Advancing solar energy forecasting with modified ANN and light GBM learning algorithms

AIMS energy, Journal Year: 2024, Volume and Issue: 12(2), P. 350 - 386

Published: Jan. 1, 2024

<abstract> <p>In the evolving field of solar energy, precise forecasting Solar Irradiance (SI) stands as a pivotal challenge for optimization photovoltaic (PV) systems. Addressing inadequacies in current techniques, we introduced advanced machine learning models, namely Rectified Linear Unit Activation with Adaptive Moment Estimation Neural Network (RELAD-ANN) and Support Vector Machine Individual Parameter Features (LSIPF). These models broke new ground by striking an unprecedented balance between computational efficiency predictive accuracy, specifically engineered to overcome common pitfalls such overfitting data inconsistency. The RELAD-ANN model, its multi-layer architecture, sets standard detecting nuanced dynamics SI meteorological variables. By integrating sophisticated regression methods like Regression (SVR) Lightweight Gradient Boosting Machines (Light GBM), our results illuminated intricate relationship influencing factors, marking novel contribution domain energy forecasting. With R² 0.935, MAE 8.20, MAPE 3.48%, model outshone other signifying potential accurate reliable forecasting, when compared existing Multi-Layer Perceptron, Long Short-Term Memory (LSTM), Multilayer-LSTM, Gated Recurrent Unit, 1-dimensional Convolutional Network, while LSIPF showed limitations ability. Light GBM emerged robust approach evaluating environmental influences on SI, outperforming SVR model. Our findings contributed significantly systems could be applied globally, offering promising direction renewable management real-time forecasting.</p> </abstract>

Language: Английский

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Enhancing Desalination and Liquid Desiccant Regeneration Efficiency Through a Hybrid Solar Still

Advances in chemical and materials engineering book series, Journal Year: 2024, Volume and Issue: unknown, P. 133 - 152

Published: July 5, 2024

Research has been conducted on the use of hybrid solar stills for desalinating salt water and regenerating weak liquid desiccant (LD). Different experimental settings were used to explore effects forced convection a thermal energy storage medium desorption from LD. Type-I employed desiccants consisting 35 wt. % magnesium chloride Type-II 45 potassium Formate; in bottom basin, salinity level 1 cm was maintained. desorbed 780 ml/m2 per day using mild desiccant, while 810 ml/m2. Total daily distillate output 295 320 Type II I. The concentration rose 2.5 1.5 I II. Hybrid as regenerators LD cooling systems have ability absorb latent heat load humid air, which is 0.132 0.145 kW d-1 respectively. still managed attain average overall efficiency 21.6 28.4% during hours bright sunshine,

Language: Английский

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Improving Solar Still Performance With Porites Coral Biomaterial

Advances in chemical and materials engineering book series, Journal Year: 2024, Volume and Issue: unknown, P. 283 - 302

Published: July 5, 2024

The most benefits of solar desalination are that it is cheap and environmentally good. This study investigated the potential a novel biomaterial called Porites coral to enhance efficiency stills by storing energy in porous medium. final product was dubbed Coral Solar Still System (CSSS). When light levels low, releases heat has stored into sea. surface also makes great absorber, which causes water get hotter since lot gets absorbed. research conducted based on weather conditions observed Thoothukudi, India. Results demonstrate 12.6% improvement productivity as compared conventional still (CSS) when storage accomplished utilising media containing coral. CSS, CSSS achieved 13% increase an 11% exergy efficiency.

Language: Английский

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Enhanced accuracy in solar irradiance forecasting through machine learning stack-based ensemble approach

International Journal of Green Energy, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 24

Published: Jan. 10, 2025

Accurate solar irradiance (SI) prediction is vital for optimizing photovoltaic systems. This study addresses shortcomings in existing forecasting methods by exploring advanced machine-learning techniques using meteorological satellite data. We develop three novel models SI forecasting: Stack-based Ensemble Fusion with Meta-Neural Network (SEFMNN), Extreme Gradient Boosting-Squared Error (XGB-SE), and Learning Machine (ELM). These predict All-sky Clear-sky shortwave across Chinese provinces (Guangdong, Shandong, Zhejiang) one Saudi Arabian province (Najran). The SEFMNN model combines Artificial Neural (ANN), Random Forest (RF), Support Vector (SVM) to improve accuracy. XGB-SE employs a specialized loss function manage extreme values historical are designed mitigate overfitting data inconsistency while balancing computational efficiency predictive Comparative analysis reveals that outperform the ELM model, achieving an R2 of 0.9979, MAE 0.0231, MSE 0.0020 Najran. demonstrates significantly enhances forecasting, aiding efficient system planning operation.

