Wind Energy Integration into the Grid - Capacity Credit

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Power plants using renewable fuels (e.g. power production based on biomass) generally allow scheduling of electricity production, as their primary source of energy can be stored and transported. Within an electricity supply system their use can be planned like any gas- or coal power plant. The process of schedule-development in an electricity supply system is called dispatch. Thus the integration of these dispatchable renewable energy plants does not cause significant changes in the system[1].

In contrast to this, wind turbines or wind parks are non-dispatchable sources of electricity production: Wind velocity and the related amount of electricity generated is only predictable by meteorological methods (with a limited certainty), but of course there is no possibility to influence the availability of the renewable resources. Electricity production by wind turbines is determined by the available wind velocity and the electricity supply system has to adapt to the characteristics of wind energy, in case the potentials of this renewable resource should be used effectively. Efficient integration of wind energy into an existing power system thus requires an advanced management of the conventional power plant[2]. This article focusses on the effects of wind energy integration on the reliability of an electricity supply system. The Capacity Credit is described as way to quantify the reliability of electricity generation by wind turbines.

Wind variability

The variability of electricity production by wind turbines is generally due to changes in wind speed over time. The wind variability can be described on several different time scales:

  • Variations of wind potentials from year to year
  • Seasonal variations of average wind speeds; in Germany average wind velocity during winter months is usually twice as high as the wind speed in the summer[3].
  • Changes in weather cause wind variability on the time-scale of weeks and several days.
  • Within 24 hours a significant difference of wind speeds between daytime and night can be observed at most sites. Depending very strongly on climatic conditions of the site, variations during daytime could show characteristic patterns
  • Wind speed varies from hour to hour and also from one minute to the next
  • Variations on the time-scale of seconds are described as turbulence[4].

The extent of variations on the listed time-scales differs considerably. The largest share of the total variability of wind speed is contributed by variations within 3-5 days, because during this period of time significant changes in weather can occur. Concerning the operation of an electricity supply system, these changes can be regarded as slow. The second major contribution to overall variability is induced by turbulence, which may cause more serious problem for the management of a supply system. If wind turbines are aggregated in a wind park, this has a balancing effect on turbulence effects on electricity production. 

Within the time-frame of 10 minutes to one hour frequency and extent of variations are relatively small. This so-called spectral gap is a very advantegous characteristic of wind speed distribution: If the the variations within this period of time had been considerable, this would have result in larger complications for wind energy integration into the electricity supply system[5].

Variability of electricity production

The characteristics of electricity production are influenced by the chosen turbine type to a considerable extent. As the description of these influences requires detailled technical explaination of the turbine types, this article abstracts from these differences. The focus is rather set on the general 'transmission' of wind variability into variability of the electricity production.

Variability in electricity production may be described concerning three main characteristics[6]:

  • Full load hours respectively annual energy yield,
  • periodical patterns of electricity generation by wind turbines,
  • Volatility of electricity generation by wind turbines

Hours of full load is a term describing the number of hours the wind turbines have been operated at their rated capacity during one year. The annual energy yield is usually given in MWh. The term 'periodical patterns of electricity generation' describes any patterns in wind variability, which can be observed with regularity irrespective the frequently changes on other time-scales. As an example the regular seasonal changes in wind speed distribution cause similar variations in electricity generation[7]. The term volatility is used for changes within small time-frames from minutes to hours.

The 'translation' of wind variability into the variability of electricity generation, fundamentally depends on the following factors:

  • Characteristics of the extraction of wind energy by modern wind turbine types
  • site selection, geographical distribution of wind turbines 
  • wind turbine operation: in a wind park (aggregated electricity generation) or as a sole application

The power – extractable by a wind turbine at a certain wind speed – is given by the following function:

 

where  is used for air density, A indicates the area swept by the turbine rotor, V describes wind velocity and Cp is the power coefficient describing the efficiency of wind energy conversion by the turbine. As electricity production changes proportional to the cube of wind speed, variability of wind speed results in significantly larger variations in electricity generation.

