IOT Based Smart Electricity Meter Monitoring and Control for Load Management

Due to lack of reliable and useful data of demand side, there is a huge gap between generation and demand side so electricity supplying companies are unable to handle losses, power failure and electricity theft which mainly stems from the inadequate metering system. The installed capacity in Pakista

Project Title

IOT Based Smart Electricity Meter Monitoring and Control for Load Management

Project Area of Specialization

Internet of Things

Project Summary

Problem Statement

Due to lack of reliable and useful data of demand side, there is a huge gap between generation and demand side so electricity supplying companies are unable to handle losses, power failure and electricity theft which mainly stems from the inadequate metering system. The installed capacity in Pakistan is 37,402 MW which is way more than the peak demand that is approximately 25,000 MW. Still, consumers are suffering and often charged way more than the units they used. There is need for such a system in the country that would benefit the consumers and allow them to make smart decisions about their energy use as well as benefit the supplier.

Project Description

This project involves the use of advanced machine learning capabilities to develop a smart metering mechanism based on IoT (Internet of Things). The proposed smart meter mechanism based on IoT would include appliance fault detection and diagnosis, load management as well as power theft control. This designed mechanism benefits the electricity supplier as well as the consumer. It aims to help the utility control power theft, as well as empower electricity consumers with the insights and tools they need to make informed decisions about their energy use. Such results facilitate timely insights for both parties to prevent future problems and save money, maximizing the value for both.

Moreover, this project aims to investigate smart metering and multiple features offered by smart meters. This contributes to measuring the power consumption data in various households and subsequent interpretation of this data for hourly measurement could help consumers to switch their electric load to off-peak hours. With the results provided in this research, users can change their behavior when they have better control on their consumption pattern. As a result, power consumption patterns of smart electricity distribution are studied and analyzed, thereby leading to an innovative idea for saving the limited resource of electrical energy.

For this project, we will be using smart electricity meters sponsored by Accurate Pvt. Limited. It is proposed that better and improved features be added onto smart meters which are already in use and being issued by electricity suppliers in Pakistan. Many benefits of smart metering have not been fully explored in our country. Smart meters are not only used for automatic meter reading, but their features make them very useful for monitoring, theft detection and load management etc., which is what will aim to explore.

Project Objectives

•To develop a Smart meter mechanism based on IoT and controllers to receive data and provide outputs based on the received data, on which informed decisions will be made.

•Appliance fault detection and diagnosis where algorithms can identify, diagnose, and predict faults for many home appliances, without the installation of any hardware and just by analyzing smart meter data.

•Load management, where utilities can provide personalized alerts that certain high load appliances are running during high price periods (peak hours) and provide the user an option to turn off secondary load.

•Power theft control, where the IoT and the meter reading system is designed to continuously monitor the meter reading and the service provider can disconnect the power source whenever they deem necessary to do so.

Project Implementation Method

This project would develop a smart meter mechanism based on IoT which includes appliance fault detection and diagnosis, load management as well as power theft control. For these objectives, the methodology adopted is illustrated through a functional block diagram approach.  We will use three 3-phase smart meters, which have been sponsored to us by Accurate Pvt. Limited. The primary meter shown in the design is installed at grid station for advance metering. It will collect real time data from line sensors, consumers and generators and is helpful for generation plants to predict the peak demand. These homes represent residential area where secondary smart meters are installed. 

Appliance fault detection and diagnosis is an objective designed to benefit the consumer, where designed algorithms identify, diagnose and predict faults without the installation of any hardware and just by analyzing smart meter data. The algorithm analyzes the data from the smart meter and in case of any abrupt changes in the unit consumption pattern of the appliances or any current surges, it will notify the consumer through a mobile application, in time to prevent damage to the appliances. 

Load management is another objective of this study that benefits the consumer. Every high load appliance in the smart meter mechanism has an IoT device attached. The IoT device informs the user through the same mobile application in case an appliance is running during high price periods (peak hours) and gives them an option to turn it off. Electrical appliances, like an AC or TV which are high load appliances are more expensive during peak hours. IoT devices in the mechanism include voltage and current sensors connected to a microcontroller, a relay driver that will drive a relay module, which will turn off the loads when a user commands to do so. The user will be able to turn off or turn on the appliances via the designed mobile app.

