• Environmental and Resource Economics Review
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• v.31 no.2
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• pp.141-163
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• 2022

This paper empirically analyzes the effect of renewable electricity generation on the System Marginal Price (SMP) in Korea. Using an ARX-GARCHX model with hourly data from 2016 to 2020, we evaluate SMP determinants and merit order effects. As a result, we find that solar and wind power, as well as gas price and total load, play a critical role in the SMP. In particular, solar power reduces the SMP level but raises volatility during peak and off-peak periods. This result implies that SMP may fall as renewable electricity generation increases, leading to a decrease in the profitability of existing power plants and investment in renewables. On the other hand, even if the subsidy of renewable energy increases the burden on the SMP, it can be offset by the merit order effect, which lowers the SMP.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.19-22
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• 1993

Demand side management (DSM) is the planning and implementation of those utility designed to influence customer use of electricity in ways that will produce desired changes in the utility's load shape. It is conspicuous that the peak load control of DSM is efficiently adopted. In this paper, the package type air conditioner(A/C) mounted radio controlled switch. During the summer of 1990 KEPCO conducted tests in Seoul areas to determine the economic feasibility of interrupting A/C units for short periods of time during peak load periods. These tests were performed between July 30 and September 20 and were limited to the hours of between 1 and 6 p.m. These tests indicated that each A/C contributes approximately 4.5kW to the system peak and can be switched off 10 minutes out of each 1/2 hour without causing the customer any discomfort. Switching each A/C off for 10 minutes out of each 1/2 hour results in a peak load demand reduction of one kW per unit.

• Journal of IKEEE
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• v.22 no.2
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• pp.324-329
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• 2018

As the environment of power systems changes, the demand and necessity for new electrical energy market are increasing. Especially, efforts to increase the efficiency of electric energy use by using demand response programs are being studied constantly in advanced countries and it is operated as a real market. This paper presents a study on the baseline load estimation required in the new power market, such as demand response, P2P electricity trading etc. The proposed method estimates the baeline load through analysis of the load pattern and verifies the effectiveness of the proposed method using actual data.

• KSBB Journal
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• v.29 no.4
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• pp.225-231
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• 2014

A microbial fuel cell (MFC) and bioelectrochemical systems are novel bioprocesses which employ exoelectrogenic biofilm on electrode as a biocatalyst for electricity generation and various useful chemical production. Previous reports show that electrogenic biofilms of MFCs are time varying systems and dynamically interactive with the electrically conductive media (carbon paper as terminal electron acceptor). It has been reported that maximum power point tracking (MPPT) method can automatically control load by algorithm so that increase power generation and columbic efficiency. In this study, we developed logic based control strategy for external load resistance by using $LabVIEW^{TM}$ which increases the power production with using flat-plate MFCs and MPPT circuit board. The flat-plate MFCs inoculated with anaerobic digester sludge were stabilized with fixed external resistance from $1000{\Omega}$ to $100{\Omega}$. Automatic load control with MPPT started load from $52{\Omega}$ during 120 hours of operation. MPPT control strategy increased approximately 2.7 times of power production and power density (1.95 mW and $13.02mW/m^3$) compared to the initial values before application of MPPT (0.72 mW and $4.79mW/m^3$).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.8
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• pp.1137-1144
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• 2015

Accurate and robust load forecasting model is very important in power system operation. In case of short-term electric load forecasting, its result is offered as an standard to decide a price of electricity and also can be used shaving peak. For this reason, various models have been developed to improve forecasting accuracy. In order to achieve accurate forecasting result for summer season, this paper proposes a forecasting model using corrected effective temperature based on Heat Index and CDH data as inputs. To do so, we establish polynomial that expressing relationship among CDH, load, temperature. After that, we estimate parameters that is multiplied to each of the terms using PSO algorithm. The forecasting results are compared to Holt-Winters and Artificial Neural Network. Proposing method shows more accurate by 1.018%, 0.269%, 0.132% than comparison groups, respectively.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.6
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• pp.251-258
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• 2023

