• Journal of Families and Better Life
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• v.26 no.4
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• pp.1-11
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• 2008

This study investigated consumers' energy saving behavior and perceptions concerning the effectiveness of their energy saving behavior. A nation wide survey was conducted involving 2000 households in urban areas and the data from 1767 households were used for the analysis. excluding cases with incomplete responses. Descriptive analysis, factor analysis, and regression analysis were applied. The results were as follows. First, electricity saving behavior was classified into three categories: Thrift (reducing energy consumption), Purchase (buying energy saving appliances), and Control (checking the energy consumption). Second, consumers rated Thrift as the best way to save energy. Third, education, age, and household income were significantly related to energy saving behavior and perceptions on the effectiveness of energy saving behavior. Consumers using above average levels of electricity tended not to practice energy saving behavior and not to positively evaluate effectiveness of the energy saving behavior. Lastly, the implications for public policies to promote energy saving behavior are suggested.

• Environmental and Resource Economics Review
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• v.16 no.4
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• pp.901-922
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• 2007

To see how the electricity demand for air-conditioning responds to weather condition and what kind of weather condition works better in forecasting maximum daily electricity demand, four different regression models, which are linear, exponential, power and S-curve, are adopted. The regression outcome turns out that the electricity demand for air-conditioning is inclined to rely on the exponential model. Another major discovery of this study is that the electricity demand for air-conditioning responds more sensitively to the weather condition year after year along with the higher non-air-conditioning electricity demand. In addition, it has also been found that the discomfort index explains the electricity demand for air-conditioning better than the highest temperature.

• Asian Journal of Atmospheric Environment
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• v.8 no.1
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• pp.59-68
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• 2014

The Fukushima nuclear accident in 2011 had an extensive impact on the national electricity plans. This paper outlines alternative electricity scenarios that meet the goals of nuclear phase-out and greenhouse gas (GHG) emission reduction. This paper also analyzes the results of each scenario in respect to the electricity mix, GHG emissions, costs and employment effects. The Long-range Energy Alternatives Planning system (LEAP) model was used to simulate the annual electricity demand and supply system from 2011 to 2030. The reference year was 2009. Scenarios are reference (where existing plans are continued), A1, A2, B1, B2, and C2 (where the levels of demand management and nuclear phase-out are different). The share of renewable energy in the electricity mix in 2030 for each scenario will be increased from about 1% in 2009 to 8% in the reference scenario and from 11% to 31% in five alternative scenarios. Total cumulative cost increases up to 14% more than the reference scenario by replacing nuclear power plants with renewable energy in alternative scenarios could be affordable. Deploying enough renewable energy to meet such targets requires a roadmap for electricity price realization, expansion of research, development and deployment for renewable energy technologies, establishment of an organization dedicated to renewable energy, and ambitious targets for renewable energy.

• Journal of the Korea Safety Management & Science
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• v.17 no.1
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• pp.271-279
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• 2015

Global warming has pressured companies to put a greater emphasis on environment management which allows them to reduce environmental impact and costs of their operations. In Korea, the coal-fired power plants take a large account of electricity generation at 31.7% of the total electricity usage in 2014. Thus, environmental impact of coal-fired power plants is significant. This paper illustrated how to compute environmental impact and costs in electricity generation at a coal-fired power plant using MFCA methodology. Compared to the traditional accounting, an advantage of MFCA is to provide information on electricity generation costs and environmental wastes incurring throughout the production process of electricity. Based on MFCA, the coal-fired power plant was able to reduce production cost of electricity by 52.3%, and environmental wastes by 47.7%. As a result, MFCA seemed to be an effective tool in environmental management for power plants.

• Journal of Korean Elementary Science Education
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• v.23 no.3
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• pp.199-207
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• 2004

Elementary science curriculum is designed to be closely-related magnetism with electricity in a physics domain and this paper explored whether elementary school students have recognized of relationships between them and whether there are any trends in the degree of recognition by grades. The elementary students of 3rd to 6th grade (total 154 persons) in a school in a local city participated in the experiment. Two forms of questionnaire were administrated to each grades. In the first questionnaire about magnetism, students were asked to rank the physics terms as the degree of proximity into magnetism and to write briefly the reason. In the second questionnaire about electricity, students were asked to do the same routine. The closer to the central term in the diagram, the lower score were given and the terms were classified as closely related to magnetism, electricity and the rest. Calculated the response frequency and averaged by the ranked terms, it was examined that the scores of proximity in how students closely rated conception to magnetism and electricity. The result said that the upper grades students showed the degree of proximity with magnetism and electricity as closely. Therefore, the sequence of comprehension of magnetism and electricity concept, which was found in the elementary school curriculum, seems to be found in the elementary students＇ recognitions by grades.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.6
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• pp.560-568
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• 2005

