Automated Energy Meter and Controller for Rural Residential Structures

Robert R. Bacarro, Alexis P. Espaldon, Analyn S. Morite


The project was conceived in order for the consumers to control and manage their electric consumption. The system was programmed to limit the use of electricity based on the energy management system and the consumers' capacity to pay. The study applies developmental research for designing and developing the system. For data analysis, Proteus 7, Arduino Uno microcontroller, electronic components and devices as well as frequency count, mean, and standard deviation were utilized. The result of this study shows that most of the low- income household can aord to have electric bill ranging from P500-P1,000. The energy meter can measure and control the power consumptions at the same time the energy controller can program the use of AC loads in a given household. Likewise, the source codes loaded to the microcontrollers were able to implement the desired function of the system. Based on the evaluation it has a satisfactory performance in terms of performance, durability, and reliability.


embedded system, electric meter, energy controller, energy management

Full Text:



Basnayake, B.A.D.J.C.K., Amarasinghe, Y.W.R., Attalage, R.A., Udayanga, T.D.I., Jayasekara, A.G.B.P. (2015). Articial intelligence based smart building automation controller for energy eciency improvements in existing buildings. International Journal of Advanced Information Science and Technology, vol. 40, pp.150-155.

Chandramohan, J., Nagarajan, R., Satheeshkumar, K., Ajithkumar, N., Gopinath, P.A., Ranjithkumar, S. (2017). Intelligent smart home automation and security system using Arduino and Wi-. International Journal of Engineering and Computer Science, vol. 6, pp.20694-20695.

Garvin, D. (1988). Eight dimensions of quality. [Online]. Viewed 2018 December 8. Available: he-eight-dimensions-of-quality

Khah, M.S., Siano, P. (2017). A stochastic home energy management system considering satisfaction cost and response fatigue. IEEE Xplore Journal. [Online]. Available: 84899

Li, C., Vasquez, J.C., Guerrero, J.M. (2016) Multiagent-based distributed control for operation cost minimization of droop controlled DC Microgrid using Incremental Cost Consensus, IEEE Xplore Journal. [Online]. Available: document/7392917

Malvar, O.C. (2017). Energy Management System - Energy Investment Forum and Stakeholders Conference. [Online]. Available: les/pdf/announcements/e-power 05 04_energymanagementsystem.pdf

Richey, R.C., Klein, J.D., Nelson, W.A. (1994). Developmental Research: The Denition and Scope. Handbook of Research for Educational Communications and Technology, Vol.2, pp.1099-1130.

Rusitschka, S., Gerdes, C., Eger, K. (2009). A low-cost alternative to smart metering infrastructure based on peer-to-peer technologies. Proc. International Conference on the European Energy Market, Leuven, May 2009, pp. 1 { 6.

Saleh, M., Esa, Y., Mohammed, A., Grebel, H., Cessa, R. (2017). Energy management algorithm for resilient controlled delivery grids. IEEE Xplore Journal. [Online]. Available: 01777


  • There are currently no refbacks.