• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1150-1152
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• 1998

Recently, our electric industry confronts a structural change and high competiveness environment in the course of deregulation. Rapid growth in electricity demand, financial need for new power plant construction, and envionmental problems have led to search for more efficient energy production and energy conservation techmologies. Especially, residential and commercial buildings consumes 40% of electricity demands and building energies are increasing more and more in Korea. The purpose of this paper is to analyze the electricity use of commercial buildings by end-use. Also, we will use it as a basic informations of DSM potential evaluation and evaluation process based on different approach by sector and type of potential.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.5
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• pp.644-651
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• 2014

The renewable energy system and the real-time pricing can provide the significant economic advantage for end-user of residential house. However, according to recent studies, high initial cost of renewable energy system such as photovoltaic (PV) system and lack of suitable load control methods adjusting electric power consumption in response to time-varying price are regarded as the major obstruction for introduction of renewable energy system and real-time pricing in residental household. In this paper, we propose automated optimal load control strategy which aim to achieve not only minimizing the electricity cost but also the increase in the utilization rates of PV generation power of residential PV house in real-time pricing environment. Simulation results show that our proposed optimal load control strategy leads to significant reduction in the electricity costs and increase in the utilization rates of power generated by PV system in comparison with the conventional PV house. Therefore, the proposed optimal load control strategy can provide more economic benefit to end-user.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.1
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• pp.117-122
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• 2010

The solar cells and fuel cells power are being encouraged to reduce the environmental pollution and combat the global warming. And the electric generation hybrid system is usually more reliable and less costly than the systems that use a single source of energy. HOMER provides a platform to design and simulate the power system and then to choose the optimization results. Based on the electricity demand conditions during a year, this paper simulates with the HOMER and performs the monthly average electrical production and the most feasible economical case includes the net present costs and the annualized costs of the hybrid system components.

• Journal of Industrial Technology
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• v.30 no.A
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• pp.9-15
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• 2010

Recently, Smart Grid is a emerging topic in power and communication industry. Smart Grid refers to a evolution of the electricity supply infrastructure that monitors, protects, and intelligently optimize the operation of the interconnected elements including various type of generators, power grid, building/home automation system and end-use consumers. In order to successful implementation of Smart Grid, energy management function will be the key factor that coordinates and optimally controls the various loads according to the operating condition and environments, and the load patterns in residential and commercial building will be required as fundamental element for load management. In this study, we collects many types of energy usage data of electric appliances, analyze their load curves, and make the general load patterns for electrical appliance.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.68-77
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• 2018

Regarding demand response (DR) by residential users (R-users), the users try to reduce electricity costs by adjusting their power consumption in response to the time-varying price. However, their power consumption may be affected not only by the price, but also by user convenience for using appliances. This paper proposes a methodology for appliance scheduling (AS) that considers the user convenience based on historical data. The usage pattern for appliances is first modeled applying the copula function or clustering method to evaluate user convenience. As the modeling results, the comfort distribution or representative scenarios are obtained, and then used to formulate a discomfort index (DI) to assess the degree of the user convenience. An AS optimization problem is formulated in terms of cost and DI. In the case study, various AS tasks are performed depending on the weights for cost and DI. The results show that user convenience has significant impacts on AS. The proposed methodology can contribute to induce more DR participation from R-users by reflecting properly user convenience to AS problem.

• Asia Pacific Journal of Business Review
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• v.3 no.1
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• pp.19-38
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• 2018

The energy intensity of Nepal is economically not worthy, lacks eco-friendly and importantly not sustainable, and almost four times the average global energy intensity. Considerable efforts have been exercised to reduce the energy gap yet, it is still much to achieve. Nation priority on energy sector was envisaged with promulgation of investment friendly rules and law in hydropower and renewable technology even though, could not harness the sufficient energy. In amid of this acute energy crisis, the government launched the Nepal Energy Efficiency Programme (NEEP) with technical assistance from German International Cooperation (GIZ). Energy Efficiency (EE) practice is the most cost-effective method to reduce the supply and demand gap, reduce on greenhouse gases and pollution, and deter on import of petroleum products which finally improves on trade imbalance. This paper had proposed a framework of energy management team to promote energy efficient technologies in residential consumer. The energy management teams study the past records of energy use pattern of consumers and suggest appropriate technology for energy saving options. The paper provides some reviews of energy efficiency initiatives undertaken by the concern regulatory body which highlights the current status. The comprehensive knowledge acquired through exploratory research is implemented in this paper to identify the various barriers that domestic consumer is experiencing towards the active participation in energy efficiency program launched by the Government of Nepal.

