Fuzzy Load Forecast with Optimized Parametric Adjustment Using Jaya Optimization Algorithm
- 10.2991/ijcis.d.200617.002How to use a DOI?
- Advanced fuzzy load forecasting model; Hybrid fuzzy-MJO load forecasting algorithm; Minimal total energy error; Minimal peak energy error; Modified Jaya optimization (MJO) algorithm
This paper proposes an advanced fuzzy load forecast method optimized by modified Jaya optimization (MJO) algorithm. MATLAB® platform is used to implement the proposed hybrid Fuzzy-MJO load forecasting algorithm and to verify the outperforming features of a Jaya technique over a fuzzy load forecast model. The novel Fuzzy-MJO load forecasting systems uses the day-time and the daily power consumption to efficiently predict the forecast power consumption. The comparative load forecasting results between proposed Fuzzy-MJO with the latest other algorithms are adequately presented. The full week forecast results using proposed hybrid Fuzzy-MJO load forecasting algorithm demonstrates an outperforming superiority, through the various tested cases, regarding to the total and the peak power error in comparison with the fuzzy-based load forecast model.
- © 2020 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Ho Pham Huy Anh PY - 2020 DA - 2020/06/29 TI - Fuzzy Load Forecast with Optimized Parametric Adjustment Using Jaya Optimization Algorithm JO - International Journal of Computational Intelligence Systems SP - 875 EP - 892 VL - 13 IS - 1 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.d.200617.002 DO - 10.2991/ijcis.d.200617.002 ID - Anh2020 ER -