Renewable Centric Grid of the Future Ryn Hamilton July 27 2016

The Renewables-Centric Grid of the Future

Ryn Hamilton Ryn Hamilton Consulting

July 27, 2016

Introduc)on

Agrowingbodyofevidencesupportsthetechnicalandeconomicfeasibilityofintegra8ngmuchhigherlevelsofvariablerenewableresourcesontothegridthanpreviouslysupposed.

Thereisnoabsolutetechnicallimittothenumberofsuchplantsthatcanbebuiltandproducepower.

Renewableresourcesarealreadycost-compe88vewithconven8onalplantsinsomemarkets.Windpowerwasthemostcost-effec8veop8onfornewgrid-basedpowerin2015.

Thechallengesofmanaginggenera8onvariabilityfromhigherpenetra8onsofvariableresourcesarefundamentallysolvablewithongoingadvancesintechnology,communica8onsandgridmanagement.Goodtoolsexisttoday,andkeepbeGer.

Suchsolu8onscanbeimplementedatapricethatisamodestshareoftotalelectricsystemcost,accordingtoAdvancedEnergyEconomy.

2

Introduc)on

3

139 countries could get all of their power from renewables by 2050.

Mark Jacobson, Mark Delucchi Scientific American, Nov. 29, 2015

Salt Lake City Makes Historic Commitment to 100% Renewables by 2032.

– July 13, 2016 –

Hawaii Commits to Generate 100% Electricity from

Renewable Resources by 2045. – June 8, 2015 –

San Diego Vows to Move Entirely to Renewable Energy in 20 Years.

– December 2015 –

The U.S. needs renewable energy

standards of at least 50% by 2030 and

100% by 2050. Hillary Clinton

Rochester Minnesota Mayor Brede Sets a Goal of 100

percent renewable energy by 2031. – October 2015 –

MakingtheCommitment

4

113RENEWABLES 2016 · GLOBAL STATUS REPORT

05

Heating and Cooling

Power

Transport

Figure 41. Countries with Renewable Energy Transport Obligations, 2010–2015

Figure 39. Countries with Renewable Energy Power Policies, by Type, 2015

Figure XX. Countries with Renewable Energy Heating & Cooling Obligations, 2010–2015

Countries withpolicies in place

in 2010–2012

Countries thatadded policiesin 2013–2015

1

20


in 2010–2012


11

55

More than one policy type

Feed-in tariff /premium payment

Tendering

Net metering

No policy or no data

Source: REN21 Policy Database

Note: Ghana added a policy in 2013 but removed it in 2014.


Source: REN21 Policy Database; see endnote 55 for this chapter.

Figure 40. Countries with Renewable Energy Heating and Cooling Obligations, 2010–2015

Note: Bolivia, Dominican Republic, State of Palestine and Zambia added policies during 2010-2012 but removed them during 2013-2015.

Countries are considered to have policies when at least one national or state/provincial-level policy is in place.

113RENEWABLES 2016 · GLOBAL STATUS REPORT

05

Heating and Cooling

Power

Transport

Figure 41. Countries with Renewable Energy Transport Obligations, 2010–2015

Figure 39. Countries with Renewable Energy Power Policies, by Type, 2015

Figure XX. Countries with Renewable Energy Heating & Cooling Obligations, 2010–2015


in 2010–2012


1

20


in 2010–2012


11

55

More than one policy type

Feed-in tariff /premium payment

Tendering

Net metering

No policy or no data


Note: Ghana added a policy in 2013 but removed it in 2014.


Source: REN21 Policy Database; see endnote 55 for this chapter.

Figure 40. Countries with Renewable Energy Heating and Cooling Obligations, 2010–2015

Note: Bolivia, Dominican Republic, State of Palestine and Zambia added policies during 2010-2012 but removed them during 2013-2015.

Countries are considered to have policies when at least one national or state/provincial-level policy is in place.

MakingtheCommitment

Swedenplanstoeliminateallfossilfuelusageuseby2030andchallengescountriestoestablish100%renewablegoals.

CostaRicaachieved99%renewableenergyconsump8onin2015andaimstobeen8relycarbon-neutralby2021.

Nicaraguaisaimingfor90%renewableenergyby2020,mainlyfromwind,solar,andgeothermal.

Denmarkaimstobe100%fossilfuelfreeby2050,muchofitfromwind.

Kenyaplanstogenerateallofitselectricitywithrenewablesby2030,mainlywithwind,solarandgeothermal.

Portugalwasrun100%onwind,solar,andhydropowerforfourconsecu8vedaysinMay2016.

