• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2011년도 춘계학술발표대회 논문집
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• pp.63-67
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• 2011

KnowledgThe Korea Institute of Energy Research(KIER) has begun collecting horizontal global insolation data since May, 1982 at different locations. Because of a poor reliability of existing data, KIER's new data will be extensively used by the solar system users as well as by research institutes. But the quality of solar insolation data is not always good. This reports on an attempt to identify systematic error in such data using clear-day analysis for data rehabilitation. Clear-day analysis is successful in uncovering solar insolation data of questionable quality. It is not proven that rehabilitation process can improve the quality of data for daily or monthly means, but it is suggested that the method can be used to improve the quality of data for monthly means of several years for use in many applications of solar energy plarming. Earlier studies finding a maximum ETR of about 0.80 are confirmed.

• 태양에너지
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• 제20권1호
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• pp.31-43
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• 2000

The Korea Institute of Energy Research(KIER) has been collecting horizontal global radiation data since May, 1982 for 16 different locations. KIER's new data is expected to be extensively used by designer and researchers of solar systems in lieu of unreliable old ones. Unfortunately, the quality of the data has not always been properly mentioned. Some of them were taken at temporary field stations where the primary goal of the measurement was quick estimation of local solar radiation. The purpose of this study is to systematically identify errors in such data set using clear-day analysis in an effort to rehabilitate error-ridden old data. Clear-day analysis successfully uncovered solar radiation data that had questionable quality. Even through the rehabilitation process not necessarily improves the quality of data for daily or monthly mean, it can be used to improve the quality of data for monthly means of several years and the processed data can be used in various applications of solar energy with more confidence. A average ETR value of 0.63 obtained in this study is in good agreement with previous results obtained by other researchers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권9호
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• pp.3151-3168
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• 2021

Internet of Things (IoT) connects several objects with embedded sensors and they are capable of exchanging information between devices to create a smart environment. IoT smart devices have limited resources, such as batteries, computing power, and bandwidth, but comprehensive sensing causes severe energy restrictions, lowering data quality. The main objective of the proposal is to build a hybrid protocol which provides high data quality and reduced energy consumption in IoT sensor network. The hybrid protocol gives a flexible and complete solution for sensor selection problem. It selects a subset of active sensor nodes in the network which will increase the data quality and optimize the energy consumption. Since the unused sensor nodes switch off during the sensing phase, the energy consumption is greatly reduced. The hybrid protocol uses Dijkstra's algorithm for determining the shortest path for sensing data and Ant colony inspired variable path selection algorithm for selecting active nodes in the network. The missing data due to inactive sensor nodes is reconstructed using enhanced belief propagation algorithm. The proposed hybrid method is evaluated using real sensor data and the demonstrated results show significant improvement in energy consumption, data utility and data reconstruction rate compared to other existing methods.

• 설비공학논문집
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• 제25권6호
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• pp.310-316
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• 2013

This study was designed to investigate a method for short-term, real-time energy demand prediction, to cope with changing loads for the effective operation and management of buildings. Through a case study, a novel methodology for real-time energy demand prediction with the use of weather forecasting data was suggested. To perform the input and output operations of weather data, and to calculate solar radiation and EnergyPlus, the BCVTB (Building Control Virtual Test Bed) was designed. Through the BCVTB, energy demand prediction for the next 24 hours was carried out, based on 4 real-time weather data and 2 solar radiation calculations. The weather parameters used in a model equation to calculate solar radiation were sourced from the weather data of the KMA (Korea Meteorological Administration). Depending on the local weather forecast data, the results showed their corresponding predicted values. Thus, this methodology was successfully applicable to anywhere that local weather forecast data is available.

• KEPCO Journal on Electric Power and Energy
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• 제8권2호
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• pp.55-59
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• 2022

This paper introduce Renewable Energy forecasting technology, which is a part of renewable management system. Then, calculation method of dedicated transmission line's meteorological data to forecast renewable energy is suggested. As the case of dedicated transmission line, there is only power output data combined the number of renewable plants' output that acquired from circuit breakers. So it is need to calculate meteorological data for dedicated transmission line that matched combined power output data. this paper suggests two calculation method. First method is select the plant has the largest capacity, and use it's meteorological data as line meteorological data. Second method is average with weight that given according to plants' capacity. In case study, suggested methods are applied to real data. Then use calculated data to Renewable forecasting and analyze the forecasting results.

