Home Energy Management Based on Harmony Search Algorithm and Crow Search Algorithm

In this work, we evaluated the performance of home energy management system (HEMS) using two meta-heuristic optimization algorithms: harmony search algorithm (HSA) and crow search algorithms (CSA). For electricity bill calculation we use real time pricing (RTP) signals. Our main objectives are optimization of energy consumption, electricity cost minimization and peak to average ratio (PAR) reduction. Our results depict that CSA performs better than HSA in term of cost and HSA perform better than CSA in term of PAR reduction and user comfort (UC) maximization. Results also verify that there will always be trade-off between electricity cost and waiting time.

[1]  Hamza Abunima,et al.  An intelligent system architecture in home energy management systems (HEMS) for efficient demand response in smart grid , 2017 .

[2]  Nadeem Javaid,et al.  Exploiting heuristic algorithms to efficiently utilize energy management controllers with renewable energy sources , 2016 .

[3]  Zhong Fan,et al.  An integer linear programming based optimization for home demand-side management in smart grid , 2012, 2012 IEEE PES Innovative Smart Grid Technologies (ISGT).

[4]  Shahram Jadid,et al.  Optimal residential appliance scheduling under dynamic pricing scheme via HEMDAS , 2015 .

[5]  Kyung-Bin Song,et al.  An Optimal Power Scheduling Method for Demand Response in Home Energy Management System , 2013, IEEE Transactions on Smart Grid.

[6]  Vincent W. S. Wong,et al.  Load Scheduling and Power Trading in Systems With High Penetration of Renewable Energy Resources , 2016, IEEE Transactions on Smart Grid.

[7]  Jacques Palicot,et al.  Application of Hierarchical and Distributed Cognitive Architecture Management for the Smart Grid , 2016, Ad Hoc Networks.

[8]  Alireza Askarzadeh,et al.  A novel metaheuristic method for solving constrained engineering optimization problems: Crow search algorithm , 2016 .

[9]  Zhong Fan,et al.  An integer linear programming and game theory based optimization for demand-side management in smart grid , 2011, 2011 IEEE GLOBECOM Workshops (GC Wkshps).

[10]  Nadeem Javaid,et al.  A Hybrid Genetic Wind Driven Heuristic Optimization Algorithm for Demand Side Management in Smart Grid , 2017 .

[11]  Lingyang Song,et al.  Residential Load Scheduling in Smart Grid: A Cost Efficiency Perspective , 2016, IEEE Transactions on Smart Grid.

[12]  Sunil Kumar,et al.  An Intelligent Home Energy Management System to Improve Demand Response , 2013, IEEE Transactions on Smart Grid.

[13]  Nadeem Javaid,et al.  A Meta-Heuristic Home Energy Management System , 2017, 2017 31st International Conference on Advanced Information Networking and Applications Workshops (WAINA).

[14]  Xinping Guan,et al.  Residential power scheduling for demand response in smart grid , 2016 .

[15]  Yi-Ping Phoebe Chen,et al.  True real time pricing and combined power scheduling of electric appliances in residential energy management system , 2016 .