• Nuclear Engineering and Technology
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• v.39 no.1
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• pp.1-8
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• 2007

Hydrogen and electricity are expected to dominate the world energy system in the long term. The world currently consumes about 50 million metric tons of hydrogen per year, with the bulk of it being consumed by the chemical and refining industries. The demand for hydrogen is expected to increase, especially if the U.S. and other countries shift their energy usage towards a hydrogen economy, with hydrogen consumed as an energy commodity by the transportation, residential and commercial sectors. However, there is strong motivation to not use fossil fuels in the future as a feedstock for hydrogen production, because the greenhouse gas carbon dioxide is a byproduct and fossil fuel prices are expected to increase significantly. An advanced reactor technology receiving considerable international interest for both electricity and hydrogen production, is the modular helium reactor (MHR), which is a passively safe concept that has evolved from earlier high-temperature gas-cooled reactor (HTGR) designs. For hydrogen production, this concept is referred to as the H2-MHR. Two different hydrogen production technologies are being investigated for the H2-MHR; an advanced sulfur-iodine (SI) thermochemical water splitting process and high-temperature electrolysis (HTE). This paper describes pre-conceptual design descriptions and economic evaluations of full-scale, nth-of-a-kind SI-Based and HTE-Based H2-MHR plants. Hydrogen production costs for both types of plants are estimated to be approximately $2 per kilogram.

• Transactions of the Korean hydrogen and new energy society
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• v.20 no.2
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• pp.104-115
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• 2009

In case of residential fuel cell system, it is significant to stably supply heat and power to a house with high efficiency and low cost for the successful commercialization. In this paper, the control strategy analysis has been performed to minimize the total cost including capital and operating cost of the residential fuel cell system. The proposed analysis methodology is based on the simulator including the efficiency models as well as the cost data for fuel cell components. The load control strategy is the key factor to decide the system efficiency and thus the cost analysis is performed when the fuel cell system is operated for several different load control logics. Additionally, annual efficiency of the system based on the seasonal load data is calculated since system efficiency is changeable according to the electric and heat demand change. As a result, the hybrid load control combined electricity oriented control and heat oriented control has the most economical operation.

• Journal of the HCI Society of Korea
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• v.12 no.4
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• pp.65-73
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• 2017

While electricity demand is generally increasing, stably controlling supply is becoming a serious challenge because renewable energies are becoming popular and often their productions are dependent on the weather. The 'demand response' programs can be used to complement the problems of renewable energies, and therefore their role is becoming increasingly important. This study provides an analysis of a demand response pilot that was conducted in Korea. The study first focused on questionnaire surveys and in-depth interviews, and the data was used to perform a Technology Acceptance Model (TAM) analysis. The goal of the pilot was to have the residential users reduce their power consumptions when an energy reduction mission is issued during peak load hours. The experimental subjects consisted of two groups with different characteristics. Subjects in group A obtained smart meters as an optional function of IoT platform service provided by a mobile service company, and received a charge deduction as their compensation. Subjects in group B either voluntarily purchased smart meters as individuals or received them by participating in an energy self-sufficient village program that was run by a local government, and were entitled to a donation as their compensation. With the analysis, group A was found to fit the extended technology acceptance model that includes perceived playfulness in addition to perceived ease of use and perceived usefulness. On the contrary, group B failed to fit the model well, but perceived usefulness was found to be relatively more important compared to group A. The results indicate that the residential energy groups' behavior changes are dependent on each group's characteristics, and group-specific DR design should be considered to improve the effectiveness of DR.

• Environmental and Resource Economics Review
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• v.26 no.4
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• pp.519-547
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• 2017

This paper explores whether it is better to forecast city gas demand in Korea using national level data directly or, alternatively, construct forecasts from regional demand models and then aggregate these regional forecasts. In the regional model, we consider gas demand for Seoul metropolitan and the other local areas. Our forecast evaluation exercise for 2013-2016 shows the regional forecast model generally outperforms the national forecasting model. This result comes from the fact that the dynamic properties of each region's gas demands can be better taken into account in the regional demand model. More specifically, the share of residential gas demand in the Seoul metropolitan area is above 50%, and subsequently this demand is heavily influenced by temperature fluctuations. Conversely, the dominant portion of regional gas demand is due to industrial gas consumption. Moreover, electricity is regarded as a substitute for city gas in the residential sector, and industrial gas competes with certain oil products. Our empirical results show that a regional demand forecast model can be an effective alternative to the demand model based on nation-wide gas consumption and that regional information about gas demand is also useful for analyzing sectoral gas consumption.