• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.19-26
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• 2019

As global demand for energy, energy prices, and power generation has increased worldwide, the government is turning to supply-oriented electricity supply and demand policies, such as behavior-based energy efficiency programs. In order to measure the implementation effect of the behavior-based energy efficiency program, the energy reduction must be accurately calculated by calculating the customer baseline load.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.6
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• pp.440-448
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• 2022

Recently, due to the introduction of distributed energy resources, the optimal resource allocation problem of the power network is more and more important, and the distributed resource allocation method is required to process huge amount of data in large-scale power networks. In the optimal resource allocation problem, many studies have been conducted on the case when the supply-demand balance is satisfied due to the limitation of the generation capacity of each generator, but the studies considering the supply-demand imbalance, that total demand exceeds the maximum generation capacity, have rarely been considered. In this paper, we propose the consensus-based distributed algorithm for the optimal resource allocation of power network considering the supply-demand imbalance condition as well as the supply-demand balance condition. The proposed distributed algorithm is designed to allocate the optimal resources when the supply-demand balance condition is satisfied, and to measure the amount of required resources when the supply-demand is imbalanced. Finally, we conduct the simulations to verify the performance of the proposed algorithm.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.693-700
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• 2024

As of the end of March 2022, the total area of domestic industrial complexes is 606 km2, which is only about 0.6% of the total land area. However, as of 2018, the annual energy consumption of domestic industrial complexes is 110,866.1 thousand TOE, accounting for 53.5% of the country's total energy consumption and 83.1% of the entire industrial sector energy consumption. In addition, industrial complexes have a significant impact on the environment, accounting for 45.1% of the country's total greenhouse gas emissions and 76.8% of industrial sector greenhouse gas emissions. Under this background, in this study, in order to contribute to the energy efficiency of industrial complexes, a prediction study on energy demand and supply for an industrial complex in Korea using machine learning was conducted. In addition, a simulator UI screen was designed to more efficiently convey information on energy demand/supply prediction results and energy consumption status. Among the machine learning algorithms, Multi-Layer Perceptron (MLP) was used, and Bayesian Optimization was applied as an optimization technique for the prediction model. The energy prediction model for the industrial complex built in this study showed a prediction accuracy of 87.90% for compressed air demand and 99.54% for the flow rate available for the public air compressor.

• 한국태양에너지학회:학술대회논문집
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• 2009.11a
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• pp.314-319
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• 2009

The photovoltaic(PV) industry has been growing worldwide. Recently, the PV industries not also in the traditional PV advanced countries but also in other countries are rapidly growing. Especially, China has become the largest supplier in the world PV supply side since 2007. Both the world PV supply and demand rose steadily in 2008 like recent bumper years. In 2008, the world solar cell production reached 6.85GW~7.91GW presenting growth of 85% over the previous year. On the demand side, 81 countries contributed to the 5.95GW presenting growth of 110% over the previous year.

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.292-294
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• 1998

It is very important for electric utility to expand generating facilities and transmission equipments in accordance with the increase of electricity demand. Regional electricity demand forecasting is among the most important step for long-term investment and power supply planning. The main objectives of this paper are to develop the methodologies for forecasting regional load demand. The Model consists of four models, regional economy, regional electricity energy demand, areal electricity energy demand. and areal peak load demand. This paper mainly suggests regional electricity energy demand model and areal peak load demand. A case study is also presented.

• Journal of the Korean Solar Energy Society
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• v.40 no.1
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• pp.25-33
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• 2020

It has been reported about the energy saving performance of UFAD(under floor air distribution) system and NPC(night purge cooling) system respectively which are applied for commercial buildings. However, when two systems are used at the same time, the effect of heat transfer from floor plenum to slab may vary depending on the operating conditions of NPC. In this study, cooling energy demands were analyzed for building models with UFAD and NPC by using TRNSYS 17 program. UFAD was applied as a cooling system of the base building model, and the cooling energy demands were compared for 64 cases in which the operating time, supply airflow rate, and outdoor air temperature(T_o) of NPC. As a result, it was confirmed that the cooling energy demands were reduced to 30 ~ 80% level compared to UFAD alone, and in particular, the energy demand was reduced in proportion to the supply airflow rate or the operating time while T_o was 16 ~ 20℃. However, when T_o was 22℃, the increase in the supply airflow rate or the operating time results in a disadvantage in terms of cooling energy demands. In addition, the cooling energy demands for UFAD+NPC model were analyzed by applying weather data from three regions with different average outdoor air temperatures. As a result, the cooling energy demand of operating NPC only when T_o was below 20℃ was reduced by 27% compared to that of operating NPC continuously for 8 hours.

