A Novel Meta-heuristic Technique for Energy Optimization in Smart Grid

Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 8)


The increase in the energy consumption causes a serious crisis, especially during on-peak hours when the demand of energy consumption is high. Consequently, the peak to average ratio and electricity cost will be increased. This issue can be overcome by integrating Demand side management (DSM) with traditional Smart grid (SG), so that electricity utilization can be minimized during on-peak hours by efficiently distributing them into off-peak hours. In this paper, Crow search algorithm (CSA) is proposed to schedule the appliances for DSM and the performance of Home energy management system (HEMS) is assessed by two meta-heuristic techniques; Enhanced differential evolution and CSA. The reduction in cost and peak to average ratio along with increase in user comfort is mainly focused in this paper. Moreover, the electricity cost is based on real time pricing scheme. The main objective is to provide a comparative analysis of the aforementioned techniques for energy optimization using simulations in HEMS. The simulations results show that our proposed technique outperformed as compared to the existing meta-heuristic technique.


Meta-heuristic Techniques Home Energy Management System (HEMS) Crow Search Algorithm (CSA) Electricity Costs User Comfort (UC) 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.COMSATS Institute of Information TechnologyIslamabadPakistan
  2. 2.University Institute of Information TechnologyPMAS - Arid Agriculture UniversityRawalpindiPakistan

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