• The Journal of the Korea institute of electronic communication sciences
• /
• v.11 no.1
• /
• pp.53-58
• /
• 2016

Because a progressive tax of home electricity rates is charged and a continuous rise of industrial electricity rates is expected in order to solve the global warming, the high oil prices and the serious power shortage problem, the efforts to apply the energy storage systems which can significantly improve the energy usage efficiency to the smart grid are trying newly. In this study, characteristics of the secondary battery which can be used as energy storage devices, the structure and operation principle of a lithium-ion battery, and the concept of energy storage systems are research and analyzed. In addition, in this paper, the base technologies which are required to apply to the energy storage system to electric power system are established by studying about installation location and application methodology of energy storage system to electric power system.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.2
• /
• pp.291-297
• /
• 2010

A system called demand response programs (DRP) is being introduced among various countries owing to the lack of new generation capacity and the higher fuel generation cost. It is a program which provides for the end-users to select their consumption of electricity by recognizing the value of their consumption in real time. That is, Demand Response can be defined as the changes in electric usage by end-use customers from their normal consumption patterns in response to changes in the price of electricity or other signals. It is expected that the effects of DRP are preventing price spike, improving supply reliability and social welfare and increasing option of customers. Considering the customer's thermal comfort zone, this paper determines the most profitable combination of optimal incentives and amounts of load reduction for a retailer to maximize profits according to predicted outdoor temperatures while implementing DRP.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.7
• /
• pp.1339-1346
• /
• 2011

This paper is developed to demand management scenario of energy consumption efficiency improvement, electricity generation efficiency improvement, network efficiency improvement, change of distribution ratio, movement of energy source, change of heating system, put of CHP to quantitatively assess to impact on energy use of demand management at the national level. This scenario can be applied Energy System Management model was developed based on Energy Balance Flow. In addition, effect analysis through built demand management scenario was quantitatively evaluated integrated demand management effectiveness of energy cost saving, CO2 emission reduction and energy savings of national level by calculating to primary energy source usage change in terms of integration demand management effect more often than not a single energy source separated electricity, heat and gas.

• Smart Media Journal
• /
• v.8 no.4
• /
• pp.72-79
• /
• 2019

The automated demand response (DR) program encourages consumers to participate in grid operation by reducing power consumption or deferring electricity usage at peak time automatically. However, successful deployment of the automated DR program sphere needs careful assessment of appliances load profile (ALP). To this end, the recent method estimates frequency, consistency, and peak time consumption parameters of the daily ALP to compute their potential score to be involved in the DR event. Nonetheless, as the daily ALP is subject to varying with respect to the DR time ALP, the existing method could lead to an inappropriate estimation; in such a case, inappropriate appliances would be selected at the automated DR operation that effected a consumer comfort level. To address this challenge, we propose a more proper method, in which all the three parameters are calculated using ALP that overlaps with DR time, not the total daily profile. Furthermore, evaluation of our method using two public residential electricity consumption data sets, i.e., REDD and REFIT, shows that our energy management systems (EMS) could properly match a DR target. A more optimal selection of appliances for the DR event achieves a power consumption decreasing target with minimum comfort level reduction. We believe that our approach could prevent the loss of both utility and consumers. It helps the successful automated DR deployment by maintaining the consumers' willingness to participate in the program.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.3
• /
• pp.1112-1118
• /
• 2014

In island and backcountry areas, electrical power is usually supplied by diesel generators. It is difficult for small scale diesel generators to have an economy of scale owing to the usage of fossil fuels to produce electricity. Also, there is a problem of carbon dioxide emissions that brings some environmental pollution to the entire region of the area. For solving those, this paper proposes a design method of autonomous micro-grid to minimize the fossil fuels of diesel generator, which is composed of diesel generator, wind turbine, battery energy storage system and photovoltaic generation system. The proposed method was verified through computer simulation and micro-grid operation system.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.29 no.3
• /
• pp.685-692
• /
• 2019

Smart grid enables efficient power management by allowing real-time awareness of electricity flows through two-way communication. Despite its various advantages, threats to user privacy caused by frequent meter reading hinder prosperous deployment of smart grid. In this paper, we propose a privacy-preserving aggregation method exploiting fully homomorphic encryption (FHE). Specifically, it achieves privacy-preserving fine-grained aggregation of electricity usage for smart grid customers in multiple electrical source environments, while further enhancing efficiency through SIMD-style operations simultaneously. Analysis of our scheme demonstrates the suitability in next-generation smart grid environment where the customers select and use a variety of power sources and systematic metering and control are enabled.

