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The use of the digital twin and artificial intelligence in solar power plants? 

Settling time
Maximum power point tracking
Reinforcement learning
Maximum power principle
Controller (irrigation)
Best insight from top research papers

The integration of digital twin technology and artificial intelligence (AI) in solar power plants is proving to be instrumental in enhancing efficiency, optimizing operations, and enabling intelligent management. Digital twins, as proposed in various studies, offer a virtual representation of physical systems, allowing for advanced monitoring, predictive maintenance, and performance optimization. AI techniques, such as machine learning algorithms and reinforcement learning, are utilized within digital twins to improve system behavior prediction, detect malfunctions early, and enhance control strategies. These technologies enable real-time simulation, training, and adjustment of control algorithms, leading to increased power output, reduced downtime, and improved overall performance of solar photovoltaic (PV) systems.

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Papers (5)Insight
Open access•Journal Article•DOI
Digital twin development of a solar power plant
Ludmila Massel, Nikita Shchukin, Alexey Cybikov 
01 Jan 2021
3 Citations
The paper focuses on developing a digital twin for a solar power plant using ontological engineering, not specifically mentioning artificial intelligence. "Not addressed in the paper."
Open access•Journal Article•DOI
Prediction of photovoltaic power generation based on LSTM and transfer learning digital twin
Weisong Wang
01 May 2023-Journal of physics
The research paper utilizes a digital twin model with LSTM and transfer learning for accurate photovoltaic power prediction, demonstrating the application of AI in solar power plants.
Open access•Journal Article•DOI
Maximum Power Point Tracker Controller for Solar Photovoltaic Based on Reinforcement Learning Agent with a Digital Twin
Eneko Artetxe, Jokin Uralde, Oscar Barambones, Isidro Calvo, Imanol Martin 
05 May 2023-Mathematics
The paper utilizes a Digital Twin and Reinforcement Learning agent to enhance Maximum Power Point Tracking in solar PV systems, improving efficiency and speed of power generation.
Open access•Journal Article•DOI
Intelligent Digital Twin Modelling for Hybrid PV-SOFC Power Generation System
Zhimin Guo, Zhiyuan Ye, Pengcheng Ni, C. Cao, Xiaozhao Wei, Jian Hui Zhao, Xing He 
17 Mar 2023-Energies
1 Citations
Intelligent digital twin modeling with artificial rabbits optimization enhances accuracy and stability in hybrid PV-SOFC power generation systems, enabling intelligent operation and management in solar power plants.
Open access•Journal Article•DOI
Exploiting Digitalization of Solar PV Plants Using Machine Learning: Digital Twin Concept for Operation
Paschalia Stefanidou-Voziki, Jose Luis Dominguez-Garcia, Tugce Demirdelen 
29 Jun 2023-Energies
The paper proposes a Digital Twin concept with AI for solar PV plants, enhancing operation, efficiency, and malfunction detection, reducing downtime, and optimizing asset management through machine learning algorithms.

Related Questions

What are the recent advances in the use of digital twins for the management of solar power plants?5 answersRecent advances in the management of solar power plants involve the utilization of digital twins enhanced by artificial intelligence and machine learning techniques. These digital twins enable improved operation, efficiency, and early malfunction detection in solar PV plants. They facilitate real-time data collection, model development, and forecasting of power output, aiding in energy balancing and system fault detection. Additionally, anomalies in solar panel operation can be efficiently identified through statistical analysis and normalized power values, leading to enhanced monitoring and performance optimization. The integration of cloud-based monitoring platforms with AI algorithms further enhances the capabilities of digital twins for health-state diagnostics and fault diagnosis in PV power plants at a large scale.
Is there a digital twin of a processing vegtable plant?5 answersThere is no specific mention of a digital twin of a processing vegetable plant in the abstracts provided. However, the concept of digital twins is discussed in the context of industrial manufacturing enterprises, process optimization, and mineral processing systems. The use of digital twins allows for simulation, training, and optimization of various processes in real-time. While the abstracts mention the development of digital twins for industrial facilities and pilot-scale plants, there is no direct reference to a digital twin of a processing vegetable plant. Further research may be required to determine if a digital twin specifically for a processing vegetable plant has been developed.
What are the challenges and opportunities of using digital twins for energy systems?5 answersDigital twins offer opportunities for designing and optimizing integrated energy systems (IESs) by creating virtual models that can simulate different configurations and provide optimal solutions. They can also be utilized to design control systems and evaluate their efficacy for real systems, leading to ideas for improvement. In the subsea pipeline industry, digital twins can bridge the gap between design and construction, and improve integrity management through data contextualization, standardization, and automated anomaly detection. In the wind energy sector, digital twins play a role in decision-making processes by influencing design choices and including/excluding actors and their concerns. For the smart energy industry, digital twins can help break technical and market barriers, but further research is needed to develop a systematic framework for their application. The challenges of using digital twins include the complexity of system configurations, diverse mathematical models, and the collection, interpretation, and sharing of data, as well as cyber-security concerns.
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