• 한국태양에너지학회 논문집
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• 제29권4호
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• pp.15-21
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• 2009

Since the solar radiation is main input for sizing any solar photovoltaic system and solar thermal power system, it will be necessary to understand and evaluate the insolation data. The Korea Institute of Energy Research(KIER) has begun collecting horizontal global insolation data since May, 1982 and direct normal insolation data since December 1992 at 16 different locations. Because of a poor reliability of existing data, KIER's new data will be extensively used by solar energy system users as well as by research institutes. Among some significant results, the yearly averaged horizontal global insolation was turned out 3.60 kWh/$m^2$/day and the yearly mean 2.62 kWh/$m^2$/day of the direct normal insolation was evaluated for all days.

• 한국태양에너지학회 논문집
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• 제39권6호
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• pp.137-151
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• 2019

This study estimated the available renewable market potential based on Levelized Cost Of Electricity and then assessed the renewable derived energy self-sufficiency for the unit of local government in South Korea. To calculate energy self-sufficiency, 1 km gridded market renewable generation and local government scale of final energy consumption data were used based on the market costs and statistics for the recent three years. The results showed that the estimated renewable market potentials were 689 TWh (Install capacity 829 GW, 128 Mtoe), which can cover 120% of power consumption. 55% of municipalities can fully replace the existing energy consumption with renewable energy generation and the surplus generation can compensate for the rest area through electricity trade. However, it was confirmed that, currently, 47% of the local governments do not fully consider all renewable energy sources such as wind, hydro and geothermal in establishing 100% renewable energy. The results of this study suggest that energy planning is decentralized, and this will greatly contribute to the establishment of power planning of local governments and close the information gap between the central government, the local governments, and the public.

• 대한임베디드공학회논문지
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• 제11권4호
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• pp.243-249
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• 2016

Energy-harvesting nodes in wireless sensor networks(WSNs) can be exhausted due to a heavy workload even though they can harvest energy from their environment. On contrast, they can sometimes fully charged, thus waste the harvested energy due to the limited battery-capacity. In order to utilize the harvested energy efficiently, we introduce a selective data compression and transmission range control scheme for energy-harvesting nodes. In this scheme, if the residual energy of a node is expected to run over the battery capacity, the node spends the surplus energy to exploit the data compression or the transmission range expansion; these operations can reduce the burden of intermediate nodes at the expanse of its own energy. Otherwise, the node performs only basic operations such as sensing or transmitting so as to avoid its blackout time. Simulation result verifies that the proposed scheme gathers more data with fewer number of blackout nodes than other schemes by consuming energy efficiently.

• KEPCO Journal on Electric Power and Energy
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• 제8권2호
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• pp.127-135
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• 2022

With the advent of high technologies such as the 4th Industrial Revolution and artificial intelligence and big data, efforts are being made to solve urban problems and improve the quality of life by applying new technologies in the smart city field. In addition, as carbon neutrality has emerged as an important issue due to global warming, smart city energy platform technologies such as urban energy management, efficiency improvement, and carbon reduction are in the spotlight. In order to effectively manage urban energy, energy resource information such as electricity, water, gas, hot water, heating, etc. must be collected from the management system of various energy utilities and managed on the central platform. The centrally integrated data is delivered to external city management systems that require city energy information through an energy platform. This study developed a CIM profile for smart city energy monitoring required to provide energy data to external systems. Electric data model were designed using the CIM class of IEC 61970, and water, gas, and heat data model were designed in compliance with the UML-based design ideas of IEC 61970.

• 태양에너지
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• 제18권3호
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• pp.31-39
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• 1998

성공적인 건물에너지 진단을 위한 주요한 인자중의 하나는 올바른 기상화일의 선정에 있다고 할 수 있다. 따라서 본 연구에서는 건물의 에너지진단을 위한 프로그램의 기상화일을 제공하기 위해 국내 주요 6개도시의 약 30년간의 Raw Data DB를 구축하였으며, 이를 활용하여 사용자로 하여금 필요한 기상요소만을 선택하여 출력할 수 있도록 구성한 기상요소 선택프로그램 "KWDP version 1.0"을 개발하였다. 또한 누락된 기상요소를 생성할 수 있는 DOE2.1E용 기상데이터 생성 프로그램인 Wmake.exe 프로그램을 개발하였고, 에너지진단을 위한 시뮬레이션의 결과에 신뢰도를 높일 수 있는 기상데이터의 선정방법을 제시하였다.