# Wireless Home Energy Management System with Smart Rule-Based Controller
## 1 Introduction  
The world still mainly relies on non-renewable resources for residential energy supply through public utility services, despite the increasing integration of renewable energy sources in the electricity generation process. In this framework, residential consumers are compelled to minimize their energy usage in order to benefit from government incentives that encourage efficient public energy utilization by adjusting the time of energy usage and efficient devices, like LED lamps [1]. However, the main obstacle to the development of such energy management systems is the user inconvenience that results from the regulated energy use. Thus, many researches have attempted to develop home energy management (HEM) systems that minimize energy utilization while maintaining the highest possible level of user comfort. A greedy iterative algorithm was used in [2] to schedule multiple user appliances in a smart grid system. The objective was to minimize the aggregated energy usage of all the consumers, mainly while using the day-ahead hourly energy price. However, the conclusions of the authors were only based on simulations and, thus, had no practical validation. In addition, a sufficient amount of constraints, such as user preference and comfort, were not properly incorporated into the optimization problem that minimizes energy consumption. In [3], an artificial neural network was used to establish a convenient thermal environment in a domestic building by controlling the thermal loads. In a related work, a thermal model of a two-story house while using a novel gray box modeling approach was presented in [4]. With the special focus on thermal device models, a HEM system was developed, in which machine learning (ML) methods were used in [5] to train and optimize the energy consumption. However, the application of the utilized algorithm to many energy variables encountered in practice is not feasible. In [6] and [7], an appliance modeling software and optimization methods were used to consider the realistic operation of various home devices in the simulation of an HEM controller. The main objective of the controller was to reduce the load peaks and smoothen the power consumption trend. The utilized optimization algorithm considered the time of use pricing and outdoor temperature information, together with the preferences of the user. The employed appliance models were realistic for the development of an optimized HEM controller, according to the authors. [PERSON] and [PERSON] in [8] developed a smart demand-side energy management and scheduling system for households with photovoltaic (PV) systems. Similarly, different types of loads are intelligently scheduled in [9] in order to minimize the electricity usage bills when considering the maximal demand limit. The scheduler computed the expected load profile and PV generation of the user based on the weather forecast for a specific day of the week. The aggregated energy consumption of all the appliances was used to minimize the energy consumption by means of an optimized schedule that utilized a PV generator whenever possible [8]. However, this simulation-based work did not consider user comfort and user override constraints and actual PV output. Similar to [5], in the simulation in [10], three types of loads were considered in the optimization problem of energy usage. The proposed controller received the outdoor temperature, energy cost, and pricing signal as inputs to the optimization problem. A convex cost function was used as the main objective function, with the maximization of user comfort. The use of a convex objective function might not be accurate from a practical perspective, because appliance-switching operations cause discontinuity in the energy consumption pattern. In [11], smart meter data consisting of the energy consumption and pricing signal from the supplier were used to simulate a HEM system. The system performed multi-objective optimization to minimize the daily electricity cost while maximizing the user convenience.