American Journal of Engineering Research (AJER) 2016 American Journal of Engineering Research (AJER) e-ISSN: 2320-0847 p-ISSN : 2320-0936 Volume-5, Issue-8, pp-199-205 www.ajer.org Research Paper Open Access www.ajer.org Page 199 Development of an Internet of Things based Electricity Load Management System Dr. D. O. Dike 1 , R.E. Ogu 1 , Dr. L. O. Uzoechi 1 , I. A. Ezenugu 2 1 Dept. of Electrical and Electronic Engineering, Federal University of Technology, Owerri, Imo State, Nigeria. 2 Dept. of Electrical/Electronic Engineering, Imo State University, Owerri, Imo State, Nigeria. ABSTRACT: Continuous overload to a power system is a problem as it reduces the life span of the generators. Load management is very vital in optimizing the performance of generating plants by properly managing the generated energy. During peak demand times, the energy used by consumers are expensive compared to that used during off peak demand time; this is because utility companies need to engage bigger generators and other infrastructures in order to supply the demanded energy. To prevent the need for the procurement of bigger generators and other infrastructures needed to augment electrical power needed by consumers during peak demand time, an Internet of Things (IoT) based Electricity Load Management System is developed in this paper. The Arduino mega 2560 board and the Arduino WiFi Shield 101 are used in the controller and connectivity elements respectively, ACS712 module is employed in the sensory block to measure current; in order to determine the power being used by loads while Solid State Relays are used for actuation purposes. The entire blocks were integrated to form a functional system whose mode of operation is based on IoT technology that can be employed for effective management electrical energy. Keywords: electricity, load, management, power, smart, grid, IoT. I. INTRODUCTION Short term generation of electrical energy to meet consumers’ demand especially at peak demand hours is very expensive. In order to meet consumer s’ demand, bigger generators that are capable of delivering huge amount power needed by the consumers during peak demand time are employed. Also, in some cases; alternative generators are started to augment the power needed by the consumers during peak time. The two approaches above are expensive and contribute to higher tariff rates which are often passed to the customer. High tariff on the other hand, encourages consumers to engage in electricity theft. Electricity theft when not curbed affects the power system negatively. It has been identified as one of the greatest challenges facing power companies in developing countries [1]. Any energy the customer uses during peak demand time is expensive when compared with the cost of the energy used during non peak demand time. The total cost associated with the generation of extra power to meet up with the consumers’ demand during peak demand time is eliminated, if the consumer can reduce the amount of energy he uses during peak demand, this in turn has a very big effect on the tariff. Electricity load management is importance because it eliminates the need to increase transformer, cable sizes and generator capacity; which are very costly [2]. Following the advancement in technology, the Internet of things (IoT) is currently applied in various areas; home automation, infrastructure management, transportation, smart grid and energy management. The Internet of Things technology is to be explored in the management of electrical energy. This will involve the constant measurement of the loads connected to a power grid to determine the peak demand time and subsequently manage electrical energy properly by shedding off low priority loads, this will lead to a smart grid, which is the expectation of today’s power system. To this end, an embedded system will be developed which will monitor the amount of load connected to a power grid in order to ascertain whether the peak demand time has been entered. If the peak demand time is reached, the system should be able to shed of some loads to prevent the grid from being overloaded and possibly eliminate the need for the services of bigger generators that would have been needed to augment the additional power during peak demand time. Also, at any point in time, the system updates the status of the grid to a web page so that the utility company can view the amount of load connected to the grid.