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Near Real-Time Load Forecasting of Power System Using Fuzzy Time Series, Artificial Neural Networks, and Wavelet Transform Models

Shahida Khatoon, Ibraheem, Mohammad Shahid, Gulshan Sharma, Emre Çelik, Erdal Bekiroğlu, Mohammad Faraz Ahmer, Priti Priti

Year
2023
Citations
5

Abstract

AbstractDue to the increasing usage of electrical power, the size of electrical power system has increased manifold over the years. There is no inventory or buffer from generation to customer; therefore, to provide a reliable and quality electrical energy whenever demanded, power utility engineers require an adequate, efficient, and precise load forecast to meet continuously varying load demands. This article presents the design and analysis of demand forecasting over shorter interval for power system. The fuzzy time series (FTS), artificial neural network (ANN), and wavelet transform (WT) based forecasting is presented and analyzed in this article. The real-time data from Indian utility is collected for forecasting the demand and to check the effectiveness of FTS, ANN, and WT. The various error definitions are used to calculate the accuracy of the proposed techniques, and the application results verify the superiority of WT and ANN over FTS by showing reduced error value with greater accuracy. Additionally, it is watched that wavelet db3, level 3 is discovered to be the most accurate Daubechies wavelet-oriented technique for predicting the demand in comparison to other dbs, and it highly aligns in reducing the error between actual and predicted demand.Keywords: Artificial Neural Network (ANN)Automatic Generation Control (AGC)Fuzzy Time Series (FTS)Load ForecastPower System OperationWavelet Transform Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsShahida KhatoonShahida Khatoon is at present Professor and Head of the Department of Electrical Engineering and Library In-charge of Library Faculty of Engineering and Technology, Jamia Millia Islamia (a Central university, Govt. of India). Dr Khatoon obtained her B. Tech in Electrical Engineering from Jamia Millia Islamia in 1990 and M. Tech in Controls and Instrumentation from IIT Delhi in 1995. She obtained her PhD degree from Jamia Millia Islamia in 2004. Prof. Khatoon has published about 100 research papers in the area of Controls and Power System engineering in the peer reviewed international journals and conferences. Prof. Khatoon has delivered many invited lectures in various institutes and conferences. Prof. Shahida is a member of various academic societies of national and international repute. She has been Track Chair of IEEE International conference INDICON-2015 and IEEE INDIACOM 2020 and technical committee member of many IEEE conferences. She can be contacted at email: skhatoon@jmi.ac.in. Her research area includes Control Systems Engineering, Robotics and Automation, soft computing techniques and their applications in power systems, control systems and electronics engineering. IbraheemIbraheem is presently working as Dean Students Welfare - Jamia Millia Islamia (A Central University), New Delhi, India. He joined the Department of Electrical Engineering, Faculty of Engineering and Technology, Jamia Millia Islamia as a Lecturer in January 1988. Before Joining Jamia Millia Islamia, he had served Delhi Development Authority for a considerable time. Prof. Ibraheem received the B.Sc. Engineering (Hons.), M.Sc. Engineering and Ph.D. degrees in Electrical Engineering from Aligarh Muslim University, Aligarh, India, in 1982, 1987 and 2000, respectively. He worked with Delhi Development Authority at Delhi, India. Since January 1998, he has been with the Department of Electrical Engineering, Faculty of Engineering & Technology, Jamia Millia Islamia (Central University), New Delhi, India. Currently, he is working as a professor in the department. He had been Head of the Department of Electrical Engineering since 2002 to 2005. He has also discharged his duties as Coordinator for M.B.A.(Evening) Program, Faculty of Engineering and Technology, Jamia Millia Islamia for a period of about two years. Prof. Ibraheem is a member of various academic societies of national and international repute. He has been engage

Keywords

Artificial neural networkWavelet transformTime seriesElectric power systemNeuro-fuzzyFuzzy logicComputer scienceSeries (stratigraphy)Artificial intelligenceDiscrete wavelet transform

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