Energy Optimization in Home Energy Management System Using Artificial Fish Swarm Algorithm and Genetic Algorithm
| Autor: | Nadeem Javaid, Muhammad Talha, Musa Ahmad, Muhammad Junaid Nazar, Ghulam Mohiuddin, Muhammad Shahid Saeed |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Schedule
Mathematical optimization Meta-optimization Computer science Heuristic (computer science) 020209 energy 020208 electrical & electronic engineering Swarm behaviour 02 engineering and technology Energy management system Artificial bee colony algorithm Genetic algorithm 0202 electrical engineering electronic engineering information engineering Multi-swarm optimization Algorithm |
| Zdroj: | Advances in Intelligent Networking and Collaborative Systems ISBN: 9783319656359 INCoS |
| DOI: | 10.1007/978-3-319-65636-6_18 |
| Popis: | In this paper, we have evaluated the performance of heuristic algorithms: Genetic Algorithm (GA) and Artificial Fish Swarm Algorithm (AFSA) for Demand Side Management. Our prime focus in this paper, is to optimally schedule appliances in a smart home in such a way that the Peak to Average Ratio (PAR) and the electricity cost can be reduced. The pricing scheme used in this paper is real time pricing. Our Simulation results validate that the two nature inspired schemes successfully reduce PAR and electricity cost by transferring load of on peak hours to off peak hours. Our results also depict a trade off between electricity cost and comfort of a user. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|