Comparative Analysis of Medium Term Load Forecasting using Genetic Algorithm and Particle Swarm Optimization

Shweta Chaturvedi, Prof. Ashish Tiwari

Abstract


The forecasting of electrical energy provides the required information about future conditions of the network to the system engineers and helps to predict essential improving actions such as putting power plants at their maximum production, electricity purchasing, switching etc. It is essential for the booking of fuel supply and maintenance activities and making arrangements for utility power exchange. With the ongoing advancement of new numerical, mining and man-made reasoning devices, it is potentially feasible to enhance the result.

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References


Willis. H.L and Northcote-Green. J.E.D. (1984). ‘Comparison tests of fourteen distribution load forecasting methods’, IEEE Trans. on Power Apparatus and Systems, 103(6): 1190-1197

Hesham, Alfares. K and Mohammad Nazeeruddin. (2002). ‘Electric load forecasting: literature survey and classification of Methods’, International Journal of Systems Science, 33(1): 23-34

Heiko Hahn, Silja Meyer-Nieberg and Stefan Pickl. (2009). ‘Electric load forecasting methods: Tools for decision making’, European Journal of Operational Research, 199: 902–907

Kumaran, Kumar J, ‘Application of artificial intelligence techniques for electric load forecasting’, PhD thesis submitted at Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya, 2015

Engle. R.F, Mustafa. C, and Rice. J (1992). ‘Modelling peak electricity demand’, Journal of Forecasting, 11: 241 – 251.

Fan.J. Y, McDonald. J.D (1994). ‘A real-time implementation of short – term load forecasting for distribution power systems’, IEEE Transactions on Power Systems, 9: 988 – 994.

Hongzhan NIE, Guohui LIU, Xiaoman LIU and Yong WANG. (2012). ‘Hybrid of ARIMA and SVMs for short-term load forecasting’, Energy Procedia, 16: 1455 – 1460.

Rao, R.V., Savsani, V.J. and Vakharia, D.P. (2011). ‘Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems’. Computer-Aided Design, 43 (3): 303-315.

M.C. Falvo, R. Lamedica, S. Pierazzo, and A. Prudenzi, "A Knowledge Based System for Medium Term Load Forecasting", Transmission and Distribution Conference and Exhibition, IEEE PES

Papia Ray, Sabha Raj Arya and Shobhit Nandkeolyar, "Electric Load Forecasts by Metaheuristic Based Back Propagation Approach", Journal of Green Engineering, Vol. 7, 61–82. 2017

Isaac Samuel, Tolulope Ojewola, Ayokunle Awelewa, Peter Amaize, "Short-Term Load Forecasting Using the Time Series And Artificial Neural Network Methods", IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE), 2016

Raman Kamboj, Mr. Ram Avtar, "Electric Load Forecasting Using Different Techniques in BPN", International Journal of Advanced Engineering Technology, 2013


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