IOT Application for Energy Management in Smart Homes ^†

Abstract

Increases in population and industrialization have caused the consumption of electrical energy to perpetually increase. Therefore, it has become necessary to monitor, control, and efficiently utilize the energy consumption. Present power systems cannot monitor and control the flow of power at the distribution level efficiently; because of this, financial losses occur. Therefore, a system should be developed which can monitor and control the power system faster and in an efficient way using modern technologies in order to avoid these losses. This paper presents an IOT-based concept for energy management to monitor and control specific loads in buildings. Among many wireless technology protocols, the proposed solution uses Wi-Fi along with the programmable ESP8266 controller in order to monitor the voltage, current, and power of a few home appliances. The IOT scheme also pursues an additional web-server-based monitoring approach for the online visualization, monitoring, and control of electrical parameters.

1. Introduction

The advancing technology in today’s era provides facility for humans in daily life. Humans have always been passionate about crafting new inventions in order to make their work comfortable. Today’s era has become advanced with smartness, and most of our complex tasks are performed easily and perfectly using modern technologies. The purpose of the design of IOT application is to create an option for home appliances to optimally be controlled and monitored from anywhere globally.

IOT application provides the interconnection of a few devices, such as relays, current sensors, controllers, and user clients, through a cloud server such that the programmable controller sets the user-defined relay ON/OFF through digital actuators in the cloud server. The cloud server is connected to the controller through Wi-Fi a connection, and the digital actuators’ ON/OFF status can command the controller to set the relay ON/OFF. The internet connection of Wi-Fi also influences the speed of the digital actuator. Apart from switching the appliances on or off, the cloud server has another task. It monitors the sensor’s data, received at its channel, and processes those data according to the requirements. The appliances’ live data, such as current voltage and power, are being stored on the cloud, which can be accessed anytime, every minute, or on an hourly, weekly, monthly, or yearly basis. Devices are also being controlled via a mobile application.

Literature Review

The interconnection of a large number of physical devices, computing tools, sensor networks, machines, digital devices, mechanical devices, humans, or animals through a network from which they can collect and send informative data is called Internet of things (IOT) [1]. The idea of a system of smart devices was initially created with the adjustment of a coke candy machine in 1982 at Carnegie Mellon University in order to check whether the apparatus was in working condition and whether the stack was cold or not [2].

Each of the devices in IOT can be assigned a unique address before uploading the collected data from other devices. For example, in hospitals, patients’ diseases are assigned with unique IDs; therefore, a doctor in the medical field can monitor over the patient easily [3]. IOT is being implemented across all the fields of human life, including domestic, commercial, and industrial building control, wireless monitoring, control of transportation, and to maximize agricultural production by implementing smart farming [4]. IOT connectivity can be either wired or wireless. Ethernet and the power line communication standards can be used in order to communicate via IOT wired connectivity. Wireless communication can be short range or long range [5,6]. Comparison of various IOT technologies with their characteristics and applications is given in [7,8]. Zigbee and Z-Wave are the most popular protocols for communication being used in the current IOT applications. Both can be utilized for the same applications of IOT, but the range of Z-Wave is larger (30 m) as compared to Zigbee’s range of 10 m.

In power systems, IOT can be implemented from generation to distribution for the efficient and easily controlled transmission of electrical power supply. The generation of neat and clean energy from renewable energy resources and integration into grids via smart grids is currently underway. At the distribution level, IOT is being implemented in the form of smart cities and smart homes [9]. In overhead transmission line along with the line data, IOT also carries the operating conditions such as weather changes, the temperature of the conductor, tension and sag, ice covering and windages, tower height and inclination, and estimation of the proportion of the the operating power system that must be digitalized [10].The smart city is a developed city in which the majority of the systems are controlled and monitored by the IOT schemes by deploying many types of sensors, such as weather forecast sensors, traffic control sensors, vehicle detection sensors, soil moisture sensors, humidity sensors, temperature sensors, etc.

This scheme enables the city authorities to communicate between the residents and the system operator. It also enables them to monitor different activities in the city from a single room [11]. Each activity and each building are being monitored from a single control room within the city, including traffic, schools, hospitals, commercial areas, libraries, etc. Along with this, a smart city provides benefits to the society’s quality, environment, mobility, economy, and daily life [12]. A smart home is a residential place in which any number of devices is connected via internet to analyze, monitor, control, and manage the appliances in the home via a simple mobile app or desktop application [13]. IOT in the form of smart homes is present in Smart TVs, Smart lighting systems, smart locks, smart surveillance cameras, smart kitchens, etc. [14].

2. IOT Working Diagram

The design of IOT application has been arranged such that all the components share their function in sequential form, from the load sensors to the cloud where data is processed for decision making. The circuit for three home appliances is arranged in such a way that it measures the current and voltage of the first, second, and third device sequentially through the current sensor and voltage sensor. The current and voltage sensors used are ACS712 and ZMPT101B. After the data are measured, they are sent to the analog inputs of a programmable Wi-Fi module or ESP8266 controller. The Wi-Fi module ESP8266 is one of the most powerful, cost-effective, and surface-mount-programmable controllers; it is most popular for online monitoring and control. It processes the data and sends them to the cloud server. The cloud server used is an MQTT cloud server with which several clients/users can be connected. The user can then have a view of the present data on the server and control the data if any digital I/O input is given.

