A review on machine learning forecasting growth trends and their real-time applications in different energy systems

T Ahmad, H Chen - Sustainable Cities and Society, 2020 - Elsevier
Energy forecasting and planning play an important role in energy sector development and
policy formulation. The forecasting model selection mostly based on the availability of the …

Different ways to improve parabolic trough solar collectors' performance over the last four decades and their applications: A comprehensive review

W Ajbar, A Parrales, A Huicochea… - … and Sustainable Energy …, 2022 - Elsevier
This paper presents an extensive review of experimental, numerical, and numerical-
experimental studies focused on compiling different aspects that lead to improved PTSC …

Artificial neural network (ANN) based prediction and optimization of an organic Rankine cycle (ORC) for diesel engine waste heat recovery

F Yang, H Cho, H Zhang, J Zhang, Y Wu - Energy conversion and …, 2018 - Elsevier
This paper presents performance prediction and optimization of an organic Rankine cycle
(ORC) for diesel engine waste heat recovery based on artificial neural network (ANN). An …

[HTML][HTML] Energy, exergy, environmental and economic comparison of various solar thermal systems using water and Thermia Oil B base fluids, and CuO and Al2O3 …

W Huang, M Marefati - Energy Reports, 2020 - Elsevier
Recently, the use of solar thermal collectors has increased significantly. In the present work,
energy, exergy, enviroeconomic and exergoeconomic analyses of various solar thermal …

Multi-objective optimization of concentrated solar power plants from an energy-water-environment nexus perspective under distinct climatic conditions–Part B: environ …

M Ahmad, M Zeeshan - Journal of Cleaner Production, 2023 - Elsevier
The objective of this study is to include environmental impact in optimization of concentrated
solar power plants previously limited to techno-economic analysis only. Performance of …

Forecasting solar-thermal systems performance under transient operation using a data-driven machine learning approach based on the deep operator network …

JD Osorio, Z Wang, G Karniadakis, S Cai… - Energy Conversion and …, 2022 - Elsevier
Modeling and prediction of the dynamic behavior of thermal systems operating under
intermittent energy input and variable load requirements represent one of the greatest …

Multi-step ahead forecasting in electrical power system using a hybrid forecasting system

P Du, J Wang, W Yang, T Niu - Renewable Energy, 2018 - Elsevier
Managers and researchers have put more emphasis on electrical power system forecasting
to obtain effective management in electrical power system. However, enhancing prediction …

Thermoeconomic investigation and multi-objective optimization of a novel efficient solar tower power plant based on supercritical Brayton cycle with inlet cooling

J Zhou, MA Ali, FM Zeki, HA Dhahad - Thermal Science and Engineering …, 2023 - Elsevier
The solar tower power plant technology offers a promising potential for large scale power
generation, amongst various solar-based systems. To decrease the produced electricity cost …

Thermoeconomic assessment of a renewable hybrid RO/PEM electrolyzer integrated with Kalina cycle and solar dryer unit using response surface methodology (RSM …

W Sun, L Feng, AM Abed, A Sharma, A Arsalanloo - Energy, 2022 - Elsevier
In this research, a non-dimension model of renewable generation system encompassing a
solar-geothermal driven Proton Exchange Membrane (PEM) electrolyzer in integration with …

Hybrid modeling for the multi-criteria decision making of energy systems: An application for geothermal district heating system

AE Arslan, O Arslan, MS Genc - Energy, 2024 - Elsevier
The efficiency analysis technique with output satisficing (EATWOS) is a successful tool for
determining the most efficient design for energy systems. Since EATWOS is rationally based …