• Architectural research
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• v.18 no.2
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• pp.59-64
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• 2016

Since the massive power outages that hit across the nation in September 2011, a growing imbalance between energy supply and demand has led to a severe backup power shortage. To overcome the energy crisis which is annually repeated, a policy change for deriving energy supply from renewable energy sources and a demand reduction strategy has become essential. Buildings account for 18% of total energy consumption and have great potential for energy efficiency improvements; it is an area considered to be a highly effective target for reducing energy demand by improving buildings' energy efficiency. In this regard, retrofitting buildings to promoting environmental conservation and energy reduction through the reuse of existing buildings can be very effective and essential for reducing maintenance costs and increasing economic output through energy savings. In this study, we compared the energy reduction efficiency of national power energy consumption by unit production volume based on thermal power generation, renewable energy power generation, and initial and operating costs for a building retrofit. The unit production was found to be 13,181GWh/trillion won for bituminous coal-fired power generation, and 5,395GWh/trillion won for LNG power generation, implying that LNG power generation seemed to be disadvantageous in terms of unit production compared to bituminous coal-fired power generation, which was attributable to a difference in unit production price. The unit production from green retrofitting increased to 38,121GWh/trillion won due to the reduced energy consumption and benefits of greenhouse gas reduction costs. Renewable energy producing no greenhouse gas emissions during power generation and showed the highest unit production of 75,638GWh/trillion won, about 5.74 times more effective than bituminous coal-fired power generation.

• Journal of the Korean Solar Energy Society
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• v.39 no.5
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• pp.29-40
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• 2019

In response to the rapid climate change, in order to save energy in the field of buildings, the country is planning not only zero energy buildings but also zero energy cities. In the Urban Development Project, the Energy Use Plan Report is prepared and submitted by predicting the amount of energy demand at the planning stage. However, due to the activation of zero-energy buildings and the increase in the supply of new and renewable energy facilities, the energy consumption behavior of buildings in the city is changing from the previous ones. In this study, to estimate urban energy demand of Zero Energy City, building energy demand forecasts based on "Passive plans for use of energy based primary energy consumption", "Actual building energy usage data from Korea Appraisal Board" and "data from Certification of Building Energy Efficiency Rating" as well as demand forecast according to existing "Consultation about Energy Use Plan Code" were calculated and then applied to Multifunctional Administrative City 5-1 zone to compare urban total energy demand forecasts.

• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.4
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• pp.302-311
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• 2016

This paper proposes a hybrid ESS that integrates an energy storage system (ESS) with an uninterruptible power supply (UPS). The hybrid ESS has a demand management and emergency power supply function while increasing the battery utilization of the UPS, which has just been used in a power failure. In addition to the critical load, the proposed system augments the capacity of emergency generation using an additional load, which has voltage and frequency-dependent characteristics to the grid side. The control algorithm of the AC-DC converter and bidirectional DC-DC converter is proposed for demand management and emergency power supply. Furthermore, seamless and autonomous transfer methods to alleviate the transient during mode transfer are proposed. To validate the proposed control scheme, experimental results from a 5 kW prototype are provided.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.139.2-139.2
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• 2011

Compared with a traditional power system of electricity providers, distributed power systems consist of power suppliers which are small and demand-oriented. Each small power supplier tends to utilizes renewable energy sources such as solar and wind power. It is because that home renewable energy systems do not need a large scale infrastructure which is required for traditional power plants. In this work we study an economic feasibility of such a renewable energy source. We describe how renewable power generation works and what it brings in terms of economic benefits. Also, we analyze limitations by the current policy and their possible solutions.