5

MakingtheCommitment

Scotlandintendstoexploititsrichresourcebasetoproduce100%ofitselectricityand>30%ofdemandfromrenewablesourcesby2020;thecountryhasalreadyachievedhalfthisgoal.In2015:

Windpowersupplied97%oftheresiden8alpowerused.

Solarpoweraccountedforoverhalftheresiden8alelectricandhotwaterhea8ngin2015.

Scotlandintendstoeliminatetheuseofallfossilfuelsandnuclearpowerby2030.

6

Beatrice Offshore Wind Farm This $3.8B project to be completed in 2019 is the largest infrastructure program in Scotland’s history, and

will result in the world’s largest lfloating wind farm.

Poten)alofRenewables

Solarandwinddominatethelandscapeforrenewableelectricityproduc8on.

Windandsolarresourcesarecharacterizedbyvariableoutput,whichmeansthatenergycannotbedispatchedunlesstheinputs(sun,wind)areavailable.

Otherrenewablesourcesaregrowinglessfast,suchasbiomass,concentratedsolarpairedwithstorage,geothermalpowerandhydroelectric.

7

²  Pumpedhydro

²  Storage²  Geothermal

²  Biofuel²  Biomass

²  Oceanthermal

²  Wind

²  SolarPV

²  Tidal

²  Wave

NotDispatchableDispatchable

Poten)alofRenewables

Land-basedwindisreadilyavailablefordevelopmentinmanyplacesintheU.S.Thereismorethan8,000GWofpoten8alcapacity.

Thecapacityofconcentra8ngsolarpowerisnearly7,000GW,mainlyinthesouthwest.Thepoten8alofsolarPVisessen8allyunlimited,accordingtotheAmericanPhysicalSocietywhosemembersincludetheScienceAdvisortothePresident.

Land-BasedWind

Solar

8

Total installed capacity of all resources as 1,064 GW in

2014. By 2030, electricity demand is projected to be

1,094 GW. (EIA)

Genera8ngplants(2015),EIA

CapacityAddi)ons

Renewableresourcesaccountedfor64%ofnewU.S.genera8onplacedinservicein2015.Scheduledplantaddi8onsfor2016areshownbelow.

9

Source:EnergyInforma8onAdministra8on

CapacityAddi)ons

77RENEWABLES 2016 · GLOBAL STATUS REPORT02

See endnote 1 for this section.

Additions are net of repowering/decommissioning.

Source: See endnote 6 for this section.

WIND POWERFigure 23. Wind Power Global Capacity and Annual Additions, 2005–2015

Figure 24. Wind Power Capacity and Additions, Top 10 Countries, 2015

Gigawatts

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Gigawatts

500

400

300

200

100

0

World Total

433 Gigawatts

318+36

370+52

+63+63

238+41

198+39159

+38121+2794

+2074+1559

+12

283+45

+39+38

+63

+27

+15

World TotalWorld Total

+45

+1559

159

Annual additionsCapacity

China United States

Germany India Spain United Kingdom

Canada France Italy Brazil

Gigawatts

150

120

90

60

30

0

+++++++ 30.8 30.8

+ 8.6

+ 5.7

+ 2.6 + 0+ 1 + 1.5 + 1.1 + 0.3 + 2.8

+ 2.6 + 0

Added in 20152014 total

Figure 25. Market Shares of Top 10 Wind Turbine Manufacturers, 2015

Goldwind (China)

12.5%

Vestas(Denmark)

11.8%

GE Wind (USA)

9.5%

Siemens (Germany)8.0%

Others

31.4%Gamesa (Spain) 5.4%Enercon (Germany) 5.0%United Power (China) 4.9%Mingyang (China) 4.1%Envision (China) 4.0%CSIC Haizhuang (China) 3.4%

Total sales = ~63 GW.

Source: FTI Consulting. See endnote 119 for

this section.

Source:RenewableEnergyPolicyNetwork

10

CapacityAddi)ons

11

62

02 MARKET AND INDUSTRY TRENDS

SOLAR PV

50 GWadded in 2015

Figure 14. Solar PV Global Capacity and Annual Additions, 2005–2015

Figure 15. Solar PV Global Capacity, by Country/Region, 2005–2015Figure ??. Solar PV Global Capacity, by Country or Region, 2005–2015

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Gigawatts

250

200

150

100

50

0

World Total

227 Gigawatts

138

177

100

70

4040

231696.75.1

Rest of WorldItalyUnited StatesJapanChinaGermany

+ 2.5

Figure 15. . Hydropower Capacity and Additions, Top Nine Countries for Capacity Added, 2015

Brazil Turkey India Vietnam Malaysia Canada Lao PDR Colombia

Gigawatts

Gigawatts

300

250

200

150

100

50

0

100

80

60

40

20

0China

+ 16.1

+ 1.9

+ 2.2+ 1.0

+ 0.7

+ 0.7

+ 0.6+ 0.6

Added in 20152014 total

Additions are net of repowering and retirements.

