• New & Renewable Energy
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• v.20 no.1
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• pp.145-174
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• 2024

Addressing climate change necessitates evidence-based policies grounded in science. The use of forest biomass for energy production is based on a broad scientific consensus at the international level. However, some environmental groups in South Korea are opposing this system of energy production. Through this study, the authors aim to reduce unnecessary confusion and foster an atmosphere conducive to meaningful evidence-based policies. We have classified the issue into eight categories: biological carbon cycle, carbon debt, nature-based solutions, air emissions, cascading principles and sustainability certification, forest environmental impacts, climate change litigation, and the behavior of environmental groups and public perception. Consequently, the following key points were derived: (1) the actions of some environmental groups seem to follow a similar pattern to denialist behavior that denies climate change and climate science; (2) the quality of evidence for campaigns that oppose the use of forest biomass for energy production is low, with a tendency to overgeneralize information, high uncertainty, and difficulty in finding new claims.; (3) most of the public believes that forest biomass energy is necessary, and the governments of major countries are aware of its importance. Significantly, Forest biomass for energy is based on an overwhelming level of scientific consensus recognized internationally.

• New & Renewable Energy
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• v.2 no.2 s.6
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• pp.37-43
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• 2006

In this paper, the first forecasting system of wind power generation, KIER Forecaster is presented. KIER Forecaster has been constructed based on statistical models and was trained with wind speed data observed at Gosan Weather Station nearby Walryong Site. Due to short period of measurements at Walryong Site for training the model, Gosan wind data were substituted and transplanted to Walryong Site by using Measure-Correlate-Predict(MCP) technique. The results of One to Three-hour advanced forecasting models are consistent with the measurement at Walryong site. In particular, the multiple regression model by classification of wind speed pattern, which has been developed in this work, shows the best performance comparing with neural network and auto-regressive models.

• New & Renewable Energy
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• v.4 no.4
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• pp.3-9
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• 2008

In design PV (photovoltaic) system, there are many important factors to consider for best site selection. It is essential to understand to know the amount of sunlight available and how to minimize the shadings. This study presents basic concepts for understanding sun's position and insolation. also it gives easy tools for topography analysis. Finally, this study shows some theoretical calculations of power generation losses by topographic obstacle's elevations and disadvantages in economic feasibility, that is about 7million won loss per year for case of 10 degree topography elevation with assuming average Korea's topography elevation as 5 degree.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.851-858
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• 2021

Due to the increase in renewable energy and distributed resources, not only traditional data but also various energy-related data are being generated in the new energy industry. In other words, there are various renewable energy facilities and power generation data, system operation data, metering and rate-related data, as well as weather and energy efficiency data necessary for new services and analysis. Energy big data processing technology can systematically analyze and diagnose data generated in the first half of the power production and consumption infrastructure, including distributed resources, systems, and AMI. Through this, it will be a technology that supports the creation of new businesses in convergence between the ICT industry and the energy industry. To this end, research on the data analysis system, such as itemized characteristic analysis of the collected data, correlation sampling, categorization of each feature, and element definition, is needed. In addition, research on data purification technology for data loss and abnormal state processing should be conducted. In addition, it is necessary to develop and structure NIFI, Spark, and HDFS systems so that energy data can be stored and managed in real time. In this study, the overall energy data processing technology and system for various power transactions as described above were proposed.

• New & Renewable Energy
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• v.10 no.4
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• pp.36-46
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• 2014

Low-grade heats are wasted even though an amount of their energy is huge. In the small and medium industrial complex sites, large amount of low-grade thermal energy generated during the manufacturing process is wasted if it is not used directly for building heating or air-conditioning. In order to utilize this waste thermal energy more efficiently, organic Rankine cycle (ORC) was adopted. The range of operating temperature of ORC was set to $60^{\circ}C$ from $30^{\circ}C$ applicable low-temperature waste heat. A study was conducted to select an appropriate organic working fluid based on these operating conditions. More than 60 working fluids were screened. Eleven working fluids were selected based on the requirements as working fluid for ORC such as environmentally friendly, safety, and good operation on the expander. Finally, six working fluids were selected by considering the operating temperature ranges. Then, a cycle analysis was conducted with these six working fluids. As a results, R-245fa and R-134a appeared as appropriate working fluids for ORC operating at low-temperature condition based on the system efficiency and the turbine output power.

