Hoon-Yang;Shon, Jin-Geun
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.63 no.4
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    • pp.333-338
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    • 2014
  • This paper concerns the development of the transformer that can reduce harmonics supplied to the system if the output of photovoltaic inverter in the photovoltaic system is grid-connected, and suggests that problems of harmonics and power factor degradation in the grid-connected photovoltaic system can be improved. In this study, the burden of increasing the investment in new facilities and securing their installation space due to harmonics has been substantially eased through the development of a hybrid transformer possessing unbalanced function and harmonics reduction function using zig-zag coils, and most of all, it is expected that the development of such high efficiency hybrid transformer possessing functions of transformation and reducing harmonics can improve the power quality as well as prevent damages caused by harmonics, leading to suppress unnecessary loss of electric power and thereby contribute to energy savings.

Moth-Flame Optimization-Based Maximum Power Point Tracking for Photovoltaic Systems Under Partial Shading Conditions

  • Shi, Ji-Ying;Zhang, Deng-Yu;Xue, Fei;Li, Ya-Jing;Qiao, Wen;Yang, Wen-Jing;Xu, Yi-Ming;Yang, Ting
    • Journal of Power Electronics
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    • v.19 no.5
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    • pp.1248-1258
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    • 2019
  • This paper presents a moth-flame optimization (MFO)-based maximum power point tracking (MPPT) method for photovoltaic (PV) systems. The MFO algorithm is a new optimization method that exhibits satisfactory performance in terms of exploration, exploitation, local optima avoidance, and convergence. Therefore, the MFO algorithm is quite suitable for solving multiple peaks of PV systems under partial shading conditions (PSCs). The proposed MFO-MPPT is compared with four MPPT algorithms, namely the perturb and observe (P&O)-MPPT, incremental conductance (INC)-MPPT, particle swarm optimization (PSO)-MPPT and whale optimization algorithm (WOA)-MPPT. Simulation and experiment results demonstrate that the proposed algorithm can extract the global maximum power point (MPP) with greater tracking speed and accuracy under various conditions.

Design and Evaluation of Dye-Sensitized Solar Cell Submodule for Self-Powered Smart Liquid Crystal Window (자가발전 스마트 액정 윈도우를 위한 염료감응 태양전지 서브 모듈 설계 및 평가)

  • Byeong-Yun Oh
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.37 no.5
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    • pp.494-499
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    • 2024
  • The possibility of a dye-sensitized solar cell (DSSC) submodule was evaluated as an independent power source that can drive a smart liquid crystal window (SLW) that selectively blocks sunlight when electricity is applied. In order to save energy and increase the functionality of buildings, SLW operation was supplied directly from DSSC submodule, rather than connecting to the existing power system and external power sources. It was confirmed that the SLW can control light transmittance through self-generation using the DSSC submodule composed of 6 cells at low light of 2,500 lux. These results imply that there is a high possibility of combining smart windows and DSSCs suitable for window-type building-integrated photovoltaic (BIPV) systems. DSSCs, which can self-generate power in low light, are expected to increase their usability in urban BIPV systems through combination with smart window technology.

An Improved Photovoltaic System Output Prediction Model under Limited Weather Information

  • Park, Sung-Won;Son, Sung-Yong;Kim, Changseob;LEE, Kwang Y.;Hwang, Hye-Mi
    • Journal of Electrical Engineering and Technology
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    • v.13 no.5
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    • pp.1874-1885
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    • 2018
  • The customer side operation is getting more complex in a smart grid environment because of the adoption of renewable resources. In performing energy management planning or scheduling, it is essential to forecast non-controllable resources accurately and robustly. The PV system is one of the common renewable energy resources in customer side. Its output depends on weather and physical characteristics of the PV system. Thus, weather information is essential to predict the amount of PV system output. However, weather forecast usually does not include enough solar irradiation information. In this study, a PV system power output prediction model (PPM) under limited weather information is proposed. In the proposed model, meteorological radiation model (MRM) is used to improve cloud cover radiation model (CRM) to consider the seasonal effect of the target region. The results of the proposed model are compared to the result of the conventional CRM prediction method on the PV generation obtained from a field test site. With the PPM, root mean square error (RMSE), and mean absolute error (MAE) are improved by 23.43% and 33.76%, respectively, compared to CRM for all days; while in clear days, they are improved by 53.36% and 62.90%, respectively.

The Development of an Intelligent Home Energy Management System Integrated with a Vehicle-to-Home Unit using a Reinforcement Learning Approach

  • Ohoud Almughram;Sami Ben Slama;Bassam Zafar
    • International Journal of Computer Science & Network Security
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    • v.24 no.4
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    • pp.87-106
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    • 2024
  • Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

Development of Current Control System for Solar LED Street Light System

  • Kim, Byun-Gon;Kim, Kwan-Woong;Jang, Tae-Su;Lee, Jun-Myung;Kim, Yong-Kab
    • International journal of advanced smart convergence
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    • v.1 no.1
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    • pp.52-56
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    • 2012
  • As inexhaustible clean energy, solar energy will be the most ideal green energy in the 21st century. The effective method to convert solar energy into electrical energy is by solar photovoltaic power generation technologies. LED Emitting Diode is a kind of component which can transform electricity into visible light. As the smart current control system for photovoltaic street lights, the proposed system has improved the battery charging and discharging mechanism to extend the lifespan and effectively controls the LED discharge current according to battery charge state and lighting.