Towards Efficient Energy Management of Smart Buildings Exploiting Heuristic Optimization with Real Time and Critical Peak Pricing Schemes

Sheraz Aslam, Zafar Iqbal, Nadeem Javaid, Zahoor Ali Khan, Khursheed Aurangzeb and Syed Irtaza Haider
Additional contact information
Sheraz Aslam: COMSATS Institute of Information Technology, Islamabad 44000, Pakistan
Zafar Iqbal: PMAS Arid Agriculture University, Rawalpindi 46000, Pakistan
Nadeem Javaid: COMSATS Institute of Information Technology, Islamabad 44000, Pakistan
Zahoor Ali Khan: CIS, Higher Colleges of Technology, Fujairah 4114, UAE
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

Energies, 2017, vol. 10, issue 12, 1-25

Abstract: The smart grid plays a vital role in decreasing electricity cost through Demand Side Management (DSM). Smart homes, a part of the smart grid, contribute greatly to minimizing electricity consumption cost via scheduling home appliances. However, user waiting time increases due to the scheduling of home appliances. This scheduling problem is the motivation to find an optimal solution that could minimize the electricity cost and Peak to Average Ratio (PAR) with minimum user waiting time. There are many studies on Home Energy Management (HEM) for cost minimization and peak load reduction. However, none of the systems gave sufficient attention to tackle multiple parameters (i.e., electricity cost and peak load reduction) at the same time as user waiting time was minimum for residential consumers with multiple homes. Hence, in this work, we propose an efficient HEM scheme using the well-known meta-heuristic Genetic Algorithm (GA), the recently developed Cuckoo Search Optimization Algorithm (CSOA) and the Crow Search Algorithm (CSA), which can be used for electricity cost and peak load alleviation with minimum user waiting time. The integration of a smart Electricity Storage System (ESS) is also taken into account for more efficient operation of the Home Energy Management System (HEMS). Furthermore, we took the real-time electricity consumption pattern for every residence, i.e., every home has its own living pattern. The proposed scheme is implemented in a smart building; comprised of thirty smart homes (apartments), Real-Time Pricing (RTP) and Critical Peak Pricing (CPP) signals are examined in terms of electricity cost estimation for both a single smart home and a smart building. In addition, feasible regions are presented for single and multiple smart homes, which show the relationship among the electricity cost, electricity consumption and user waiting time. Experimental results demonstrate the effectiveness of our proposed scheme for single and multiple smart homes in terms of electricity cost and PAR minimization. Moreover, there exists a tradeoff between electricity cost and user waiting.

Keywords: smart grid; demand side management (DSM); heuristic techniques; embedded computing systems (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: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (26)

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