Design and Arduino Implementation of Artificial Neural Network Based Intelligent Power Management System of Bangladesh

Md. Mahfuzur Rahman, Joy Shaha, Navid Hossain, Arifur Rahman Sabuj

Abstract


The research contrivance is to maintain and control load detachment or shedding in local distribution area and also utilize different types of power generation units such as conventional and non-conventional energy sources. The artificial neural network will anticipate, predict and exploit idea when generation is insufficient to meet the load demand. If the demand for the load is more than a generation, the artificial neural network will acknowledge the specific area where load detachment would be appropriately needed. Basically, an intelligent power management system of Bangladesh is developed by using artificial neural network (ANN) and implemented using Arduino for validation this work. We have designed the artificial neural network by utilizing and manipulating different types of seasonal and occasional load data. For further utilization, we actually divided an area into different sub-areas such as residential-load, industrial-load, commercial-load and VIP-load. However, it can suggest the area where load-shedding would be preferable on the basis of priority. Hence, artificial neural network suggests the area where maximum load-shedding is desired which is demonstrated by Arduino.


Keywords: Power system, artificial neural network, supervised learning, solar radiation, regression plot, error histogram

Cite this Article
Mahfuzur Rahman, Joy Shaha, Navid Hossain et al. Design and Arduino Implementation of Artificial Neural Network Based Intelligent Power Management System of Bangladesh. Journal of Power Electronics & Power Systems. 2017; 7(3): 17–29p.



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References


Du Xin-hui, Tian Feng. (2010).Study of Power System Short-term Load Forecast Based on Artificial Neural Network and Genetic Algorithm.1(1),3.

Swetha G C1, H.R.Sudarshana Reddy 2. (2007). Voltage Stability Assessment in Power Network Using Artificial Neural Network. 1 (1), 2-5.

Amamihe Onwuachumba. (2014). New reduced model approach for power system state estimation using artificial neural networks and principal component analysis. 1 (1), 2.

Dr. Jagdish kumar. (2011). Power System Stabilizer Based On Artificial Neural Network. Power System Stabilizer Based On Artificial Neural Network. 1 (1), 2-4.

Sabir Messalti. (2015). Artificial Neural Networks Controller for Power System Voltage Improvement. 1 (1), 5.

Amamihe Onwuachumba,Mohamad Musavi. (2013). Reduced model for power system state estimation using artificial neural networks. 2013 IEEE Green Technologies Conference. 1 (1), 1.

Shengyang He,Shelli K. Starrett. (2009). Modeling Power System Load using Adaptive Neural Fuzzy Logic and Artificial Neural Networks. 1 (1), 1.

Mohammad Hadi Salar, Mahmoud Reza Haghifam. (2010). Transmission Loss Allocation in Power Systems Using Artificial Neural Network. 2010 IEEE International Conference on Power and Energy (PECon2010), Nov 29 - Dec 1, 2010, Kuala Lumpur, Malaysia. 1 (1), 1.

J.A. Jaleel, T.P. Imthias Ahammed. (2008). Simulation of Artificial Neural Network Controller for Automatic Generation Control of Hydro Electric Power System. 1 (1), 1

Maureen Caudill.Neural Network Primer: Part I. AI Expert. Feb. 1989

Igor Aleksander, Helen Morton (2007). An Introduction to Neural Computing. 2, illustrated: International Thomson Computer Press, 1995. 156.

Mohamad R. Khaldi, “Power System Voltage Stability using Artificial Neural Network,” Department of Electrical Engineering, University of Balamand, Tripoli, Lebanon, 2008

Arturo S. Bretas, “Artificial Neural Networks in Power System Restoration,” IEEE Transactions on Power Delivery, vol. 18, No.4, October 2003.

Tej Pal Singh, Assistant Professor, TIT Bhopal MP(India), “Face Recognition using Feed Forward Back Propagation Neural Network,” International Journal of Innovative Research in Technology & Science(IJIRTS), vol. 1, No.1, 2004.

Raul Rojas. (1996). The Backpropagation Algorithm. In: 1 Neural Networks: A Systematic Introduction. Berlin: Springer-Verlag. 159-162.

Godfrey Boyle, Renewable energy. United Kingdom: OXFORD university press, 2004.

S. P. Sukhatme, Solar Energy. 3rd ed. India: Tata Mcgrawhill Publishers, 1996.




DOI: https://doi.org/10.37591/.v7i3.15

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