Journal article
Risk-oriented multi-area economic dispatch solution with high penetration of wind power generation and compressed air energy storage system
IEEE Transactions on Sustainable Energy, Vol.11(3), pp.1569-1578
2020
Abstract
This paper investigates the risk-oriented multi-area economic dispatch (MAED) problem with high penetration of wind farms (WFs) combined with compressed air energy storage (CAES). The main objective is to help system operators to minimize the operational cost of thermal units and CAES units with an appropriate level of security through optimized WF power generation curtailment strategy and CAES charging/discharging control. In the obtained MAED model, several WFs integrated with CAES units are considered in different generation zones, and the probability to meet demand by available spinning reserve during N−1 security contingency is characterized as a risk function. Furthermore, the contribution of CAES units in providing the system spinning reserve is taken into account in the MAED model. The proposed framework is demonstrated by a case study using the modified IEEE 40-generator system. The numerical results reveal that the proposed method brings a significant advantage to the efficient scheduling of thermal units’ power generation, WF power curtailment, and CAES charging/discharging control in the power system.
Details
- Title
- Risk-oriented multi-area economic dispatch solution with high penetration of wind power generation and compressed air energy storage system
- Authors/Creators
- A. Azizivahed (Author/Creator) - University of Technology SydneyS-E Razavi (Author/Creator) - Murdoch UniversityA. Arefi (Author/Creator) - Murdoch UniversityM.J. Ghadi (Author/Creator) - University of Technology SydneyL. Li (Author/Creator) - University of Technology SydneyJ. Zhang (Author/Creator) - University of Technology SydneyM. Shafie-khah (Author/Creator)J.P.S. Catalao (Author/Creator) - University of Vaasa
- Publication Details
- IEEE Transactions on Sustainable Energy, Vol.11(3), pp.1569-1578
- Publisher
- IEEE
- Identifiers
- 991005544375807891
- Copyright
- © 2020 IEEE
- Murdoch Affiliation
- School of Engineering and Energy
- Language
- English
- Resource Type
- Journal article
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- Collaboration types
- Domestic collaboration
- International 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
- Engineering, Electrical & Electronic
- Green & Sustainable Science & Technology
- ESI research areas
- Engineering