• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.7
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• pp.1025-1031
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• 2017

This study compares the characteristics and the determinants of household electricity consumption for low electricity consuming and high electricity consuming households. The data are drawn from a household energy consumption sample survey by Korea Energy Economics Institute in 2015. The results show the differences in socio-demographic, dwelling, and electricity consumption characteristics between two households. Next, the factors affecting the household's electricity consumption are investigated. Common factor affecting the electricity consumption function is only the number of electrical appliances. There are also the differences in major determinants of the household's electricity consumption functions for two households. The results of this study would be useful for understanding socio-demographic, dwelling, and electricity consumption characteristics of low electricity consuming and high electricity consuming households.

• Journal of the Korean Home Economics Association
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• v.46 no.3
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• pp.37-47
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• 2008

This study investigated (1) consumer perception about the level of electricity price, (2) the amount of household electricity consumption, and (3) consumer perception on electricity pricing system reform. For data collection, a national wide survey was conducted between November 22 and December 15, 2006. Excluding 233 cases, because of incomplete responses, data from 1767 households were analyzed. The major findings were as follows; More than 50% of the respondents consumed between 100-300kWh of electricity per month. Household size and income were significantly associated with electricity consumption. Approximately 50% of respondents perceived that electricity was being overcharged. Approximately 50% of the respondents positively evaluated the effects of the graduation pricing system. Households consuming more than 300kWh of electricity per month preferred a flat unit price. Based on these results, we suggest the implications to reforming the electricity pricing system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.2
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• pp.79-89
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• 2003

A research about finding a new electricity load model that is sensitive to the price of electricity is conducted. This new model i5 polynomial type price sensitive electricity consumption model, while former electricity consumption models have exponential terms or statistic terms. The pattern of electricity consumption of each electricity using devices were identified first, then the proportion of the devices at buses or nodes are investigated, finally weighted sum of electricity consumption and the proportion makes the load model or consumption model of electricity at one bus or node. This new model is easy to use in the simulations or calculations of the electricity consumption, because the arithmetic of functions with polynomial terms are easy compared to the functions with transcendental terms.

• The Journal of Information Systems
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• v.28 no.1
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• pp.133-153
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• 2019

Purpose The purpose of this study is to design a regional electricity planning model rather than the existing single region ones and verify its usefulness. The regional electricity planning model is to determine both electricity distribution among regions and power plant planning at the same time satisfying regional demands and distribution networks. Design/methodology/approach This study made a regional electricity planning model by integrating power plant planning and electricity distribution among regions. The regional electricity planning model is formulated into a linear programming problem, and coded and run using the OSeMOSYS, one of open source energy systems. Findings According to the empirical analysis result, this study confirmed that the regional electricity planning model proposed in this study deducts the unfairness among regions in view of electricity and green house gas. In addition, the model is expected to be used in evaluating and developing the national policies concerning fine dust and/or green house gas.

• Nuclear Engineering and Technology
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• v.54 no.8
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• pp.2883-2897
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• 2022

According to the Renewable Energy 3020 Implementation Plan announced in 2017 by the South Korean government, the electricity share of renewable energy will be expanded to 20% of the total electricity generation by 2030. Given the intermittency of electricity generation from renewable energy, realization of such a plan presents challenges to managing South Korea's isolated national electric grid and implies potentially large excess electricity generation in certain situations. The purpose of this study is: 1) to develop a model to accurately simulate the effects of excess electricity generation from renewables which would arise during the transition, and 2) to propose strategies to manage excess electricity generation through effective utilization of domestic electricity generating capabilities. Our results show that in periods of greater PV and wind power, namely the spring and fall seasons, the frequency of excess electricity generation increases, while electricity demand decreases. This being the case, flexible operation of coal and nuclear power plants along with LNG and pumped-storage hydroelectricity can be used to counterbalance the excess electricity generation from renewables. In addition, nuclear energy plays an important role in reducing CO₂ emissions and electricity costs unlike the fossil fuel-based generation sources outlined in the 8th Basic Plan.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.289-291
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• 2000

In a competitive electricity power market, the price of electricity changes instantly, that of conventional market is predetermined and hardly changes. In such a new environment, customers' behaviors change instantly according to the changing electricity prices. If we develop a electricity load model that well describes the behavior of electricity consumers, we can utilize that model in forecasting the amount of future load, solving the load flow problem and finding the weak point of the system. In this paper new electricity model that considers the price of electricity and power factor of the load is presented. While conventional load model, which is demand function of electricity, uses the price of real and reactive power as the independent variable of the demand function. this new load model uses price of real power and penalty factor according to the power factor for the calculation of amount of electricity demand.

