Demand Side Management Using Bacterial Foraging and Crow Search Algorithm Optimization Techniques
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Energy is the most valuable resource in every day life. However, energy demand is going high day by day. The high consumption of energy causes series of energy crisis. This problem can be handled with many optimization techniques by integrating demand side management with traditional grid. The main purpose of demand side management is to reduce the peak load and smart grid targets reduce the electric cost and load management by shifting the load from on peak hours to off peak hours. In this work, I adopt the Bacterial Foraging Algorithm (BFA) and Crow Search Algorithm (CSA). Simulation results show that our propose techniques reduce the total cost and peak average ratio by scheduling the load for 24 h. Results show that BFA is perform better than CSA and archived the objectives.
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