Energy Optimization in Smart Grid Using Grey Wolf Optimization Algorithm and Bacterial Foraging Algorithm
- 915 Downloads
Nowadays, energy is the most valuable resource, new techniques and methods are discovered to fulfill the energy demand. These techniques and methods are very useful for Home Energy Management System (HEMS) in terms of electricity cost reduction, load balancing and power consumption. We evaluated the performance of HEMS using Grey Wolf Optimization (GWO) and Bacterial Foraging Algorithm (BFA) techniques inspired by the nature of grey wolf and bacterium respectively. For this purpose we categorize the home appliances into two classes on the bases of their power consumption pattern. Critical Peak Pricing (CPP) scheme is used to calculate the electricity bill. The load is balanced by scheduling the appliances in Peak Hours (PHs) and Off Peak Hours (OPHs) in order to reduce the cost and Peak to Average Ratio (PAR) and manage the power consumption.
KeywordsBacterial Foraging Algorithm (BFA) Grey Wolf Optimizer (GWO) Home Energy Management System (HEMS) Peak Office Hours (OPHs) Critical Peak Pricing (CPP)
- 1.Zhu, Z., et al.: An integer linear programming based optimization for home demand-side management in Smart Grid. In: 2012 IEEE PES Innovative Smart Grid Technologies (ISGT). IEEE (2012)Google Scholar
- 7.Zhou, Y., et al.: Home energy management with PSO in Smart Grid. In: 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE). IEEE (2014)Google Scholar
- 10.Ma, J., et al.: Residential load scheduling in Smart Grid: a cost efficiency perspective. IEEE Trans. Smart Grid 7(2), 771–784 (2016)Google Scholar
- 11.Ranjini, A., Zoraida, B.S.E.: Intelligent residential energy management in Smart Grid. Indian J. Sci. Technol. 9(45) (2016)Google Scholar