NDLI: Electricity price forecasting using a new data fusion algorithm

Content Provider	IET Digital Library
Author	Darudi, Ali Bashari, Masoud Javidi, Mohammad Hossein
Abstract	Accurate price forecasting is crucial for all market participants in electricity markets. This study presents a hybrid price forecasting framework based on a new data fusion algorithm. Owing to the complexity and distinct nature of the electricity price, a single forecast engine cannot capture all different patterns of the price signals. Hence, this study focuses on a hybrid forecasting method to extract the advantages of several forecasting engines. In the proposed method, artificial neural network, adaptive neuro-fuzzy inference system and autoregressive moving average are employed as primary forecast engines (agents) which provide three independent price forecasts. Then, a new data fusion algorithm, the modified ordered weighted average (modified OWA), is proposed to combine the three forecasts to generate a single unified price forecast. Hopefully, the fusion's output outperforms all the agents’ forecasts. The author's proposed fusion algorithm, unlike conventional OWA, uses the feedback from the agents’ error. The proposed framework is evaluated on the Spanish electricity market. The results confirm the ability of the proposed fusion framework to provide more accurate forecasts compared with the input agents forecasts. Results are also compared with some of the recent electricity price forecasting methods.
Starting Page	1382
Ending Page	1390
Page Count	9
ISSN	17518687
Volume Number	9
e-ISSN	17518695
Issue Number	Issue 12, Sep (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/9/12
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2014.0653
Journal	IET Generation, Transmission & Distribution
Publisher Date	2015-04-13
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaptive Neuro-fuzzy Inference System Artificial Neural Network Autoregressive Moving Average Autoregressive Moving Average Processes Data Fusion Algorithm Electricity Price Forecasting Fuzzy Neural Nets Hybrid Price Forecasting Framework Inference Mechanisms Knowledge Engineering Technique Modified Ordered Weighted Average Modified OWA Neural Computing Technique Power Engineering Computing Power Market Power System Economics Power System Managemen Power System Operation Pricing Primary Forecast Engines Sensor Fusion Spanish Electricity Market Statistics
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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