Towards Effective and Efficient Energy Management of Single Home and a Smart Community Exploiting Heuristic Optimization Algorithms with Critical Peak and Real-Time Pricing Tariffs in Smart Grids

Muhammad Awais, Nadeem Javaid, Khursheed Aurangzeb, Syed Irtaza Haider, Zahoor Ali Khan and Danish Mahmood
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Muhammad Awais: Department of Computer Sciences, COMSATS University Islamabad, Islamabad 44000, Pakistan
Nadeem Javaid: Department of Computer Sciences, COMSATS University Islamabad, Islamabad 44000, Pakistan
Khursheed Aurangzeb: College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia
Syed Irtaza Haider: College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia
Zahoor Ali Khan: Computer Information Science, Higher Colleges of Technology, Fujairah 4114, UAE
Danish Mahmood: Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Islamabad 44000, Pakistan

Energies, 2018, vol. 11, issue 11, 1-30

Abstract: Nowadays, automated appliances are exponentially increasing. Therefore, there is a need for a scheme to accomplish the electricity demand of automated appliances. Recently, many Demand Side Management (DSM) schemes have been explored to alleviate Electricity Cost (EC) and Peak to Average Ratio (PAR). In this paper, energy consumption problem in a residential area is considered. To solve this problem, a heuristic based DSM technique is proposed to minimize EC and PAR with affordable user’s Waiting Time (WT). In heuristic techniques: Bacterial Foraging Optimization Algorithm (BFOA) and Flower Pollination Algorithm (FPA) are implemented. Furthermore, a novel heuristic algorithm has been proposed by merging the best features of the aforementioned existing algorithms. We test the proposed scheme on single homes and on smart community (involving multiple households). Different Operational Time Intervals (OTIs) are also considered for implementation. We have performed simulations for validating the our scheme. Results clearly demonstrate that the proposed Hybrid Bacterial Flower Pollination Algorithm (HBFPA) shows efficacy for EC and for reduction of PAR with reasonable user WT.

Keywords: scheduling; demand side management; smart grid; home energy management (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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