Energy Big Data: A Survey

IEEE Model for planning Big Data Energy Applications through a Smart Grid (including Use Case Scenarios)

Type of content: Assets
Type of asset:
Model
Big data potential
No
Policy domains: Environment & Energy
Phase in the policy cycle:
Policy Design and Analysis
Open license availability
No
Ease of use
High
Tags: Smart work Strategic planning
Addresses:
SWOT Analysis for
Energy Big Data: A Survey
Helpful Harmful
Internal
Strengths• Provides a community of professionals in industry, academia, and government working to solve the challenges associated with Big Data
• Recognition of useful versus irrelevant data
• Collection of distributed data
• Accuracy, completeness, and timeliness of data
• Efficient storage and transfer
• Privacy and security of data
• Fault tolerance
• Scalability and economic impact of implementation
• Intelligent analysis
• Insightful and flexible presentation
Weaknesses• The volume of energy big data is increasing at an exponential speed. At the same time, difficulties also arise up in data storage, mining, querying, processing, etc. Therefore, cryptography technologies, fuzzy data computing, qualified data processing are all essential for big data applied better in smart grid.
External
Opportunities• The volume of energy big data is increasing at an exponential speed. At the same time, difficulties also arise up in data storage, mining, querying, processing, etc. Therefore, cryptography technologies, fuzzy data computing, qualified data processing are all essential for big data applied better in smart grid. Threats• Data privacy
• Integrity: Preventing unauthorised persons or systems modifying information
• Authentication: verify participator’s identity and map this identity to the existing authentication table in power network.
• Third party protection: a third-party must be listed in the authentication table in power network

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