• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.523-531
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• 2018

The purpose of this paper is to derive priorities and implications for the organic resource conservation policy in the livestock sector. We conducted a survey on the importance-performance of the organic waste resource reclamation of livestock sector using a 5-point Likert scale. The importance average for the resource recycling of livestock organic waste was 3.63 and the average of performance was 3.04. As a result of the IPA on livestock manure recycling measures, it is necessary to improve feed quality, establish a local recycling system, increase demand for compost and liquid, enhance customer linkages, and develop cost reduction technologies. It requires intensive support for promoting the spread of odor reduction technologies and integrated management of biomass. It is necessary to introduce mid- and long-term measures such as the revival of feed in tariff, promote by-product feeding, establish solid fuel process management standards, create hygiene safety standards, develop eco-beads and promotion of feed conversion. It is required to strengthen support for the development of odor reduction technologies and prepare consultative organizations among related departments, develop eco-friendly solid fuel technology, and support policies for renewable energy certification.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.8
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• pp.502-507
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• 2016

The transition from a carbon economy based on fossil fuels to a hydrogen economy is necessary to ensure energy security and to combat climate change. In order to pursue the transition to a hydrogen economy while achieving sustainable economic growth, a preliminary study into the establishment of the necessary infrastructure for the future hydrogen economy needs to be carried out. This study addresses the economic and environmental interactions in a dynamic computable general equilibrium (CGE) model focusing on the economic effects of the introduction of renewable energy into the Korean energy system. Firstly, the introduction of hydrogen results in an increase in the investment in hydrogen production and the reduction of the production cost, ultimately leading to GDP growth. Secondly, the mandatory introduction of renewable energy and associated government subsidies bring about a reduction in total demand. Additionally, the mandatory introduction of hydrogen energy into the power sector helps to reduce CO2 emissions through the transition from a carbon economy-based on fossil energy to a hydrogen economy. This means that hydrogen energy needs to come from non-fossil fuel sources in order for greenhouse gases to be effectively reduced. Therefore, it seems necessary for policy support to be strengthened substantially and for additional studies to be conducted into the production of hydrogen energy from renewable sources.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.534-548
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• 2021

In this paper, the feasibility of generating solar power near an abandoned quarry is examined with the objectives of resolving the essential problems that quarries encounter, such as rockfalls and space usage issues. On an abandoned quarry site in Sadang, Seoul, Republic of Korea, two different PV installation methods were analyzed. The first is attaching PV directly on the quarry slope. Since there are no corresponding safety standards and precedents for installing solar panels directly on slopes, the power generation potential was calculated by using topographic data and reasonable assumptions. The surface area of cut slope section was extracted from the Digital Elevation Model(DEM) via ArcGIS and Python programming to calculate the tilt and power capacity of installable panels. The other approach is installing PV as a rockfall barrier, and the power generation potential was analyzed with the assumption that the panel is installed in the direction of facing solar irradiation. For the derivation of power generation, the renewable energy generation analysis program SAM(System Advisor Model) was used for both methods. According to the result, quarries that have terminated resource extraction and remain devastated have the potential to be transformed into renewable energy generation sites.

• Environmental and Resource Economics Review
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• v.22 no.4
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• pp.691-726
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• 2013

We develop a hybrid model which allows the change in electricity generation mix by adding the electricity-sector components of bottom-up model to the conventional CGE model. The electricity sector is represented as a sum of separate generation technologies, each of which has the form of DRTS (Decreasing Returns to Scale) production function, unlike the conventional CGE model. We compare the effects of the 30% emission reduction target using the hybrid model with those using the conventional CGE model. The cost of meeting the target is lower with the hybrid model than the conventional CGE. It is consistent with previous studies in that adding the bottom-up components to the top-down model reduces the cost of emission reduction. In an extra analysis we find that an additional regulation like RPS (Renewable Portfolio Standard) increases the cost.

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.185.1-185.1
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• 2010

원격탐사(remote sensing)란 관측 대상과의 접촉 없이 멀리서 정보를 얻어내는 기술을 말한다. 기상관측분야에는 이미 소다(SODAR) 장비가 폭넓게 사용되거 왔으나 최근 풍력자원평가(wind resource assessment)를 위한 풍황측정에 SODAR와 더불어 라이다(LIDAR)가 적극적으로 활용되기 시작하고 있다. 참고로 SODAR(SOnic Detection And Ranging)는 수직 및 동서 남북 방향으로 음파를 발생시키고 대기유동에 의해 산란 반사된 에코를 수신하여 진동수 변화와 반사에코 강도를 측정하여 각 방향의 에코자료를 벡터 합성함으로써 풍향 및 풍속을 산출하는 원리이다. 반면 LIDAR(Light Detection And Ranging)는 비교적 최근에 풍황측정 용도로 개발된 레이저 탐지에 바탕을 둔 원거리 센서로, 공기입자(먼지, 수증기, 구름, 안개, 오염물질 등)에 의해 산란된 레이저 발산의 도플러 쉬프트(Doppler shift)를 이용하여 풍향 및 풍속을 측정하는 원격탐사 장비이다. 풍력자원평가 측면에서 라이다는 그 정확도가 IEC61400-12에 의거한 풍황탑(met-mast) 측정자료 다수와의 비교검증 실측평가(Albers et al., 2009)를 통하여 입증된 바 있다. 한편 한국에너지기술연구원에서 운용 중인 라이다 시스템은 그림 1의 우측 그림과 같이 1초에 $360^{\circ}$를 스캔하여 50지점에서 반사되는 레이저를 스펙트럼으로 측정하되 설정된 관측높이에서 풍속은 샘플링 부피(sampling volume)의 평균값으로 정의된다. 그런데 샘플링 부피는 설정된 관측높이로부터 상하 12.5m, 총 25m의 높이구간에서 관측한 스펙트럼의 평균값을 그 중앙지점에서의 풍속으로 환산하는 알고리듬(algorithm)을 채택하고 있다. 따라서 비선형적으로 변화하는 풍속연직분포 관측 시 풍속환산 알고리듬에 의한 측정오차가 개입될 가능성이 존재하는 것이다. 이에 본 연구에서는 라이다에 의한 풍속연직분포 측정 시 샘플링 부피의 구간 평균화 과정에서 발생하는 불확도(uncertainty)를 정량적으로 분석함으로써 라이다에 의한 풍속연직분포 관측의 불확도를 정량평가하고자 한다.

