Comprehensive analysis of multi-objective optimization algorithms for sustainable hybrid electric vehicle charging systems

NF Alshammari, MM Samy, S Barakat - Mathematics, 2023 - mdpi.com
This study presents a multi-objective optimization approach for designing hybrid renewable
energy systems for electric vehicle (EV) charging stations that considers both economic and …

[HTML][HTML] Evaluating the use of a Net-Metering mechanism in microgrids to reduce power generation costs with a swarm-intelligent algorithm

CG Marcelino, GMC Leite, EF Wanner… - Energy, 2023 - Elsevier
The micro-generation of electricity arises as a clean and efficient alternative to provide
electrical power. However, the unpredictability of wind and solar radiation poses a challenge …

[HTML][HTML] Solving an energy resource management problem with a novel multi-objective evolutionary reinforcement learning method

GMC Leite, S Jiménez-Fernández… - Knowledge-Based …, 2023 - Elsevier
Microgrids have become popular candidates for integrating diverse energy sources into the
power grid as means of reducing fossil fuel usage. Energy Resource Management (ERM) is …

Multi-strategy Slime Mould Algorithm for hydropower multi-reservoir systems optimization

I Ahmadianfar, RM Noori, H Togun, MW Falah… - Knowledge-Based …, 2022 - Elsevier
The challenge to determine the best policies for hydropower multiple reservoir systems is a
high-dimensional and nonlinear problem, making it challenging to attain a global solution …

Hydropower station scheduling with ship arrival prediction and energy storage

E Zhou, X Liu, Z Meng, S Yu, J Mei, Q Qu - Scientific Reports, 2023 - nature.com
Effectiveness improvement in power generation and navigation for grid-connected
hydropower stations have emerged as a significant concern due to the challenges such as …

A constrained multiobjective differential evolution algorithm based on the fusion of two rankings

Z Zeng, X Zhang, Z Hong - Information Sciences, 2023 - Elsevier
The tradeoff between objective functions and constraints is a key issue that needs to be
addressed by constrained multiobjective optimization algorithms, and constraint handling …

Evaluating the risk of uncertainty in smart grids with electric vehicles using an evolutionary swarm-intelligent algorithm

GMC Leite, CG Marcelino, CE Pedreira… - Journal of Cleaner …, 2023 - Elsevier
In the last years, distributed clean energy resources such as solar irradiation, wind
generation and electric vehicles as dispatchable units have been targeted as alternatives to …

Application of machine learning and internet of things techniques in evaluation of English teaching effect in colleges

W Shang - Computational Intelligence and Neuroscience, 2022 - Wiley Online Library
College English classroom teaching evaluation is one of the key issues discussed by all
schools at present. First of all, teachers and students are highly concerned about English …

Low-carbon optimal scheduling for multi-source power systems based on source-load matching under active demand response

J Ye, L Xie, L Ma, Y Bian, C Cui - Solar Energy, 2024 - Elsevier
To reduce the source-load uncertainty and carbon emission levels of the power system, this
study proposes a novel low-carbon economic stochastic optimization scheduling model …

[HTML][HTML] Application of MOMSA algorithm for optimal operation of Karun multi objective multi reservoir dams with the aim of increasing the energy generation

MR Sharifi, S Akbarifard, MR Madadi, K Qaderi… - Energy Strategy …, 2022 - Elsevier
Multi-reservoir system operation is a challenging and complex task, because of the curse of
uncertainties, nonlinearities, dimensionalities and conflicts among the various contradictory …