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Appl. Sci. 2014, 4(3), 366-379; doi:10.3390/app4030366

Optimizing Re-planning Operation for Smart House Applying Solar Radiation Forecasting

1
Faculty of Engineering, University of the Ryukyus, 1 Senbaru Nishihara-cho Nakagami, Okinawa 903-0213, Japan
2
Department of Electrical Engineering and Computer Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan
3
Department of Electrical and Computer Engineering, University of Texas at El Paso, 500 West University Avenue, El Paso, TX 79968, USA
4
School of Electrical and Computer Engineering, Sungkyunkwan University, Suwon City 440-746, Korea
*
Author to whom correspondence should be addressed.
Received: 31 January 2014 / Revised: 3 June 2014 / Accepted: 4 August 2014 / Published: 22 August 2014
(This article belongs to the Special Issue Photovoltaic Generation)
View Full-Text   |   Download PDF [457 KB, uploaded 22 August 2014]   |  

Abstract

This paper proposes the re-planning operation method using Tabu Search for direct current (DC) smart house with photovoltaic (PV), solar collector (SC), battery and heat pump system. The proposed method is based on solar radiation forecasting using reported weather data, Fuzzy theory and Recurrent Neural Network. Additionally, the re-planning operation method is proposed with consideration of solar radiation forecast error, battery and inverter losses. In this paper, it is assumed that the installation location for DC smart house is Okinawa, which is located in Southwest Japan. The validity of proposed method is confirmed by comparing the simulation results. View Full-Text
Keywords: DC smart house; forecast error; re-planning operation; photovoltaic; solar collector DC smart house; forecast error; re-planning operation; photovoltaic; solar collector
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Yona, A.; Senjyu, T.; Funabashi, T.; Mandal, P.; Kim, C.-H. Optimizing Re-planning Operation for Smart House Applying Solar Radiation Forecasting. Appl. Sci. 2014, 4, 366-379.

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