A HYBRID APPROACH FOR MID-TERM ELECTRICITY PRICE FORECASTING BASED ON SUPPORT VECTOR MACHINE AND NEURAL NETWORKS

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NAZERI NAVID; MOAZZAMI MAJID; SHAHGHOLIAN GHAZANFAR

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Journal: COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING) Year:2018 | Volume:9 | Issue:2 Page(s): 41-54

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Title

A HYBRID APPROACH FOR MID-TERM ELECTRICITY PRICE FORECASTING BASED ON SUPPORT VECTOR MACHINE AND NEURAL NETWORKS

Author(s)

NAZERI NAVID | MOAZZAMI MAJID | SHAHGHOLIAN GHAZANFAR | Issue Writer Certificate

Keywords

AUTOENCODERQ1

ELECTRICITY PRICE FORECASTINGQ1

FEED-FORWARD NEURAL NETWORKQ2

SUPPORT VECTOR MACHINE (SVM)Q2

Abstract

In future smart grids, it's imperative to know the price of electricity market to guide the behavior of consumers and suppliers. This paper presents a hybrid approach for mid-term ELECTRICITY PRICE FORECASTING based on support vector machine and neural networks. In this method, at first, the price upper bound is considered. Then, the training set is divided into two parts including normal price and price spikes. Feature extraction applies on input data sets using stacked auto-encoders and a prediction model trained using each training set. Support Vector Machine (SVM) models with different kernel functions and a two layered feed forward neural network were trained and tested with the proposed method. Simulation results using the proposed method show that this method has a significant effect on the speed of model training and improves forecasting accuracy.

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APA: Copy

NAZERI, NAVID, MOAZZAMI, MAJID, & SHAHGHOLIAN, GHAZANFAR. (2018). A HYBRID APPROACH FOR MID-TERM ELECTRICITY PRICE FORECASTING BASED ON SUPPORT VECTOR MACHINE AND NEURAL NETWORKS. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), 9(2 ), 41-54. SID. https://sid.ir/paper/203003/en

Vancouver: Copy

NAZERI NAVID, MOAZZAMI MAJID, SHAHGHOLIAN GHAZANFAR. A HYBRID APPROACH FOR MID-TERM ELECTRICITY PRICE FORECASTING BASED ON SUPPORT VECTOR MACHINE AND NEURAL NETWORKS. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING)[Internet]. 2018;9(2 ):41-54. Available from: https://sid.ir/paper/203003/en

IEEE: Copy

NAVID NAZERI, MAJID MOAZZAMI, and GHAZANFAR SHAHGHOLIAN, “A HYBRID APPROACH FOR MID-TERM ELECTRICITY PRICE FORECASTING BASED ON SUPPORT VECTOR MACHINE AND NEURAL NETWORKS,” COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), vol. 9, no. 2 , pp. 41–54, 2018, [Online]. Available: https://sid.ir/paper/203003/en

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