Journal article
Mitigation strategies to minimize potential technical challenges of renewable energy integration
Sustainable Energy Technologies and Assessments, Vol.25, pp.24-42
2018
Abstract
A recent issue of increasing public focus is the need for robust, sustainable and climate friendly power systems that are intelligent, reliable and green. The intermittent nature of renewable energy generation and the associated power electronic inverters creates a number of potential challenges in integrating large-scale renewable energy (RE) into the grid that affects power quality of the distribution network. Therefore, this study initially, investigates the potential technical impacts in particular voltage regulation, active and reactive power variations, transformer loading and current and voltage harmonics causes with RE integration. Then, to reduce the level of impacts observed, STATCOM and energy storage system (both optimised) were integrated into the network that ensures a smooth power supply to the customers. As a case study, the Berserker Street Feeder, Frenchville Substation under Rockhampton distribution network, Central Queensland, Australia has been considered. Similar analyses also carried out with the IEEE 13 bus network to investigate the potential technical challenges of RE integration and identify suitable mitigation measures. Results shows that integration of both optimised STATCOM and energy storage enhances the overall power quality of the power network as it improves voltage regulation, power distribution, and transformer utilisation and reduce total harmonic distortion of the power network.
Details
- Title
- Mitigation strategies to minimize potential technical challenges of renewable energy integration
- Authors/Creators
- GM. Shafiullah (Author/Creator) - Murdoch UniversityM.T. Arif (Author/Creator) - Deakin UniversityA.M.T. Oo (Author/Creator) - Deakin University
- Publication Details
- Sustainable Energy Technologies and Assessments, Vol.25, pp.24-42
- Publisher
- Elsevier
- Identifiers
- 991005543895007891
- Copyright
- © 2017 Elsevier Ltd.
- Murdoch Affiliation
- School of Engineering and Information Technology
- Language
- English
- Resource Type
- Journal article
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- Collaboration types
- Domestic collaboration
- Citation topics
- 4 Electrical Engineering, Electronics & Computer Science
- 4.18 Power Systems & Electric Vehicles
- 4.18.204 Smart Grid Optimization
- Web Of Science research areas
- Energy & Fuels
- Green & Sustainable Science & Technology
- ESI research areas
- Engineering