A Deep Neural Network Based Approach for Electrical Load Forecasting
Sachin Jagwanshi
, Prof. Mithlesh Gautam
Electrical load forecasting, Wavelet Transform artificial neural Regresion Learning Algorithm, Mean Absolute Percentage Error (MAPE).
Electrical Load Prediction is an important aspect in the power sector for proper planning and maintenance of power systems. Accurate load prediction is generally challenging due to the fact that the load used by the end user lies completely at the discretion of the user but still it is possible to get fair estimates of the average load conditions using surveys and prediction mechanisms. Any information related to pattern to be followed by connected Electrical Load will helps any electric utility organization to make important decisions regarding purchasing and generating electric power, unit commitment decisions, load switching, reduce spinning reserve capacity and infrastructure development. Hence load forecasting is viewed as field of research to develop a model so that efficient and reliable operation of power system could be carried out. The paper also presents a short summary of previous techniques pertaining to the adopted methodology. The proposed algorithm uses the discrete wavelet transform for data pre-processing i.e. removing sudden spikes or irregularities in the electrical load data. The regression back propagation algorithm is used for the training purpose. It is found that the proposed system attains a Mean Absolute Percentage Error (MAPE) of around 2.5%.
"A Deep Neural Network Based Approach for Electrical Load Forecasting", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.7, Issue 5, page no.640 - 650, May-2022, Available :https://ijsdr.org/papers/IJSDR2205116.pdf
Volume 7
Issue 5,
May-2022
Pages : 640 - 650
Paper Reg. ID: IJSDR_200355
Published Paper Id: IJSDR2205116
Downloads: 000347199
Research Area: Engineering
Country: Narmadapuram, Madhya Pradesh, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