Power theft control is an objective of this study which helps the electricity supplier. Eighty percent of global power theft is done by ‘cable hooking’ or direct tapping from the power lines.  The person involved in power theft taps into the power line from a point ahead of the energy meter. This energy consumption is unmeasured. Utility does not receive the revenue associated with power consumed due to theft and this power in the system is left unaccounted for.  Our strategy to identify the power theft is to add power consumed from the secondary meters and compare it to the power supplied from the primary meter. Bearing in mind some losses, these should be the same, if not, the algorithm will notify the electricity supplier.

Benefits of the Project

• Reduces power theft: Eighty percent of global power theft is done by ‘cable hooking’ or direct tapping from the power lines.  The person involved in power theft taps into the power line from a point ahead of the energy meter. This energy consumption is unmeasured. Utility does not receive the revenue associated with power consumed due to theft and this power in the system is left unaccounted for. The designed system continuously monitors the meter reading, and the service provider can disconnect the power source whenever they deem necessary to do so.
• Reduces the running costs of manual operations, through automated metering infrastructure, in a remote manner, and allow services such as meter reading, service disconnection, etc.
• Easier monitoring and tracking of produced and consumed power.
• Support for Home-Area Networks (HANs): Home area networks are envisaged to deploy appliance monitoring and control through Smart Meters in near future. With HANs, consumers will be able to respond on a minute-by-minute basis to energy pricing changes and remotely shift demand into off-peak periods, when energy is more available and less costly.
• Due to demand side response, and consumer behavior during peak hours, enabled through smart metering, the utility also gets benefit of reduced peak hour load, therefore, the utility is better able to balance the demand and supply.
• Appliance fault detection and diagnosis, where designed algorithms identify, diagnose and predict faults without the installation of any hardware and just by analyzing smart meter data. The algorithm analyzes the data from the smart meter and in case of any abrupt changes in the unit consumption pattern of the appliances or any current surges, it will notify the consumer through a mobile application, in time to prevent damage to the appliances.

Technical Details of Final Deliverable

IoT device

Every high load appliance in the smart meter mechanism has an IoT device attached. The IoT device informs the user through the mobile application in case an appliance is running during high price periods (peak hours) and gives them an option to turn it off. Electrical appliances, like an AC or TV which are high load appliances are more expensive during peak hours.

IoT devices in the mechanism include voltage and current sensors connected to a microcontroller. The sensors sense the information from the appliance to which it is connected. It gathers the information to the micro controller. The wireless module transfers sensed data to the data concentrator and the cloud. The cloud as stated earlier will store, analyze and process the information. A relay driver that will drive a relay module, which will turn off the loads when a user commands to do so. The user will be able to turn off or turn on the appliances via the designed mobile app.

Algorithm

We will be analyzing Smart meter data in cloud, through a designed algorithm. The designed algorithm on the cloud, in this study, is based on Artificial Neural Network (ANN), which uses a method called Supervised Learning. Neural networks are trained by processing data that contains a known input and result, forming probability-weighted associations between the two which is then stored within the data structure of the neural network itself. Successive processing causes the neural network to produce output which gradually becomes similar to the target output. This algorithm is designed on PyCharm software using python language. It analyses the meter’s parameters and identifies faults in appliances by detecting deviations in the energy usage pattern profiles of the user, identifies power theft and helps in power load management. 

Mobile Application

The developed mobile application is meant to create communication between the control unit and the managing unit. Moreover, it enables the user to track their usage at any time and view metering data on their phone. The reason behind integrating the mobile application with the smart energy meter mechanism is that it will make it easier for consumers to monitor their energy consumption even if they are not nearby their meter display.

The mobile application is also used to generate alerts regarding appliance faults and if any secondary load is running during high price periods. The user will also be able to turn off or turn on the appliances via the designed mobile app. IoT devices in the mechanism include voltage and current sensors connected to a microcontroller, a relay driver that will drive a relay module, which will turn off the loads when a user commands to do so.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Energy

Other Industries

IT , Others , Security , Telecommunication

Core Technology

Internet of Things (IoT)

Other Technologies

Artificial Intelligence(AI), NeuroTech

Sustainable Development Goals

Industry, Innovation and Infrastructure, Responsible Consumption and Production

Required Resources

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