Multi-Objective Air-Conditioning Control Considering Fuzzy Parameters Using Immune Clonal Selection Programming

Smart home integrates disaster protection, medical care, entertainment and energy-saving systems, making the living environment more secure and comfortable. This paper investigates the demand response achieved by the "smart energy management system" in a smart home environment, and aims to...

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Bibliographic Details
Published in:IEEE transactions on smart grid 2012-12, Vol.3 (4), p.1603-1610
Main Authors: Hong, Ying-Yi, Lin, Jie-Kai, Wu, Ching-Ping, Chuang, Chi-Cheng
Format: Article
Language:English
Subjects:
Atmospheric modeling
Cloning
Day-ahead pricing
demand response
Electricity
fuzzy set theory
immune programming
Programming
smart home
Smart homes
Temperature
Temperature control
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Summary:Smart home integrates disaster protection, medical care, entertainment and energy-saving systems, making the living environment more secure and comfortable. This paper investigates the demand response achieved by the "smart energy management system" in a smart home environment, and aims to obtain the optimal temperature scheduling for air-conditioning according to the day-ahead electricity price and outdoor temperature forecasts. Because the retail electricity price and temperature are predicted 24 h in advance and there exists uncertainty, the predicted retail electricity prices and temperatures are modeled by the fuzzy set. The immune clonal selection programming is employed to determine the day-ahead 24-h temperature schedule for air-conditioning. The electricity expense is hence minimized while comfort is still retained. The simulation result shows the applicability of the proposed method.
ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2012.2210059