An Agent Based Fuzzy Control for Smart Home Energy Management in Smart Grid Environment

Garrab, Asma; Bouallegue, Adel; Bouallègue, Ridha

doi:10.20508/ijrer.v7i2.5475.g7035

Cited by 9 publications

(1 citation statement)

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“…In recent years, artificial intelligence techniques such as genetic algorithm (GA) are often used for energy management of renewable energy and smart grid [2][3][4][5][6][7][8][9][10][11][12][13][14]. GA is regarded as a powerful method of combinatorial optimization, and it has capability to deal with nonlinearity, multimodality and constraint conditions [15].…”

Section: Introductionmentioning

confidence: 99%

GA Based Optimization for Configuration and Operation of Emergency Generators in Medical Facility Using Renewable Energy

Tanaka

Eto

Mizuno

et al. 2018

IJRER

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In this paper, a simultaneous optimization method using GA of configuration and operation of emergency generators in medical facilities with power source of renewable energy is proposed. The simultaneous optimization of configuration and operation needs search of enormous combinations, which is generally considered to be a difficult problem. Here, PV is assumed as renewable energy, but since its output depends on the weather, fluctuation of the generated power is not small. From the viewpoint of an emergency generator, this is a factor of short-term variations in load, so there is concern that the efficiency will decline. In the proposed method, genes are divided into configuration chromosomes and operation chromosomes, and the operation chromosomes are multiplexed so that they can be switched by the time zones and the loads so as to be robust for short-term variability. The effectiveness of the proposed method is examined by a case study using amount of insolation and actual data in a hospital.

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