Reliability assessment method of composite power system with wind farms and its application in capacity credit evaluation of wind farms

Chen, Fan; Li, Fangxing; Feng, Wei; Wei, Zhinong; Cui, Hantao; Liu, Haitao

doi:10.1016/j.epsr.2018.09.023

Cited by 54 publications

(17 citation statements)

References 26 publications

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“…3. Replace the scarcity time slices 6 (that determine the total installed capacity for the reference case) with off-peak time slices and impose a PRM-like constraint that determines the total installed firm capacity. The off-peak time slices are taken to be the time slices that precede each scarcity time slice by 24 hours.…”

Section: General Setupmentioning

confidence: 99%

“…The capacity credit is a well-established concept for conventional and renewable generators (see, e.g., [5,6]), and is often broadly defined as the share of a generator's nameplate capacity that can be relied on during critical peak moments [7]. Methods to calculate the capacity credit are traditionally categorized in two groups, i.e., (i) the reliability-based methods and (ii) the approximation-based methods [8].…”

Section: Introductionmentioning

confidence: 99%

“…Note that in a realistic case renewable technologies would compete alongside storage technologies in a planning model/capacity and energy market. However, to put the emphasis on the two capacity credit interpretations we assume the renewable penetration to be fixed 6. The number of scarcity time slices is typically lower than 10.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Capacity credit of storage in long-term planning models and capacity markets

Mertens

Bruninx

Duerinck

et al. 2021

Electric Power Systems Research

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Section: General Setupmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Capacity credit of storage in long-term planning models and capacity markets

Mertens

Bruninx

Duerinck

et al. 2021

Electric Power Systems Research

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“…This method is improved in ref. [13] by incorporating the parallel computing technique to accelerate the reliability assessment process.…”

Section: Introductionmentioning

confidence: 99%

Capacity value evaluation of wind farms considering the correlation between wind power output and load

Cai

2021

IET Generation Trans & Dist

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A method of capacity value evaluation for wind farms considering the correlation between wind power and load is presented. The paper starts with defining the metric of capacity value called capacity credit, and its basic evaluation process. Then the core part of capacity credit evaluation, which is the reliability assessment of power systems, is focused on. In this core part, two limitations of the frequently used cross entropy based importance sampling method are analysed. To solve the problems, an improved method is proposed by using truncated Gaussian mixture model as the proposal distribution of the cross entropy based importance sampling methods. This improved method is adopted to speed up the reliability assessment of composite power systems in the capacity credit evaluation. Finally, several numerical tests are designed and performed on the IEEE-RTS 79 and IEEE-RTS 96 test systems. The results show that the improved method is faster than traditional cross entropy based importance sampling methods when assessing the reliability of power system. Besides, the efficiency of the improved method is almost impervious to the correlation of load and wind power output, which ensures its applicability in different scenarios. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…Wind farm reliability is a subject of interest to industry and academia [1][2][3][4]. The availability of wind as a resource alongside the reliability of wind turbine generators may significantly affect power system reliability [5][6][7][8][9][10][11][12]. As a general concept, wind power diversification means that different wind farms can complement each other, leading to a smoother global power output [13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2018

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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.

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Reliability assessment method of composite power system with wind farms and its application in capacity credit evaluation of wind farms

Cited by 54 publications

References 26 publications

Capacity credit of storage in long-term planning models and capacity markets

Capacity credit of storage in long-term planning models and capacity markets

Capacity value evaluation of wind farms considering the correlation between wind power output and load

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

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