Large wind generation in existing power system increase the requirement of frequency response (FR) services, as the existing wind generators are weak in providing inertial and Primary Frequency Response (PFR). This necessitates optimal PFR schedules from unit commitment (UC). PFR constrains have been considered in Stochastic Unit Commitment (SUC) problem. However, the simulation process is computationally demanding and necessitates a modelling technique with minimal computational burden, to optimize generation and PFR schedules simultaneously, considering wind uncertainty. This paper proposes computationally fast Modified Interval Unit Commitment (MIUC) model to minimize the generation scheduling cost and optimize PFR. Uncertainty is modelled using upper and lower limit, while ramp requirements of consecutive hours depend on the net load scenarios. Case studies are carried out on a single area IEEE RTS; comparative analysis with stochastic scheduling technique show that the proposed method can drastically reduce the simulation time, while offering similar level of operating cost, PFR cost, and PFR schedules, thus addressing wind uncertainty at different penetration level adequately. Further, proposed model has the potential to offer solutions within acceptable operational time frames for the PFR ancillary service market clearing and dispatch for future low carbon systems.
- Computational modeling
- Frequency response
- stochastic scheduling
- system inertia
- unit commitment
- Wind forecasting
- wind generation
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
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- Department of Electronic & Electrical Engineering - Professor
- Centre for Sustainable Power Distribution
- EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa)
- Centre for Doctoral Training in Decarbonisation of the Built Environment (dCarb)
Person: Research & Teaching