In this way, the cloud server acts as a broker between the user and the loads. All communication is made wirelessly and through internet using Wi-Fi. Data can be monitored and controlled easily via the Human machine Interface (HMI) using a desktop computer or mobile application. The block diagram of IOT for three appliances is shown in Figure 1. There are two additional loads of supply indication and overload detection. Initially, loads are connected to the power supply through the 4-channel relay. This relay can operate in two modes: “normally open (NO)” and “normally closed (NC)”. The setup was set to the “NO” condition initially to avoid any mishap. Voltages were set to a constant 220 V. The detailed data representation can be observed at the cloud station using MQTT on a mobile or PC Screen. Different cases with different loads are discussed.

3. Case Studies and Results

Load specifications are listed in

Table 1. Load Specifications.

Loads	Load 1	Load 2	Load 3
Power rating	65 W	100 W	120 W
t	Resistive	Resistive	Resistive

. To validate the hardware implementation, we present three case studies.

3.1. Data Collection at Remote Locaton

• Load 1 of 60 W turned ON

In this case, only the supply indication was turned ON via a manually operated switch in order to check the supply continuity. As a result, the “device 4” that represent the supply indicator on the cloud will show the supply data, indicating load as a total power and total current drawn by the indicator load of the 60 W bulb. Device 4 works to measure the total power of the system. The results are presented in Figure 2a. The supply indicator was a lamp of 60 W.

2.

When single load is ON

After checking the supply, when Load 1 of 60 W was turned ON, the real time data were received at the cloud. The data contain voltage, current, and the power. The real-time live graphs for the power and the current were also displayed in the channel. The data were also saved in the form of an excel sheet in the cloud, which can be downloaded at any time. The data can be saved in the excel sheet for minutes, days, months, or years. Figure 2a–c show the data of loads that were received at the cloud.

3.

When two loads are switched ON

In this case, two loads of 65 W and 100 W, respectively, were switched ON simultaneously, namely Load 1 and Load 2. Their individual data and the total sum of the data were obtained at the cloud. Figure 2d shows the sum of the data of the two loads (Load 1 and Load 2).

4.

When all three loads are ON

This case describes the measurement and control of data whenever all three loads are ON. When all loads are switched ON, the total sum of the data of all three devices is measured, as shown in Figure 2e. A live power chart of the cumulative sum of the three loads’ power is shown in Figure 2f.

5.

Automatic Load Reduction Based on Device Priority

This case describes the power priority in two ways.

At a domestic level, we have some loads that are necessary to operate (room lighting or air conditioning), while some of them are less important, and can be switched off and scheduled for another time duration (e.g., washing machine or TV).

When Pl > 300 W, the power of the loads increases from a priority set value (300 W for this IOT scheme), the controller opens up all the relays, and the system is shut down.

When there is restriction on the demand limits, i.e., P_l should be less than 220 W and greater 200 W, then a less important load (say Load 3 of 120 W) is turned OFF, and the other two loads demand 165 W input power, so Load 1 and 2 will operate. When the utility limits the power, less important loads must be turned off in order to maintain the system according to the supply. Here, Load 3 is considered to be a less important load, Load 2 to be more important, and Load 1 has priority over the others. The resulting data are shown in Figure 2g.

3.2. Overload/Underload Detection and Control

Overload detection is controlled by the estimation of total power that can be drawn from each load. Whenever the total power is above 300 W or below 60 W, the programmable controller sends a command to the control center that there is an overload/underload in the system. The control center will disconnect the supply system and shut down all the appliances.

The live data are also received in another window for all devices, and we can download the data in the form of an excel sheet. The excel sheet can be arranged according to whether the user wants data for one device, all devices, only current for all devices, or only two values for one device. All possible combinations for data reception can be chosen. The data are arranged in the window. Each sensor is assigned a unique ID and the real-time data of each sensor is stored on the cloud. Data of any sensor can be accessed by selecting that sensor for any time and duration of days, months, or years.

4. Conclusions

In this paper, IOT-based load monitoring for managing electrical demand for a prototype system is presented. The controlling of loads has enabled us to minimize the waste of energy, which is one of the major issues of Pakistan. Implementation of this paper includes ESP8266, which is a powerful, smart, and an efficient tool for wireless communication of data. Visualization and the ability to change the pre-defined values of different parameters is also an addition to this paper which could be performed using Cayenne MQTT. Devices can easily be controlled and monitored through the mobile application MQTT. The measured values of current, voltage, and power using the proposed scheme are also compared with the metric measurements of ammeter and voltmeter and verified with an accuracy of 2.5 percent. This work can further be extended as an actual implementation for residential or commercial loads to gain energy savings.