Journal article
Dynamic operation and control of a hybrid nanogrid system for future community houses
IET Generation, Transmission & Distribution, Vol.9(11), pp.1168-1178
2015
Abstract
A hybrid NanoGrid (NG) can be considered as the power supply system, for future community houses. In this study, the operation and control of an NG are presented. The NG consists of an AC bus and a DC bus, interconnected through a tie-converter (TC). All AC loads and distributed energy resources (DERs) of the community houses are connected to the AC bus while all their DC loads and DERs are connected to the DC bus. The NG has an adequate generation capacity to supply its loads in off-grid status as well as the capability to exchange power with the grid. The TC exchanges the power between two buses and regulates the voltage in both buses, in the case of off-grid operation. The NG dynamics, with the proposed structure and developed primary and secondary control algorithms are validated through extensive computer simulations in PSCAD/EMTDC.
Details
- Title
- Dynamic operation and control of a hybrid nanogrid system for future community houses
- Authors/Creators
- R.P.S. Chandrasena (Author/Creator) - Department of Electrical and Information EngineeringUniversity of RuhunaGalleSri LankaF. Shahnia (Author/Creator) - Department of Electrical and Computer EngineeringCurtin UniversityPerthAustraliaA. Ghosh (Author/Creator) - Department of Electrical and Computer EngineeringCurtin UniversityPerthAustraliaS. Rajakaruna (Author/Creator) - Department of Electrical and Computer EngineeringCurtin UniversityPerthAustralia
- Publication Details
- IET Generation, Transmission & Distribution, Vol.9(11), pp.1168-1178
- Publisher
- IET Digital Library
- Identifiers
- 991005541546607891
- Copyright
- 2015 The Institution of Engineering and Technology
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Journal article
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- 4 Electrical Engineering, Electronics & Computer Science
- 4.18 Power Systems & Electric Vehicles
- 4.18.204 Smart Grid Optimization
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- Engineering