Earth Worm Optimization for Home Energy Management System in Smart Grid
Smart grid based energy management system promises an efficient consumption of electricity. For optimized energy consumption, a bio inspired meta-heuristic algorithms: Earth Worm Algorithm (EWA) and Bacterial Foraging Algorithm (BFA) are presented in this paper. In this work, we targeted residential area. Our aim is to reduce the electricity cost and Peak to Average Ratio (PAR). We have used the Critical Peak Pricing (CPP) scheme for calculating electricity bill. Through simulations, we have compared the results of EWA, BFA and unscheduled appliances. After implementing our techniques, EWA based energy management controller gives more efficient results than BFA in term of cost, while for PAR reduction, BFA performs better than EWA.
KeywordsSmart grid Meta heuristic techniques EWA algorithm BFA algorithm Critical peak point Home Energy Management System PAR
- 4.Wang, G.G., Deb, S., Coelho, L.D.S.: Earthworm optimization algorithm: a bio-inspired metaheuristic algorithm for global optimization problems. Int. J. Bio-Inspired Comput. (2015)Google Scholar
- 5.Khalid, A., Javaid, N., Mateen, A., Khan, Z.A., Qasim, U.: Demand side management using hybrid bacterial foraging and genetic algorithm optimization techniques. IEEE Transactions on Smart Grid, Conference Paper, Japan, 6–8 July 2016Google Scholar
- 10.Zhu, Z., Tang, J., Lambotharan, S., Chin, W.H., Fan, Z.: An integer linear programming based optimization for home demand-side management in smart grid. In: Innovative Smart Grid Technologies (ISGT), 2012 IEEE PES, pp. 1–5. IEEE (2012)Google Scholar