• Journal of Korea Technology Innovation Society
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• v.13 no.3
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• pp.399-422
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• 2010

Global expansion of regulation for carbon emission has brought new industrial regulations and trade barriers while the global economy is promoting economic stimulus through a variety of green investments such as renewable energy development, energy efficiency increase, and environmental improvement simultaneously. Korean government is trying to seek a new opportunity to grow through green investment in this change of business environment and businesses are facing the transition to low-carbon and eco-friendly structure for their survival. It is promoting not only industry structure changes and conversion but also demanding changes of workforce composition and requirement skills. In response to convergence of green economy, manpower development for future skills needs is provided the main impetus for response as well as promotion green growth. This study will analyze human resource development plan due to future skills needs emphasizing on automative industry. Also the study will be researched on the problems of present curriculum of undergraduate and look for improvements tasks. Upon the result, promotion plans for human resource development in other sectors of green car in response to future skills needs in green growth can be found.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.8
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• pp.1504-1511
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• 2009

By development of renewable energies and high-efficient facilities and deregulated electricity market, the operation cost of distributed generation(DG) becomes more competitive. The amount of distributed resource is considerably increasing in the distribution network consequently. Also, international environmental regulations of the leaking carbon become effective to keep pace with the global efforts for low-carbon paradigm. It contributes to spread out the business of DG. Therefore, the operator of DG is able to supply electric power to customers who are connected directly to DG as well as loads that are connected to entire network. In this situation, community energy system(CES) having DGs is recently a new participant in the energy market. DG's purchase price from the market is different from the DG's sales price to the market due to the transmission service charges and etc. Therefore, CES who owns DGs has to control the produced electric power per hourly period in order to maximize the profit. If there is no regulation for carbon emission(CE), the generators which get higher production than generation cost will hold a prominent position in a competitive price. However, considering the international environment regulation, CE newly will be an important element to decide the marginal cost of generators as well as the classified fuel unit cost and unit's efficiency. This paper will introduce the optimal operation of CES's DG connected to the distribution network considering CE. The purpose of optimization is to maximize the profit of CES and Particle Swarm Optimization (PSO) will be used to solve this problem. The optimal operation of DG represented in this paper is to be resource to CES and system operator for determining the decision making criteria.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.2
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• pp.228-231
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• 2015

In power system research fields, one of current key issues is the construction and commercialization of micro grid site which is called green island, carbon zero island, energy independent island, building micro grid, etc. and various affiliated technologies have been being vigorously developed to realize. In addition, various researches about electric vehicles (EVs) are in progress and it is expected to penetrate rapidly with the next a few years. Some new load models should be developed integrating with electric vehicle loads because the EVs' deployment could cause the change of load composition rate on power system planning and operations. EVs are also resources for micro grid as well as distributed generation and demand response so that various supply and demand side resources should be considered for micro grid researches. In this paper, the load composition rate of residential sectors is prospected considering the deployment of EVs and the resource configuration of micro grid is optimized based on net present cost. In the optimization, the load patten of case studies includes EV's charging characteristics and various cases are simulated comparing micro grid environment and normal condition. HOMER is used to compare various cases and economic effects.

• Journal of Navigation and Port Research
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• v.35 no.5
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• pp.381-385
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• 2011

In this paper, an economic feasibility study of wind-diesel hybrid power systems for an island in the Yellow Sea, where the maximum power generation is about 500kW, was performed. For the study, annual electric load variation and wind resource data of the island were collected and analyzed. HOMER program - a typical hybrid optimization model for electric renewables including wind resource, developed by the National Renewable Energy Laboratory - was used. Wind speed and diesel price were picked out as variables for the sensitivity analysis in order to find the economic accountability for the wind-diesel hybrid power system. As the result, even though it is not feasible economically under the present condition, if mean wind speed is over 3 m/sec. or diesel price goes up to 2.4 $ per liter, the wind-diesel hybrid power system for the island becomes a prospective candidate.

• Environmental and Resource Economics Review
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• v.28 no.4
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• pp.467-495
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• 2019

Uncertainty of renewable energy such as photovoltaic(PV) power is detrimental to the flexibility of the power system. Therefore, precise prediction of PV power generation is important to make the power system stable. The purpose of this study is to forecast PV power generation using meteorological data including particulate matter(PM). In this study, PV power generation is predicted by support vector machine using RBF kernel function based on machine learning. Comparing the forecasting performances by including or excluding PM variable in predictor variables, we find that the forecasting model considering PM is better. Forecasting models considering PM variable show error reduction of 1.43%, 3.60%, and 3.88% in forecasting power generation between 6am~8pm, between 12pm~2pm, and at 1pm, respectively. Especially, the accuracy of the forecasting model including PM variable is increased in daytime when PV power generation is high.