Impact Evaluation of Wind Power Geographic Dispersion on Future Operating Reserve Needs

Fernando Manuel Carvalho da Silva Santos, Leonardo Elizeire Bremermann, Tadeu Da Mata Medeiros Branco, Diego Issicaba and Mauro Augusto da Rosa
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Fernando Manuel Carvalho da Silva Santos: College of Electrical Engineering, Federal University of Pará, Pará 66075-110, Brazil
Leonardo Elizeire Bremermann: Department of Electrical and Electronics Engineering, Federal University of Santa Catarina, Santa Catarina 88040-900, Brazil
Tadeu Da Mata Medeiros Branco: College of Electrical Engineering, Federal University of Pará, Pará 66075-110, Brazil
Diego Issicaba: Department of Electrical and Electronics Engineering, Federal University of Santa Catarina, Santa Catarina 88040-900, Brazil
Mauro Augusto da Rosa: Department of Electrical and Electronics Engineering, Federal University of Santa Catarina, Santa Catarina 88040-900, Brazil

Energies, 2018, vol. 11, issue 11, 1-13

Abstract: This paper evaluates the potential of diverse wind power patterns to balance the global power output of wind farms using the concept of operating reserve assessment. To achieve this, operating reserve assessment models are utilized to evaluate bulk generation systems under several conditions of wind power geographic distribution. Different wind behavior patterns and wind power penetration levels are tested using a modified configuration of the Institute of Electrical and Electronics Engineers Reliability Test System 96 (IEEE RTS-96). The results highlight that on a large country scale system with different wind characteristics, the diversification of wind behavior might be conducive to a compensation of wind power fluctuations, which may significantly decrease the need for system operating reserves. This effect is verified using probability distribution functions of reserve needs estimated by sequential Monte Carlo simulations (SMCS), such that useful information regarding generation capacity flexibility is drawn from the evaluations.

Keywords: operating reserve capacity; sequential Monte Carlo simulation; wind power (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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