Solar photovoltaic power prediction using artificial neural network and multiple regression considering ambient and operating conditions

Energy Conversion and Management, Journal Year: 2023, Volume and Issue: 288, P. 117186 - 117186

Published: May 18, 2023

Language: Английский

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A comprehensive analysis of the emerging modern trends in research on photovoltaic systems and desalination in the era of artificial intelligence and machine learning

Heliyon, Journal Year: 2024, Volume and Issue: 10(3), P. e25407 - e25407

Published: Feb. 1, 2024

Integration of photovoltaic (PV) systems, desalination technologies, and Artificial Intelligence (AI) combined with Machine Learning (ML) has introduced a new era remarkable research innovation. This review article thoroughly examines the recent advancements in field, focusing on interplay between PV systems water within framework AI ML applications, along it analyses current to identify significant patterns, obstacles, prospects this interdisciplinary field. Furthermore, incorporation methods improving performance systems. includes raising their efficiency, implementing predictive maintenance strategies, enabling real-time monitoring. It also explores transformative influence intelligent algorithms techniques, specifically addressing concerns pertaining energy usage, scalability, environmental sustainability. provides thorough analysis literature, identifying areas where is lacking suggesting potential future avenues for investigation. These have resulted increased decreased expenses, improved sustainability system. By utilizing artificial intelligence freshwater productivity can increase by 10 % efficiency. offers informative perspectives researchers, engineers, policymakers involved renewable technology. sheds light latest desalination, which are facilitated ML. The aims guide towards more sustainable technologically advanced future.

Language: Английский

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A novel MPPT technology based on dung beetle optimization algorithm for PV systems under complex partial shade conditions

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: March 18, 2024

Abstract Solar power is a renewable energy source, and its efficient development utilization are important for achieving global carbon neutrality. However, partial shading conditions cause the output of PV systems to exhibit nonlinear multipeak characteristics, resulting in loss power. In this paper, we propose novel Maximum Power Point Tracking (MPPT) technique based on Dung Beetle Optimization Algorithm (DBO) maximize under various weather conditions. We performed performance comparison analysis DBO with existing renowned MPPT techniques such as Squirrel Search Algorithm, Cuckoo search Optimization, Horse Herd Particle Swarm Adaptive Factorized Gray Wolf Hybrid Nelder-mead. The experimental validation carried out HIL + RCP physical platform, which fully demonstrates advantages terms tracking speed accuracy. results show that proposed achieves 99.99% maximum point (GMPP) efficiency, well improvement 80% convergence rate stabilization rate, 8% average A faster, more robust GMPP significant contribution controller.

Language: Английский

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Chaotic Spiral based Reconfiguration scheme for the Mitigation of Power Loss in Solar Photovoltaic (PV) systems

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104111 - 104111

Published: Jan. 1, 2025

Language: Английский

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Optimizing efficiency of Vehicle-to-Grid system with intelligent management and ANN-PSO algorithm for battery electric vehicles

Electric Power Systems Research, Journal Year: 2023, Volume and Issue: 226, P. 109936 - 109936

Published: Oct. 17, 2023

Language: Английский

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Modeling and Optimization of Hydraulic and Thermal Performance of a Tesla Valve Using a Numerical Method and Artificial Neural Network

Entropy, Journal Year: 2023, Volume and Issue: 25(7), P. 967 - 967

Published: June 22, 2023

The Tesla valve is a non-moving check used in various industries to control fluid flow. It passive flow device that does not require external power operate. Due its unique geometry, it causes more pressure drop the reverse direction than forward direction. This device’s optimal performance heat transfer applications has led use of designs sinks and exchangers. study investigated with unconventional geometry through numerical analysis. Two geometrical parameters inlet velocity were selected as input variables. Also, ratio (PDR) temperature difference (TDR) chosen responses. By leveraging data, artificial neural networks trained construct precise prediction models for different conditions then reported using genetic algorithm method models. results indicated coefficient determination both was above 0.99, demonstrating high accuracy. most PDR value 4.581, indicating 358.1% higher best TDR response found be 1.862.

