Germany

5.1.3 Alternative Methods

Because of the relatively intense calculation and data requirements for a reliability assessment of wind capacity value, some approximation methods have been developed.

Although reliability-based approaches (including new methods recently developed, and new ones that may appear) appear to be the most robust methods of assessing wind capacity value, there has been considerable interest in developing simpler methods that can be applied on abbreviated data sets. This appears to be more prevalent in the United States. Simplified methods are generally based on wind capacity factor that is calculated over a suitably-defined peak period. The advantage of this approach is that the metric is transparent, and is easy to understand and to relate to system conditions. The disadvantage of these methods is that they are not capable of assessing and finding times that the system may be at risk even though loads are not especially high. If a significant fraction of the generating capacity is on maintenance during the shoulder seasons, this can cause a potentially large increase in LOLP and can result in potentially much higher risk than peak periods.

There is also emerging interest in reliability-based approaches that differ from LOLP-based methods. Rather than look at LOLP, it may be useful to examine state transition probabilities, focusing on the likelihood that the system will evolve into a state that requires additional balancing or other operator action that arises because of wind (Doherty & O’Malley 2005). More work is anticipated in this area, and as the experience with wind grows around the world, international collaboration will move the state of the art forward.

January and February). The maximum positive or negative deviations of the individual sensitivity calculations from the mean value are approximately +1% or -1,5% for 2003 and drop to under +0,5% or -0,7% for 2015. These differences can be regarded as marginal and have no major bearing on subsequent calculations.

0%

2%

4%

6%

8%

10%

12%

2003 2007 2010 2015

% of installed WT capacity

20 coldest days All winter days

Annual peak-load days Nov & Dec

December Mean value Level of supply reliability

99%

Figure 30. Average gain in secured capacity of the wind turbines in% of the installed WT capacity at the time of the annual peak load (DENA, 2005).

The additionally secured capacity which can be assigned to the installed wind turbines depends on the level of supply reliability. To analyse the influence of this factor, sensitivity calculations were conducted with a level of supply reliability of 97%, 98%

and 99%. The selected level of supply reliability influences the values for the specific secured capacity of wind turbines at the time of the annual peak load only slightly (see following figure).

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

2003 2007 2010 2015

% of installed WT capacity 97% 98% 99%

Level of supply reliability

Figure 31. Sensitivities to rises in secured capacity of wind turbines at the time of the annual peak load in relation to the level of supply reliability (DENA, 2005).

The level of the secured capacity of the wind turbines varies seasonally. It is the highest in spring and winter, and in summer it is distinctly below these values (see following table).

Table 16. Seasonal rise in secured capacity of wind turbines (DENA, 2005).

2003 2007 2010 2015

% of installed wind turbine capacity

Winter 8,3% 6,9% 6,5% 6,0%

Spring 8,6% 7,2% 6,9% 6,4%

Summer 6,1% 5,3% 5,4% 5,1%

Autumn 7,2% 6,1% 5,9% 5,5%

in MW

Winter 1199 1542 1941 2163

Spring 1245 1605 2057 2289

Summer 889 1187 1599 1824

Autumn 1040 1352 1750 1970

Methodology: The secured capacity of the entire generation system is determined by using a model in several steps. In the first step the secured capacity of the thermal generation system is determined; in the second step the secured capacity of the entire generation system including the conventional generation system and the dispersed wind power generation system is determined. Dispersed wind power generation includes all wind turbines installed onshore and offshore taking into account their spatial distribution.

The probability and level of outage of thermal generating capacity is determined by an analytical derivation based on the outage probabilities of the single generating units using the recursive convolution method known from probability calculus.

Assumptions: The probability function of the seasonal feed-in of the dispersed wind power generation system is based on quarter-hour feed-in values for the forecast years 2003, 2007, 2010 und 2015. For winter not only the probability function for the entire period (November to February) is determined, but also probability functions for other periods – days when historically annual peak loads were reached, 20 coldest days, days in November and December as well as days in December – are determined.

Assumptions about unplanned outages are differentiated according to the technology involved. They range from 1,8 to 4% (see following table). An unplanned outage of 0%

is assumed for storage head installations and pumped storage power stations.

Heat controlled combined heat and power plants, run-of-river power stations as well as other electricity options based on renewable energy sources (except wind) are not included endogenously in the model because they are given a secured capacity according to the average feed-in during peak load hours.

A level of supply reliability of 99% is assumed for further calculations. Levels of supply reliability between 97% and 99% are used for sensitivity calculations.

It is assumed that the peak-load case occurs in the winter and without significant wind power feed-in. The peak-load is assumed to be constant over the long term. Depending on the grid region, the peak load can occur up to 800 hours a year.

Table 17. Outage rates for power plants (DENA, 2005).

Power plant technologies Unplanned, non-disposable outages

Nuclear power stations 3,0%

Lignite fired power stations 3,2%

Hard coal fired power stations 3,8%

Natural gas and steam fired power plants 1,8%

Gas fired steam turbine 1,8%

Gas turbines 3,0%

Oil fired power station 1,8%

Storage power station 0,0%

Pumped storage hydro power stations 0,0%

Limitations: No additional measures to raise the level of the secured capacity of wind turbines like storage systems or extended power exchange over large areas with different weather conditions were assumed in this study.