Smart Grid Data Analytics for Security of Energy Supply
Lead Research Organisation:
Queen's University Belfast
Department Name: Sch of Electronics, Elec Eng & Comp Sci
Abstract
SONI (System Operator for Northern Ireland) has recently launched a new five-year strategy to ensure that Northern Ireland's grid can handle 95% renewable energy at any one time. This ambition will see a significant increase from the current 65% clean energy in the mix. As of 2019, Northern Ireland has installed about 1300 MW of wind power generation capacity. With a peak system demand of circa 1700 MW and min load of circa 500 MW, wind could, at times, theoretically supply all of the system demand. However, the variability and uncertainty associated with wind power generation and the nature of the technology create operational challenges. In such an environment, new, more intelligent tools are needed by the power system operator to deal with the increased challenges.
The project intends to investigate an intelligent big data approach to improve the reliability and security of future energy networks, at the transmission level as well as the distribution level.
The objectives of the project are:
1. To become familiar with smart grid and distributed renewable generation
2. To become familiar with various system scenarios, models and software to increase employability
3. Big data analytics using real-time measurements
4. Investigate a methodology to compile and reports for operational presentation
5. Develop graphical user interface for displaying results/findings
6. Real-time visualisation of power systems/smart grid to assist decision making
The project intends to investigate an intelligent big data approach to improve the reliability and security of future energy networks, at the transmission level as well as the distribution level.
The objectives of the project are:
1. To become familiar with smart grid and distributed renewable generation
2. To become familiar with various system scenarios, models and software to increase employability
3. Big data analytics using real-time measurements
4. Investigate a methodology to compile and reports for operational presentation
5. Develop graphical user interface for displaying results/findings
6. Real-time visualisation of power systems/smart grid to assist decision making
Organisations
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/N509541/1 | 30/09/2016 | 29/09/2021 | |||
2278077 | Studentship | EP/N509541/1 | 30/09/2019 | 29/09/2026 | Paul Maybin |
EP/R513118/1 | 30/09/2018 | 29/09/2023 | |||
2278077 | Studentship | EP/R513118/1 | 30/09/2019 | 29/09/2026 | Paul Maybin |