Wind   Energy   and   Electric   Grid   Integration
Electricity   consumption   varies   continuously.
Every   time   someone   turns   on   or   off   a   light   bulb,   computer,   or   television   the   electric   infrastructure   makes   minute   changes   to   compensate   for   the   fluctuating   electric   load.
When   entire   city   blocks   and   cities   are   aggregated   together,   the   fluctuations   are   smoothed   out   considerably,   and   daily   patterns   can   be   observed.
Figure   1   shows   a   typical   load   profile.
At   the   top   is   an   example   of   a   load   profile   for   a   single   day.
The   electricity   demand   reaches   its   lowest   point   in   the   early   hours   of   the   morning,   but   even   then   the   demand   is   not   zero.
Loads   such   as   heating,   air   conditioning,   ventilation,   and   refrigeration   systems   consume   power   constantly.
This   constant   demand   is   called   baseload .
The   electricity   consumption   increases   in   the   morning   as   appliances   are   turned   on,   and   reaches   a   peak   sometime   in   the   middle   of   the   day.
This   load   above   baseload   is   called   peaking   load .
Consumption   is   seen   to   decline   slightly   in   the   late   afternoon   before   it   picks   up   again   in   the   evenings   as   people   prepare   dinner   and   then   switch   on   lighting   when   the   sun   sets.
The   demand   then   tails   off   sharply   as   people   begin   to   go   to   bed,   and   the   cycle   repeats.
At   the   bottom   of   Figure   1   is   an   example   of   a   typical   weekly   electric   demand   profile.
The   demand   profile   varies   from   day   to   day   and   may   be   different   between   weekdays   and   weekends.
The   demand   also   varies   significantly   by   season.
Air   conditioning
Figure   1   consumes   enormous   amounts   of   electricity   on   hot   summer   afternoons.
Demand   also   varies   by   region   of   the   country,   largely   because   of   different   heating   fuel   types,   varying   daylight   hours,   and   different   air   conditioning   demands.
There   are   many   different   types   of   electric   power   generation   equipment   in   use   today.
Each   type   of   equipment   has   a   unique   set   of   characteristics   that   may   make   it   best   suited   for   different   roles   in   meeting   our   nation’s   power   demand.
Such   characteristics   include   the   time   it   takes   for   it   to   ramp   up   to   maximum   power,   its   maximum   and   minimum   power   (both   are   important),   and   operating   and   fuel   costs.
Large   power   plants   that   use   boilers,   such   as   nuclear   and   coal   often   have   long   start ‐ up   times,   slow   power   ramp ‐ up   rates   and   low   marginal   operating   costs.
This   makes   them   well ‐ suited   for   meeting   baseload   electricity   demands.
Power   generation   systems   that   meet   peaking   loads   generally   have   faster   start ‐ up   times   but   often   have   higher   marginal   operating   costs.
An   example   of   a   traditional   peaking   generation   plant   is   a   gas   turbine   generator.
1

If   there   is   one   thing   that   everyone   understands   about   wind,   it   is   that   wind   is   a   variable   resource.
Wind   forecasting   has   improved   in   recent   years,   which   allows   companies   to   compile   increasingly   accurate   day ‐ ahead   projections   for   the   power   output   of   wind   turbines   at   a   specific   site.
Even   so,   the   fact   remains   that   wind   turbines   can   only   generate   power   when   the   fuel   (wind)   is   available.
This   has   led   to   concerns   about   whether   wind   energy   actually   adds   net   capacity   to   the   electric   grid   infrastructure,   and   whether   wind   energy   can   legitimately   provide   reliable   baseload   electric   power.
In   fact,   wind   energy   does   have   some   capacity   value   (not   to   be
Figure   2   confused   with   capacity   factor ;   please   see
FAQ’s),   and   does   have   the   potential   to   contribute   to   baseload   power.
Figure   2   shows   capacity   value   estimates   in   use   today   by   several
Figure   2   utilities   and   grid   operators   around   the   United   States.
