This study aims to provide power generating plants with eco-efficiency information. To implement the purposes, of study, both DEA(Data, Envelopment Analysis) model and interview were incorporated in terms of methodologies. To analyze the managerial efficiency, total labor cost and number of employees were considered as input factors. CO2, NOx, and water also were considered as input factors to analyze eco-efficiency. Both annual total power product and annual total revenue were used as output factors. CRS(Constant Return to Scale) and VRS(Variable Return to) model were facilitated in this analysis. According to the findings, most of the power plants were evaluated as 'Efficient'' taking into consideration of average value, both 0.928 from CCR model and 0.969 from VRS model. 7 DMUs including DMU3 and DMU12 are efficient out of 35 DMUs relatively, other DMUs are inefficient. For results of inefficient output factors distribution, it was found that inefficiency for NOx was marked relatively higher than CO2. In order to improve the eco-efficiency in the power plants in the long term, the target amount of Co2 as well as NOx reduction needs to be properly proposed in consideration of particularity of power plants. In the long run, renewable energy, alternative fuels should be adapted to reduce the eco-inefficient.
The paper affirms the weight proportion concept as an element, which could be empirically analyzed quantitatively through the developmental expansion of qualitative empirical analysis on taxonomy that is required for the construction Low-Carbon Green Cities and their eco-friendly elements, such as a pleasant residential environment The weight proportion concept is proposed as a new measure to identify eco-friendly elements and as an objective assessment indicators. To perform an empirical analysis, surveys were first given to the residents of Metropolitan Newtown (50 persons) and outside experts (50 persons) for the total of 100 persons. Second, the paper surveyed 74 sites of Eco-Environmental Certified Apartment Housing Complexes. Upon analysis of eco-friendly elements by their type and total weight, the largest weight proportion was expressed in the interior and eco-environmental elements, carbon-decrease types, and carbon-absorption types. The results of this paper confirm recent positive sentiments and preference toward a variety of future-oriented and sustainable eco-friendly elements like the eco-housing and new renewable energy, In addition, the paper affirmed the new housing trend towards constructing eco-friendly elements, such as carbon-decrease and carbon-absorption, that induce long-term investments, despite their need for higher investments.
Competitions for secure oil are intense around the world due to the limited oil reserves. The situations are becoming more serious as China has participated in the competition. This paper aims to investigate China's offshore oil development strategies to balance the supply and demand of oil and then suggest its policy implications. A surging increase of oil demand due to the rapid economic growth as well as the stagnation in domestic oil output has turned China into a net oil importer since 1993. Therefore, China has placed a significant priority on securing long-term stability of its offshore oil to cope with the rapid growing demand. It has taken a variety of strategies to secure stable oil resource such as development of offshore oil resource, increasing the number of oil importing countries. China with the highest foreign exchange reserve of approximately $3 trillion as of 2010, has considered to employ foreign exchange reserves while making a huge amount of investment to secure oil resource. China has pursued several policies such as loan to oil production country for securing oil, foreign direct investment on offshore oil development, M&A of oil exploration and production companies and geographical diversification of oil importing countries. China has promoted offensive strategies for securing oil resource rather than cooperation with other countries. Thus, China should find a trade-off point for recovering relationship with international society while developing and investing renewable energy for long-term future. It will also address some implications for Korea, which has to prepare new strategies of overseas oil development.
Journal of the Korea Academia-Industrial cooperation Society
/
v.20
no.11
/
pp.239-249
/
2019
Recently, the Korean government has implemented a policy to expand renewable energy sources. Large-scale PV systems are being actively interconnected with the distribution system. On the other hand, when a large-scale PV system is installed and operated, the customer voltages could violate the allowable voltage limit due to reverse power flow of the PV system. To overcome these problems, an enhancement method for hosting the capacity of the PV system in a distribution system is being actively conducted. Therefore, to improve the hosting capacity of the PV system, this paper proposes a model of a reconfiguration of the distribution system, which is composed of three sections and three connections based on PSCAD/EMTDC S/W, and proposes an evaluation algorithm for the feeder reconfiguration to maximize an adaption of the PV system. In addition, this paper presents the optimal method of the feeder reconfiguration section to evaluate the maximum capacity of the PV system to keep customer voltages within the allowable voltage limits based on various operation scenarios, such as the capacity of a PV system and section of feeder reconfiguration. From the simulation results based on the PSCAD/EMTDC modeling and evaluation algorithm, it was confirmed that they are a useful and practical tool to enhance hosting the capacity of a PV system in a distribution system.
