Home Energy Management Using Fish Swarm Optimization Bacterial Foraging Algorithm and Genetic Algorithm in Smart Grid

Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 12)


Energy crises are serious issues due to exponential increase in demand of energy. To tackle the issue of increase in demand, an integration of traditional grid with Demand Side Management (DSM). As need to resolve energy crises issues in residential areas smart homes are introduced; contains Smart Meters (SM), which allows bidirectional communication between utilities and end users. Different heuristic techniques are used to overcome these issues. The energy management is more necessary in residential area as there is verity of different appliances and power rates to schedule. The heuristics techniques provide most optimal solution. The purpose of our implementation is to reduce the total cost and Peak to Average Ratio (PAR) value and while keeping in mind the trade-off with waiting time up to an acceptable limit.


Demand Side Management (DSM) Home Energy Management System (HEMS) Unscheduled Load Multi-objective Mixed Integer Linear Programming (MOMILP) Binary Particle Swarm Optimization (BPSO) 
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.National University of Science and TechnologyIslamabadPakistan

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