Depending on the design of modern wind turbines, this is only valid for a certain range of wind speed variations:

Very low wind speeds do not contain sufficient power to operate wind turbines. Typically modern wind turbines have a so-called Cut-in-wind speed Vci of 3,5 m/s and reach their maximum power at a rated wind speed Vn. Many turbines have a Vn-value of 15 m/s. Above this wind speed the operation of the wind turbines are regulated by aerodynamic control mechanisms to limit rotor speed and the related output. As a result variations of power output at wind speeds between 15 m/s und 25 m/s are low. The wind velocity 25 m/s (equivalent to wind force 10 Beaufort) is often determined as Cut-out-Wind speed Vco (Freris und Infield, 2008, S.30ff). Der Standort einer WEA ist auf Grund unterschiedlicher regionaler Windverhältnisse einer der wichtigsten Einflüsse auf die zu erwartende Stromerzeugung der WEA und deren Variabilität. Durchschnittlich kann in Deutschland für Offshore-Standorte von einer höheren und konstanteren Windgeschwindigkeit ausgegangen werden als an Land. Die höhere Leistung der Offshore-Anlagen basiert aber zudem auf dem umgebenden ’Gelände’ des Standortes: Jegliche Erhebungen (etwa Hügel, Wald oder Infrastruktur) wirken als Reibung auf die Windströmung und führen zu einer Verringerung der Leistung der WEA (Dena, 2005). Die Integration von WEA in das Stromnetz findet in den meisten Fällen nicht als Einzelanlagen sondern in Form aggregierter Windparks statt. Der Effekt dieser Aggregierung ist eine starke Verringerung der Variabilität der Stromerzeugung aus WEA, die mit der räumlichen Verteilung der WEA zusammenhängt: Sind die WEA eines Windparks räumlich über ein große Fläche verteilt, so wirken Turbulenzen in unkorrelierter Weise auf die Stromerzeugung der WEA. Die Aggregierung gleicht auf diese Weise kurzfristige Schwankungen weitgehend aus. Für die Integration von Windenergie in das Stromnetz wird die Gesamtheit der verschiedenen Windparks, die geographisch weit verteilt liegen, betrachtet. Hier wirkt sich der Effekt der Aggregierung auf Variationen auf größeren Zeitskalen aus. Kann die Leistung eines einzelnen Windparks von Stunde zu Stunde um bis zu 60% schwanken, so liegt dieser Wert für eine aggregiertes System bei lediglich 20%. Dieser Effekt der Aggregierung geographisch weit verteilter Windparks hat große Vorteile für die WEA-Integration, da die vorzuhaltende Regelkapazität für den Ausgleich der WEAVariabilität geringer ausfallen kann (Freris und Infield, 2008, S.75). Da die räumliche Verteilung mit dem Ausbau der Windenergie in Deutschland zwingend zunimmt (etwa die Erweiterung in den Raum der Nord- und Ostsee) kann davon ausgegangen werden, dass dieser positive Effekt für die Integration verstärkt genutzt werden kann (Dena, 2005).

References

  1. Gatzen C (2008) The Economics of Power Storage - Theory and Empirical Analysis for Central Europe, Schriften des Energiewirtschaftlichen Instituts zu Köln, vol 63. Oldenbourg Industrieverlag
  2. Gatzen C (2008) The Economics of Power Storage - Theory and Empirical Analysis for Central Europe, Schriften des Energiewirtschaftlichen Instituts zu Köln, vol 63. Oldenbourg Industrieverlag
  3. Jarass L, Obermair G, Voigt W (2009) Windenergie – Zuverlässige Integration in diefckLREnergieversorgung. Springer
  4. Freris L, Infield D (2008) Renewable energy in power systems. John Wiley & Sons, Ltd
  5. Freris L, Infield D (2008) Renewable energy in power systems. John Wiley & Sons, Ltd
  6. Dena (2005) Konzept für eine stufenweise Entwicklung des Stromnetzes in DeutschlandfckLRzur Anbindung und Integration von Windkraftanlagen Onshore und Offshore unter BerücksichtigungfckLRder Erzeugungs- und Kraftwerksentwicklungen sowie der erforderlichenfckLRRegelleistung. In: Energiewirtschaftliche Planung für die Netzintegration von WindenergiefckLRin Deutschland an Land und Offshore bis zum Jahr 2020 - Netzstudie I, DeutschefckLREnergie Agentur
  7. Dena (2005) Konzept für eine stufenweise Entwicklung des Stromnetzes in DeutschlandfckLRzur Anbindung und Integration von Windkraftanlagen Onshore und Offshore unter BerücksichtigungfckLRder Erzeugungs- und Kraftwerksentwicklungen sowie der erforderlichenfckLRRegelleistung. In: Energiewirtschaftliche Planung für die Netzintegration von WindenergiefckLRin Deutschland an Land und Offshore bis zum Jahr 2020 - Netzstudie I, DeutschefckLREnergie Agentur