Using Standard Deviation as a Measure of Increased Operational Reserve Requirement for Wind Power

Abstract

The variability inherent in wind power production will require increased flexibility in the power system, when a significant amount of load is covered with wind power. Standard deviation (σ) of variability in load and net load (load net of wind) has been used when estimating the effect of wind power on the short term reserves of the power system. This method is straightforward and easy to use when data on wind power and load exist. In this paper, the use of standard deviation as a measure of reserve requirement is studied. The confidence level given by ±3–6 times σ is compared to other means of deriving the extra reserve requirements over different operating time scales. Also taking into account the total variability of load and wind generation and only the unpredicted part of the variability of load and wind is compared. Using an exceedence level can provide an alternative approach to confidence level by standard deviation that provides the same level of risk. The results from US indicate that the number of σ that result in 99% exceedence in load following time scale is between 2.3–2.5 and the number of σ for 99.7% exceedence is 3.4. For regulation time scale the number of σ for 99.7 % exceedence is 5.6. The results from the Nordic countries indicate that the number of σ should be increased by 67–100% if better load predictability is taken into account (combining wind variability with load forecast errors).

Offshore Wind and Wave Energy Assessment around Malè and Magoodhoo Island (Maldives)

“…The combination of wind and wave energy resources reduce the overall dimensions per unit of power, the operational requirement for reserve and regulating power [97][98][99][100][101] as well as the requirement for generation capacity to maintain the power system reliability [102][103][104]. By the co-location of wind and wave generators, also the nearshore or shoreline devices are further promoted.…”

An enhanced method for the determination of the ramping reserves

“…As discussed in [3], the quantity of reserves is determined a posteriori on the basis of historical experience of power system operation. The standard deviation of potential imbalances, s , is determined from the forecast error or the net load variability.…”

“…NERC defines the minimum score for the Control Performance Standard 2 (CPS2) equal to 90% [4]. Under the assumption of normal distribution, a 2s confidence interval is chosen [3], [5]. Other studies have used a 3s confidence interval [6], [7] to comply with the industry standard of 95% [8].…”

A System Analysis on Steppe Sustainability and Its Driving Forces—A Case Study in China

“…Standard deviation is a very important parameter for exploratory data analysis [70] and it has been used successfully to predict the requirement of reserve for wind power [71], appreciate the reliability of measures in sports medicine and science [72], assess agreement between methods of clinical measurement [73], estimate noise levels of image, and so on. According to the Pauta criterion, the standard deviation (namely mean square error in error analysis) multiplied by 1, 2, and 3 can reflect the fluctuation of NDVI or NPP difference data with different degrees or confidence [74][75][76], where positive fluctuation denotes an improved case and negative fluctuation denotes a degraded case.…”

“…(2) A copula model is suitable for variables obeying any type of distribution, and (3) a copula model is powerful for analyzing the nonlinear correlation between variables [79][80][81][82]. Recently, the copula model has been used to predict flooding using meteorological factors [69,70] and applied with satisfactory results in geoscience, hydrology, finance, and other fields [71][72][73]. Consequently, the copula model was a reasonable choice for analyzing correlations between NPP changes and meteorological factors in this study.…”