Source: See endnote 3

for this section.

Source: See endnote 9

for this section.

Source:RenewableEnergyPolicyNetwork

T&DInfrastructure

Arisingshareofrenewableresourceswillrequirebothtransmissionanddistribu8oninfrastructureimprovements.

12

Transmissioninfrastructureisneededtobringelectricityfrom

thegeneratortodistant

loadcenters.InmanSquare,Cambridge

Distribu)oninfrastructuremustbe

updatedtogivedistributedresourcesthecapabilitytopushexcesspower

ontothelocalgrid.Residen)alrooJopsolar

MaintainingSystemBalance

Aprolifera8onofnewtechnologiesandapproachestohelpmanagethegridarebecomingavailable.

Generatoroutputisvariableinreal8me,whichmeansthattoolstokeepthesystembalancedneedtooperateonasimilar8mescale.

Thiscanrangefromsecondstomonths.

²  Californiawillhaveathreehourabernoonrampof13GWby2020.

²  Overalongerhorizon,GermanyhaslowwindandsolaroutputformostofNovember.

Newtechnologiesandapproachesenablerapidandcoordinatedresponsestoan8cipatedandunan8cipatedchanges.

13


9

a constant rate all the time unless there is a maintenance shut-down. Of all major renewable

technologies, only solar and wind are VERs.

These patterns of generation can be compared to the electricity load, which is the amount of

electricity demanded at any period in time. Figure 3 plots the electricity load on March 31 in the

CAISO electric grid for 2013 to 2016. The load is lowest during the night, ramps up in the morning,

is relatively level throughout the day, and peaks in the evening. Wholesale electricity prices are

based on both the supply and demand of electricity. In an electric grid with all dispatchable

generation technologies, wholesale electricity prices would tend to follow the load over the day,

with occasional spikes during steep ramps when higher marginal cost generation (“peaking

plants”) must be ramped up to meet those ramps. In contrast, retail prices are typically fixed and

do not follow the load, as discussed above.

Geothermal

Biomass

Biogas

Small Hydro

Wind

Solar PV

Solar Thermal

0

1,000

2,000

3,000

4,000

5,000

6,000

0 2 4 6 8 1 0 1 2 1 4 1 6 1 8 2 0 2 2

Source: CAISO

Hour of the Day

Figure 2. Hourly Renewables Ouput Illustrative DayMW

March 2016

Source:CaliforniaISO

14


15

Hour

Megaw

aGs

Source:Interna8onalElectrotechnicalCommissionprojectteam,includingtheUnivofColoradoatBoulderandNREL

24

RE generation: the present, the future and the integration challenges

� Partial unpredictability: The availability of wind and sunlight is partially unpredictable. A wind turbine may only produce electricity when the wind is blowing, and solar PV systems require the presence of sunlight in order to operate. Figure 2-18 shows how actual wind power can differ from forecasts, even when multiple forecast scenarios are considered. Unpredictability can be managed through improved weather and generation forecasting technologies, the maintenance of reserves that stand ready to provide additional power when RE generation produces less energy than predicted, and the availability of dispatchable load to “soak up” excess power when RE generation produces more energy than predicted.

� Location dependence: The best wind and solar resources are based in specifi c locations and, unlike coal, gas, oil or uranium, cannot be transported to a generation site that is grid-optimal. Generation must be co-located with the resource itself, and often these locations are far

from the places where the power will ultimately be used. New transmission capacity is often required to connect wind and solar resources to the rest of the grid. Transmission costs are especially important for offshore wind resources, and such lines often necessitate the use of special technologies not found in land-based transmission lines. The global map in Figure 2-19 displays the latest data on mean land-based wind speeds around the world.

Because the presence of wind and sunlight are both temporally and spatially outside human control, integrating wind and solar generation resources into the electricity grid involves managing other controllable operations that may affect many other parts of the grid, including conventional generation. These operations and activities occur along a multitude of time scales, from seconds to years, and include new dispatch strategies for rampable generation resources, load management, provision of ancillary services for frequency and voltage control, expansion of transmission capacity, utilization of energy storage

Figure 2-17 | Hourly wind power output on 29 different days in April 2005 at the Tehachapi wind plant in California [haw06]

Variablegenera8onfromspecificunitscanbequitevariablefromdaytoday,aswellasthroughoutthehoursofanypar8cularday.


