• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2008년도 추계학술발표대회 논문집
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• pp.337-340
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• 2008

As a 'Construction of Information System on GIS based and Resource Map', establish the strategic of design about construction of Spatial Data Warehouse for New & Renewable Energy For Construction of comfortable Spatial Data Warehouse, It suggested The Construction of Spatial Data Warehouse on Block(Grid) Based with Analyze into the old Data & Method of Study. For Decide the Block(Grid) Size, We need The Study of Data & Method. Also, we expect Standardize The Process of Change & Apply with Data. make the best use of New & Renewable Energy Part

• 전기학회논문지
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• 제64권3호
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• pp.393-398
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• 2015

City or Community-scale Energy Management System(CEMS) is used to reduce the total energy consumed in the city by arranging the energy resources efficiently at the planning stage and controlling them economically at the operating stage. Of the operational functions of the CEMS, generation forecasting of renewable energy resources is an essential feature for the effective supply scheduling. This is because it can develop daily operating schedules of controllable generators in the city (e.g. diesel turbine, micro-gas turbine, ESS, CHP and so on) in order to minimize the inflow of the external power supply system, considering the amount of power generated by the uncontrollable renewable energy resources. This paper is written to introduce numerical models for photo-voltaic power generation prediction based on the weather forecasting information. Unlike the conventional methods using the average radiation or average utilization rate, the proposed models are developed for CEMS applications using the realtime weather forecast information provided by the National Weather Service.

• 한국태양에너지학회 논문집
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• 제38권2호
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• pp.45-53
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• 2018

For the preliminary step for estimating the performance of roof-type photovoltaic system in urban areas, we analyzed the solar radiation reduction ratio by shadow effect by buildings using DSM (Digital Surface Model) and GIS (Geographical Information System) tools. An average loss by the shadow is about 19% in Seoul. The result was related to the building density and distribution. Monthly results show that the winter season (December and January) was more affected by the shading than during the summer season (June and July). It is expected that useful empirical formulas can be made if more detailed correlation studies are performed.

• Journal of Electrical Engineering and Technology
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• 제13권5호
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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.

• 한국정보시스템학회지:정보시스템연구
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• 제28권1호
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• pp.115-132
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• 2019

Purpose The purpose of this study is to explain the agrophotovolatic system built by the Korea South-East Power Company and to propose methods to activate the agrophotovolatic system for the development of the renewable energy industry. Design/methodology/approach We conducted a three-step simulation in order to design a photovoltaic module, and we built the agrophotovolatic system based on the results of the simulation. Then, we analyzed the monthly generation of power and the rice harvests produced on farmland using the photovoltaic module. Based on the results of the analysis, we proposed institutional improvements to increase the use of the agrophotovolatic system, and we proposed new business models to increase the participation of farmers and business persons. Findings When we compared the agrophotovolastic system with the general photovoltaic system, we found that the agrophotovoltaic system had higher utilization rates and power generation. An analysis of rice produced on farmland using the photovoltaic module showed that more than 80% of the rice produced on general farmland was harvested. We suggested activation plans that involved the revision of the farmland law and the introduction of renewable energy certificate (REC). We also proposed a land lease model and a farmer participation model as two new business models, and we conducted economic evaluations and sensitivity analyses for both models.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2017년도 추계학술발표대회
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• pp.1241-1243
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• 2017

As the era of the fourth industrial revolution, renewable energy has been highlighted instead of fossil energy resource. Solar energy is constantly being developed in renewable energy, but energy gathering methods are not yet effective. In this paper, we study an efficient monitoring module for photovoltaic system for better performance of light sensor based solar tracking photovoltaic system with real time manner.