Journal of the Korea Academia-Industrial cooperation Society
/
v.21
no.7
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pp.20-28
/
2020
According to the 3020 RE (renewable energy) policy of the Korean Government, distributed generators, including PV (photovoltaic) and WP (wind power) systems, have been installed and operated in distribution systems. On the other hand, if large-scale PV systems are interconnected in a distribution system, the spread of PV systems may be postponed due to a reduction of the hosting capacity in PV systems because of the over-voltage phenomena at the customer end by violating the allowable voltage limits. Under these circumstances, this paper proposes an evaluation algorithm of the hosting capacity of a PV system based on the LDC (line drop compensation) method of SVR (step voltage regulator) to improve the hosting capacity when large-scale PV systems are installed in a distribution system. Moreover, this paper presents a modeling of a complex distribution system, which is composed of a large-scale PV system and SVR with the LDC method using PSCAD/EMTDC. The simulation results confirmed that the proposed algorithm and modeling are useful and practical tools for improving the hosting capacity of a PV system because the customer voltages are maintained within the allowable voltage limits even if 6.5[MW] of the PV system is installed in a distribution system with the LDC method of SVR.
Recently, there has been a debate as to whether bioethanol should replace some portion of gasoline for fuels in South Korea, as energy security as well as climate change issues are rising as a significant national agenda. However, a considerable amount of subsidy will be required to compensate for the higher price of bioethanol-blended gasoline. In this context, government subsidy will obtain justification only when the positive social gains from consuming bioethanol for fuels can exceed the negative social costs. Through a nation-wide choice experimental survey, we examine if South Koreans have a positive value as well as non-linear preferences on substituting bioethanol for gasoline. The results reveal that the willingness to pay for purely domestic bioethanol-blended gasoline within 10% is about 52 KRW; Koreans have concave preferences on the blending ratio of bioethanol to gasoline. The turning point of the blending ratio of bioethanol was 6.5%. Also, we found inverse U-shaped curve between income and bioethanol choice probability and the turning point of the income was calculated as 250~299million KRW. Politically conservative propensity advocates uses of bioethanol blended gasoline, but awareness on bioethanol or more weights on environmental conservation have significantly negative effects on the choice of bioethanol. However, the design of the survey questionnaire is incompatible with the RFS of Korea and assumes orthogonality among the following four interrelated attributes: (i) domestic or offshore procurement of feedstocks in the case of domestic production, (ii) domestic production or import of bioethanol, (iii) the blending ratios, and (iv) the retail price increases. In addition, the results of model estimation and of model selection test are not definite. Hence, the results in this study should not be directly applied to the design of the specifics of the Korean RFS. Hence, the results in this study require cautions in applying to the design of the Korean RFS policy.
Recently the construction of solar plant showed a steady growth in influence of renewable energy policy. It is very important to determine the optimal location and aspect of solar panel using analyzed data of solar radiation to solar plant area beforehand. This study analyzed solar radiation in solar plant area using DEM acquired from UAV geospatial information. Mean solar radiation of 2017 was calculated as $1,474,466W/m^2$ and total solar radiation of 2017 considering solar plant area showed $33,639MW/m^2$ on analyzed result. It is important to analyze monthly solar radiation in aspect of maintenance works of solar plant. Monthly solar radiation of May to July was calculated over $160,000W/m^2$ and that of January to February and November to December showed under $80,000W/m^2$ in monthly solar radiation analysis of solar plant area. Also this study compared with solar radiation being calculated from UAV geospatial information and that of National Institute of Meteorological Sciences. And mean solar radiation of study area showed a little high in comparison with whole country data of National Institute of Meteorological Sciences, because the 93.7% of study area was composed of south aspect. Therefore this study can be applied to calculate solar radiation in new developed solar plant area very quickly using UAV.
