A Fuzzy Logic Controller for Demand Side Management in Smart Grids Sara Atef and Amr B. Eltawil Industrial Engineering and Systems Management, Egypt-Japan University of Science and Technology (E-JUST), New Borg Elarab City, Alexandria 21934, Egypt Keywords: Artificial Intelligence, Fuzzy-logic, HVAC, Demand Side Management, Residential Customer, Smart Grid, IOT. Abstract: Smart Grid Demand Side Management is the effective way for energy providers to encourage their customers on reducing their consumption during peak loads through several Demand Response programs. In this paper, An Artificial Intelligence approach based on a Fuzzy Logic control system is proposed for the home appliance scheduling problem. This is typically used in Home Energy Management Systems for the control of Heating, Ventilation, and Air Conditioning Systems (HVAC). The simulation results demonstrate the capability of the proposed model to manage and control of HVAC systems in a smarter way than traditional techniques. Furthermore, a reduction of 18.33% in total hourly energy consumption has been obtained after introducing a new parameter among the fuzzy input variables. 1 INTRODUCTION As a consequence of recent advancement in smart grid communication and information systems, demand-side management (DSM) has become an efficient tool that can manage peak energy demand. DSM aims to peak load demand reduction, energy consumption optimization, reshaping the demand load profile and improving the grid sustainability by minimizing the total cost and carbon emission rates. Dynamic DSM (DDSM) has been ignored for a long time due to the inability of predicting users’ performance, poor computational techniques, and complexity of consumption dynamics. Nowadays, DDSM has attracted great attention as Demand Response (DR) programs target the end-user customers’ response by making changes to their normal load profile which could lead to lower electricity usage when it is required, hence improving the system performance, reliability and sustainability. There are three main categories of DSM techniques, residential, commercial and industrial energy management (Khan et al., 2016). One of the major sectors in consuming energy is the residential sector. It is also expected that the residential electricity demand will keep increasing through the upcoming decades(J. Conti, P. Holtberg, J. Beamon, A. Schaal, 2010). In order to manage energy consumption in the residential sector, Home Energy Management Systems (HEMS) have been implemented. HEMS can be classified under three main categories: dynamic pricing schemes like Time of Use (ToU), Real Time Pricing (RTP) and Critical Peak Pricing (CPP), appliances scheduling and load forecasting. The heating, ventilation, and air conditioning (HVAC) systems are considered an important target for HEMS due to their huge share of the annual total energy consumption in the world. In traditional Building Automation Systems (BAS), users have the capability to manage and control their load consumption schedules manually through a single application. Today, they do not need anymore to physically interact with the system because of having Internet Of Things (IoT) based operating systems. According to (Emerson Climate Technologies, no date), 33% of thermostats sold in 2014 were wifi- enabled and this percentage will jump to 75% in 2019. IoT has several benefits for HVAC systems such as: real-time monitoring, total controllability, remote diagnostics, inherent connectivity, system adaption, increased efficiency, continuous comfort and predictive maintenance. Monitoring systems play a vital role in smart grids as they help to keep the system supervised and controlled all the time. Thus, Atef, S. and Eltawil, A. A Fuzzy Logic Controller for Demand Side Management in Smart Grids. DOI: 10.5220/0007297202210228 In Proceedings of the 8th International Conference on Operations Research and Enterprise Systems (ICORES 2019), pages 221-228 ISBN: 978-989-758-352-0 Copyright c  2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved 221