16

Integra8onneedsarisingfromvariableresourcesonthegriddependontheregion,resourcetypeandsize,climate,regionalmarketandloadcharacteris8cs.

Advancesinwindandsolararemakingitpossibletousevariablegenera8onplantsoverabroaderrangeofcondi8ons.

Someplantsareenabledtoprovideancillaryservicessuchasfrequencyregula8onorvoltagecontrol.

DiversetoolscanmanagepaGernsofsupplyanddemand.

Toolsincludetransmissionextension,coordina8onbetweenbalancingregions,smartgrid-enabledtechnologies,distributedresources(demandresponse,storage),favorableregula8on,microgridsandancillaryservices.


RequirementsandToolsforVariableRenewablesIntegra)onIsthis

availabletoday?

An)cipatemajor

advances?Gridmanagementmechanismstohandlesystemvariabilityandreducepeak ✔ ✔

Technologiesandapproachesforgridopera8onandcontrol(frequencyregula8on,voltagecontrol,powerbalance) ✔ ✔

Interconnec8onandcoordina8onbetweenregionalgridsforscalethatenhancesbalancingcapabili8es,reliabilityandstability ✔ ✔

Flexibledistributedresourcessuchasstorageanddemandresponse earlystage ✔

Bi-direc8onalflowofenergy(topdownandboGomup)allowingdistributedresourcestoprovidepowertothegrid ✔ ✔

Legisla8veandregulatorysupport/marketrules ✔ ✔

Businessmodelsthatcapturefullbenefitsandcosts,andfacilitateop8miza8on

earlystage ✔

17

GridManagement

Integra8onofvariablegenera8onresourcesontotheelectricgridisnotperformedbyanyoneen8tybutbytheac8onsofmany.

Theseen88esincludeu8li8es,generators,gridoperators,transmissionplanners,regulators,ISO/RTOmarkets,vendorsandcustomers.

Controlandop8miza8onisachievableateverylevel,fromthewholesalegriddowntoindividualfacilityloads.

Energymanagementsystemsmustbedexterousandenterprisingtoop8mizescheduling,dispatchandcontrol.

Fastschedulingwithdispatchdecisionsthatoccurinneartoreal-8mecanmanageuncertainty,andthusreducetheneedforreserves.

18

GridManagementFaster Scheduling to Reduce Expensive Reserves

Hourly schedules and interchanges

Dispatch decisions closer to real-time (e.g., intraday scheduling adjustments; short gate closure) reduce uncertainty.

Source: NREL

Sub-hourly scheduling

System Operations

HourlyScheduling&InterchangesSub-hourly

Source:Na8onalRenewableEnergyLaboratory

19

EnlargedBalancingAreas

Geographicaggrega8onofvariablegenera8oncansmoothfluctua8onsinoutputfromindividualunits.

Exis8ngboundariesaregenerallydefinedbythehistoricaldevelopmentofthegridandthedis8nctu8li8esandins8tu8onsthatdrovethatdevelopment.

Coopera8onbetweenbalancingareasorexpansionoftheseareassignificantlyenhancesreliabilityandreducesopera8ngcostandforecasterror.

20

Spa8aldifferencesinwindspeedsandsolarirradiancecanreducevariabilityanddampenthesteepnessofnetloadcurves.

ExpandingtheCaliforniaenergyelectricmarketintoamul8-stateregionwillhelpthestatemeetits50%renewableenergygoalby2030,accordingtotheCaliforniaISO.

Broader balancing areas and geographic diversity can reduce variability and need for reserves

Source: NREL wind plant data (Approximately 8 hours)

1.61.41.21.00.80.6

Outp

ut

Norm

aliz

ed to M

ean

30x1032520151050Seconds

1.61.41.21.00.80.6

1.61.41.21.00.80.6

15 Turbines Stdev = 1.21, Stdev/Mean = .184 200 Turbines Stdev = 14.89, Stdev/Mean = .126 215 Turbines Stdev = 15.63, Stdev/Mean = .125

Source: NREL Wind Plant Data

200 Turbines

15 Turbines

Approximately 8 hours

System Operations Expand Balancing Footprint

Source:Na8onalRenewableEnergyLaboratory

EnlargedBalancingAreas

Broaderbalancingareasincreasediversityandreduceoutput.Sampledatafromalterna8veaggrega8onsofwindplantsareshownbelow.

21

AncillaryServices

Ancillaryservicesaretoolsusedbysystemoperatorstomanageshort-termmismatchesbetweenelectricsupplyanddemand,andhavehistoricallybeenprovidedbytradi8onalgenerators..

AncillaryservicesmarketsarebeingredesignedincompliancewithcertainFERCorders.Thiswillneedtocon8nuetofullyincorporateenergystorage,fastdispatchabledemandresponseanddistributedgenera8on.