The cost accounting of electricity and heat produced from an energy system is important in evaluating the economical efficiency and deciding the reasonable sale price. The OECOPC method, suggested by the author, was applied to a 650 MW combined cycle cogeneration system having 4 operating modes, and each unit cost of electricity and heat products was calculated. In case that a fuel cost is ${\\}400/kg$ and there are no direct and indirect cost, they were calculated as follows; electricity cost of ${\\}23,700/GJ$ at gas-turbine mode, electricity cost of ${\\}15,890/GJ$ at combined cycle mode, electricity cost of ${\\}14,146/GJ$ and heat cost of ${\\}6,466/GJ$ at cogeneration mode, and electricity cost of ${\\}14,387/GJ$ and heat cost of ${\\}4,421/GJ$ at combined cycle cogeneration mode. Further, these unit costs are applied to account benefit on this system. Since the suggested OECOPC method can be applied to any energy system, it is expected to contribute to cost accounting of various energy systems.

• Journal of the Korea Convergence Society
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• v.8 no.1
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• pp.19-23
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• 2017

Energy is a vital resource for the economic growth and the social development for any country. As the industry becomes more sophisticated and the economy more grows, the electricity demand is increasing. So forecasting electricity demand is an important for electricity suppliers. Forecasting electricity demand makes it possible to distribute electricity demand. As the market for Negawatt market began to grow in Korea from 2014, the prediction of electricity consumption demand becomes more important. Moreover, power consumption forecasting provides a way for demand management to be directly or indirectly participated by consumers in the electricity market. We use Genetic Algorithms to predict the energy demand of the fishing industry in Jeju Island by using GDP, per capita gross national income, value add, and domestic electricity consumption from 1999 to 2011. Genetic Algorithm is useful for finding optimal solutions in various fields. In this paper, genetic algorithm finds optimal parameters. The objective is to find the optimal value of the coefficients used to predict the electricity demand and to minimize the error rate between the predicted value and the actual power consumption values.

• Journal of Energy Engineering
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• v.22 no.1
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• pp.1-7
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• 2013

This paper attempts to estimate the residential electricity demand function, using survey data of 521 households in Korea. As the residential electricity demand function provides us information on the pattern of consumer's electricity consumption, it can be usefully utilized in predicting the impact of policy variables such as electricity price and forecasting electricity demands. We apply least absolute deviation(LAD) estimation as a robust approach to estimating parameters. The results showed that price and income elasticities are -0.68 and 0.14 respectively, and statistically significant at the 10% levels. The price and income elasticities portray that residential electricity is price- and income-inelastic. This implies that the residential electricity is indispensable goods to human-being's life, thus the residential electricity demand would not be promptly adjusted to responding to price and/or income change.

• Environmental and Resource Economics Review
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• v.20 no.2
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• pp.381-398
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• 2011

Recently, electricity peaks have frequently occurred in winter, and the concerns about failure in power supply are soaring. One of reasons is due to the increase in industrial demand with economic recovery, and the increases in household and commercial demand with unusual cold waves are spotted as a primary cause. Especially, the diffusion of electricity heat pumps (EHP) has led to the rapid increase in commercial electricity demand. The EHP diffusion is mainly associated with low electricity tariff and cheaper heating and cooling costs compared to those of gas-engine heat pumps (GHP). The problem is that distorted electricity tariff and herd behaviour toward heating and cooling devices could bring about nation-wide inefficiencies in resource allocation. The key countermeasures are as follows. The electricity tariff should be readjusted to a realistic level. The tariff scheme should be so modified that consumers rationally respond to the tariff. In addition, one should find ways to effectively manage electricity demand.

• Clean Technology
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• v.29 no.1
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• pp.53-58
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• 2023

This study shows the summary of the economic performance of excess electricity conversion to hydrogen as well as methane and returned conversion to electricity using a fuel cell. The methane production process has been examined in a previous study. Here, this study focuses on the conversion of methane to electricity. As a part of this study, capital expenditure (CAPEX) is estimated under various sized plants (0.3, 3, 9, and 30 MW). The study shows a method for economic optimization of electricity generation using a fuel cell. The CAPEX and operating expenditure (OPEX) as well as the feed cost are used to calculate the discounted cash flow. Then the levelized cost of returned electricity (LCORE) is estimated from the discounted cash flow. This study found the LCORE value was ¢10.2/kWh electricity when a 9 MW electricity generating fuel cell was used. A methane production plant size of 1,500 Nm³/hr, a methane production cost of $11.47/mcf, a storage cost of $1/mcf, and a fuel cell efficiency of 54% were used as a baseline. A sensitivity analysis was performed by varying the storage cost, fuel cell efficiency, and excess electricity cost by ±20%, and fuel cell efficiency was found as the most dominating parameter in terms of the LCORE sensitivity. Therefore, for the best cost-performance, fuel cell manufacturing and efficiency need to be carefully evaluated. This study provides a general guideline for cost performance comparison with LCORE.