Big Data management in smart grid: concepts, requirements and implementation

Daki, Houda; Hannani, Asmaa El; Aqqal, Abdelhak; Haidine, Abdelfattah; Dahbi, Aziz

doi:10.1186/s40537-017-0070-y

Cited by 170 publications

(89 citation statements)

References 23 publications

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“…Smart grids, in particular, present an important opportunity to transform the energy sector by making the electrical system more reliable, safe, and cost-effective. Data collected from smart grids makes possible the automated and real-time management of the electrical network, leading to opportunities for energy efficiency that can impact both the costs and the environment in a positive manner (Daki et al 2017).…”

Section: Findings and Resultsmentioning

confidence: 99%

Artificial Intelligence and Broadband Development through the Asia-Pacific Information Superhighway

Okuda

'Ofa

2018

J Infrastruct Policy Dev

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This exploratory study aims to identify the main characteristics and relationships between artificial intelligence (AI) and broadband development in Asia and the Pacific. Broadband networks are the foundation and prerequisite for the development of AI. But what types of broadband networks would be conducive are not adequately discussed so far. Furthermore, in addition to broadband networks, other factors, such as income level, broadband quality, and investment, are expected to influence the uptake of AI in the region. The findings are synthesized into a set of policy recommendations at the end of the article, which highlights the need for regional cooperation through an initiative, such as the Asia-Pacific Information Superhighway (AP-IS).

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Section: Findings and Resultsmentioning

confidence: 99%

Artificial Intelligence and Broadband Development through the Asia-Pacific Information Superhighway

Okuda

'Ofa

2018

J Infrastruct Policy Dev

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“…BDVC has also attracted much attention in smart grid area, Daki et al [70] has presented Big Data architecture by providing several steps from data sources to visualization. The proposed architecture enables to manage different flux coming from the electricity grid and various producers, users or communicating devices or deliver added value in the consumption and distribution of energy systems to monitor its sustainability.…”

Section: Big Data Value Chain Models In the Literaturementioning

confidence: 99%

Big data monetization throughout Big Data Value Chain: a comprehensive review

et al. 2020

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Value creation is the rational goal of any organization. However, in a changing world, in terms of data, it is very difficult to find strategies to sustainably generate new value and improve operations. In this respect, generating value may mean revisiting some deeplyheld conceptions of different processes. For this, each organization has to ensure an efficient and updated management of value creation processes for both inter-organization and partners. Value chain (VC) is one of the key solutions to such dilemmas.

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“…In the future market design, the peak load shave would be achieved by shifting the usage time of the energy without changing the total energy consumption [45]. It works on the application of smart meters to collect data and optimize energy production [46]. Although this strategy improves the conventional grid, the IoE framework is not considered a mathematical model and the inclusion of renewable energy sources is lacking.…”

Section: Literature Reviewmentioning

confidence: 99%

Internet of Energy (IoE) and High-Renewables Electricity System Market Design

et al. 2019

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The growing importance of the Internet of Energy (IoE) brands the high-renewables electricity system a realistic scenario for the future electricity system market design. In general, the whole gist behind the IoE is developed upon a somewhat broader idea encompassing the so-called “Internet of Things” (IoT), which envisioned a plethora of household appliances, utensils, clothing, smart trackers, smart meters, and vehicles furnished with tiny devices. These devices would record all possible data from all those objects in real time and allow for a two-way exchange of information that makes it possible to optimize their use. IoT employs the Internet Protocol (IP) and the worldwide web (WWW) network for transferring information and data through various types of networks and gateways as well as sensor technologies. This paper presents an outline stemming from the implications of the high-renewables electric system that would employ the Internet of Energy (IoE). In doing so, it focuses on the implications that IoE brings into the high-renewables electricity market inhabited by smart homes, smart meters, electric vehicles, solar panels, and wind turbines, such as the peer-to-peer (P2P) energy exchange between prosumers, optimization of location of charging stations for electric vehicles (EVs), or the information and energy exchange in the smart grids. We show that such issues as compatibility, connection speed, and most notoriously, trust in IoE applications among households and consumers would play a decisive role in the transition to the high-renewables electricity systems of the 21st century. Our findings demonstrate that the decentralized approach to energy system effective control and operation that is offered by IoE is highly likely to become ubiquitous as early as 2030. Since it may be optimal that large-scale rollouts start in the early 2020s, some form of government incentives and funding (e.g. subsidies for installing wind turbines or solar panels or special feed-in-tariffs for buying renewable energy) may be needed for the energy market to make early progress in embracing more renewables and in reducing the costs of later investments. In addition, there might be some other alternative approaches aimed at facilitating this development. We show that the objective is to minimize the overall system cost, which consists of the system investment cost and the system operating cost, subject to CO2 emissions constraints and the operating constraints of generation units, network assets, and novel carbon-free technologies, which is quite cumbersome given the trend in consumption and the planned obsolescence. This can be done through increasing energy efficiency, developing demand side management strategies, and improving matching between supply and demand side, just to name a few possibilities.

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Big Data management in smart grid: concepts, requirements and implementation

Cited by 170 publications

References 23 publications

Artificial Intelligence and Broadband Development through the Asia-Pacific Information Superhighway

Artificial Intelligence and Broadband Development through the Asia-Pacific Information Superhighway

Big data monetization throughout Big Data Value Chain: a comprehensive review

Internet of Energy (IoE) and High-Renewables Electricity System Market Design

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