Advancesincompu8ngandcontrolsareallowingcleanflexibleresourcessuchasdemandresponseandstoragetoprovideancillaryservicesthatcaninclude:

²  Frequencyresponseisusedformanagementofthefrequencyonthegridfor0to30secondintervalsandrequiresveryfastresponse.

²  Regula)onwhichisanincreaseordecreaseingenera8onoveracertainnumberofminutesandwithresponse8mesfrom4secondsto5minutes.

²  Reservesusedforcommitmentstoincreasegenera8ontocorrectforshorttermchangesinelectricityusethatcouldaffectthestabilityofthepowersystem(intervalsvary).

22

AncillaryServices

23

Source:PennsylvaniaStateUniversity

AncillaryServices

Invertersareusedonbothlargegenera8onunitsandsmalldistributedsystems(micro-inverters),tosynchronizeelectricityproducedwiththegrid.

Integratedsmartinvertershaveenhancedgeneratorcapabili8esandarerela8velyinexpensive.

Ac8ngasa‘brain’,theycaneasevoltagemanagementproblemsandprovidefrequencycontrolthroughac8vepowerregula8on.

Theseadvancedsobwaresystemscansendandreceivemessagesandsharegranulardataquickly.

Smartinverterscanfacilitatestaggeringofvariableresourcestomeetgridneedsatspecificmoments.

TheyincreasethevalueofintermiGentgenera8on.Germany’ssmartinvertersallowfor40%moresolarPVcapacityonthesamelineatacostwellbelowthatofupgradingdistribu8on.

24

25

AncillaryServices

SolarPVInstalla8onNewton,MA

FlexibleResources

Storageisaflexibleenergyresourcewitharangeofconfigura8onsandusesthatmakeitthepoten8alkillerappforgridintegra8on.

Thedefiningcharacteris8csareafastresponse(dispatch)8meandarangeofdura8onlimits.Unitsizecanrangefromgrid-scaletocarbaGeries(R&Dstage).

Storageunitsofvarioussizescanbothshavepeaksthroughdispatchofenergyandabsorbpowerduring8mesofexcessvariablesupply.Itcansmoothfluctua8onsonasub-hourly8mescale.

Largescalestoragecanbridgesignificantimbalances,muchthewaypumpedhydroisused.

StorageiscanbeusedinISO/RTOenergyandcapacitymarkets,andincreasinglyforancillaryservices.

Storageremainsgenerallymorecostlythanotherflexibleresources,butthiswillchangewithtechnologyadvancesandbroaderuse.

Globalcapacityisexpectedtogrowfrom6GWin2017to22GWin2025(EnergyStorageAssocia8on).

26

FlexibleResources

27

FlexibleResources

Demandresponseisaflexiblegridtoolthatcancost-effec8velyhelpintegratevariableenergyresourcesbyflaGeningthenetloadcurveandsmoothingthesteepnessoframps.

Supplyanddemandmustremaininperpetualbalance,anddemandresponsecanmodifyboth–itcanreducedemandforelectricityandprovideasourceofsupply.

Fast-ac8ngautomateddispatchabledemandresponsecanbedeployedtohelpbalancegenera8onandloadinreal8me.

Loadsareaggregatedanddirectedtoquicklyfollowthefastrampsofvariablegenera8on,ideallyreducingtheneedforalterna8ve(fossil-fuelbased)rampingcapability.

Advancesinautoma8onandcommunica8ontechnologiesenabledemandresponsewithminimalcustomerawarenessorfacilityinterrup8on.

Demandresponsecanpar8cipateinmostISO/RTOenergymarkets,aswellascapacitymarketsatISO-NE,PJMandNYISO.Addi8onally,demandresponsewillbeatoolinreservesmarkets.

28

FlexibleResources150

The Power of Transformation: Wind, Sun and the Economics of Flexible Power Systems

In order for DSI’s potential to be realised, the following preconditions need to be met:

�� metering time of electricity consumption at high accuracy

�� price signals with high temporal (and spatial) accuracy for consumers

�� incentives for operating load in a system-friendly way

�� policies and regulation conducive to the establishment of load aggregators that can manage consumer loads

�� infrastructure for the remote control of loads.

In most countries, the above conditions are only met for large consumers, limiting participation to this segment. Today, DSI is commonly used as a way of responding to exceptional system conditions (usually short-term capacity shortages during contingencies or times of peak demand). However, with the recent emergence of low-cost, highly reliable and versatile IT infrastructure, DSI capabilities can now reach more market segments and alter consumption patterns in a more sophisticated way.