• Journal of Hydrogen and New Energy
• /
• v.30 no.3
• /
• pp.276-281
• /
• 2019

The process of separating oxygen and nitrogen from the air is mainly performed by electric liquefaction, which consumes a lot of electricity, resulting in higher operating costs. On the other hand, when used for cold energy of LNG, electric power can be reduced compared to the electric Linde cycle. Currently, LNG cold energy is used in the cold refrigeration warehouse, separation of air-liquefaction, and LNG cold energy generation in Japan. In this study, the system using LNG cold energy and the Linde cycle process system were simulated by PRO/II simulators, respectively, to cool the elevated air temperature from the compressor to about $-183^{\circ}C$ in the air liquefaction separation process. The required amount of electricity was compared with the latent heat utilization fraction of LNG, the LNG supply pressure, and the LNG cold energy usage. At the air flow rate of $17,600m^3/h$, the power source unit of the Linde cycle system was $0.77kWh/m^3$, compared with $0.3kWh/m^3$.

• Journal of the Korean Society of Industry Convergence
• /
• v.26 no.4_2
• /
• pp.715-724
• /
• 2023

Solar energy forecasting is essential for (1) power system planning, management, and operation, requiring accurate predictions. It is crucial for (2) ensuring a continuous and sustainable power supply to customers and (3) optimizing the operation and control of renewable energy systems and the electricity market. Recently, research has been focusing on developing solar energy forecasting models that can provide daily plans for power usage and production and be verified in the electricity market. In these prediction models, various data, including solar energy generation and climate data, are chosen to be utilized in the forecasting process. The most commonly used climate data (such as temperature, relative humidity, precipitation, solar radiation, and wind speed) significantly influence the fluctuations in solar energy generation based on weather conditions. Therefore, this paper proposes a hybrid forecasting model by combining the strengths of the Prophet model and the GRU model, which exhibits excellent predictive performance. The forecasting periods for solar energy generation are tested in short-term (2 days, 7 days) and medium-term (15 days, 30 days) scenarios. The experimental results demonstrate that the proposed approach outperforms the conventional Prophet model by more than twice in terms of Root Mean Square Error (RMSE) and surpasses the modified GRU model by more than 1.5 times, showcasing superior performance.

• Journal of Korean Society of Water and Wastewater
• /
• v.38 no.1
• /
• pp.29-38
• /
• 2024

Wastewater management is increasingly emphasizing economic and environmental sustainability. Traditional methods in sewage treatment plants have significant implications for the environment and the economy due to power and chemical consumption, and sludge generation. To address these challenges, a study was conducted to develop the Intermittent Cycle Extended Aeration System (ICEAS). This approach was implemented as the primary technique in a full-scale wastewater treatment facility, utilizing key operational factors within the standard Sequencing Batch Reactor (SBR) process. The optimal operational approach, identified in this study, was put into practice at the research facility from January 2020 to December 2022. By implementing management strategies within the biological reactor, it was shown that maintaining and reducing chemical quantities, sludge generation, power consumption, and related costs could yield economic benefits. Moreover, adapting operations to influent characteristics and seasonal conditions allowed for efficient blower operation, reducing unnecessary electricity consumption and ensuring proper dissolved oxygen levels. Despite annual increases in influent flow rate and concentration, this study demonstrated the ability to maintain and reduce sludge production, electricity consumption, and chemical usage. Additionally, systematic responses to emergencies and abnormal situations significantly contributed to economic, technical, and environmental benefits.

• The Journal of Society for e-Business Studies
• /
• v.17 no.2
• /
• pp.105-114
• /
• 2012

Recently, global warming, energy shortage, and environmental disruption have been serious problems in every nation. It became more and more important to reduce the emission of CO2 and to use of energy efficiently. Smart grid was also introduced using the rapidly developing information technology. It deployed the mutual communication concept between customers and the suppliers in the electricity supply. There were increasing demands to adopt the smart meter and to present incentive for efficient energy usage in many developed countries. The objective of this research was to develop the optimal real time pricing model which maximized the profit of the power retailer and reduced the usage of energy. The simulation study was given to show the usefulness of the model. Simulation considered the customer demand response rate and price elasticity rate. The price elasticity rate was compared in the condition of fixed value according to time and variable value according to the customers. The optimal price model could maximize the profit of the power retailer and reduce the energy usage of the consumers.