Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline

Article Types

Countries / Regions

Search Results (1)

Search Parameters:
Keywords = teaching-learning-based turbulent flow of water-based optimization (TLTFWO)

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
37 pages, 2537 KB  
Article
Power Flow Optimization by Integrating Novel Metaheuristic Algorithms and Adopting Renewables to Improve Power System Operation
by Mohana Alanazi, Abdulaziz Alanazi, Almoataz Y. Abdelaziz and Pierluigi Siano
Appl. Sci. 2023, 13(1), 527; https://doi.org/10.3390/app13010527 - 30 Dec 2022
Cited by 13 | Viewed by 2508
Abstract
The present study merges the teaching and learning algorithm (TLBO) and turbulent flow of water optimization (TFWO) to propose the hybrid TLTFWO. The main purpose is to provide optimal power flow (OPF) of the power network. To this end, the paper also incorporated [...] Read more.
The present study merges the teaching and learning algorithm (TLBO) and turbulent flow of water optimization (TFWO) to propose the hybrid TLTFWO. The main purpose is to provide optimal power flow (OPF) of the power network. To this end, the paper also incorporated photovoltaics (PV) and wind turbine (WT) generating units. The estimated output power of PVs/WTs and voltage magnitudes of PV/WT buses are included, respectively, as dependent and control (decision) variables in the mathematical expression of OPF. Real-time wind speed and irradiance measurements help estimate and predict the power generation by WT/PV units. An IEEE 30-bus system is also used to verify the accuracy and validity of the suggested OPF and the hybrid TLTFWO method. Moreover, a comparison is made between the suggested approach and the competing algorithms in solving the OPF problem to demonstrate the capability of the TLTFWO from robustness and efficiency perspectives. Full article
(This article belongs to the Section Energy Science and Technology)
Show Figures

Figure 1

Back to TopTop