SPECIAL SECTION ON REAL-TIME EDGE ANALYTICS FOR BIG DATA IN INTERNET OF THINGS Received December 25, 2017, accepted February 6, 2018, date of publication February 13, 2018, date of current version July 12, 2018. Digital Object Identifier 10.1109/ACCESS.2018.2805849 Energy Efficient Smart Buildings Using Coordination Among Appliances Generating Large Data MUHAMMAD HASSAN RAHIM 1 , ADIA KHALID 1 , NADEEM JAVAID 1 , (Senior Member, IEEE), MUSAED ALHUSSEIN 2 , KHURSHEED AURANGZEB 2 , AND ZAHOOR ALI KHAN 3 , (Senior Member, IEEE) 1 COMSATS Institute of Information Technology, Islamabad 44000, Pakistan 2 College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia 3 CIS, Higher Colleges of Technology at Fujairah, Fujairah 4114, United Arab Emirates Corresponding author: Nadeem Javaid (nadeemjavaidqau@gmail.com) The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through research group NO (RG-1438-034). ABSTRACT Internet of Things based smart grids (SGs) represent a vision of future power systems which helps to provide electricity in a smart and user friendly way. Demand side management is one of the most important component of a SG which allows energy consumers to change their electricity consumption pat- terns to reduce the electricity consumption cost. In this paper, we propose a home energy management system which helps to achieve our desired objectives: reduced electricity consumption cost, peak to average ratio and maximize user comfort. For this purpose, we have proposed a scheduling technique which is a hybrid of already existing optimization techniques: bacteria foraging algorithm and harmony search algorithm and is named as hybrid bacterial harmony (HBH) algorithm. Being producer of electricity units to the consumers, a utility establishes an incentive based pricing tariff; we, on top of it have employed seasonal time of use tariff which allows consumers to take decisions regarding their consumption patterns. Moreover, we introduce the concept of coordination among smart appliances using dynamic programming (DP) approach. The coordination among appliances is achieved by the help of the large data generated from the appliances of multiple homes with the joint work of heuristic techniques and DP. The resultant coordination not only reduces the electricity cost but also increases the user comfort. At last, we evaluate the performance of our proposed energy management system using our proposed optimization technique HBH. To comparatively evaluate the performance of our proposed technique, we compare it with already existing techniques. Simulation results validate that the proposed technique effectively accomplish the desired objectives while considering the consumer comfort. INDEX TERMS Smart grids, coordination, game theory, dynamic programming, big data. I. INTRODUCTION Numerous challenges are being faced by the electric power industry. The reliability of existing power grid is one of the challenges of power system which is affected by the increase in power demand, a limited amount of natural resources, and aging infrastructure. To satisfy peak load demands, util- ities turns on generators running on fossil fuels and natural gases which ultimately cause environmental issues as these generators are a great source of emitting harmful gasses. Therefore, a need of more reliable, sustainable, and an effi- cient power grid system has emerged. In order to make power grids more reliable, sustainable, and robust, an intel- ligent and revolutionary SG infrastructure is established. This revolutionized infrastructure is established by integrat- ing two way communication technology such as advanced metering infrastructure, smart meters and smart appliances in already existing power system. Various methods; such as distributed energy, smart pricing and demand response (DR) are introduced to facilitate this continuously evolving infras- tructure. It is observed that more than 65% of the reduction in the electricity consumption is achieved by residential sec- tor and small commercial building [1]. Home energy man- agement (HEM) system plays a vital role to enhance the efficiency of SG. Demand side management (DSM) and DR are the two major components of SG. DSM strategies are adopted by 34670 This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/ VOLUME 6, 2018