Scalability for Smart Infrastructure System in Smart Grid: A Survey

Su, Ma; Zhang, Hong; Xing, Xiangwei

doi:10.1007/s11277-017-5045-y

Cited by 19 publications

(9 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This work is a continuation of previous work [ 8 ], were we coined the term sioe to refer to the synergy between DSM and SIoT. On the one hand, a survey about SG scalability [ 45 ] reports that in terms of communication, the transition from a centralized architecture to a distributed one is necessary for a SG. Also, it reports that machine-to-machine communications (e.g., expressed in the SIoT paradigm), can open new opportunities and reduce communication costs.…”

Section: Related Workmentioning

confidence: 80%

A Heuristic to Create Prosumer Community Groups in the Social Internet of Energy

Caballero

Vernet

Zaballos

2020

Sensors

View full text Add to dashboard Cite

Contrary to the rapid evolution experienced in the last decade of Information and Communication Technologies and particularly the Internet of Things, electric power distribution systems have remained exceptionally steady for a long time. Energy users are no longer passive actors; the prosumer is expected to be the primary agent in the Future Grid. Demand Side Management refers to the management of energy production and consumption at the demand side, and there seems to be an increasing concern about the scalability of Demand Side Management services. The creation of prosumer communities leveraging the Smart Grid to improve energy production and consumption patterns has been proposed in the literature, and several works concerned with scalability of Demand Side Management services group prosumers to improve Demand Side Management services scalability. In our previous work, we coin the term Social Internet of Energy to refer to the integration between devices, prosumers and groups of prosumers via social relationships. In this work, we develop an algorithm to coordinate the different clusters we create using the clustering method by load profile compatibility (instead of similarity). Our objective is to explore the possibilities of the cluster-by-compatibility heuristic we proposed in our previous work. We perform experiments using synthetic and real datasets. Results show that we can obtain a global reduction in Peak-to-Average Ratio with datasets containing up to 200 rosumers and creating up to 6 Prosumer Community Groups, and imply that those Prosumer Community Groups can perform load rescheduling semi-autonomously and in parallel with each other.

show abstract

Section: Related Workmentioning

confidence: 80%

A Heuristic to Create Prosumer Community Groups in the Social Internet of Energy

Caballero

Vernet

Zaballos

2020

Sensors

View full text Add to dashboard Cite

show abstract

“…Scalability: The majority of smart grids today are deployed on a modest scale with local experimental design. Globalization of the smart grid, however, necessitates large-scale implementation (Ma et al 2018;Rodriguez-Calvo et al 2018;Sigrist et al 2016). On a wide scale, smart grid will confront severe difficulties and might not function properly.…”

Section: Grid Efficiencymentioning

confidence: 99%

The determinants of reliable smart grid from experts’ perspective

et al. 2023

View full text Add to dashboard Cite

A smart grid integrates communication networks with the conventional electrical grid. Due to their potential, smart grids are anticipated to achieve widespread deployment. A key component of the success and adoption of smart grids is reliability. Without knowing users’ impressions of the reliability of the smart grid, users will not easily accept and participate in it or its services. However, very few studies address smart grid reliability from the perspective of users. Thus, there is a urgent need to identify key factors that affect smart grid reliability from the user’s viewpoint. The goal of this paper is to examine user perceptions of smart grid reliability and assess their success factors in an effort to close the gap in the literature. This paper propose a model to investigate and determine the most crucial factors that affect the smart grid's reliability based on the Multiple-criteria decision-making (MCDM) method. Firstly, a comprehensive literature analysis was conducted to determine the criteria and sub-criteria used to construct the model; then, the model is constructed using fifteen sub-criteria covering big data, network systems, and grid efficiency criteria; finally, the Fuzzy Analytic Hierarchy Approach (FAHP) and fuzzy triangular numbers are used to evaluate and prioritize the criteria. Twenty smart grid experts were consulted to collect data. The results indicate the significance of the ‘Big Data’ criterion, closely followed by ‘Grid Efficiency’ criterion. Additionally, it is discovered that the sub-criteria of ‘Privacy’ and ‘Interoperability’ had a significant impact on the reliability of the smart grid. The sensitivity analysis shows the variation of factors ranking and the stability and robustness of the model and the results. The research presented in this study has practical applications for academics, engineers, decision-makers, and stakeholders.

show abstract

“…Nowadays, smart grids are implemented on small scale with a small pilot and local experimental design (Lin et al, 2020). However, smart grid global realization requires implementation on global scale (Sigrist et al, 2016;Rodriguez-Calvo et al, 2018;Ma et al, 2018). Smart grid would face significant challenges on the large scale and may not work accurately.…”

Section: System Characteristicsmentioning

confidence: 99%

Smart grid reliability evaluation and assessment

Mashal¹

2022

View full text Add to dashboard Cite

PurposeSmart grid is an integration between traditional electricity grid and communication systems and networks. Providing reliable services and functions is a critical challenge for the success and diffusion of smart grids that needs to be addressed. The purpose of this study is to determine the critical criteria that affect smart grid reliability from the perspective of users and investigate the role big data plays in smart grid reliability.Design/methodology/approachThis study presents a model to investigate and identify criteria that influence smart grid reliability from the perspective of users. The model consists of 12 sub-criteria covering big data management, communication system and system characteristics aspects. Multi-criteria decision-making approach is applied to analyze data and prioritize the criteria using the fuzzy analytic hierarchy process based on the triangular fuzzy numbers. Data was collected from 16 experts in the fields of smart grid and Internet of things.FindingsThe results show that the “Big Data Management” criterion has a significant impact on smart grid reliability followed by the “System Characteristics” criterion. The “Data Analytics” and the “Data Visualization” were ranked as the most influential sub-criteria on smart grid reliability. Moreover, sensitivity analysis has been applied to investigate the stability and robustness of results. The findings of this paper provide useful implications for academicians, engineers, policymakers and many other smart grid stakeholders.Originality/valueThe users are not expected to actively participate in smart grid and its services without understanding their perceptions on smart grid reliability. Very few works have studied smart grid reliability from the perspective of users. This study attempts to fill this considerable gap in literature by proposing a fuzzy model to prioritize smart grid reliability criteria.

show abstract

Scalability for Smart Infrastructure System in Smart Grid: A Survey

Cited by 19 publications

References 37 publications

A Heuristic to Create Prosumer Community Groups in the Social Internet of Energy

A Heuristic to Create Prosumer Community Groups in the Social Internet of Energy

The determinants of reliable smart grid from experts’ perspective

Smart grid reliability evaluation and assessment

Contact Info

Product

Resources

About