It is necessary to predict peak load accurately in order to supply electric power and operate the power system stably. Especially, it is more important to predict peak load accurately in winter and summer because peak load is higher than other seasons. If peak load is predicted to be higher than actual peak load, the start-up costs of power plants would increase. It causes economic loss to the company. On the other hand, if the peak load is predicted to be lower than the actual peak load, blackout may occur due to a lack of power plants capable of generating electricity. Economic losses and blackouts can be prevented by minimizing the prediction error of the peak load. In this paper, the latest deep learning model such as TCN is used to minimize the prediction error of peak load. Even if the same deep learning model is used, there is a difference in performance depending on the hyper-parameters. So, I propose methods for optimizing hyper-parameters of TCN for predicting the peak load. Data from 2006 to 2021 were input into the model and trained, and prediction error was tested using data in 2022. It was confirmed that the performance of the deep learning model optimized by the methods proposed in this study is superior to other deep learning models.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.633-642
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• 2021

Growing demand for electricity, when combined with the need to limit carbon emissions, drives a huge increase in renewable energy industry. In the electric power system, electricity supply always needs to be balanced with electricity demand and network losses to maintain safe, dependable, and stable system operation. There are three broad challenges when it comes to a power system with a high penetration of renewable energy: transient stability, small signal stability, and frequency stability. Transient stability analyze the system response to disturbances such as the loss of generation, line-switching operations, faults, and sudden load changes in the first several seconds following the disturbance. Small signal stability refers to the system's ability to maintain synchronization between generators and steady voltages when it is subjected to small perturbations such as incremental changes in system load. Frequency stability refers to the ability of a power system to maintain steady frequency following a severe system upset resulting in significant imbalance between generation and load. In this paper, we discusses these stability using system simulation by renewable energy deployment plan, and also analyses the influence of the renewable energy sources to the grid stability.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.5
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• pp.376-383
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• 2022

The improved performance of computer parts, such as graphic card, CPU, and main board, has led to the need for power supplies with a high power output. The dynamic load profile rapidly changes the usage of power consumption depending on load operations, such as PC power and air conditioner. Under dynamic load profile conditions, power consumption can be classified into maximum, normal, and standby power. Several problems arise in the case of maximum power. Peak power is generated at the system power source in the maximum-power situation. Frequent generation of peak power can cause high-frequency problems and reduce the life of high-pressure parts (especially high-pressure capacitors). For example, when a plurality of PCs are used, system overload occurs due to peak power generation and causes problems, such as power failure and increase in electricity bills due to exceeded contract power. To solve this problem, a system peak power limit/compensation power circuit is proposed for a power supply under dynamic load profile conditions. The proposed circuit detects the system current to determine the power situation of the load. When the system current is higher than the set level, the circuit recognizes that the system current generates peak power and compensates for the load power through a converter using a super capacitor as the power source. Thus, the peak power of loads with a dynamic load profile is limited and compensated for, and problems, such as high-frequency issues, are solved. In addition, the life of high-pressure parts is increased.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.3
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• pp.536-542
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• 2010

This paper presents an unique approach to scheme a demand response (DR) program in the electricity market from a customer-oriented perspective, which is based on the analytic hierarchy process (AHP). The proposed program has the objective to maintain the system reliability at the emergency period, and it is designed as an incentive-based program (IBP) considering Korea power systems with the cost-based generation pool (CBP). The DR program using AHP could represent the mutual importance degrees of load curtailment criteria from the viewpoint of different load-holders, thus customers' participation in this program is determined by the incentive payments corresponding the specific load curtailment conditions. A test system for the case study is used to demonstrate the usefulness and applicability of the proposed approach, and the load profiles with the proposed DR program and the required incentive payments are obtained. The results show not only the enhancement of system reliability but also the economic benefit within Pareto-improvement.

• 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.