Forecasting Electricity Consumption Using Weather Data in an Edge-Fog-Cloud Data Analytics Architecture

Olivares-Rojas, Juan C.; Reyes-Archundia, Enrique; Gnecchi, José Antonio Gutiérrez; Molina-Moreno, Ismael; Méndez-Patiño, Arturo; Cerda-Jacobo, Jaime

doi:10.1007/978-3-030-61105-7_41

Cited by 4 publications

(2 citation statements)

References 31 publications

(58 reference statements)

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“…Several studies have proposed different architectures and frameworks for integrating edge computing into grid operations. For example, Carlos et al [1] propose a cloudedge-fog architecture for smart grid systems that uses edge computing for real-time data processing and decision-making, and weather data to predict power consumption. Li et al proposed an edge cloud architecture for power grid monitoring, using edge devices to collect and process data, and using cloud servers for long-term storage and analysis [2].…”

Section: Related Workmentioning

confidence: 99%

Cloud-Edge Collaborative Scheduling with a Focus on Clean Energy

Wang¹,

Zheng²

2023

JCEIM

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With the promotion of the national "double carbon" goal, the power system is developing towards the direction of low-carbon transformation. In order to achieve the goal of "striving to peak carbon dioxide emissions by 2030 and striving to achieve carbon neutrality by 2060", we must actively promote the consumption of a high proportion of renewable energy from the grid, which is the most urgent issue to be addressed. In this chapter, access to clean energy will involve multiple aspects such as source, network, load and storage. However, due to the intermittent, random and volatile nature of wind power and photovoltaic power generation, the challenges faced by significant users of the power system are enormous. Traditional energy Internet dispatching adopts centralized dispatching. In this paper, by deploying edge nodes, the autonomous decision-making and autonomous collaboration of power grid nodes at all levels are enhanced, and the collaborative integration level of source, network, load and storage of smart power grid is improved. Aimed at the current power supply and demand imbalance, new energy access problems and energy storage problems. In this paper, a service adaptation algorithm based on dynamic priority is proposed based on the scenario of load storage integration of source network under renewable energy access. Experimental results show that, compared with other algorithms, this algorithm has lower scheduling time and execution time and better performance under the condition of ensuring the highest clean energy consumption rate and first-order load priority response.

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Section: Related Workmentioning

confidence: 99%

Cloud-Edge Collaborative Scheduling with a Focus on Clean Energy

Wang¹,

Zheng²

2023

JCEIM

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“…IoT and cloud computing can contribute towards weather and climate forecasting and science by facilitating observations empowered by IoT devices [21]. Traditionally measurements of weather parameters such as air pollution, humidity and others are observed, saved and displayed to the public and are also used by the researchers to improve the science behind the natural phenomena [22].…”

Section: Weather Forecastingmentioning

confidence: 99%

A Manifesto for Modern Fog and Edge Computing: Vision, New Paradigms, Opportunities, and Future Directions

Gill

2021

EAI/Springer Innovations in Communication and Computing

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The advancements in the use of Internet of Things (IoT) devices is increasing continuously and generating huge amounts of data in a fast manner. Cloud computing is an important paradigm which processes and manages user data effectively. Further, fog and edge computing paradigms are introduced to improve user service by reducing latency and response time. This chapter presents a manifesto for modern fog and edge computing systems based on the current research trends. Further, architectures and applications of fog and edge computing are explained.Moreover, research opportunities and promising future directions are presented with respect to the new paradigms, which will be helpful for practitioners, researchers and academicians to continue their research.

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An Edge-Fog-Cloud computing architecture for IoT and smart metering data

Oprea

Bârã

2023

Peer-to-Peer Netw. Appl.

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Forecasting Electricity Consumption Using Weather Data in an Edge-Fog-Cloud Data Analytics Architecture

Cited by 4 publications

References 31 publications

Cloud-Edge Collaborative Scheduling with a Focus on Clean Energy

Cloud-Edge Collaborative Scheduling with a Focus on Clean Energy

A Manifesto for Modern Fog and Edge Computing: Vision, New Paradigms, Opportunities, and Future Directions

An Edge-Fog-Cloud computing architecture for IoT and smart metering data

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