Remote monitoring and controlling of the sub-station equipment is an important issue for the power/energy management department which is normally done manually, or using an expensive PLC and SCADA system. With the emergence of the internet and computational era, a smart monitoring and reliable controlling system over the entire sub-station equipment is highly desirable that can be achieved by introducing the Internet of Things (IoT) technology. IoT is the network of physical devices embedded with electronics, software, sensors, actuators and network connectivity which have the ability to identify, collect and exchange the data. Each thing is uniquely identifiable through its embedded computing system and able to interoperate within the existing internet infrastructure. This paper proposed an IoT based network strategy for monitoring and controlling the sub-station equipment so that managing time and resources can take place as efficiently as possible. The IoT based system allows objects to be sensed or controlled remotely across existing network infrastructure, creating opportunities for more direct integration of the physical world into computer-based systems and resulting in improved efficiency, accuracy and economic benefit with the added merits of minimum human intervention. Moreover, a prototype system has been implemented and tested for measuring the effectiveness of the proposed model.

A smart IoT based system for monitoring and controlling the sub-station equipment

In the era of modern digitalization world, it is a simple to monitor and control the substation equipment remotely using expensive PLC and SCADA system, but it is desirable to design a system which is cost-effective, smart and reliable. So that IoT is an effective solution as the real-time capability of IoT is considered as a key feature for monitoring and control applications of power systems. The IoT is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human to human or human to computer interaction. These devices capable of interacting with one another directly or indirectly and also data collection are performed locally or remotely via centralized servers or cloud-based applications. This paper aims to design a low-cost energy monitoring and controlling system using IoT devices. This paper shows a result of the effective use of IoT devices in a power system to obtain better efficiency with less time. The use of IoT devices improves the power system performance remotely without any human intervention. In this project, the prototype of the system using Raspberry pi has been designed. The use of Raspberry pi reduces manpower and maintenance cost. It performed mainly two functions such as oil quality and oil level sensing and transformer differential protection.

Design of an IoT Based System for Monitoring and Controlling the Sub-Station Equipment

Energy is one of the most important factors in a country growth, both in the industrial and household fields. Among these fields, the industrial sector that needs the most in supporting the development of a company, energy saving is an important target for every company. Therefore, an accurate prediction is needed to determine future energy consumption. Many researchers have proposed research on the prediction of energy consumption using either machine learning or deep learning. One of the challenging factors in predicting energy consumption is data using a multivariate time series model with several uses in the area. In this project, researchers will conduct research on energy consumption predictions in manufacturing companies engaged in the food sector. This company has several areas as well as several predictable energies such as electricity, water, and diesel fuel, the data studied are multivariate time series modeled data. For the case of a data model like this, we use two algorithms, namely prophet and LSTM, because this algorithm can predict time series data. From the results of our research, it shows that Prophet Facebook which has the best results in predicting the energy consumption of electricity, water, and diesel fuel, a very significant difference in error rate is obtained by the LSTM algorithm for predicting time series models.

Multivariate time series with Prophet Facebook and LSTM algorithm to predict the energy consumption

Energy is one of the most important factors in a country growth, both in the industrial and household fields. Among these fields, the industrial sector that needs the most in supporting the development of a company, energy saving is an important target for every company. Therefore, an accurate prediction is needed to determine future energy consumption. Many researchers have proposed research on the prediction of energy consumption using either machine learning or deep learning. One of the challenging factors in predicting energy consumption is data using a multivariate time series model with several uses in the area. In this project, researchers will conduct research on energy consumption predictions in manufacturing companies engaged in the food sector. This company has several areas as well as several predictable energies such as electricity, water, and diesel fuel, the data studied are multivariate time series modeled data. For the case of a data model like this, we use two algorithms, namely prophet and LSTM, because this algorithm can predict time series data. From the results of our research, it shows that Prophet Facebook which has the best results in predicting the energy consumption of electricity, water, and diesel fuel, a very significant difference in error rate is obtained by the LSTM algorithm for predicting time series models. 

This research work has designed and proposed an energy management system for the KCG college campus. The campus built-up are has recently been increased due to the increase in student strength, introduction of new courses & laboratories. As a result the electrical load demand of the college campus has also been increased in the past few years. The proposed Energy Management System (EMS) monitors all electrical parameters such as voltage, current, frequency, kWh, kVA, and run hour by using a personal computer and further the load of a particular feeder during peak hours can also be controlled. The connected load details for the entire college campus was collected and single line diagram has also been developed for the college campus. The multifunctional meters are also utilized in developing the proposed energy management system.

Design of Energy Management System for College Campus

Energy management is becoming a trending topic in the 21st century. It includes planning and operation of energy production and energy consumption units. One of initial steps for an effective energy cost control program is the assessment of energy consumption and pattern of energy usage. This is the place where Energy Monitoring comes into picture. It is a technique based on the standard management axiom stating that "You cannot manage what you cannot measure". It serves as an effective guide for energy management. Unlike energy meters which are installed at locations which cannot be accessed easily, this monitoring system can be installed within the house i.e. nearby the switchboard or distribution box. By this way the people can get an idea of how much energy they are consuming in real time, inside their house itself. By uploading the data into the cloud, detailed consumption of energy will be available for every month, every day and every hour. This serves as a tool for Energy management. Apart from this, the loads in the houses can also be controlled remotely via computers/smart phones in case of overloads or when a person is not available at home.

S. Balamurugan

Papers

Energy monitoring and management using internet of things