In line with the above distinction of DSM and DSR, demand integration programmes can be classified as follows (Figure 7.19) (MIT, 2011):

�� Dispatchable programmes, also known as load management or control programmes, which allow direct control of load responses by the grid operator or a third-party aggregator. An incentive is often offered to customers in return for participation.

�� Reactive programmes, which rely on customers’ voluntary responses to a variety of signals communicated to them. The most common signal used at present is price, although other types of information, such as environmental signals or neighbourhood-comparative data, may prove useful in the future. Reactive programmes can further be divided into wholesale programmes administered by system operators and retail programmes that present customers with retail prices carefully determined by specific time-varying pricing structures.

Figure 7.19��Ƚ Types of DSI programmes

Demand management(dispatchable programmes)

Demand response(reactive programmes)

Critical peak pricing

Time-of-use pricing

Peak time rebate

Real-time pricing

Capacity markets

Ancillary services markets

Demand-side bidding marketsWholesale programmes

Interruptible/curtailable services

Emergency response payment

Direct load controlLoad control programmes

Incentiveba

sed

Retail programmes

Priceba

sed

Demand-side integration(DSI)

Source: MIT, 2011.

Key point Ƚ Demand integration programmes can be classified as dispatchable and reactive programmes.

The cost-benefit profile of DSI may be affected by the contractual arrangements governing it. A good example of this is a recent study conducted by the electro-mobility company Better Place, in collaboration with the system operator, PJM.18 The impact of electrical vehicle charging on the system was assessed under three scenarios:

18. PJM Interconnection is a regional transmission organisation that co-ordinates the movement of wholesale electricity in all or parts of Delaware, Illinois, Indiana, Kentucky, Maryland, Michigan, New Jersey, North Carolina, Ohio, Pennsylvania, Tennessee, Virginia, West Virginia and the District of Columbia.

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Source:Interna8onalEnergyAgency

29

FlexibleResources

Microgridsareindependentenergysystemsthatconsistofvariousdistributedenergyresourcesthatcanbeusedtomanagethelargerelectricgrid.

Microgridscanofferacampusorcommunityindependencefromthegridandasourceofcleanenergy.

Microgridsofferthelocalgridbenefitssuchaslossreduc8on,conges8onreliefandvoltagecontrol.

Microgridsarenormallylocatedclosetoloadcentersandprovideapoten8alcontrollableloadsthatcansupportthelargergrid.

Theycanoperateeitherinparallelwiththegrid(wheretheyappearasasingleunittothenetworkoperator)orinislandmode.

Whenamainnetworkfacesdifficultyalocalcontrolsystemcanenableindependentopera8onofthemicrogrid.

30

FlexibleResources

31

Source:NYRSEDA

38

The Power of Transformation: Wind, Sun and the Economics of Flexible Power Systems

Uncertainty differs from the other VRE properties. It is not a characteristic of VRE per se, but is tied to the accuracy of meteorological forecasts. This immediately highlights the critical role of accurate forecasting techniques; the better the forecast, the lower the uncertainty.

Forecast errors are distributed randomly;8 an increase in sample size tends to decrease the error. Therefore, forecasts for larger areas are more accurate and relative uncertainty of VRE production is smaller.

The quality of forecasts has seen important improvements over recent years. For example, the mean absolute forecast error in Spain has been significantly reduced during the past five years (Figure 2.9), as a consequence of methodological improvements but also of increased observability of VRE. Short-term forecasts (i.e. looking ahead one to three hours) show only half the forecast error that was observed four years ago. Day-ahead forecast errors have been reduced by one-third. Hour-ahead forecasts are approximately three times as accurate as day-ahead forecasts. This has important implications for integration strategies. Moving operational decisions closer to real-time makes planning decisions much more accurate.

Solar PV power forecasts are less mature than wind power forecasts. Given clear skies, solar PV power output can be predicted with very high accuracy, because the output is determined by the position of the sun, which is easy to calculate. However, snow coverage and fog can lead to rare but high forecast errors. In Germany, fog impacts have only been included in forecasts for about two years (i.e. since 2011). However, these are often still included manually, based on fog maps produced by the German meteorological service. Automated inclusion of detailed fog forecasts is the subject of ongoing research.9

Every power system holds reserves available to provide electricity supply in the case of an unexpected event, such as failures or forecast errors. Traditionally forecast errors related to forecasts for electricity demand.

Figure 2.9��Ƚ Improvement in wind power forecasts in Spain, 2008-12

0%

5%

10%

15%

20%

25%

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47

Mean

absolute

error/averag

eprod

uctio

n

Forecast horizon (hours before real time)

2008

2009

2010

2011

2012

Source: based on data from Red Eléctrica de España.