Language: Английский

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Maximizing Green Hydrogen Production from Water Electrocatalysis: Modeling and Optimization

Journal of Marine Science and Engineering, Journal Year: 2023, Volume and Issue: 11(3), P. 617 - 617

Published: March 15, 2023

The use of green hydrogen as a fuel source for marine applications has the potential to significantly reduce carbon footprint industry. development sustainable and cost-effective method producing gained lot attention. Water electrolysis is best most environmentally friendly hydrogen-based renewable energy. Therefore, identifying ideal operating parameters water process critical production. Three controlling factors must be appropriately identified boost generation, namely time (min), electric voltage (V), catalyst amount (μg). proposed methodology contains following two phases: modeling optimization. Initially, robust model in terms was established using an adaptive neuro-fuzzy inference system (ANFIS) based on experimental dataset. After that, modern pelican optimization algorithm (POA) employed identify duration, voltage, enhance Compared measured datasets response surface (RSM), integration ANFIS POA improved generated by around 1.3% 1.7%, respectively. Overall, this study highlights optimal parameter identification optimizing performance solar-powered electrocatalysis systems production applications. This research could pave way more widespread adoption technology industry, which would help industry’s promote sustainability.

Language: Английский

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Solar Photovoltaic Energy as a Promising Enhanced Share of Clean Energy Sources in the Future—A Comprehensive Review

Energies, Journal Year: 2023, Volume and Issue: 16(24), P. 7919 - 7919

Published: Dec. 5, 2023

The use of solar energy is now a common and modern alternative that many countries throughout the world have adopted. Different studies on PV systems been documented in literature; however, several reviews focus excessively particular facets modules. In this paper, literature published between 2000 2023 was reviewed thoroughly. This review structured three main parts. Primarily, factors impacting dust deposition modules are discussed. These include temperature, wind speed, inclination angle, location, climatic conditions, photovoltaic module surface characteristics, characteristics. Many methods for mitigating reducing as well approaches to cleaning also study. types modules, together with their most important characteristics operational effectiveness, presented. As more panels expand end life (EOL), solutions required recycle dispose at lowest economic cost least environmental damage through reduced carbon emissions greenhouse gases. Subsequently, paper further green environment waste recycling its costs. Moreover, integrating other clean constituting an source hard-to-reach areas fuel Therefore, comprehensive production helpful increased share various sectors future.

Language: Английский

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Towards highly efficient solar photovoltaic thermal cooling by waste heat utilization: A review

Energy Conversion and Management X, Journal Year: 2024, Volume and Issue: 23, P. 100671 - 100671

Published: July 1, 2024

Photovoltaic (PV) systems are popular for their reliability and zero fuel costs. However, only around 20 % of solar energy is converted into electricity, while the remainder dissipated as waste heat. Excessive heat affects lifespan PV systems, leading to abnormal operating temperatures. In this notion, Photovoltaic-thermal (PV/T) introduced extract through various cooling techniques harness electrical thermal energies, demonstrating capabilities experimental modeling techniques. Researchers have sought develop optimized based on empirical, semi-empirical, AI-based efficient execution PV/T systems. This study reviews current optimization developments in focusing multiple numerical designs. Various methods, including air, water, phase change materials (PCM) with nanofluids, examined promising contributions efficiency enhancement. Additionally, methods been investigated by incorporating automated processes employing self-automation These aim reduce overall cost establish a self-sustaining performance. Finally, challenges recommendations future research enhancement highlighted.

Language: Английский

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An adapted model predictive control MPPT for validation of optimum GMPP tracking under partial shading conditions

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: April 24, 2024

Abstract The energy generation efficiency of photovoltaic (PV) systems is compromised by partial shading conditions (PSCs) solar irradiance with many maximum power points (MPPs) while tracking output power. Addressing this challenge in the PV system, article proposes an adapted hybrid control algorithm that tracks global point (GMPP) preventing it from settling at different local (LMPPs). proposed scheme involves deployment a 3 × multi-string array single modified boost converter model and perturb observe-based predictive (APO-MPC) algorithm. In contrast to traditional strategies, technique effectively extracts stabilizes predicting upcoming future states through computation reference current. regulates voltage current levels whole array, dynamically adjusts converter's operation track GMPP minimizing cost function MPC. Additionally, reduces hardware costs eliminating need for sensor, all ensuring effective across variety climatic profiles. research illustrates efficient validation method accurate stable convergence towards minimal sensors, consequently reducing overall expenses. Simulation hardware-based outcomes reveal approach outperforms classical techniques terms both cost-effectiveness extraction efficiency, even under PSCs constant, rapidly changing, linearly changing irradiances.

Language: Английский

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