Qian Wang¹, Xiaolong Yang^2,*, Di Pu³, Yingying Fan⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 269-286, 2022, DOI:10.32604/cmes.2022.016437

Abstract This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine (DRBM) optimized by the Lion algorithm (LA). Firstly, two factors including transmission and distribution price reform (TDPR) and 5G station construction were comprehensively incorporated into the consideration of influencing factors, and the fuzzy threshold method was used to screen out critical influencing factors. Then, the LA was used to optimize the parameters of the DRBM model to improve the model's prediction accuracy, and the model was trained with the selected influencing factors and investment. Finally, the LA-DRBM model was used to predict the… More >

Nour EL Yakine Kouba^a, Mohamed Menaa^a, Kambiz Tehrani^b, Mohamed Boudour^a

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 279-294, 2019, DOI:10.31209/2018.100000007

Abstract This paper presents the use of a novel nature inspired meta-heuristic algorithm namely Ant Lion Optimizer (ALO), which is inspired from the ant lions hunting mechanism to enhance the frequency regulation and optimize the load frequency control (LFC) loop parameters. The frequency regulation issue was formulated as an optimal load frequency control problem (OLFC). The proposed ALO algorithm was applied to reach the best combination of the PID controller parameters in each control area to achieve both frequency and tie-line power flow exchange deviations minimization. The control strategy has been tested firstly with the standard two-area power system, followed by… More >