Key point Ƚ Wind power forecasts have improved over recent years. Forecasts looking ahead only a few hours are more accurate than day-ahead forecasts.

Increasing VRE deployment tends to lead to increased reserve requirements, because the risk of forecast errors increases. However, the exact definition of reserves, the way they are calculated, how they are procured and what technologies are allowed to provide them, all have an influence on the overall significance of VRE’s effects on reserve requirements.

8. Forecast errors do not follow a normal distribution. They follow a non-parametric distribution with thick tales; this means that infrequent but very large errors are relevant for system planning and operation (Hodge et al., 2012).

9. E.g. “Improvement of grid integration from electricity generated by photovoltaic systems via the optimized forecast and real-time estimation of solar power input”, see www.energymeteo.com/en/projects/Solar.php.

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Forecasthorizon(hours)

Meanabsoluteerror

Source:IEA,RedEléctricadeEspaña.

Forecas)ng

32

Advancesinforecas8ngofgenera8oninputs(windspeed,solarirradiance)andoutput(power)reduceuncertaintyandtheneedtoprocurereservestoachievereliability.

ResearchandDevelopment

Apoten8alsuperconductorelectricitypipelinemayonedaycarrylargeamountsofrenewablepowerlongdistances,essen8allyservingasaninterstatehighwaysystemforelectricity.

24 Integrating Renewable Electricity on the Grid

Long distance transmission offers a partial solution to the variability challenge of renew-able energy. Balancing generation with load typically takes place within a local or regional balancing area with sufficient dispatchable conventional resources to meet load fluctua-tions. Aggregating wind power over many wind plants substantially increases reliability and decreases fluctuations, reducing the need for conventional reserves and lowering cost.47, 48, 49, 50

The complexity of balancing over large areas with many generation and load resources eventually limits the size of the balancing area. Even in this case, however, long distance transmission plays a role. Generation excesses and deficits across the country can be anticipated by forecasting and matched over long distances to balance the system. An excess of wind power in the upper central US might be balanced by transmission to a power deficit in the East. Under these conditions specific excesses and deficits are identified and balanced much like conventional generation is switched in or out to balance load at present. With adequate forecasting, such specific opportunities can be identified and arranged in advance and executed dynamically as the situation develops.43, 44 This distant generation balancing requires additional high-capacity long distance transmission that is operator controllable by power electronics, allowing excess generation in one area to be directed to specific targets of deficit far away, instead of getting sidetracked in the grid by local conditions

Figure 11. The proposed DC superconductor electricity pipeline for carrying large amounts of renewable power long distances. This network provides an interstate highway system for electricity. (Image courtesy of American Superconductor.)

Source:NREL

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Future: technical solutions for integrating more large-capacity RE

to be avoided. Taking reactive power control as an example [pei12]: with multiple wind plants having requirements to provide reactive power and control grid voltages, problems have emerged when the

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Figure 4-3 | Schematic diagram of the Jiuquan Wind Power Base, Gansu, China (SGCC)

voltage and reactive power controllers in nearby plants have been incompatible, resulting in poor voltage control and counterproductive reactive power fl ows. There have been numerous reports

Figure 4-4 | RE power plant cluster control system structure (SGCC)

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ResearchandDevelopment

AnAustralianwindpilotdeployeda250kWprojectontheVictoriacoastthatusesanoscilla8ngstructureinspiredbynature,specificallyunderseaplantsthatswaybackandforthbeneaththeoceanswell.

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02 MARKET AND INDUSTRY TRENDS

Wales, the Swedish tidal stream technology company Minesto secured USD 14.2 million (EUR 13 million) of EU funds to support development of its Deep Green device, which operates as an underwater kite.12 Minesto partnered with Schottel Hydro, a German turbine manufacturer that will supply turbine compo-nents for upcoming deployments of Deep Green devices.13

Also in the United Kingdom, Sustainable Marine Energy Ltd. (UK) installed its PLAT-O turbine platform, which the company hopes will drive down the cost of tidal energy. The platform was fitted with two Schottel instream turbines and installed off the Isle of Wight, where it met all expectations.14 Schottel notes that there is synergy in the combination of turbine and platform because both are designed to be lightweight, robust and simple.15

Nova Innovation (Scotland) and its partner ELSA (Belgium) secured additional funding from the Scottish government for a 500 kW tidal array in Shetland’s (Scotland) Bluemull Sound. The project uses Nova’s 100 kW M100 direct-drive turbine, and the first unit delivered power to the grid in early 2016.16

