A hierarchical optimization model for energy data flow in smart grid power systems

Jarrah, Moath; Jaradat, Manar; Jararweh, Yaser; Al‐Ayyoub, Mahmoud; Bousselham, Abdelkader

doi:10.1016/j.is.2014.12.003

Cited by 36 publications

(12 citation statements)

References 27 publications

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“…The latter should possess not only professional, but also social competences in the Smart Grids system, that enable them to work with the population giving consultations on day-to-day issues and having bilateral contact. Unfortunately, the national system of bachelor training in the field of electrical power engineering and heat power engineering does not include the formation of such competences [8,9].…”

Section: Resultsmentioning

confidence: 99%

Status of Social Competencies of Power Engineers in the Context of Forming the Concept of an Intelligent Network or Smart Grid

Ardashkin

Korobeynikova

Popova

2015

MATEC Web of Conferences

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Abstract. The article reviews the trends which define development of power engineering in the world and in Russia. The authors emphasize that establishment of smart grids is the consequence of not only technological but also social transformations of a modern society. The authors sum up that social competencies are an integral part of professional skills of engineers who work in the field of power engineering. The authors make a hypothesis that the major (educational module) "Energy consultant for the population" might develop social competencies.

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Section: Resultsmentioning

confidence: 99%

Status of Social Competencies of Power Engineers in the Context of Forming the Concept of an Intelligent Network or Smart Grid

Ardashkin

Korobeynikova

Popova

2015

MATEC Web of Conferences

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“…Cloud storage optimization [16][17][18][19][20][21][22] is another issue to improve the quality of service of the cloud computing systems. In [16], optimizations are proposed to reduce the volume of data to be transferred per data access for the respects of privacy and security, which did not consider the storage cost.…”

Section: Related Workmentioning

confidence: 99%

“…Aiming to improve the storage utilization and workflow scheduling performance in the cloud, Wang et al [21] proposed a user-level file system and a scheduling algorithm for scientific workflow computation in the cloud, in which the storage utilization was improved by using the workflow-aware file system and the scheduler to control the number of concurrent workflow instances at runtime. Jarrah et al [22] proposed a hierarchical optimization model for energy data flow in smart grid power systems aiming to minimize daily electricity cost through maximizing the used percentage of renewable energy.…”

Section: Related Workmentioning

confidence: 99%

Multiobjective Reliable Cloud Storage with Its Particle Swarm Optimization Algorithm

Liu

Fan

Wei

et al. 2016

Mathematical Problems in Engineering

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Information abounds in all fields of the real life, which is often recorded as digital data in computer systems and treated as a kind of increasingly important resource. Its increasing volume growth causes great difficulties in both storage and analysis. The massive data storage in cloud environments has significant impacts on the quality of service (QoS) of the systems, which is becoming an increasingly challenging problem. In this paper, we propose a multiobjective optimization model for the reliable data storage in clouds through considering both cost and reliability of the storage service simultaneously. In the proposed model, the total cost is analyzed to be composed of storage space occupation cost, data migration cost, and communication cost. According to the analysis of the storage process, the transmission reliability, equipment stability, and software reliability are taken into account in the storage reliability evaluation. To solve the proposed multiobjective model, a Constrained Multiobjective Particle Swarm Optimization (CMPSO) algorithm is designed. At last, experiments are designed to validate the proposed model and its solution PSO algorithm. In the experiments, the proposed model is tested in cooperation with 3 storage strategies. Experimental results show that the proposed model is positive and effective. The experimental results also demonstrate that the proposed model can perform much better in alliance with proper file splitting methods.

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“…Communication network should be the next focus after the measurement system. Smart Grid network should be classified in the typical payload, data sampling, latency, and reliability [16]. This study has divided the communication network basically by its data rate and coverage area [3] [17].…”

Section: Introductionmentioning

confidence: 99%

Smart Grid communication applications: measurement equipment and networks architecture for data and energy flow

Atmaja

Andriani

Darussalam³

2019

J. Mechatron. Electr. Power Veh. Technol.

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Smart Grid is an advanced two way data and energy flow capable of self-healing, adaptive, resilient, and sustainable with prediction capability of possible fault. This article aimed to disclose Smart Grid communication in a logical way to facilitate the understanding of each component function. The study was focused on the improvement, advantages, common used design, and possible feature of Smart Grid communication components. The results of the study divide the Smart Grid communication application into two main category i.e. measurement equipment and network architecture. Measurement equipment consists of Advance Metering Infrastructure, Phasor Measurement Unit, Intelligent Electronic Devices, and Wide Area Measurement System. The network architecture is divided based on three hierarchies; local area network for 1 to 100 m with 100 kbps data rate, neighbour area network for 100 m to 10 km with 100 Mbps data rate, and wide area network for up to 100 km with 1 Gbps data rate. More information is provided regarding the routing protocol for each network from various available protocols. The final section presents the energy and data flow architecture for Smart Grid implementation based on the measurement equipment and the network suitability. This article is expected to provide a comprehensive guide and comparison surrounding the technologies supporting Smart Grid implementation especially on communication applications.

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A hierarchical optimization model for energy data flow in smart grid power systems

Cited by 36 publications

References 27 publications

Status of Social Competencies of Power Engineers in the Context of Forming the Concept of an Intelligent Network or Smart Grid

Status of Social Competencies of Power Engineers in the Context of Forming the Concept of an Intelligent Network or Smart Grid

Multiobjective Reliable Cloud Storage with Its Particle Swarm Optimization Algorithm

Smart Grid communication applications: measurement equipment and networks architecture for data and energy flow

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