The   amount   of   power   produced   by   a   wind   farm   that   can   be   considered   reliable   power   for   scheduling   purposes   (the   percentage   of   wind   power   that   has   capacity   value)   depends   on   circumstances   unique   to   the   area   being   considered.
Among   the   biggest   factors:   increasing   the   area   being   considered   (the   size   of   the   balancing   area ),   increasing   the   number   of   turbines,   increasing   the   geographic   diversity   of   the   turbines,   and   increasing   the   frequency   with   which   the   load   is   balanced   all   have   the   effect   of   increasing   the   percentage   of   the   turbine’s   output   that   can   be   considered   as   reliable   power.
In   short,   the   best   strategy   is   diversification.
While   the   output   of   a   single   1.5
MW   wind   turbine   is   highly   variable,   the   output   of   a   100   MW   wind   farm   is   significantly   less   so.
This   fact   is   shown   in   Figure   3,   where   three   scenarios   are   represented.
All   three   scenarios   present   a   graph   of   summed   power   outputs   normalized   to   the   mean.
That   is,   the   power   output   over   time   is   displayed   as   a   multiple   of   the   average   power   output.
The   bottom   graph   in   blue   is   a   summation   of   the   power   output   from   15   wind   turbines   at   a   particular   wind   farm.
The   peak   power   output   is   approximately   1.5
times   the   mean   power   output.
The   middle   graph   is   a   summation   of   200   wind   turbines   at   the   same   wind   farm   over   the   same   time   period.
There   is   significantly   less   variability   in   this   graph,   and   the   peak   value   is   only   1.2
times   the   mean.
The   top   graph   is   the   summation   of   the   two   bottom   graphs,   with   the   power   output   of   215   wind   turbines   represented.
If   the   output   of   the   wind   farm   in   Figure   3   was   combined   with   the   output   of   another   wind   farm   200   miles   away,   the   summation   of   the   two   wind   farms   could   be   expected   to   have   even   less   variability.
The   reason   is   that   while   the   wind   might   not   be   blowing   right   now   in   our   particular   location,
2

there   is   a   good   chance   that   it   is   blowing   somewhere   in   one   of   our   neighboring   states.
Tomorrow   the   situation   might   be   reversed.
In   other   words,   the   correlation   between   wind   speeds   at   two   turbines   200   miles   apart   is   expected   to   be   much   lower   than   the   correlation   between   wind
Figure   3   speeds   at   two   turbines   in   the   same   wind   farm.
This   has   a   stabilizing   effect   on   the   total   power   output.
According   to   a
2007   study   by   scientists   at
Stanford
University,   if   wind   is   interconnected   on   a   large   scale,   at   least   33%   of   the   total   energy   produced   could   be   used   as   reliable   baseload   electric   power.
In   a   separate   report,   the   National   Renewable   Energy   Laboratory   recently   found   that   between   5%  ‐  40%   of   the   power   output   from   wind   energy   could   be   considered   as   capacity   value   added   to   the   electric   grid   infrastructure,   depending   on   the   unique   characteristics   of   the   area   in   question.
Even   the   wind   energy   that   is   not   considered   baseload   power   is   useful   to   the   electric   grid.
In   practical   application,   any   excess   wind   power   will   typically   offset   peaking   plants   such   as   gas   turbines.
The   power   output   of   the   peaking   plant   is   throttled   back   when   the   wind   power   output   is   high,   and   vice   versa   when   the   wind   is   calm.
Therefore,   less   fuel   is   burned   by   the   peaking   plants   when   more   wind   power   is   on   the   grid.
As   it   turns   out,   wind   energy   can   make   a   valuable   contribution   to   the   nation’s   energy   demands.
The   keys   to   maximizing   the   contributions   of   wind   energy   are   utilizing   modern   forecasting   tools   to   plan   energy   production,   intelligently   planning   wind   assets   to   take   advantage   of   geographic   diversity,   and   recognizing   both   the   baseload   and   peaking   components   of   wind   energy’s   potential.
3