An Evolutionary Multiobjective Optimization Approach for HEV Energy Management System

2015 ◽  
pp. 345-354
Author(s):  
Alberto Pajares Ferrando ◽  
Xavier Blasco Ferragud ◽  
Gilberto Reynoso-Meza ◽  
Juan Manuel Herrero Dura
Keyword(s):  
Multiobjective Optimization ◽  
Energy Management ◽  
Management System ◽  
Energy Management System ◽  
Optimization Approach ◽  
Evolutionary Multiobjective Optimization

scholarly journals A Novel Multiobjective Optimization Algorithm for Home Energy Management System in Smart Grid

2015 ◽  
Vol 2015 ◽  
pp. 1-19 ◽  
Author(s):  
Yanyu Zhang ◽  
Peng Zeng ◽  
Shuhui Li ◽  
Chuanzhi Zang ◽  
Hepeng Li
Keyword(s):  
Multiobjective Optimization ◽  
Smart Grid ◽  
Energy Management ◽  
Optimization Algorithm ◽  
Management System ◽  
Comfort Level ◽  
Energy Management System ◽  
Electricity Cost ◽  
Home Energy Management ◽  
Home Energy Management System

Demand response (DR) is an effective method to lower peak-to-average ratio of demand, facilitate the integration of renewable resources (e.g., wind and solar) and plug-in hybrid electric vehicles, and strengthen the reliability of power system. In smart grid, implementing DR through home energy management system (HEMS) in residential sector has a great significance. However, an algorithm that only optimally controls parts of HEMS rather than the overall system cannot obtain the best results. In addition, single objective optimization algorithm that minimizes electricity cost cannot quantify user’s comfort level and cannot take a tradeoff between electricity cost and comfort level conveniently. To tackle these problems, this paper proposes a framework of HEMS that consists of grid, load, renewable resource (i.e., solar resource), and battery. In this framework, a user has the ability to sell electricity to utility grid for revenue. Different comfort level indicators are proposed for different home appliances according to their characteristics and user preferences. Based on these comfort level indicators, this paper proposes a multiobjective optimization algorithm for HEMS that minimizes electricity cost and maximizes user’s comfort level simultaneously. Simulation results indicate that the algorithm can reduce user’s electricity cost significantly, ensure user’s comfort level, and take a tradeoff between the cost and comfort level conveniently.

Home Energy Management System

2012 ◽  
Vol 132 (10) ◽  
pp. 695-697 ◽  
Author(s):  
Hideki HAYASHI ◽  
Yukitoki TSUKAMOTO ◽  
Shouji MOCHIZUKI
Keyword(s):  
Energy Management ◽  
Management System ◽  
Energy Management System ◽  
Home Energy Management ◽  
Home Energy Management System

Buildings Energy Management System

2012 ◽  
Vol 132 (10) ◽  
pp. 692-694 ◽  
Author(s):  
Yoshihiro OGITA ◽  
Yutaka IINO ◽  
Hideki HAYASHI
Keyword(s):  
Energy Management ◽  
Management System ◽  
Energy Management System
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