Journal of the Korea Academia-Industrial cooperation Society
/
v.21
no.9
/
pp.652-661
/
2020
Recently, the Korean government developed the RE3020 (renewable energy) policy to overcome environmental problems, such as fine dust, climate change, and large-scale PV systems interconnected with a distribution system. When a large-scale PV system is interconnected in the distribution system, however, a malfunction can occur, and the protection devices may not be operated because of the dividing effect depending on the magnitude and direction of fault current as well as connection types and location of the PV system. Therefore, this paper proposes a search algorithm for the malfunction pattern of protection devices based on various scenarios, when large-scale PV systems are operated and interconnected in a distribution system. This paper presents a malfunction mechanism of protection devices according to the installation locations of recloser (R/C). Furthermore, the modeling of a distribution system with large-scale PV systems was performed using Off-DAS S/W, and the malfunction patterns of protection devices were analyzed based on a range of scenarios. From the simulation results with the proposed model and algorithm for searching for protection devices, it was confirmed that they are useful and effective in identifying a malfunction phenomenon depending on the installation location of the R/C and connection type of PV system.
An emergy analysis of the main energy flows driving the economy of humans and life support systems was made including environmental energies, fuels, and imports, all expressed as solar emjoules. The total emergy use (4, 373 E20 sej/yr) is 90 per cent from imported sources, fuels and goods and services. The emergy flows from the environment are modest, because the share of global inputs such as ruin and geological uplift flux is modest. Consequently, the ratio of outside investment to attracting natural resources is already large, like other industrialized countries. The population level is already in excess of carrying capacity. The emergy use per person in Korea indicates a moderate emergy standard of living, even though the indigenous resource is very poor. If the present economy were running entirely on stored reserves of fuels, soils, woods, etc., it would last about 2 years. Its carrying capacity for steady state on its renewable sources is only 3.3 million people, compared to 43.3 million in 1991. Continued availability of foreign oil at a favorable balance of emergy trade, currently about 7 to 1 net emergy, is the basis for present economic activity and must decrease as the net emergy of foreign oil purchased goes down. Close economic integration with Middle East may determine how long this is possible in the future.
Solar energy, which is rapidly increasing in proportion, is being continuously developed and invested. As the installation of new and renewable energy policy green new deal and home solar panels increases, the supply of solar energy in Korea is gradually expanding, and research on accurate demand prediction of power generation is actively underway. In addition, the importance of solar radiation prediction was identified in that solar radiation prediction is acting as a factor that most influences power generation demand prediction. In addition, this study can confirm the biggest difference in that it attempted to predict solar radiation using medium-term forecast weather data not used in previous studies. In this paper, we combined the multi-linear regression model, KNN, random fores, and SVR model and the clustering technique, K-means, to predict solar radiation by hour, by calculating the probability density function for each cluster. Before using medium-term forecast data, mean absolute error (MAE) and root mean squared error (RMSE) were used as indicators to compare model prediction results. The data were converted into daily data according to the medium-term forecast data format from March 1, 2017 to February 28, 2022. As a result of comparing the predictive performance of the model, the method showed the best performance by predicting daily solar radiation with random forest, classifying dates with similar climate factors, and calculating the probability density function of solar radiation by cluster. In addition, when the prediction results were checked after fitting the model to the medium-term forecast data using this methodology, it was confirmed that the prediction error increased by date. This seems to be due to a prediction error in the mid-term forecast weather data. In future studies, among the weather factors that can be used in the mid-term forecast data, studies that add exogenous variables such as precipitation or apply time series clustering techniques should be conducted.
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