A review of uncertainty modelling techniques for probabilistic stability analysis of renewable-rich power systems

AM Hakami, KN Hasan, M Alzubaidi, M Datta - Energies, 2022 - mdpi.com
In pursuit of identifying the most accurate and efficient uncertainty modelling (UM)
techniques, this paper provides an extensive review and classification of the available UM …

Prediction of IC engine performance and emission parameters using machine learning: A review

K Karunamurthy, AA Janvekar, PL Palaniappan… - Journal of Thermal …, 2023 - Springer
The human kind is facing various natural calamities such as Elnino, forest fires, climate
change, etc., due to environmental degradation and pollution. The United Nations has come …

Solar photovoltaic Maximum Power Point Tracking controller optimization using Grey Wolf Optimizer: A performance comparison between bio-inspired and traditional …

J Aguila-Leon, C Vargas-Salgado… - Expert Systems with …, 2023 - Elsevier
Solar photovoltaic systems are widely used; however, their performance is bound to weather
conditions, depending on irradiation, temperature, and the effect of shadows. Maximum …

Reduced simulative performance analysis of variable step size ANN based MPPT techniques for partially shaded solar PV systems

SR Kiran, CHH Basha, VP Singh… - IEEE …, 2022 - ieeexplore.ieee.org
The rise in energy demand in the present scenario can be balanced with the help of solar
Photovoltaic (PV) systems. But, the nonlinearity in IV and PV characteristics makes it very …

Real-time implementation of a novel MPPT control based on the improved PSO algorithm using an adaptive factor selection strategy for photovoltaic systems

CB Regaya, H Hamdi, F Farhani, A Marai, A Zaafouri… - ISA transactions, 2024 - Elsevier
Abstract Particle Swarm Optimization (PSO) is considered as one of Maximum Power Point
Tracking (MPPT) controller algorithm developed for PhotoVoltaic system (PV) to guarantee a …

Control and implementation of an energy management strategy for a PV–wind–battery microgrid based on an intelligent prediction algorithm of energy production

S Mahjoub, L Chrifi-Alaoui, S Drid, N Derbel - Energies, 2023 - mdpi.com
This paper describes an energy management strategy for a DC microgrid that utilizes a
hybrid renewable energy system (HRES) composed of a photovoltaic (PV) module, a wind …

[HTML][HTML] Improved coot optimizer algorithm-based MPPT for PV systems under complex partial shading conditions and load variation

AT Naser, KK Mohammed, NF Ab Aziz… - Energy Conversion and …, 2024 - Elsevier
Solar power is considered one of the most common renewable energy sources. However,
the effective harnessing of maximum solar energy in photovoltaic (PV) systems faces a …

Experimental validation of a low-cost maximum power point tracking technique based on artificial neural network for photovoltaic systems

AF Abouzeid, H Eleraky, A Kalas, R Rizk… - Scientific Reports, 2024 - nature.com
Maximum power point tracking (MPPT) is a technique involved in photovoltaic (PV) systems
for optimizing the output power of solar panels. Traditional solutions like perturb and …

A novel fault detection technique for PV systems based on the K-means algorithm, coded wireless Orthogonal Frequency Division Multiplexing and thermal image …

A Et-taleby, Y Chaibi, M Boussetta, A Allouhi… - Solar Energy, 2022 - Elsevier
Solar energy is considered one of the most ecological energy systems, which provides
clean, reliable, and unlimited power. However, the solar system can be exposed during its …

A novel adaptive PID controller design for a PEM fuel cell using stochastic gradient descent with momentum enhanced by whale optimizer

MY Silaa, O Barambones, A Bencherif - Electronics, 2022 - mdpi.com
This paper presents an adaptive PID using stochastic gradient descent with momentum
(SGDM) for a proton exchange membrane fuel cell (PEMFC) power system. PEMFC is a …