To the south, Sabella SAS (France) launched its full-scale, grid-connected 1 MW D10 tidal turbine off the coast of Brittany, in the Fromveur Strait, where it supplies electricity to the Ushant Island.17

OpenHydro (a subsidiary of DCNS, France) continued its work off the French coast, deploying the first of two new turbines at EDF’s (France) site at Paimpol-Bréhat, following a few years of testing.18 Across the Atlantic, OpenHydro also advanced a project at Canada’s Fundy Ocean Research Center for Energy (FORCE) in the Bay of Fundy, where the company was awarded USD 4.5 million (CAD 6.3 million) to support its deployment of two 2 MW tidal turbines with local partner Emera.19 The joint venture anticipated turbine deployment in 2016.20

Wave energy also saw progress during the year, with the deployment of several devices in pilot and demonstration projects in Europe, Australia, the United States and elsewhere. AW-Energy of Finland continued to refine its WaveRoller device in 2015, with plans to deploy 350 kW commercial units in a 5.6 MW array in Portugal in the near future.21 In neighbouring Sweden, the 1 MW Sotenäs Wave Power Plant by Seabased (Sweden) started generating power in early 2016. The Sotenäs plant couples linear

generators on the sea floor to surface buoys (point absorbers) and is said to be the world’s first array of multiple wave energy converters in operation.22

Off the coast of Tuscany in Italy, 40South Energy (UK) launched its new 50 kW H24 wave energy converter, a fully submerged machine that is optimised to convert wave and tidal energy in shallow waters.23

Also in 2015, Eco Wave Power (Israel) deployed its second-generation wave energy conversion device in the Jaffa Port of Israel.24 The company also advanced on the first 100 kW phase of a 5 MW EU-funded plant across the Mediterranean Sea in Gibraltar; the plant is expected to meet 15% of local electricity demand when it is completed.25

In Australia, BioPower Systems (Australia) deployed its 250 kW bioWAVE pilot demonstration unit off the coast of Port Fairy, Victoria. The device is a 26-metre-tall oscillating structure that was inspired by undersea plants; it is designed to sway back and forth beneath the ocean swell, capturing energy.26 Another Australian firm, Carnegie Wave Energy Ltd, moved towards deployment of its 1 MW CETO 6 device in early 2016, a scaled-up version of the CETO 5 deployed in 2014.27

Across the South Pacific, the US state of Hawaii, home to the US Navy’s Wave Energy Test Site (WETS), saw some progress during the year. Northwest Energy Innovations was chosen by the US Department of Energy to demonstrate its half-scale Azura wave energy device for one year of grid-connected testing at WETS, where the company implemented various improvements that were based on previous (2012) trials.28 Other wave energy technology developers are scheduled to test their devices at WETS in coming years.29

The global wave energy industry received significant support from the Scottish Government in 2015. The government-funded Wave Energy Scotland, which was established in late 2014 to support development of wave energy technology, awarded over USD 13 million (over GBP 9 million) in 2015 to multiple developers in several countries for the advancement of innovative wave energy technologies at various stages of development.30

Among the most notable success stories in wave energy conversion has been the 296 kW Mutriku plant in the Basque

Underdevelopmentarerenewableenergypowerbasescanbeorganizedintoclusterswithacentralcontrolsystemtocoordinateac8veandreac8vepowercontrol.Belowisarepresenta8onofwindturbinegeneratorsconnectedtospecificsubsta8ons.

Source:IEC,Schema8cofJiuquanWindPowerBase,Gansu,China 34

Takeaway

ª  Facilitateeconomicuseofvariablegenera8onandflexibleresources

ª  BaGeries,inverters,automatedDR,dashboardcontrol,etc.

ª  Expansionandcoordina8on,betweenbalancingareas

ª  Op8mizethroughdiversityandscale

ª  Stateandfederalsupport

Improvedgridmanagement 1ª  Op8miza8onofscheduling,

dispatchandcontrol

ª  Toolsforfrequency,voltageandpowerbalance

ª  Demandresponse,storage,etc.

ª  Genera8oninputs(wind,solar)ª  Genera8onoutput

ª  Captureandmone8zevaluestreams

ª  Op8mizedecisionmaking

Flexibleresources 1

BeTerforecas)ng 1

Technologyadvances

Transmissionexpand/interconnect

1

Regulatory 1

1

Businessmodels 1

BeTerstructuredmarkets 1

35

Thankyou!

RynHamiltonRynHamiltonConsul8ng

[email protected]

45FayeGeStreet,Cambridge,MA02459617.461.7200

MonsterundergroundoiltankOurhousebeforewemoved,Newton,MA

Documents

Renewable Centric Grid of the Future Ryn Hamilton July 27 2016