RENEWABLE ENERGY ENHANCED SMART ENERGY MANAGEMENT SYSTEM USING INTERNET OF THINGS

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Published Oct 17, 2021
G. Ramya P. Suresh R. Arthi K. Murugesan Mayakannan Selvaraju

Abstract

Purpose: The paper presents the renewable energy enhanced smart energy management system using Internet of Things (IoT).

Methodology:

As we are living in a world where climate change is unpredictable, we chose the combination of solar and wind energy as renewable sources of energy, which has a rapid growth in the last decade. The renewable source of energy will be utilized alternatively when there is insufficient grid power and it will be achieved using an industrial microcontroller. The power generated by the renewable sources is sensed by the sensors and the data is transmitted to the microcontroller, which chooses what sources to be supplied based on availability. These enable users to monitor renewable energy as well as it can be controlled by switching it from grid power to any one of the renewable sources. The transmitted data can be controlled and monitored remotely using IoT platform.

Findings:

The unpredictable weather and climate are the main important drawbacks of wind and solar based renewable energy systems. The proper combination of two resources can help to overcome the drawback partially, the strength of each source overcomes the drawbacks of the other. The capacity of the batteries is maintained well when it is maintained with a full charge or charged quickly during deep and partial discharges. PV modules do not protect the batteries against deep discharges during rainy seasons or no sunshine. The batteries will be protected from deep discharge with the aid of a dynamic source of energy from the wind turbine, which extends the life of the batteries. The generated wind and solar energies are maintained with a common voltage of 12 Volts to 16 Volts using boost converters to be supplied to the load. The block diagram of the system.

Originality/value:

The hybrid energy management system is employed and it can generate electrical energy for the apartments, private houses, educational institutions, small companies, and so on.  The proposed method incorporates solar and wind energy sources for the sustainable generation of renewable energies. The area required by the module is less as it is built on a single module with a combination of wind and solar energies. The main objective is to produce green energy with the best efficiency by proper incorporation of algorithms between solar and wind energy sources. The best suitable hybrid renewable energy system to utilize the local renewable resources are solar and wind energy resources. The outputs of solar and wind are complementary to each other during some seasons. When compared to the performance of solar and the performance of wind energy, the combination of solar and wind performs better. Further, the PIC16F877A automatically determines the best available energy at any given time to be provided to the load. Since the present proposed model provides more energy output per unit area it can be used in several house rooftops as a reserve energy supply unit reducing the dependency of the customer from the main EB supply and thereby reducing the overall power consumption cost.

How to Cite

G. Ramya, P. Suresh, R. Arthi, K. Murugesan, & Selvaraju, M. (2021). RENEWABLE ENERGY ENHANCED SMART ENERGY MANAGEMENT SYSTEM USING INTERNET OF THINGS. SPAST Abstracts, 1(01). Retrieved from https://spast.org/techrep/article/view/2614
Abstract 108 |

Article Details

Keywords

Internet of Things (IoT), Renewable Energy Sources, Energy Management System

References
[1] Wei, Min, Seung Ho Hong, and Musharraf Alam. "An IoT-based energy-management platform for industrial facilities." Applied energy 164 (2016): 607-619.
[2] Liu, Yi, Chao Yang, Li Jiang, Shengli Xie, and Yan Zhang. "Intelligent edge computing for IoT-based energy management in smart cities." IEEE Network 33, no. 2 (2019): 111-117.
[3] Bagdadee, Amam Hossain, Li Zhang, and Md Saddam Hossain Remus. "A brief review of the IoT-based energy management system in the smart industry." Artificial Intelligence and Evolutionary Computations in Engineering Systems (2020): 443-459.
[4] Mani, Vignesh, Abhilasha Gunasekhar, and S. Sankaranarayanan. "IOT based smart energy management system." International Journal of Applied Engineering Research 12, no. 16 (2017): 5455-5462.
Section
GE3- Computers & Information Technology

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