• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.8
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• pp.1111-1115
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• 2014

With the increasing interest of a demand side management using a Smart Grid infrastructure, the demand resources and energy usage data management becomes an important factor in energy industry. In addition, with the help of Advanced Measuring Infrastructure(AMI), energy usage data becomes a Big Data System. Therefore, it becomes difficult to store and manage the demand resources big data using a traditional relational database management system. Furthermore, not many researches have been done to analyze the big energy data collected using AMI. In this paper, we are proposing a Hadoop based Big Data system to manage the demand resources energy data and we will also show how the demand side management systems can be used to improve energy efficiency.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.3
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• pp.44-50
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• 2014

This paper describes reasonable methods by considering change of outdoor temperature into Customer Baseline Load(CBL) of Demand Resources in Smart Demand Resource Market, which controls peak power demand and maintains reliability of power system. The Smart Demand Resouce Market, which KPX(Korea Power Exchange) implement, is explained and then effects for CBL calculated by considering temperature correction factor are established. Finally, four methods for calculation of CBL are proposed and those results are compared and analyzed.

• ETRI Journal
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• v.44 no.4
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• pp.624-640
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• 2022

Taxi-demand forecasting and hotspot prediction can be critical in reducing response times and designing a cost effective online taxi-booking model. Taxi demand in a region can be predicted by considering the past demand accumulated in that region over a span of time. However, other covariates-like neighborhood influence, sociodemographic parameters, and point-of-interest data-may also influence the spatiotemporal variation of demand. To study the effects of these covariates, in this paper, we propose three models that consider different covariates in order to select a set of independent variables. These models predict taxi demand in spatial units for a given temporal resolution using linear and ensemble regression. We eventually combine the characteristics (covariates) of each of these models to propose a robust forecasting framework which we call the combined covariates model (CCM). Experimental results show that the CCM performs better than the other models proposed in this paper.

• Transactions of the KSME C: Technology and Education
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• v.4 no.1
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• pp.57-62
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• 2016

The Demand Response Market is a nation-wide power and energy management program of electric power demand response operated by KPX (Korea Power eXchange). Therefore, any savings could be determined by KEPCO's AMR(Automatic Meter Reading) data. However, the customers and the service providers participating in the market could not know the real time value due to the 15 minute or even more delayed AMR data communicated. Here, a new concept of a smart box has been introduced and demonstrated to provide the real time saving values compared to the current KEPCO's AMR data approach.

• Journal of the Korea Concrete Institute
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• v.11 no.5
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• pp.89-98
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• 1999

This paper evaluates nonlinear response characteristics of precast concrete frame buildings. where plastics hinging occurs in the precast connection. Designs were developed for buildings of 5, 10 and 15 stories in hight for moderate seismic risk regions of the U. S. The responses of the buildings were analyzed using DRAIN-2DX and following Nonlinear static analysis procedure of ATC 19. The main variables of the analyses were the strength and stiffness of the connection. Also, for the analysis, the bi-linear response model, developed and inserted into the DRAIN-2DX program by Shan Shi and D. Fouch, was used. With the results of analysis, the deformation demands of the connection of precast concrete frame buildings are proposed by using equal-dissipated energy capacity. It was shown that the strength of the buildings as well as their displacement capacities decreased with the decrease of either the strength or stiffness in the connections. Therefore such changes also require reductions in the response modification factors for such buildings. However, if the precast concrete frame building has plastic hinging in the connection, and has a more ductile connection than the monolithic frame building, then no reduction in R may be necessary. The deformation demand required of the connection to achieve that condition is evaluated and a simple relation is suggested in the paper.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2220-2226
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• 2018

Electric vehicles (EVs) are significant resources for demand response (DR). Thus, it is essential for EV aggregators to quantitatively evaluate their capability for DR. In this paper, a concept of dynamic equivalent battery (DEB) is proposed as a metric for evaluating the DR performance using EVs. The DEB is the available virtual battery for DR. The capacity of DEB is determined from stochastic calculation while satisfying the charging requirements of each EV, and it varies also with time. Further, a new indicator based on the DEB and time-varying electricity prices, named as value of DEB (VoDEB), is introduced to quantify the value of DEB coupled with the electricity prices. The effectiveness of the DEB and the VoDEB as metrics for the DR performance of EVs is verified with the simulations, where the difference of charging cost reduction between direct charging and optimized bidding methods is used to express the DR performance. The simulation results show that the proposed metrics accord well with the DR performance of an EV fleet. Thus, an EV aggregator may utilize the proposed concepts of DEB and VoDEB for designing an incentive scheme to EV users, who participate in a DR program.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.60-67
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• 2004

The designer of a tall building even in moderate and low seismic regions should, in finalizing the desist consider the probable impact of the design basis earthquake on the selected structural system. In this study, seismic response analysis was conducted to evaluate the seismic performance of concentrically braced steel highrise buildings which were designed only for governing wind loading under moderate seismicity. The main purpose of this analysis was to see if the wind design would create a system whose elastic capacity clearly exceeds the probable demand as suggested by the design basis earthquake. The strength demand-to-capacity study revealed that the wind-designed steel highrise buildings with the aspect ratio of larger than five can withstand the design basis earthquake elastically by a sufficient margin due to the system over-strength resulting from the wind-serviceability criterion. The maximum story drift demand from the design basis earthquake was just 0.25% (or half the limit of Immediate Occupancy performance level in FEMA 273)

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.755-765
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• 2015

A thermostatically controlled load (TCL) can be one of the most appropriate resources for demand response (DR) in a smart grid environment. DR capability can be effectively implemented in a TCL with various intelligent control methods. However, because traditional on-off control is still a commonly used method in a TCL, it is useful to develop a method for adding DR capability to the TCL with an existing on-off controller. As a specific realization of supervisory control for implementing DR capability in the TCL, two methods are proposed - a method involving the changing of a set point and a method involving the paralleling of an identified system without delay. The proposed methods are analyzed through the simulations with an electric heater for different power consumption levels in the on-state. Considerable cost benefit can be achieved with the proposed methods when compared with the case without DR. In addition, the observations suggest that a medium power consumption level, instead of the maximum power, in the on-state should be used for consistently obtaining the cost benefit without severe temperature deviation from the specified temperature range for DR.

• ETRI Journal
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• v.35 no.4
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• pp.677-686
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• 2013

In this paper, we first introduce a general architecture of an energy management system in a home area network based on a smart grid. Then, we propose an efficient scheduling method for home power usage. The home gateway (HG) receives the demand response (DR) information indicating the real-time electricity price, which is transferred to an energy management controller (EMC). Referring to the DR, the EMC achieves an optimal power scheduling scheme, which is delivered to each electric appliance by the HG. Accordingly, all appliances in the home operate automatically in the most cost-effective way possible. In our research, to avoid the high peak-to-average ratio (PAR) of power, we combine the real-time pricing model with the inclining block rate model. By adopting this combined pricing model, our proposed power scheduling method effectively reduces both the electricity cost and the PAR, ultimately strengthening the stability of the entire electricity system.

• Journal of Satellite, Information and Communications
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• v.7 no.2
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• pp.13-17
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• 2012

In recent years, type of the car is changing. Instead of cars that use internal combustion engines, we will use mainly eco-friendly electric vehicles. However, the utilization of electric vehicles brings enormous increase of power consumption. Thus, efficient power management and intelligent power consumption is required. Demand response can be effective measures of power consumption. In this paper, we present demand response technology applications, communication method, PLC application and simulation result.