Energy Consumption Optimization and User Comfort Management in Residential Buildings Using a Bat Algorithm and Fuzzy Logic
Energy management in residential buildings has grabbed the attention of many scientists for the last few years due to the fact that the residential sector consumes the highest amount of total energy produced by different energy resources. To manage the energy in residential buildings effectively, an...
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Online Access: | http://www.mdpi.com/1996-1073/11/1/161 |
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doaj-b1ab743e039e4aaa916296bfd93329c22020-11-24T22:38:57ZengMDPI AGEnergies1996-10732018-01-0111116110.3390/en11010161en11010161Energy Consumption Optimization and User Comfort Management in Residential Buildings Using a Bat Algorithm and Fuzzy LogicMuhammad Fayaz0DoHyeun Kim1Department of Computer Engineering, Jeju National University, Jeju City 63243, KoreaDepartment of Computer Engineering, Jeju National University, Jeju City 63243, KoreaEnergy management in residential buildings has grabbed the attention of many scientists for the last few years due to the fact that the residential sector consumes the highest amount of total energy produced by different energy resources. To manage the energy in residential buildings effectively, an efficient energy control system is required, capable of decreasing the total energy consumption without compromising the user-preferred environment inside the building. In the literature, many approaches have been proposed to achieve the goals of minimizing the energy consumption and maximizing the user preferred comfort by keeping different parameters under consideration, but all these methods face some problems in resolving the issue properly. The bat algorithm is one of the most recently introduced optimization approaches that has drawn the attention of researchers to apply it for solving different types of optimization problems. In this paper, the bat algorithm is applied for energy optimization in residential buildings, which is one of the most focused optimization problems in recent years. Three environmental parameters, namely temperature, illumination and air quality are bat algorithm inputs and optimized values of these parameters are the outputs. The error difference between the environmental parameters and optimized parameters are inputs of the fuzzy controllers which give energy as output which in turn change the status of the concerned actuators. It is proven from the experimental results that the proposed approach has been effectively successful in managing the whole energy consumption management system.http://www.mdpi.com/1996-1073/11/1/161bat algorithmcomfort indexenergy optimizationfuzzy logicmembership functions (MFs)residential building |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Muhammad Fayaz DoHyeun Kim |
spellingShingle |
Muhammad Fayaz DoHyeun Kim Energy Consumption Optimization and User Comfort Management in Residential Buildings Using a Bat Algorithm and Fuzzy Logic Energies bat algorithm comfort index energy optimization fuzzy logic membership functions (MFs) residential building |
author_facet |
Muhammad Fayaz DoHyeun Kim |
author_sort |
Muhammad Fayaz |
title |
Energy Consumption Optimization and User Comfort Management in Residential Buildings Using a Bat Algorithm and Fuzzy Logic |
title_short |
Energy Consumption Optimization and User Comfort Management in Residential Buildings Using a Bat Algorithm and Fuzzy Logic |
title_full |
Energy Consumption Optimization and User Comfort Management in Residential Buildings Using a Bat Algorithm and Fuzzy Logic |
title_fullStr |
Energy Consumption Optimization and User Comfort Management in Residential Buildings Using a Bat Algorithm and Fuzzy Logic |
title_full_unstemmed |
Energy Consumption Optimization and User Comfort Management in Residential Buildings Using a Bat Algorithm and Fuzzy Logic |
title_sort |
energy consumption optimization and user comfort management in residential buildings using a bat algorithm and fuzzy logic |
publisher |
MDPI AG |
series |
Energies |
issn |
1996-1073 |
publishDate |
2018-01-01 |
description |
Energy management in residential buildings has grabbed the attention of many scientists for the last few years due to the fact that the residential sector consumes the highest amount of total energy produced by different energy resources. To manage the energy in residential buildings effectively, an efficient energy control system is required, capable of decreasing the total energy consumption without compromising the user-preferred environment inside the building. In the literature, many approaches have been proposed to achieve the goals of minimizing the energy consumption and maximizing the user preferred comfort by keeping different parameters under consideration, but all these methods face some problems in resolving the issue properly. The bat algorithm is one of the most recently introduced optimization approaches that has drawn the attention of researchers to apply it for solving different types of optimization problems. In this paper, the bat algorithm is applied for energy optimization in residential buildings, which is one of the most focused optimization problems in recent years. Three environmental parameters, namely temperature, illumination and air quality are bat algorithm inputs and optimized values of these parameters are the outputs. The error difference between the environmental parameters and optimized parameters are inputs of the fuzzy controllers which give energy as output which in turn change the status of the concerned actuators. It is proven from the experimental results that the proposed approach has been effectively successful in managing the whole energy consumption management system. |
topic |
bat algorithm comfort index energy optimization fuzzy logic membership functions (MFs) residential building |
url |
http://www.mdpi.com/1996-1073/11/1/161 |
work_keys_str_mv |
AT muhammadfayaz energyconsumptionoptimizationandusercomfortmanagementinresidentialbuildingsusingabatalgorithmandfuzzylogic AT dohyeunkim energyconsumptionoptimizationandusercomfortmanagementinresidentialbuildingsusingabatalgorithmandfuzzylogic |
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1725711062326575104 |