Demand for flexibility in the power system under different shares of renewable generation

Spisto, Amanda; Möbius, Thomas; Quoilin, Sylvain

doi:10.1109/eem.2015.7216775

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…The provision of flexibility comes from institutional enablers (such as market design [3] and interconnection [5]), flexible generation technology [6], energy storage [7], [8], spinning reserves [9], and additional sources of flexibility (e.g., electric vehicles [10] and demand response (DR) [11], [12]). Especially, hourly DR program is beneficial in reducing the cost of security-based power system scheduling [13], in lowering load payment [14], and in improving the thermal generation flexibility [15].…”

Section: A Related Workmentioning

confidence: 99%

“…Note that the effective spinning reserve (determined by τ i,t,c RU i ) should not exceed the available reserve (see e.g., [44]). The dispatchable generators are subject to ramping rate limits (7). Some dispatchable generators are supposed to deliver certain energy (8) due to bilateral contract constraints or fuel constraints (e.g., natural gas contract and reservoir capacity).…”

Section: B Mathematical Formulationmentioning

confidence: 99%

“…Particularly, in the presence of transmission contingencies, the adjustment of each dispatchable generator for corrective control is limited to the corresponding contingency reserve (9) (see e.g., [37], [45]) due to the short dispatch lead time. Note that the spinning up/down reserve to hedge the uncertainty of the net load (3a) has been determined by (4) and (7).…”

Section: B Mathematical Formulationmentioning

confidence: 99%

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Quantification of Intra-hour Security-Constrained Flexibility Region

Qin

Hou

Lei

et al. 2017

IEEE Trans. Sustain. Energy

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Rapid growth of renewable energy sources (RES) in the generation capacity mix poses substantial challenges on the operation of power systems in various time scales. Particularly in the intra-hour time scale, the interplay among variability and uncertainty of RES, unexpected transmission/generation outages, and short dispatch lead time cause difficulties in generationload balancing. This paper proposes a method to quantify the intra-hour flexibility region. A robust security-constrained multiperiod optimal power flow (RSC-OPF) model is first constructed to quantify the frequency, magnitude, and intensity of insufficient flexibility. The randomness of RES is captured by uncertainty sets in this model. The N-k contingency, spinning reserve, and corrective control limit constraints are included. This model is then cast into a two-stage robust optimization (RO) model and solved by the column-and-constraint generation (C&CG) method. The emergency measures with a least number of affected buses are derived and subsequently assessed by the post-optimization sensitivity analysis. Finally, the operational flexibility region is determined by continuous perturbation on the RES penetration level and the forecast error. The IEEE 14-bus system and a realistic Chinese 157-bus system are used to demonstrate the proposed method.

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