• Journal of Energy Engineering
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• v.27 no.3
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• pp.10-20
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• 2018

Due to cheap electricity tariff on agricultural use, electricity consumption in agricultural sector has grown dramatically. We evaluated the negative effects of the cheap electricity tariff such as electricity over-consumption, increased dependency on electricity, decreased electricity productivity, and unequal distribution of the benefit. We also estimated the effects of agricultral output growth, structural change, and electricity intensity change on sharp electricity consumption increase in agricultural sector between 1998 and 2016 using the Log Mean Divisia Index decomposition method. The findings reinforce the necessity of raising the electricity tariff for agricultural use.

• Journal of Construction Engineering and Project Management
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• v.3 no.3
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• pp.23-34
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• 2013

As climate change and environmental pollution become one of the biggest global issues today, new renewable energy, especially solar photovoltaic (PV) system, is getting great attention as a sustainable energy source. However, initial investment cost of PV system is considerable, and thus, it is crucial to predict electricity generation accurately before installation of the system. This study analyzes the loss ratio of solar photovoltaic electricity generation from the actual PV system monitoring data to predict electricity generation more accurately in advance. This study is carried out with the following five steps: (i) Data collection of actual electricity generation from PV system and the related information; (ii) Calculation of simulation-based electricity generation; (iii) Comparative analysis between actual electricity generation and simulation-based electricity generation based on the seasonality; (iv) Stochastic approach by defining probability distribution of loss ratio between actual electricity generation and simulation-based electricity generation ; and (v) Case study by conducting Monte-Carlo Simulation (MCS) based on the probability distribution function of loss ratio. The results of this study could be used (i) to estimate electricity generation from PV system more accurately before installation of the system, (ii) to establish the optimal maintenance strategy for the different application fields and the different season, and (iii) to conduct feasibility study on investment at the level of life cycle.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.375-385
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• 2013

As climate change and environmental pollution become one of the biggest global issues today, new renewable energy, especially solar photovoltaic (PV) system, is getting great attention as a sustainable energy source. However, initial investment cost of PV system is considerable, and thus, it is crucial to predict electricity generation accurately before installation of the system. This study analyzes the loss ratio of solar photovoltaic electricity generation from the actual PV system monitoring data to predict electricity generation more accurately in advance. This study is carried out with the following five steps: (i) Data collection of actual electricity generation from PV system and the related information; (ii) Calculation of simulation-based electricity generation; (iii) Comparative analysis between actual electricity generation and simulation-based electricity generation based on the seasonality; (iv) Stochastic approach by defining probability distribution of loss ratio between actual electricity generation and simulation-based electricity generation ; and (v) Case study by conducting Monte-Carlo Simulation (MCS) based on the probability distribution function of loss ratio. The results of this study could be used (i) to estimate electricity generation from PV system more accurately before installation of the system, (ii) to establish the optimal maintenance strategy for the different application fields and the different season, and (iii) to conduct feasibility study on investment at the level of life cycle.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.4
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• pp.11-27
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• 2002

This paper is aimed at surveying the method that supports logical and theoretical back grounds of electricity service pricing, to investigate whether the ESPM can reflect comprehensively the various interests of parties and persons concerned with electricity supply and demand, and analyzing the practical applicability of the model in short-term perspectives. The major findings of this study can be summarized as fellows. First, the ESPM explains what process the equilibrium price is attained through, which is the essential concept and object in evaluating the value of public enterprises or utilities and the price of electricity Second, the ESPM provides the logics and methods that can objectify the discrete price by each electricity user. Third, the ESPM presents theoretical logics and practical methods that can calculate the basic price and the variable price per electricity unit which are key concepts in the two-part tariff. Fourth, the ESPM has powerful practical applicabilities in the reasonable electricity pricing and in the explanation for the balance between parties and persons interested with electricity supply and demand.