• New & Renewable Energy
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• v.20 no.2
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• pp.2-16
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• 2024

Various loads induced by marine environmental conditions, such as waves, currents, and wind, are crucial for the operation and viability of offshore wind power (OWP) systems. In particular, waves have a significant impact on the stress and fatigue load of offshore structures, and highly reliable design parameters should be derived through extreme value analysis (EVA) techniques. In this study, extreme wave analyses were conducted with various Weibull distribution models to determine the reliable design parameters of an OWP system suitable for the Ulsan area. Forty-three years of long-term hindcast data generated by a numerical wave model were adopted as the analyses data, and the least-squares method was used to estimate the parameters of the distribution function for EVA. The inverse first-order reliability method was employed as the EVA technique. The obtained results were compared among themselves under the assumption that the marginal probability distributions were 2p, 3p, and exponentiated Weibull distributions.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1605-1614
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• 2013

This paper presents a probabilistic methodology for small signal stability analysis of power system with correlated wind sources. The approach considers not only the stochastic characteristics of wind speeds which are treated as random variables with Weibull distributions, while also the wind speed spatial correlations which are characterized by a correlation matrix. The approach based on the 2m+1 point estimate method and Cornish Fisher expansion, the orthogonal transformation technique is used to deal with the correlation of wind farms. A case study is carried out on IEEE New England system and the probabilistic indexes for eigenvalue analysis are computed from the statistical processing of the obtained results. The accuracy and efficiency of the proposed method are confirmed by comparing with the results of Monte Carlo simulation. The numerical results indicate that the proposed method can actually capture the probabilistic characteristics of mode properties of the power systems with correlated wind sources and the consideration of spatial correlation has influence on the probability of system small signal stability.

• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.365-368
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• 2008

This experiment is significant because we can provide information by measuring effect of energy saving for whom plan to install a geothermal heat & cooling system. The result shows geothemal system can save about 50% of energy(heating : 35%, cooling : 60%) and we verified that when using curtain can help saving $4{\sim}12%$ of energy additionally

• Journal of the Korean Solar Energy Society
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• v.33 no.6
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• pp.62-69
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• 2013

In this paper, Korea Institute of Energy Research, building integrated renewable energy monitoring system that utilizes solar power generation forecast data forecast model is proposed. Renewable energy integration of real-time monitoring system based on monitoring data were building a database and the database of the weather conditions and to study the correlation structure was tailoring. The weather forecast cloud cover data, generation data, and solar radiation data, a data mining and time series analysis using the method developed models to forecast solar power. The development of solar power in order to forecast model of weather forecast data it is important to secure. To this end, in three hours, including a three-day forecast today Meteorological data were used from the KMA(korea Meteorological Administration) site offers. In order to verify the accuracy of the predicted solar circle for each prediction and the actual environment can be applied to generation and were analyzed.

• New & Renewable Energy
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• v.10 no.3
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• pp.47-54
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• 2014

Recently, BESS is considered as one of essential countermeasure for demand side management. However, an economic evaluation is critical issue for the introduction of power system because the cost of BESS is very high in present stage. Therefor, this paper presents economic evaluation method for customer use case by considering peak shaving function based on the real time price. From the case study on the model power system and educational customer, it is confirmed that the proposed method is a practical tool for the economic analysis of BESS. and analytical approach for the reliability assessment in radially operated distribution systems. The approach can estimate the expected reliability performance of distribution systems by a direct assessment of the configuration of the systems using the reliability indexes such as NDP (Non-Delivery Power) and NDE (Non-Delivery Energy). The indexes can only consider the number and configuration of the load, but can not consider the characteristics of the load which is the one of the most important factor in the investment cost for the distribution systems. Therefore, this paper presents the new performance indexes for the investment of the distribution facilities considering both the expected interruption cost for the load section and the operation characteristics of Energy Storage System. The results from a case study show that the proposed methods can be a practical tool for the reliability management in distribution systems including Energy Storage System.