Swarm Intelligence Based Home Energy Management Controller Under Dynamic Pricing Scheme
| Autor: | Nadeem Javaid, Fozia Feroze, Ayesha Zafar, Adnan Ahmed, Muhammad Hassan Rahim, Sheraz Aslam, Itrat Fatima |
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| Rok vydání: | 2017 |
| Předmět: |
Mathematical optimization
Computer science business.industry 020209 energy 020208 electrical & electronic engineering 02 engineering and technology Schedule (project management) Energy consumption Demand response Load management Smart grid Home automation Dynamic pricing 0202 electrical engineering electronic engineering information engineering Firefly algorithm business |
| Zdroj: | Advances on Broad-Band Wireless Computing, Communication and Applications ISBN: 9783319698106 BWCCA |
| Popis: | Energy management controller (EMC) is widely adopted for residential load management in smart grid (SG). Its main focus is on minimizing cost with minimal consumer interaction. EMC effectiveness is improved in the context of demand response (DR) program. In the era of demand side management (DSM) EMC plays a significant role in residential energy management by curtailing the peak to average ratio (PAR) and electricity bill. In this research work, we are reducing the electricity cost and PAR by maximizing the user comfort. In our research work, we consider a smart home with three smart appliances and schedule these appliances energy consumption and user comfort by using heuristic techniques: binary particle swarm optimization (BPSO) and firefly algorithm (FA). Simulations are conducted by utilizing the day-ahead real time pricing (DA-RTP). Simulation results depict that firefly algorithm (FA) has better performance as compared to BPSO in term of minimizing cost and PAR, while also maximizing user satisfaction level. A trade-off analysis between user satisfaction and energy consumption cost is demonstrated in simulations. |
| Databáze: | OpenAIRE |
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