Green energy harvesting strategies on edge-based urban computing in sustainable internet of things

Lu, Man; Fu, Guifang; Osman, Nisreen Beshir; Konbr, Usama

doi:10.1016/j.scs.2021.103349

Cited by 36 publications

(12 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Broring et al proposed a network aware edge computing framework for power systems, which uses a software-defined network approach for effective network management [13]. Lu et al proposed an edge-based communication system for distributed renewable energy systems, which utilizes cognitive radio technology for effective spectrum utilization [14].…”

Section: Related Workmentioning

confidence: 99%

Cloud-Edge Collaborative Scheduling with a Focus on Clean Energy

Wang¹,

Zheng²

2023

JCEIM

View full text Add to dashboard Cite

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.

show abstract

Section: Related Workmentioning

confidence: 99%

Cloud-Edge Collaborative Scheduling with a Focus on Clean Energy

Wang¹,

Zheng²

2023

JCEIM

View full text Add to dashboard Cite

show abstract

“…One of the interesting and potentially fruitful solutions to meet the ever-increasing energy demands of the globe is to collect energy from the sun. The total system for collecting solar energy is made up of a variety of different devices and components, including as PV arrays, MPPT controllers, DC-DC converters, batteries, loads (both AC and DC), and inverters [9], [11], [12], [16], [17], [58], [119], [120]. The comprehensive schematic block of the solar energy collecting system is shown in Figure 1.…”

Section: Structure Of a Solar Photovoltaic Energy Harvesting Systemmentioning

confidence: 99%

Modernisation of DC-DC converter topologies for solar energy harvesting applications: A review

Sutikno

Purnama

Aprilianto

et al. 2022

IJEECS

View full text Add to dashboard Cite

Solar photovoltaic (PV) power generation has become increasingly important as a renewable source of energy due to the many benefits it offers. These benefits include the ease with which it can be allocated; the absence of noise; the longer life; the absence of pollution; the shorter amount of time required for installation; the high mobility and portability of its parts; and the capability of its output power to meet peak load requirements. DC-DC converters are typically incorporated into solar energy harvesting systems because they allow for the more efficient exploitation of solar cells. One of the difficulties is in the selection of a suitable converter since this has an effect on the operation of the PV system. This study discusses the modernisation of several different DC-DC converter topologies for solar energy harvesting systems. Some of these topologies are boost, buck-boost, single-ended primary-inductance converter (SEPIC), Cuk, and flyback. The topologies have been compared so that detailed information on the complexity of the hardware, the cost of implementation, the efficiency of the energy transfer elements, the tracking efficiency, and the efficiency of the converters can be provided. This paper will be useful as a handy reference in choosing the best converter topology for solar energy harvesting applications.

show abstract

“…One way that IoT edge computing may be used to protect humans is to automatically shut down machines when someone enters a prohibited area at a factory. Autonomous cars require data in order to make critical real-time decisions that might mean the difference between life and death on the road [24], [26], [67], [100], [109], [133], [145], [184], [186], [216], [220], [221], [267], [268], [293], [297], [335].…”

Section: Edge Computing: Low Latency and Securitymentioning

confidence: 99%

Insights on the internet of things: past, present, and future directions

Sutikno

Thalmann

2022

TELKOMNIKA

View full text Add to dashboard Cite

The internet of things (IoT) is rapidly expanding and improving operations in a wide range of real-world applications, from consumer IoT and enterprise IoT to manufacturing and industrial IoT (IIoT). Consumer markets, wearable devices, healthcare, smart buildings, agriculture, and smart cities are just a few examples. This paper discusses the current state of the IoT ecosystem, its primary applications and benefits, important architectural stages, some of the problems and challenges it faces, and its future. This paper explains how an appropriate IoT architecture that saves data, analyzes it, and recommends corrective action improves the process's ground reality. The IoT system architecture is divided into three layers: device, gateway, and platform. This then cascades into the four stages of the IoT architectural layout: sensors and actuators; gateways and data acquisition systems; edge IT data processing; and datacenter and cloud, which use high-end apps to collect data, evaluate it, process it, and provide remedial solutions. This elegant combination provides excellent value in automatic action. In the future, IoT will continue to serve as the foundation for many technologies. Machine learning will become more popular in the coming years as IoT networks take center stage in a variety of industries.

show abstract

Green energy harvesting strategies on edge-based urban computing in sustainable internet of things

Cited by 36 publications

References 58 publications

Cloud-Edge Collaborative Scheduling with a Focus on Clean Energy

Cloud-Edge Collaborative Scheduling with a Focus on Clean Energy

Modernisation of DC-DC converter topologies for solar energy harvesting applications: A review

Insights on the internet of things: past, present, and future directions

Contact Info

Product

Resources

About