Energy Consumption Assessment in Refrigeration Equipment: The SmartFridge Project

Griva, Aikaterini I.; Rekkas, Vasileios P.; Koritsoglou, Kyriakos; Sotiroudis, Sotirios P.; Boursianis, Achilles D.; Papadopoulou, Maria S.; Goudos, Sotirios K.

doi:10.1109/mocast57943.2023.10176514

Cited by 4 publications

(2 citation statements)

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“…Some other authors from the study from this year (2023) conducted a SmartFridge project as a study toward environmental sustainability and the economy. In their paper [66], they evaluated a refrigerator model in terms of its energy consumption, considering factors such as indoor temperature and moisture. The results of their study show that as the indoor temperature increases, energy consumption increases.…”

Section: Pvmentioning

confidence: 99%

“…Predictive MaintenanceSmart refrigerators use AI to monitor their own performance and detect early signs of malfunctions or maintenance issues. By identifying problems in advance, they can schedule repairs or maintenance during low-demand periods, preventing sudden breakdowns that might lead to energy waste Integration Smart refrigerators can be integrated into larger home energy management systems, allowing homeowners to coordinate the operation of various smart appliances, heating and cooling systems, and lighting to maximize energy efficiency throughout the home.PVResearch on the development of solar PV-powered refrigerators.Source: Authors' own work based on[63][64][65][66][67][68][69].…”

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confidence: 99%

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AI-Driven Urban Energy Solutions—From Individuals to Society: A Review

Stecuła,

Wolniak,

Grebski

2023

Energies

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This paper provides a comprehensive review of solutions based on artificial intelligence (AI) in the urban energy sector, with a focus on their applications and impacts. The study employed a literature review methodology to analyze recent research on AI’s role in energy-related solutions, covering the years 2019 to 2023. The authors classified publications according to their main focus, resulting in two key areas of AI implementation: residential and individual user applications, and urban infrastructure integration for society. The objectives of this review of the literature are the following: O1: to identify trends, emerging technologies, and applications using AI in the energy field; O2: to provide up-to-date insights into the use of AI in energy-related applications; O3: to gain a comprehensive understanding of the current state of AI-driven urban energy solutions; O4: to explore future directions, emerging trends, and challenges in the field of AI-driven energy solutions. This paper contributes to a deeper understanding of the transformative potential of AI in urban energy management, providing valuable insights and directions for researchers and practitioners in the field. Based on the results, it can be claimed that AI connected to energy at homes is used in the following areas: heating and cooling, lighting, windows and blinds, home devices, and energy management systems. AI is integrating into urban infrastructure through the following solutions: enhancement of electric vehicle charging infrastructure, reduction in vehicle emissions, development of smart grids, and efficient energy storage. What is more, the latest challenges associated with the implementation of AI-driven energy solutions include the need to balance resident comfort with energy efficiency in smart homes, ensuring compatibility and cooperation among various devices, preventing unintended energy consumption increases due to constant connectivity, the management of renewable energy sources, and the coordination of energy consumption.

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Section: Pvmentioning

confidence: 99%