• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권6호
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• pp.2398-2421
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• 2020

In third world countries like Pakistan, the production of electricity has been quickly reduced in past years due to rely on the fossil fuel. According to a survey conducted in 2017, the overall electrical energy capacity was 22,797MW, since the electrical grids have gone too old, therefore the efficiency of grids, goes down to nearly 17000MW. Significant addition of fossil fuel, hydro and nuclear is 64.2%, 29% and 5.8% respectively in the total electricity production in Pakistan. In 2018, the demand crossed 20,223MW, compared to peak generation of 15,400 to 15,700MW as by the Ministry of Water and Power. Country faces a deficit of almost 4000MW to 5000MW for the duration of 2019 hot summer term. Focus on one aspect considering Demand Side Management (DSM) cannot oversea the reduction of gap between power demand and customer supply, which eventually leads to the issue of load shedding. Hence, a scheduling scheme is proposed in this paper called RPSMDSM that is based on selection of those appliances that need to be only Turned-On, on priority during peak hours consuming minimum energy. The Home Energy Management (HEM) system is integrated between consumer and utility and bidirectional flow is presented in the scheme. During peak hours of electricity, the RPSMDSM is capable to persuade less power consumption and accomplish productivity in load management. Simulations show that RPSMDSM scheme helps in scheduling the electricity loads from peak price to off-peak price hours. As a result, minimization in electricity cost as well as (Peak-to-Average Ratio) PAR are accomplished with sensible waiting time.

• Journal of Electrical Engineering and Technology
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• 제9권3호
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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.

• KIEE International Transactions on Power Engineering
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• 제5A권4호
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• pp.403-411
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• 2005

At present, the Cournot model is one of the most commonly used theories to analyze the gaming situation in an oligopoly type market. However, several problems exist in the successful application of this model to the electricity market. The representative one is obtaining the inverse demand curve able to be induced from the relationship between market price and demand response. In the Cournot model, each player offers their generation quantity to obtain maximum profit, which is accomplished by reducing their quantity compared with available total capacity. As stated above, to obtain the probable Cournot equilibrium to reflect the real market situation, we have to induce the correct demand function first of all. Usually the correlation between price and demand appears over the long-term through statistical data analysis (for example, regression analysis) or by investigating consumer utility functions of several consumer groups classified as residential, industrial, and commercial. However, the elasticity has a tendency to change continuously according to the total market demand size or the level of market price. Therefore it should be updated as the trading period passes by. In this paper we propose a method for inducing and updating this price elasticity of demand function for more realistic market equilibrium.

• Journal of Communications and Networks
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• 제14권6호
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• pp.672-681
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• 2012

A potential breakthrough of the electrification of the vehicle fleet will incur a steep rise in the load on the electrical power grid. To avoid huge grid investments, coordinated charging of those vehicles is a must. In this paper, we assess algorithms to schedule charging of plug-in (hybrid) electric vehicles as to minimize the additional peak load they might cause. We first introduce two approaches, one based on a classical optimization approach using quadratic programming, and a second one, market based coordination, which is a multi-agent system that uses bidding on a virtual market to reach an equilibrium price that matches demand and supply. We benchmark these two methods against each other, as well as to a baseline scenario of uncontrolled charging. Our simulation results covering a residential area with 63 households show that controlled charging reduces peak load, load variability, and deviations from the nominal grid voltage.

• 전기학회논문지
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• 제63권5호
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• pp.644-651
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• 2014

The renewable energy system and the real-time pricing can provide the significant economic advantage for end-user of residential house. However, according to recent studies, high initial cost of renewable energy system such as photovoltaic (PV) system and lack of suitable load control methods adjusting electric power consumption in response to time-varying price are regarded as the major obstruction for introduction of renewable energy system and real-time pricing in residental household. In this paper, we propose automated optimal load control strategy which aim to achieve not only minimizing the electricity cost but also the increase in the utilization rates of PV generation power of residential PV house in real-time pricing environment. Simulation results show that our proposed optimal load control strategy leads to significant reduction in the electricity costs and increase in the utilization rates of power generated by PV system in comparison with the conventional PV house. Therefore, the proposed optimal load control strategy can provide more economic benefit to end-user.

