• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1125-1131
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• 2014

Application of residential demand response (DR) programs are currently realized up to a limited extent due to customers' difficulty in manually responding to the time-differentiated prices. As a solution, this paper proposes an automatic home load management (HLM) framework to achieve the household minimum payment as well as meet the operational constraints to provide customer's comfort. The projected HLM method controls on/off statuses of responsive appliances and the charging/discharging periods of plug-in hybrid electric vehicle (PHEV) and battery storage at home. This paper also studies the impacts of different time-varying tariffs, i.e., time of use (TOU), real time pricing (RTP), and inclining block rate (IBR), on the home load management (HLM). The study is effectuated in a smart home with electrical appliances, a PHEV, and a storage system. The simulation results are presented to demonstrate the effectiveness of the proposed HLM program. Peak of household load demand along with the customer payment costs are reported as the consequence of applying different pricings models in HLM.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.16-22
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• 2016

This paper addresses the load usage scheduling in the HEMS for residential power consumers. The HEMS would lead the residential users to change their power usage, so as to minimize the cost in response to external information such as a time-varying electricity price, the outside temperature. However, there may be a consumer's inconvenience in the change of the power usage. In order to improve this, it is required to understand the pattern of load usage according to the external information. Therefore, this paper suggests a methodology to model the load usage pattern, which classifies home appliances according to external information affecting the load usage and models the usage pattern for each appliance based on a copula function representing the correlation between variables. The modeled pattern would be reflected as a constraint condition for an optimal load usage scheduling problem in HEMS. To explain an application of the methodology, a case study is performed on an electrical water heater (EWH) and an optimal load usage scheduling for EHW is performed based on the branch-and-bound method. From the case study, it is shown that the load usage pattern can contribute to an efficient power consumption.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.741-747
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• 2008

This paper proposes a new concept of IDSP(Intelligent Digital Switchgear Panel) which can solve the problem of the safety, the reliability and the convenience to correspond to the requirement of the general electric customer or electric power company under the ubiquitous-based home automation environments. By analyzing their requirement functions, a 32-bit micro processor is adopted as main controller to support the designed functions efficiently. The DSP-based single phase power management device is utilized to collect the electric power information and the ethernet convertor to communicate through internet among the IDSPs and the remote computer system. In the proposed IDSP, the several functions are implemented such as the earth leakage level display and waveform transmission, the electric fee display, the voltage management, the load management and the load control function. Finally, the prototype of the IDSP is made experimently based on the designed results, and then the effectiveness is verified by testing its basic functions.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.555-556
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• 2007

This paper proposes a new concept's IDSFHA(Intelligent Digital Switchgear For Home Automation) which can obtain the safety, the reliability and the easy to correspond to the request of the general electric customer or electric power company under the ubiquitous-based home automation environments The IDSFHA is designed by analyzing their requirement functions, a 32-bit micro processor is adopted as main controller to support efficiently the designed functions. The single phase power IC(ADE7753) is utilized to collect the electric power information, and makes it possible to communicate as internet among the IDSFHA and their using the ethernet convertor. In the proposed IDSFHA, the several functions are implemented such as the earth leakage level display and waveform transmitting, the electric power using fee display, voltage management, load management and load control function. Finally, the prototype of the IDSFHA is made experimently based on the designed results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.8
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• pp.1025-1032
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• 2014

The effective energy management method will provide the significant advantage to the residential customers under real time pricing plan since it can reduce the electricity charge by controlling the energy consumption according to electricity rate. The earlier studies for load management mainly aim to minimize the electricity charges and peak power but put a less emphasis on the human comfort dwelling in the residence. The discomfort and displeasure from the energy management only focusing on reduction of electricity charge will make the residential customer reluctant to enroll the real time pricing plan. In this paper, therefore, we propose optimal load control strategy which aim to achieve not only minimizing the electricity charges but also maintaining human comfort by introducing "the human comfort coefficient." Using the human comfort coefficient, the energy management system can reflect the various human personality and control the loads within the range that the human comfort is maintained. Simulation results show that proposed load control strategy leads to significant reduction in the electricity charges and peak power in comparison with the conventional load management method.

• International Journal of Advanced Culture Technology
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• v.2 no.2
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• pp.11-14
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• 2014

In the smart grid, it will be possible to communicate with the consumers for the purposes of monitoring and controlling their power consumption without disturbing their business or comfort. This will bring easier administration capabilities for the utilities. On the other hand, consumers will require more advanced home automation tools which can be implemented by using advanced sensor technologies. For instance, consumers may need to adapt their consumption according to the dynamically varying electricity prices which necessitates home automation tools. This paper tries to combine neural network and nonlinear autoregressive with exogenous variable (NARX) class for next week electric load forecasting. The suitability of the proposed approach is illustrated through an application to electric load consumption data. The suggested system provides a useful and suitable tool especially for the load forecasting.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.87-106
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• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

• 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.

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2839-2844
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• 2008

A PEMFC(proton exchange membrane fuel cell) is a good candidate for residential power generation to be cope with the shortage of fossil fuel and green house gas emission. The attractive benefit of the PEMFC is to produce electric power as well as hot water for home usage. Typically, thermal management of vehicular PEMFC is to reject the heat from the PEMFC to the ambient air. Different from that, the thermal management of PEMFC for RPG is to utilize the heat of PEMFC so that the PEMFC can be operated at its optimal efficiency. In this study, dynamic thermal management system is modeled to understand the response of the thermal management system during dynamic operation. The thermal management system of PEMFC for RPGFC is composed of two cooling circuits, one for controling the fuel cell temperature and the other for heating up the water for home usage. Dynamic responses and operating strategies of the PEMFC system are investigated during load changes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.8
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• pp.55-63
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• 2017

Due to spatial problems and system size,conventional measurement methods used to acquire the information needed for existing electrical energy and management have been limited to new buildings or areas where replacement is possible. This electric load management method is problematic when applying it to energy and safety management of vulnerable areas or existing homes or offices. The problem with installing a measurement module in every branch is that the system is too large. Even if the measurement module is installed, the type of load is not recognized, and efficient management is not performed. In particular, it is very difficult to apply it to traditional markets and backward facilities in Korea. In this paper, we apply NIALM technology and arc detection technology to solve these problems and verify the feasibility of NIALM for normal arc generation. Also, based on the verification results, we propose a new smart home safety management system that can effectively manage electrical safety and that can be applied to conventional market and existing home safety management systems. The proposed system conducts a comparative performance test with an existing safety management system. In addition, it achieves 95% or more load recognition for four loads, which is impossible in 40% of the existing systems, and the arc detection function was confirmed.