• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.241-246
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• 1997

본 논문에서는 사용이 편리하여 산업 발전의 원동력이 되고 있는 전기에너지의 이용합리화의 수단의 하나인 디맨드 감시/제어 장치에 대한 퍼지제어의 적용에 대해 제안한다. 이 장치는 전력사용이 많은 300㎾이상의 수용가에 있어서 피크(Peak)시 전력이 계약전력을 초과하지 않도록 감시/제어하여 에너지 사용의 합리화 및 전기요금 절감효과를 도모할수 있는 에너지 기기의 개발에 기여할 수 있다. 본 연구에서는 효율적인 디맨드 감시/제어를 위해 지수평활법을 이용한 부하예측과 퍼지제어기를 제안하고자 한다.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.8 no.4
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• pp.1-7
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• 2012

In this study, computer simulation for demand control strategies to save the electric energy and power price in the building central cooling system is done. The demand control and outdoor reset control algorithms are applied by consideration the electric energy and power price according to the energy consumption characteristics. The suggested control methods show better responses in the power price and energy consumption in comparison with the conventional one.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.9
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• pp.4610-4615
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• 2013

In this study, optimal operation strategies to save the electric energy and power price in the building central cooling system is researched by experiments. The optimal strategies of demand response control and outdoor temperature reset control algorithms are applied by consideration the electric energy and power price according to the energy consumption characteristics. The suggested optimal control method shows better responses in the power price and energy consumption in comparison with the conventional one and saves energy consumption by 9.5% and electronic price by 15.7%, respectively.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.9
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• pp.417-424
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• 2002

This paper presents an industrial peak load management system for the peak demand control. Kohonen neural network and wavelet transform based techniques are adopted for industrial peak load forecasting that will be used as input data of the peak demand control. Firstly, one year of historical load data of a steel company were sorted and clustered into several groups using Kohonen neural network and then wavelet transforms are applied with Biorthogonal 1.3 mother wavelet in order to forecast the peak load of one minute ahead. In addition, for the peak demand control, composite fuzzy model is proposed and implemented in this work. The results are compared with those of conventional model, fuzzy model and composite model, respectively. The outcome of the study clearly indicates that the composite fuzzy model approach can be used as an attractive and effective means of the peak demand control.