A hybrid metaheuritic technique developed for hourly load forecasting

Mahrami, Mohsen, Rahmani, Rasoul, Seyedmahmoudian, Mohammadmehdi, Mashayekhi, Reza, Karimi, Hediyeh and Hosseini, Ebrahim 2016, A hybrid metaheuritic technique developed for hourly load forecasting, Complexity, vol. 21, no. S1, pp. 521-532, doi: 10.1002/cplx.21766.

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Title A hybrid metaheuritic technique developed for hourly load forecasting
Author(s) Mahrami, Mohsen
Rahmani, Rasoul
Seyedmahmoudian, Mohammadmehdi
Mashayekhi, Reza
Karimi, Hediyeh
Hosseini, Ebrahim
Journal name Complexity
Volume number 21
Issue number S1
Start page 521
End page 532
Total pages 12
Publisher John Wiley & Sons
Place of publication Chichester, Eng.
Publication date 2016-09
ISSN 1076-2787
Keyword(s) complex forecasting
fuzzy inference
radian movement optimization
electricity demand
Summary Electricity load forecasting has become one of the most functioning tools in energy efficiency and load management and utility companies which has been made very complex due to deregulation. Due to the importance of providing a secure and economic electricty for the consumers, having a reliable and robust enough forecast engine in short-term load management is very needful. Fuzzy inference system is one of primal branches of Artificial Intelligence techniques which has been widely used for different applications of decision making in complex systems. This paper aims to develop a Fuzzy inference system as a main forecast engine for Short term Load Forecasting (STLF) of a city in Iran. However, the optimization of this platform for this special case remains a basic problem. Hence, to address this issue, the Radial Movement Optimization (RMO) technique is proposed to optimize the whole Fuzzy platform. To support this idea, the accuracy of the proposed model is analyzed using MAPE index and an average error of 1.38% is obtained for the forecast load demand which represents the reliability of the proposed method. Finally, results achieved by this method, demonstrate that an adaptive two-stage hybrid system consisting of Fuzzy & RMO can be an accurate and robust enough choice for STLF problems.
Language eng
DOI 10.1002/cplx.21766
Field of Research 010299 Applied Mathematics not elsewhere classified
090608 Renewable Power and Energy Systems Engineering (excl Solar Cells)
090607 Power and Energy Systems Engineering (excl Renewable Power)
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016, Wiley Periodicals
Persistent URL http://hdl.handle.net/10536/DRO/DU:30084725

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