Smart Grid Communication Infrastructure, Automation Technologies and Recent Trends
Masood Aslam,
Nadeem Shahbaz,
Rauf Ur Rahim,
Muhammad Gufran Khan
Issue:
Volume 7, Issue 3, May 2018
Pages:
25-32
Received:
31 May 2018
Accepted:
12 June 2018
Published:
5 July 2018
Abstract: In the last century, there was no major alteration in the structure of power grids. Studies have shown that existing infrastructure is no longer suitable to meet requirements of the future. To overcome the challenges and fulfil future requirements, we need a network that is reliable, efficient and intelligent. This has led to the development of emerging concept of smart grid (SG). Smart grids are the next generation of electrical power grids; a promising solution to overcome energy crises. Smart grid system is the integration of advanced computing and communication technologies with power system infrastructure. In this paper, we provide a survey of the communication infrastructure in smart grids that includes communication architecture and different network compositions, technologies, and intelligent functions that are employed in this architecture. This survey is expected to provide improved understanding of the technologies, its potential benefits and impact. Moreover, we intend to provoke interest amongst the research community to discover more about this emerging area to realize the potential of smart grid concept.
Abstract: In the last century, there was no major alteration in the structure of power grids. Studies have shown that existing infrastructure is no longer suitable to meet requirements of the future. To overcome the challenges and fulfil future requirements, we need a network that is reliable, efficient and intelligent. This has led to the development of eme...
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Investigation into the Optimal Wind Turbine Layout Patterns for a Wind Farm in Walvis Bay, Namibia
Issue:
Volume 7, Issue 3, May 2018
Pages:
33-41
Received:
13 June 2018
Accepted:
3 August 2018
Published:
30 August 2018
Abstract: Due to the unpredictable nature of wind speed and direction, there is a need to optimize the wind turbines placement to extract maximum available wind power at a low cost. Through optimization, best positions of the wind turbines that lead to maximum output are determined. This paper presents an into an optimal Wind Turbine (WT) layout pattern for three Wind Farm (WF) configurations (aligned, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). A Hypothetical WF (2km X 2km) is analyzed based on 2016 Wind data. Result shows that the total power generated from the customized is 863.098 kW, from Genetic Algorithm (GA) layout, the total power generated is 1296.286 kW while from Particle Swarm Optimization (PSO) the total power generated is 1300.668 kW. In comparison to the customized layout, optimization algorithms layouts resulted in a good improvement of the total power generated, GA improved the total power generated by 50.2% while PSO improved the total power generated by 50.7%. Optimization Algorithms layout proved to be efficient as compared to the customized layout because they have fewer power losses. GA and PSO layout have losses of 13.5% and 13.3% respectively, while the customized layout resulted in the most losses which are at 43%. The results from GA and PSO slightly differ, with a small difference in power of 4.4 kW.
Abstract: Due to the unpredictable nature of wind speed and direction, there is a need to optimize the wind turbines placement to extract maximum available wind power at a low cost. Through optimization, best positions of the wind turbines that lead to maximum output are determined. This paper presents an into an optimal Wind Turbine (WT) layout pattern for ...
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