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Operation of Distribution Systems with High Penetration of Wind Energy
Asgary, Farid | 2014
499
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- Type of Document: M.Sc. Thesis
- Language: Farsi
- Document No: 47954 (05)
- University: Sharif University of Technology
- Department: Electrical Engineering
- Advisor(s): Fotuhi-Firuzabad, Mahmoud
- Abstract:
- Power distribution systems have been traditionally operated as passive networks which consume electric power supplied by the transmission grid. Increasing utilization of wind energy in distribution systems, notably wind energy, is changing the way distribution sys-tems are operated. The distribution system operators (DSO) would operate the available wind power for reducing the power purchased from the wholesale market. However, high penetration of wind energy in distribution systems would require advanced operation mod-els and additional flexibility in system to offset the variability and uncertainty associated with wind energy. In addition, wind availability often does not positively correlate with electricity demand, either in terms of time of availability or geographic location. These op-erational challenges would impose financial risks to the DSO and would reduce the bene-fits of wind energy in system operation. In this project, we propose to utilize the demand-side flexibility to mitigate the opera-tional challenges of wind energy in distribution system. In this regard, we design targeted demand response (DR) programs to solicit the customers’ flexibility for maximizing the wind energy utilization in DSO’s operation. We formulate a stochastic model for DSO’s day-ahead operation, which models the operational impacts of wind energy integration dur-ing the DSO’s operation decisions. The DR programs are utilized to cover the variability and uncertainty of wind energy in the proposed day-ahead operation model. The problem is formulated as a two-stage stochastic programming model and considers the DSO’s finan-cial risks due to wind energy operation
- Keywords:
- Demand Response ; Wind Energy ; Two Stage Stochastic Programming ; Distribution System ; Uncertainty
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