In this study, a comprehensive review on artificial intelligence applications in renewable systems and intelligent buildings, has been conducted, from perspectives of modelling techniques on PV power forecasting, underlying learning mechanisms, solar energy potential prediction, multi-level stochastic uncertainty analysis, smart controls, fault
Promising research directions include hybrid energy storage systems, energy management strategies based on deep reinforcement learning, sustainability and resilience indicators, and scale methods based on distributed robust optimisation. With the continuous development and application of new technologies and equipment, the basic architecture of
Abstract: This paper''s main objective is to examine the state of the art of artificial intelligence (AI) techniques and tools in power management, maintenance, and control of renewable energy systems (RES) and specifically to the solar power systems. The findings would allow researchers to innovate the current state of technologies and
Efficient management of solar radiation through architectural glazing is a key strategy for achieving a comfortable indoor environment with minimum energy consumption. Conventional glazing consisting of a single or multiple glass pane(s) exhibits high visible light transmittance and solar heat gain coefficient, which can be a double-edged sword, i.e., it
Due to the current emphasis on applying Artificial Intelligence (AI) techniques to Renewable Energy (RE) systems, particularly Photovoltaic (PV), a thorough study of Maximum Power Point Tracking (MPPT) control techniques-based AI
This study addresses solar energy applications in protected agriculture, focusing on greenhouses and related technologies. A bibliometric and technical analysis is developed, covering research published between 1976 and 2024, to identify the main trends and challenges in the use of solar energy in controlled environments. The methodology was based
Researchers can use these synergies to create intelligent, linked solar energy ecosystems capable of real-time optimization of energy production, delivery, and consumption. These technologies have the potential to transform the renewable energy environment, allowing for more resilient and sustainable energy infrastructures.
The diverse applications of AI in enhancing France''s energy infrastructure encompass integrating renewable resources, efficiently managing the power grid, and
Lytras, M.D., Chui, K.T.: The recent development of artificial intelligence for smart and sustainable energy systems and applications. Energies 12(16), 3108 (2019) Article Google Scholar Ren, B., et al.: Machine learning applications in health monitoring of renewable energy systems. Renew. Sustain. Energy Rev. 189, 114039 (2024)
Researchers can use these synergies to create intelligent, linked solar energy ecosystems capable of real-time optimization of energy production, delivery, and consumption.
Through savvy application of artificial intelligence, solar energy developers can reduce delays, minimize build costs, and improve project time-to-completion. Throughout a solar project lifecycle, AI can also be applied to maximize solar energy output, while minimizing operational expense and risk. And this is just the beginning; the
This article analyzes the relationship between artificial intelligence (AI) and photovoltaic (PV) systems. Solar energy is one of the most important renewable energies, and the investment of businesses and governments is increasing every year. AI is used to solve the most important problems found in PV systems, such as the tracking of the Max Power Point of the
Solar energy management systems with AI capabilities make it easier to trade energy and integrate solar power into the grid. These systems can decide when to sell e xtra energy, b uy energy from
This review specifically explored the applications of diverse artificial intelligence approaches over a wide range of sources of renewable energy innovations spanning solar power, photovoltaics, microgrid integration, energy storage and power management, wind, and geothermal energy comprehensively. The current technological advances, research
This research paper aims to review the applications of artificial intelligence in energy and to develop a future vision for new applications. The research methodology focuses on clarifying the
The intelligent monitoring and detection control system of solar energy power generation mainly includes three parts: (1) data acquisition perception layer: This layer realizes the collection and storage of data such as the amount of sunlight radiation, the temperature value of the energy harvesting plate surface, the photoelectric conversion efficiency and the power
Through savvy application of artificial intelligence, solar energy developers can reduce delays, minimize build costs, and improve project time-to-completion. Throughout a solar project lifecycle, AI can also be applied to
This study provided an overview of techniques, methods, components, and approaches used in intelligent energy management for both independent and grid-connected
Due to the current emphasis on applying Artificial Intelligence (AI) techniques to Renewable Energy (RE) systems, particularly Photovoltaic (PV), a thorough study of Maximum Power Point Tracking (MPPT) control techniques-based AI approaches, particularly Fuzzy Logic Controller (FLC), Artificial Neural Network (ANN), and Adaptive Neural Fuzzy Inf...
This study provided an overview of techniques, methods, components, and approaches used in intelligent energy management for both independent and grid-connected hybrid renewable energy systems, with a focus on IoT in PV power generation. The study underlined the importance the Internet of Things is to providing two-way control and real-time
This chapter presents a review of the application of artificial intelligence in a solar PV system while highlighting the challenges and prospects for effective utilization in the renewable...
[I]Sharma, U., Singh, B., & Kumar, S. (2017). Intelligent grid interfaced solar water pumping system [1] proposed a solar photovoltaic (SPV) water pumping system integrated with the single phase distribution system by utilising induction motor drive (IMD) with an intelligent power sharing concept. In addition to the power exchange from SPV to
In this study, a comprehensive review on artificial intelligence applications in renewable systems and intelligent buildings, has been conducted, from perspectives of
Abstract: This paper''s main objective is to examine the state of the art of artificial intelligence (AI) techniques and tools in power management, maintenance, and control of renewable energy
In this paper, we explore the impact of AI technology on PV power generation systems and its applications from a global perspective. Central to the discussion are the
The diverse applications of AI in enhancing France''s energy infrastructure encompass integrating renewable resources, efficiently managing the power grid, and optimizing energy consumption to...
This review specifically explored the applications of diverse artificial intelligence approaches over a wide range of sources of renewable energy innovations spanning solar power, photovoltaics, microgrid integration, energy storage and power management, wind, and
This chapter presents a review of the application of artificial intelligence in a solar PV system while highlighting the challenges and prospects for effective utilization in the renewable...
We train a "graph neural network" to simulate the dynamics of our solar system''s Sun, planets, and large moons from 30 years of trajectory data. We then use symbolic regression to correctly
In this paper, we explore the impact of AI technology on PV power generation systems and its applications from a global perspective. Central to the discussion are the pivotal applications of AI in maximum power point tracking (MPPT), power forecasting, and fault detection within the PV system.
1. AI Applications in Solar Energy systems is detailed in different review articl es [74-76]. one of the most important considerations. As mentioned, AI methodologies are used in many applications. One such forecasting. Among the many techniques introduced in solar [77-102]. and cloudy days, respectiv ely . building energy prediction.
There are mainly six application areas, including solar energy resources and potentials’ estimation, solar PV output power prediction with urban PV power potentials, stochastic uncertainty analysis and robust design, smart system control, fault detection and diagnosis (FDD) and system optimisations.
A holistic overview on artificial intelligence applications in renewable systems. Underlying learning mechanisms of AI algorithms and adaption to dynamic environment. Power forecasting, stochastic uncertainty analysis and smart controls with AI. Semi-empirical and data-driven models for fault detection and diagnosis.
Central to the discussion are the pivotal applications of AI in maximum power point tracking (MPPT), power forecasting, and fault detection within the PV system. On the one hand, the integration with AI technology enables the optimization and improvement of the operational efficiency of PV systems.
The findings would allow researchers to innovate the current state of technologies and possibly use the standard and successful techniques in building AI-powered renewable energy systems, specifically for solar energy.
This study provided an overview of techniques, methods, components, and approaches used in intelligent energy management for both independent and grid-connected hybrid renewable energy systems, with a focus on IoT in PV power generation.
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