• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2165-2172
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• 2010

This paper presents the operation algorithm of microgrid on the Real Time Pricing(RTP) for building the smart grid. RTP is higher power price variability than flat rate and time of use. However it has an effect on peak clipping and peak load shifting due to the increased price on peak time power demand. When the RTP are applied to the microgrid system, the proposed algorithm is able to be effective and economic operation. The implemented system is operated for the economic operation in microgrid connected with the power system. On the other hand, when the microgrid is operated on isolation mode, it focus on the improvement of stability and the power supply reliability of the sensitive loads. The test system are implemented and calculated on various operation modes based on non-dispachable generator output and RTP data for validating the proposed operation algorithm. The calculated results are compared to the implemented results using real-time simulator. It can be confirmed that the proposed operation system are identical results to the calculated one. When the proposed operation algorithm is applied to the system, it can be show the effectiveness of the peak clipping and peak load shifting and the improvement of economic feasibility.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.11
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• pp.39-49
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• 2011

Smart Grid has two main objectives on both supply and demand aspects which are to distribute the renewable energy sources on supply side and to develop realtime price responses on demand side. Renewable energy does not consume fossil fuels, therefore it improves the eco-friendliness and saves the cost of power system operation at the same time. Demand response increases the flexibility of the power system by mitigating the fluctuation from renewable energies, and reduces the capacity investment cost by shedding the peak load to off-peak periods. Currently Smart Grid technologies mainly focus on energy monitoring and display services but it has been proved that enabling technologies can induce the higher demand responses through many pilot projects in USA. On this context, this paper provides a price responsive algorithm for HEMS (home energy management system) on the real time pricing environment. This paper identifies the demand response as a core function of HEMS and classifies the demand into 3 categories of fixed, transferable, and realtime responsive loads which are coordinated and operated for the utility maximization or cost minimization with the optimal usage combination of three kinds of demand.

• Journal of Energy Engineering
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• v.15 no.4 s.48
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• pp.229-234
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• 2006

Electric energy is too difficult to manage realtime for irregular change of load because of non-storage. In specially, operation of reserve is ancillary service to supply stably to defend large troubles in electric power system. But whole of electric power system brings to economical loss because of reserve operation. Therefore optimal reserve quantity and optimal reserve price are necessary in order to minimize loss. In this paper, we have presents optimal dispatch and reserve price consideration of opportunity cost.

• Journal of Information Technology Services
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• v.11 no.sup
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• pp.41-50
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• 2012

With the recent advances in smart grid technologies and the increasing dissemination of smart meters, the power usage of each time unit can be detected in modern smart building environments. Thus, the utility company can adopt different price of electricity at each time slot considering the peak time. Korea government also announces the smart-grid roadmap that includes a law for realtime price of electricity. In this paper, we propose an efficient power scheduling scheme for smart buildings that adopt smart meters and real-time pricing of electricity. Our scheme dynamically changes the power mode of each consumer device according to the change of power rates. Specifically, we analyze the electricity demands and prices at each time, and then perform real-time power scheduling of consumer devices based on collaboration of each device. Experimental results show that the proposed scheme reduces the electricity charge of a smart building by up to 36.4%.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.803-811
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• 2014

The moment when Electrical Vehicle (EV) starts charging or discharging is one of the most important parameters in estimating the impact of EV load on the grid. In this paper, a decision-making problem of determining the start time of charging and discharging during allowed period is proposed and studied under the uncertainty of real-time price. Prospect theory is utilized in the decision-making problem of this paper for it describes a kind of decision making behaviors under uncertainty. The case study uses the parameters of Springo SGM7001EV and adopts the historical realtime locational marginal pricing (LMP) data of PJM market for scenario reduction. Prospect values are calculated for every possible start time in the allowed charging or discharging period. By comparing the calculated prospect values, the optimal decisions are obtained accordingly and the results are compared with those based on Expected Utility Theory. Results show that with different initial State-of-Charge ($SoC_0$) and different reference points, the optimal start time of charging can be the one between 12 a.m. to 3 a.m. and optimal discharging starts at 2 p.m. or 3p.m. Moreover, the decision results of Prospect Theory may differ from that of the Expected Utility Theory with the reference points changing.