• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.63-75
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• 2002

To improve the efficiency of the electric power generation, monthly maximum electric power consumptions for a next one year should be forecasted in advance and used as the fundamental input to the yearly electric power-generating master plan, which has a greatly influence upon relevant sub-plans successively. In this paper, we analyze the past 22-year hourly maximum electric load data available from KEPCO(Korea Electric Power Corporation) and select necessary data from the raw data for our model in order to reflect more recent trends and seasonal components, which hopefully result in a better forecasting model in terms of forecasted errors. After analyzing the selected data, we recommend to KEPCO the Winters' multiplicative model with decomposition and exponential smoothing technique among many candidate forecasting models and provide forecasts for the electric power consumptions and their 95% confidence intervals up to December of 1999. It turns out that the relative errors of our forecasts over the twelve actual load data are ranged between 0.1% and 6.6% and that the average relative error is only 3.3%. These results indicate that our model, which was accepted as the first statistical forecasting model for monthly maximum power consumption, is very suitable to KEPCO.

• Journal of Navigation and Port Research
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• v.36 no.6
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• pp.501-506
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• 2012

To serve basic data for the design of capacity and management of Distributed(or On-site) Power Generation System using renewable energies, this study measured the electric power consumption(hereafter abbreviated as EPC) of 5 families of fishing village located at island in southeastern area of Korea. The results are as following. The maximum monthly average EPC occurred in December or January. Although the total monthly EPC of H family is 2~3 times more than J family, individual monthly EPC of J family is 10~30 % more than H family. Hourly EPC pattern shows that the maximum EPC occurred between 20~24 o'clock in summer season, but it occurred between 18~24 o'clock in winter season. Compared to summer, the height of fluctuation through a day is small. And the EPC patterns of weekdays and weekend estimated as very similar.

• Journal of the Korean Solar Energy Society
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• v.26 no.2
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• pp.69-77
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• 2006

Photovoltaic is an attractive technology to remote power applications, because of its reliability, low maintenance, and zero fuel requirements. In this paper represents residential PV system based on BESS(battery energy storage system) for managing the electric power, a pattern of daily operation considering the load characteristics of the house, the generation characteristics of PV power, and utility power leveling. For apply to control algorithm, we consider the load on monthly power consumption trend and daily usage pattern. As for the control of the proposed system, to increase the conversion efficiency of the PV power, bidirectional converter is used for MPPT and SPWM inverter. An experimental system is implemented, and some experimental results are provided to demonstrate the effectiveness of the proposed system.