Language: Английский

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Adam Lyrebird Optimization-Based DLSTM for Solar Irradiance Prediction Using Time Series Data

Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 17 - 30

Published: Jan. 1, 2025

Language: Английский

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Impact of Nanoparticle Concentration on Thermal Properties of Nanofluids in Heat Exchangers

E3S Web of Conferences, Journal Year: 2025, Volume and Issue: 619, P. 05008 - 05008

Published: Jan. 1, 2025

This research experimentally examined the efficacy of a shell & tube heat transfer running on nanofluids composed copper nanoparticles with water (Cu-W) and alumina (Al 2 O 3 -W). Surface treatment was omitted during preparation Cu-W Al -W nanofluids. Research focused how their concentration in given volume affected coefficient transfer, pressure drop, viscosity, thermal conductivity, Nusselt number. Because one-of-a-kind intrinsic properties, results demonstrated that nanofluids’ conductivity raised by 29% 39%, respectively, when 0.12 wt.% Cu were added. Furthermore, friction factor increased due to higher density convection elevated two-phase mixture its improved conductivity. nanofluid outperformed terms drop thermophysical characteristics.

Language: Английский

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Comparative analysis of flat heat pipe heat exchanger with conventional heat recovery systems in steel industry

E3S Web of Conferences, Journal Year: 2025, Volume and Issue: 619, P. 03008 - 03008

Published: Jan. 1, 2025

The steel industry relies on heating for the majority of its energy needs. Reduced production costs and emissions greenhouse gases are two major benefits recovering residual heat. A Flat Heat Pipe (FHP) heat transfer-based retrieval system is outlined in this study as procedures conception, production, evaluation. Stainless Steel (SS) Pipes (HP) integrated into FHP a shell-and-tube configuration, connected by top bottom header. After analyzing FHP’s thermal performance both lab an industry, improved processing temperature reported. Predicting device’s was made possible with use theoretical modeling tool. results acquired from experiments those theory reasonable accord. findings indicate that cutting-edge, highly efficient method these types industrial applications .

Language: Английский

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Experimental investigation to improve the performance of thermal storage unit with flat Microheat pipe arrays

E3S Web of Conferences, Journal Year: 2025, Volume and Issue: 619, P. 03009 - 03009

Published: Jan. 1, 2025

In this study, the experimental investigation is focused on Thermal Storage Unit (TSU) that utilizes flat Microheat pipe array as its heat transmission core. power intensity suggested a thorough TSU evaluation metric. Additionally, we look into how transfer characteristics of are impacted by air side and phase change materials length proportions. Heat properties, thermal resistance distribution, phase-change performance examined. According to findings, rate among was substantially enhanced FMHPAs. On side, almost three times higher than PCM side. With storage section 480 mm heating cooling lengths ranging from 130, 160 190 mm, optimal achieved with length.

Language: Английский

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Enhancing Desalination Systems with IoT, Solar Energy, and Advanced Sensor Technologies

E3S Web of Conferences, Journal Year: 2025, Volume and Issue: 619, P. 02009 - 02009

Published: Jan. 1, 2025

Desalination management, the process of turning saltwater into potable water, has long been under pressure from rising water demands and environmental degradation, necessitating innovative solutions. We can streamline a number procedures that used to be labour-intensive resource-intensive. Improving administration treatment is one such thing. This study proposes smart environment regulate facilities offers workable model for system. The suggested method collects data analyses it find best way desalinate water. Incorporating enabling technologies like cloud portal, network communication, internet things, solar-powered sensors an old purification system what desalination framework all about seawater. To ensure systems run smoothly efficiently, makes use cutting- edge technology. Utilizing solar energy, dual membrane employs time-honoured techniques purify saltwater, creating irrigation-ready was cost- effective, producing 0.51 m 3 / l freshwater salt concentration 12 g/ with energy usage 9.12 KWh/m.

Language: Английский

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Enhancing the Efficiency and Schedule of Solar Thermal Power Plants by Utilizing Thermal Storage Devices to Minimize Carbon Emissions

E3S Web of Conferences, Journal Year: 2025, Volume and Issue: 619, P. 02004 - 02004

Published: Jan. 1, 2025

The renewable energy method of photo thermal power generation has great promise for future advancements. core structure and characteristics flow plants are often overlooked when operating scheduling these facilities. This paper details the architecture a Photo Thermal Power Plant (PTPP) with Storage System (TSS) examines primary patterns plant in order to develop schedule optimization model facility that runs autonomously generates no carbon emissions. results simulation showed photovoltaic plant’s output capacity revenue may be improved by adding TSS self- was originally developed planning peak valley pricing. When more than 6 hours, there fine inadequate simulation. A rise 84.9 % achieved increasing (TS) system’s capacity. Carbon emissions dropped from 26.4×103 tons 22.1×103 overall cost went down 136531.02 k ₹ 102247.98 enhanced 0 8 hours. In comparison previous research, this study’s exhaustive analysis flows yields thorough rigorous response. Improving long-term viability sources, developing efficient systems, new clean technologies goals study.

Language: Английский

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