Proton exchange membrane fuel cells (PEMFCs) are attractive energy sources for clean and efficient power generation; however, their nonlinear characteristics and sensitivity to operating condition variations make maximum power point tracking (MPPT) a challenging control problem. Conventional MPPT techniques often exhibit slow convergence, steady-state oscillations, and degraded performance under dynamic fuel flow variations. This paper proposes a machine learning–driven MPPT control strategy for a PEMFC system integrated with a DC–DC boost converter. The MPPT problem is formulated as a supervised classification task, where machine learning classifiers generate duty-cycle commands to regulate the converter and ensure operation at the maximum power point. A detailed PEMFC–converter model is developed in MATLAB/Simulink-2025b, and a dataset of 3000 labeled samples is generated under varying fuel flow conditions. Several classification algorithms, including decision trees, support vector machines (SVM), k-nearest neighbors (kNN), and ensemble learning methods, are systematically evaluated within an identical simulation framework. Simulation results show that the proposed machine learning-based MPPT controller significantly improves dynamic and steady-state performance. Ensemble Boosted Trees achieve the best overall response with a settling time of approximately 32 ms, peak power overshoot below 4.5%, and steady-state power ripple limited to 1.5%. Quadratic SVM and weighted kNN classifiers also demonstrate stable tracking behavior with power ripple below 2.1%, while overly complex models such as Cubic SVM suffer from large oscillations and reduced accuracy. These results confirm that classification-based machine learning offers an effective, fast, and robust MPPT solution for PEMFC systems under dynamic operating conditions.

The electricity which is generated from the photovoltaic (PV) module needs a couple of requirements for utilizing. Firstly, the PV module should work in maximum power point, and secondly, it is needed a power conversion unit. To calculate to Maximum Power Point (MPP) of a PV module or array, solar radiation, ambient temperature, cloudiness ratio, and even wind speed have to be considered. In this paper, the duty cycle of the power conversion unit has been calculated by considering solar radiation. In these calculations, a conventional method which is perturb and observation (P&O), and another approach which is fuzzy logic control (FLC) were studied and compared by using MATLAB/Simulink.

This paper presents the development and performance testing of the three-level inverter used in distributed power generation systems or Hybrid / Electric /Fuel Cell Vehicles, employing the Space Vector Pulse Width Modulation Technique...

Today, with the global energy crisis and the increasing environmental pollution, it shows that energy is one of the most basic factors in determining the development level of countries. The need for energy in every field of daily life and the increase in the use of technological tools, especially during the pandemic, has showed one more time the importance of energy sources and energy production process. Recent studies shows that, as energy shortage and environmental pollution become increasingly prominent, the renewable energy is replacing conventional energy resources (fossil fuels) all around the world. By using renewable energy sources it is possible to minimize the damage to the environment caused by the CO2 gas released as a result of the use of fossil fuels. The energy obtained from natural sources such as the sun and wind has an important place compared to fossil fuels, as it minimizes the damage to the environment, provides an inexhaustible energy opportunity and is a clean energy source. Solar energy, which is one of the renewable energy sources, is a highly preferred energy source because it does not require any fuel or moving part, does not produce waste material during use, is environmentally friendly and is abundant and free. The geographical location of Turkey is located in the solar energy belt. By this reason, it can be foreseen that a solar power plant that can be established in almost every region can contribute to the regional energy or contribute to the country's economy. In this study, solar energy potentials were investigated for the provinces of Siirt, Adana, Erzincan, Kırşehir, Kütahya, Balıkesir and Amasya, which were selected from seven different regions of Turkey. According to the results of the research, it has been determined that there are similar solar radiation intensities even if they are provinces in different climatic conditions (such as snow, rain, cloud and etc.). This shows how important Turkey is in terms of solar energy potential.

Dünya enerji talebinin artmasıyla birlikte, sınırlı fosil yakıt kaynakları ve bunların çevresel etkileri göz önüne alındığında, güneş enerjisi alternatif bir çözüm olarak öne çıkmaktadır. Bu bağlamda, fotovoltaik panellerin verimliliği üzerindeki etkilerin daha detaylı bir şekilde anlaşılması, güneş enerjisi teknolojisinin geliştirilmesi ve daha verimli enerji üretimi için önem taşımaktadır. Güneş panellerinin tasarımında kullanılan malzemelerin seçimi, üretim teknikleri ve test süreçlerinin, panelin nihai verimliliği üzerinde belirleyici olduğu bilinmektedir. Bu nedenle, bu çalışmada, güneş paneli tasarımı ve üretimindeki değişkenlerin verimlilik üzerindeki etkilerin sistematik bir şekilde analiz edilmesi amaçlanmıştır. Tasarlanan güneş panelleri üzerinde, Sun-Simulator cihazı kullanılarak farklı durumlar için tesler yapılarak, bu panellere ait akım-gerilim (I-V) karakteristikleri elde edilmiştir. Gölgelenme, kirlilik, gibi çevresel faktörler ile çeşitli fiziksel faktörlerin güneş panellerinin verimliliği üzerindeki etkileri de detaylı bir şekilde incelmiş ve analiz edilmiştir. Karşılaşılan sorunların giderilmesiyle sürdürülebilir enerji dönüşümüne katkı sağlanması amaçlanmaktadır.