Biogeography Based Optimization for Home Energy Management in Smart Grid

Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 7)


In this paper, we use meta-heuristic algorithm: Genetic Algorithm (GA) and Biogeography based Optimization (BBO) integrated in Energy Management Controller (EMC) to evaluate the performance of home energy management in residential area. EMC is introduced with the objective of cost reduction and to manage high peak demand problem. Time of use tariff model is used for electricity bill calculation. Simulation results show the effectiveness and efficiency of proposed scheme by load management and cost reduction. BBO based EMC performs better than GA based EMC. We also perform comparison both GA based EMC and BBO based EMC with unscheduled scheme and results show both outperform than unscheduled. BBO based EMC is more efficient in electricity cost minimization and peak to average ratio minimization as compared to GA based EMC.


Biogeography-based Optimization (BBO) Home Energy Management (HEM) Energy Management Controller (EMC) Electricity Bill Calculation Reduce Electricity Costs 
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

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