• 한국HCI학회논문지
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• 제12권4호
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• pp.65-73
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• 2017

전력 수요가 증가하고 재생 가능 에너지에 대한 관심이 증폭됨에 따라, 수요를 억제하여 필요한 공급량을 줄일 수 있는 '수요반응' 프로그램에 대한 관심이 증가하고 있다. 본 연구는 가정에 스마트미터를 구비한 국내 사용자들을 대상으로 진행된 에너지 수요반응 실증사업에 대한 실증분석으로, 사전심층 인터뷰, 설문 및 기술수용모델 분석을 통하여 가정 전력 사용자들이 수요반응 프로그램을 받아들이는 데 중요한 요인들을 살펴본다. 수요반응의 목표는 피크시간대에 미션이 발령되면 전력사용량을 평소보다 줄이는 것이며, 실험대상은 스마트미터 구입 경로와 에너지를 절감했을 때 보상받는 방식에 따라 2개의 상이한 집단으로 구성되었다. 집단 A는 주로 IoT플랫폼 서비스에 가입하는 과정에서 마케터와의 대화를 통해 전체 서비스 중 하나인 스마트미터 서비스에 함께 가입하는 경로로 수요반응 프로그램에 유입되었고, 보상으로는 통신비 할인을 받았다. 반면 집단 B는 스마트미터를 자발적으로 구매하거나 에너지 자립 마을 지역주민으로서 지자체 지원을 통해 스마트미터를 지원 받아 프로그램에 유입되었고, 미션 성공에 대한 보상은 사회적 기부를 통해 이루어졌다. 분석 결과 집단 A는 인지된 용이성과 인지된 유용성 외에 인지된 유희성도 포함된 확장된 기술수용모델이 적합함을 알 수 있었고,집단 B는 모델의 적합도가 떨어지기는 하지만 집단 A에 비해 인지된 유용성에 대한 중요도가 높음을 확인할 수 있었다. 이와 같은 결과는 집단 특성에 따른 프로그램 설계방향을 제시하여 향후 수요반응 프로그램을 효과적으로 운영하는 데에 도움을 줄 것으로 보인다.

• 설비공학논문집
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• 제12권2호
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• pp.200-208
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• 2000

The use of air-conditioning systems for cooling in residential buildings has negative effects on the environment and causes the problem in peak electric power demand in summer. The objective of this study is to demonstrate the potential of radiant cooling systems using ondol as an alternative cooling system in our residential buildings. Computer simulation has been performed for the floor radiant cooling system performance. The results of this study show that. 1) This system can control the temperature of Ondol room within comfort limits. 2) This system can be operated with a little risk of condensation but the control of latent heat will make this system more potential.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1481-1483
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• 1999

Power distribution system planning for maximum customer satisfaction and system efficiency requires accurate forecast of future demand in service area. Spatial load forecasting method provides a more accurate estimation of both magnitudes and location of future electrical load. This method considers the causes of load growth due to addition of customers and per capita consumption among customers by land use (residential, commercial and industrial). So the land-use study and it's preference for small area is quite important. This paper proposes land-use preference estimation method based on fuzzy logic. Fuzzy logic is applied to computing preference scores for each land-use and by these scores the customer growth is allocated in service area. An simulation example is used to illustrate the proposed method.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2007년도 하계학술대회 논문집
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• pp.64-66
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• 2007

Photovoltaic power systems convert sunlight directly into electricity. A residential PV power system enables a homeowner to generate some or all of their daily electrical energy demand on their own roof, exchanging daytime excess power for future energy needs In this paper, It was suggested that new design method for PV system installation for the purpose of system efficiency improvement. and according to loss parameter compensation method, designed for the PV system and investigated through the simulation practically.

• 한국수소및신에너지학회논문집
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• 제20권2호
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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.