• Journal of international Conference on Electrical Machines and Systems
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• 제2권3호
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• pp.361-366
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• 2013

This paper presents the effect on application of the flywheel energy storage system (FESS) for load frequency control (LFC) of an interconnected 2 area power system. To do this, the control characteristics with the FESS were compared with that of the conventional governor controller. The controller for the FESS control and the governor control used a PID type controller. Both the FESS PID controller and the governor PID controller using genetic algorithm (GA) were designed to optimize the PID parameters. The frequency and generation output characteristics with the only FESS controller and with the only conventional governor controller were compared. To verify robust performance of the FESS controller, the computer simulations were performed under various disturbances. The simulation results showed that the FESS controller provided better dynamic responses in comparison with the conventional governor controller.

• 자원ㆍ환경경제연구
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• 제15권4호
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• pp.693-712
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• 2006

하이브리드 시스템의 최적 설계 및 운영을 위한 프로그램으로 해외의 여러 곳에서 활용중인 Homer를 사용하여 현재 디젤발전기를 전원으로 사용하고 있는 독립계통의 도서지역에 신 재생에너지원의 조합으로 구성된 하이브리드 시스템을 보급할 경우의 타당성 분석을 시도하였다. 에너지기술연구원의 풍속자료, 일사량, 온도자료 등을 근거로 추자도, 거문도, 그리고 영산도를 평가대상으로 선정하였다. 해당지역의 전력부하 자료는 부분적으로 실측된 자료를 바탕으로 재구성하였으며, 시스템 구성 발전기들의 비용 자료는 국내 관련 자료가 미비한 관제로 해외 시장의 자료를 이용하였다. 추자도, 거문도, 영산도의 평가결과가 각각 278원/kWh, 234원/kWh 그리고 353원/kWh으로 나타났다. 정부 보조금에 의한 디젤발전시스템의 발전단가가 300원/kWh($0.300/kWh)인 것을 고려한다면, 추자도와 거문도는 자체적으로 경제성을 확보하는 반면 영산도의 경우는 그렇지 못함을 알 수 있다. 이러한 결과 차이는 기본적으로 해당지역의 재생에너지 자원조건의 차이, 그 중에서도 특히 풍력자원의 차이에 기인하는 것으로 나타난다. 결론적으로 독립계통의 도서지역에 대한 신 재생복합전력시스템의 도입은 경제성 평가의 결과에 의거해야 하며 모든 도서지역이 이 조건을 충족시키는 것이 아님을 지적한다.

• 한국정보전자통신기술학회논문지
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• 제15권2호
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• pp.95-102
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• 2022

신재생에너지 확대를 위한 배전자동화시스템의 안정성 평가를 위한 연구이다. 정부는 재생에너지 3020 이행계획 정책을 통해 2030년까지 신재생에너지를 확대하여 국민의 삶의 질을 높이는 참여형 에너지 체계로 전환할 계획이다. 정부는 2030년까지 재생에너지 발전량 비중을 국내 보급 에너지의 20%로 목표 설정하였다. 신규 설비용량의 95% 이상을 태양광 풍력 등 청정에너지로 설립할 계획이다. 재생에너지 보급 확대로 에너지 신사업과 분산전원 산업이 육성되어 과거의 대규모 전원 개발이 아닌 근거리, 저압, 소규모 발전이 급속히 확대되었다. 이런 수요로 인해 배전 설비 운영의 중요성이 대두 되었고 배전자동화시스템이 필요성 증대되고 있다. 본 논문에서는 배전자동화시스템의 성능 및 기능 평가를 위한 배전시뮬레이터 개발에 대해 다루었고 이와 배전자동화시스템과의 연동시험 결과를 제시한다. 배전계통에 진보된 시스템을 도입하기 위해서는 송변전시스템의 장점을 취해야 한다. 배전시스템에서 DNP3.0프로토콜을 사용하고 송배전시스템에서 IEC61850 프로토콜을 사용한다. 이 두 프로토콜을 배전자동화시스템에서 혼용하여 사용시 제어, 모니터링 등의 운영에 대한 기능과 성능을 충족한다는 결론을 보였다.

• International Journal of Computer Science & Network Security
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• 제24권4호
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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.