PV Hosting Capacity on Distribution Feeders PES Template pdf · Jeff Smith, Matt Rylander EPRI IEEE...

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Jeff Smith, Matt Rylander EPRI IEEE PES 2014, Washington, D.C. 7/29/2014 PV Hosting Capacity on Distribution Feeders

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  • Jeff Smith, Matt RylanderEPRI

    IEEE PES 2014, Washington, D.C.7/29/2014

    PV Hosting Capacity on Distribution Feeders

  • 2

    Key Factors that Determine How Much PV a Feeder Can Accommodate (Hosting Capacity)

    Large Scale PV Near Sub

    Large Scale PV @ End Line

    Size of PV Location of PV Feeder characteristics Electrical proximity to

    other PV Unique solar resource

    characteristics in the area

    PV control 105%100%

    95%

    Distance from Substation

    Vol

    tage

    VoltageRisefrom PV

    Headroom

  • 3

    Key Requirements to Determine Hosting Capacity Distribution characteristics

    Voltage response Short-circuit response Locational information Accurate feeder Models Proxy feeders arent sufficient

    PV characteristics Location Size What about time?

    Feeder Voltage Heat

    Map

    *all simulations performed with OpenDSS

  • 4

    Feeder Hosting Capacity: A Brief Primer

    Baseline No PV

    PV Penetration 1

    PV Penetration 2

    PV Penetration 3

    Beyond

    Increase Penetration Levels Until Violations

    Occur voltage protection power quality thermal

    PV Systems

    Process is repeated

    100s of times to capture

    many possible

    scenarios

  • 5

    Hosting CapacityOvervoltage Results Shown for Feeder J1

    2500 cases shownEach point = highest primary voltage

    ANSI voltage limit

    Max

    imum

    Fee

    der V

    olta

    ges

    (pu)

    Increasing penetration (kW)

    Minimum Hosting CapacityMaximum Hosting Capacity

    Total PV: 540 kW

    Total PV: 1173 kW Voltage violation

    No observable violations regardless of size/location

    Possible violations based upon size/location

    Observable violations occur regardless of size/location

  • 6

    Industry-Wide Assessment

    Collaborative Effort

    >30 feeders to date throughout US

    Methodology Consistent Transparent

    Open-source tools Advanced application of

    traditional planning techniques

    Details on analysis method: Stochastic Analysis to Determine Feeder Hosting Capacity for Distributed Solar PV. EPRI, Palo Alto, CA: 2012. 1026640.

  • 7

    Sample Results from Single feederSmall-Scale (Residential/Commercial)

    Characteristic ValuekV 12PkLd 6.2MinLd 0.62TotalRegs 1Setpoint 1.0Band 4.0TotalCaps 1Totalkvar 1200EndofLineZ 15.88AvgZ 5.86MinZ 1.11MaxXR 7.87AvgXR 2.52MinXR 0.70TotalMiles 71.87TotalCustCount 1140.00EndofLineLength(mi) 11.07AvgR 2.16EndofLineMVA 9.10MinHeadrom 0.03LoadCenterR 5.90

    Feeder Characteristics Hosting Capacity Results

  • 8

    Summary of Results from 18 Feeders

    Research results found here:Distributed Photovoltaic Feeder Analysis: Preliminary

    Findings from Hosting Capacity Analysis of 18 Distribution Feeders. EPRI, Palo Alto, CA: 2013. 3002001245.

    All penetrations in this region are acceptable, regardless of location

    Some penetrations in this region are

    acceptable, site specific

    No penetrations in this region are acceptable, regardless of location

    0 2 4 6 8 10

    J1

    R1

    R2

    R3

    R4

    T1

    T2

    G1

    G2

    G3

    P1

    P2

    P3

    P4

    P5

    D1

    D2

    D3

    MWofConsumerPV

    Feed

    er

    0 2 4 6 8

    P3

    P5

    PVPenetration(MW)

    Feed

    er Location matters

    Noissues Mayrequireupgrades Requiresupgrades

    2 similar feeders

    0 2 4 6 8

    P3

    P5

    PVPenetration(MW)

    Feed

    er Location matters

    Noissues Mayrequireupgrades Requiresupgrades

    2 similar feeders

    *voltage-based hosting capacity shown

  • 9

    Summary of Results from 18 Feeders

    Research results found here:Distributed Photovoltaic Feeder Analysis: Preliminary

    Findings from Hosting Capacity Analysis of 18 Distribution Feeders. EPRI, Palo Alto, CA: 2013. 3002001245.

    All penetrations in this region are acceptable, regardless of location

    Some penetrations in this region are

    acceptable, site specific

    No penetrations in this region are acceptable, regardless of location

    0 2 4 6 8 10

    J1

    R1

    R2

    R3

    R4

    T1

    T2

    G1

    G2

    G3

    P1

    P2

    P3

    P4

    P5

    D1

    D2

    D3

    MWofConsumerPV

    Feed

    er

    0 2 4 6 8 10

    J1

    R1

    R2

    R3

    R4

    T1

    T2

    G1

    G2

    G3

    P1

    P2

    P3

    P4

    P5

    D1

    D2

    D3

    MWofLargePV

    Feed

    er

    Small-Scale Distributed Large-Scale Distributed

    *voltage-based hosting capacity shown

  • 10

    Detailed Hosting Capacity Analysis Can load be used to predict hosting capacity?

    0

    0.5

    1

    1.5

    2

    2.5

    3

    3.5

    0 2 4 6 8 10 12 14 16 18

    Minim

    umHostin

    gCapacity(M

    W)

    PeakLoad(MW)

    Not without knowledge of other feeder characteristics

    No correlation between hosting capacity and peak load

  • 11

    0

    1

    2

    3

    4

    5

    6

    J1 R1 R2 R3 R4 T1 T2 G1 G2 G3 P1 P2 P3 P4 P5 D1 D2 D3

    MW

    Feeder

    MinimumHostingCapacity100%ofDaytimeMinimumLoad

    How Effective are Current Screening Practices? Keeping in mind, screens should be conservative by nature

    0

    0.5

    1

    1.5

    2

    2.5

    3

    3.5

    J1 R1 R2 R3 R4 T1 T2 G1 G2 G3 P1 P2 P3 P4 P5 D1 D2 D3

    MW

    Feeder

    MinimumHostingCapacity15%ofMaximumLoad

    15% peak and 100% minimum load overestimates hosting capacity on many feeders

    Feeders at risk for PV to pass through screens without issues being flagged

  • 12

    Correlation to Feeder CharacteristicsSmall-Scale PV, Primary Voltage Deviation Hosting Capacity

    Strong correlation Number of line

    regulators Total circuit length End of line length Load Center

    Location PV Center

    Location

  • 13

    Next Step Applications

    Developing better screening techniques for solar PV

    Developing streamlined methods for determining hosting capacity Application across entire

    service territory (100s to 1000s of feeders)

    Commercial software Identifying technical solutions for

    accommodating higher penetration levels Streamlined

    methods

  • 14

    Conclusions

    Consistent and repeatable methodology allows greater understanding of impacts due to Location of PV Feeder characteristics

    Many of issues start arising at secondary level Models typically dont go there!

    Trends in hosting capacity dependency are found Regulation, line impedance, and load location Load level not so much

    Other factors play in as well How close to thresholds in basecase (headroom)

  • 15

    Questions

    Contact:

    Jeff SmithManager, Power System [email protected]