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Energies
Volume 14
Issue 12
10.3390/en14123591
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Article

Electrical Load Prediction Using Interval Type-2 Atanassov Intuitionist Fuzzy System: Gravitational Search Algorithm Tuning Approach

by
Mojtaba Ahmadieh Khanesar
*,
Jingyi Lu
,
Thomas Smith
and
David Branson
Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK
*
Author to whom correspondence should be addressed.
Energies 2021, 14(12), 3591; https://doi.org/10.3390/en14123591
Submission received: 24 May 2021 / Revised: 7 June 2021 / Accepted: 11 June 2021 / Published: 16 June 2021
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Abstract

Establishing accurate electrical load prediction is vital for pricing and power system management. However, the unpredictable behavior of private and industrial users results in uncertainty in these power systems. Furthermore, the utilization of renewable energy sources, which are often variable in their production rates, also increases the complexity making predictions even more difficult. In this paper an interval type-2 intuitionist fuzzy logic system whose parameters are trained in a hybrid fashion using gravitational search algorithms with the ridge least square algorithm is presented for short-term prediction of electrical loading. Simulation results are provided to compare the performance of the proposed approach with that of state-of-the-art electrical load prediction algorithms for Poland, and five regions of Australia. The simulation results demonstrate the superior performance of the proposed approach over seven different current state-of-the-art prediction algorithms in the literature, namely: SVR, ANN, ELM, EEMD-ELM-GOA, EEMD-ELM-DA, EEMD-ELM-PSO and EEMD-ELM-GWO.
Keywords: electrical load prediction; interval type-2 Atanassov intuitionist fuzzy logic system; ridge least square algorithm; gravitational search algorithm electrical load prediction; interval type-2 Atanassov intuitionist fuzzy logic system; ridge least square algorithm; gravitational search algorithm

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MDPI and ACS Style

Khanesar, M.A.; Lu, J.; Smith, T.; Branson, D. Electrical Load Prediction Using Interval Type-2 Atanassov Intuitionist Fuzzy System: Gravitational Search Algorithm Tuning Approach. Energies 2021, 14, 3591. https://doi.org/10.3390/en14123591

AMA Style

Khanesar MA, Lu J, Smith T, Branson D. Electrical Load Prediction Using Interval Type-2 Atanassov Intuitionist Fuzzy System: Gravitational Search Algorithm Tuning Approach. Energies. 2021; 14(12):3591. https://doi.org/10.3390/en14123591

Chicago/Turabian Style

Khanesar, Mojtaba Ahmadieh, Jingyi Lu, Thomas Smith, and David Branson. 2021. "Electrical Load Prediction Using Interval Type-2 Atanassov Intuitionist Fuzzy System: Gravitational Search Algorithm Tuning Approach" Energies 14, no. 12: 3591. https://doi.org/10.3390/en14123591

APA Style

Khanesar, M. A., Lu, J., Smith, T., & Branson, D. (2021). Electrical Load Prediction Using Interval Type-2 Atanassov Intuitionist Fuzzy System: Gravitational Search Algorithm Tuning Approach. Energies, 14(12), 3591. https://doi.org/10.3390/en14123591

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