2013 plan data and assumptions · web viewin the 2013 plan, teppc took steps toward this objective...

Document name 2013 Interconnection-wide PlanVariable Generation Integration

Category ( ) Regional reliability standard( ) Regional criteria( ) Policy( ) Guideline( ) Report or other( ) Charter

Document date September 19, 2013

Adopted/approved by The WECC Board of Directors

Date adopted/approved September 19, 2013

Custodian (entity responsible for maintenance and upkeep)

TEPPC

Stored/filed Physical location:Web URL:

Previous name/number (if any)

Status ( ) in effect( ) usable, minor formatting/editing required( ) modification needed( ) superseded by _____________________( ) other _____________________________( ) obsolete/archived)

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W E S T E R N E L E C T R I C I T Y C O O R D I N A T I N G C O U N C I L • W W W . W E C C . B I Z1 5 5 N O R T H 4 0 0 W E S T • S U I T E 2 0 0 • S A L T L A K E C I T Y • U T A H • 8 4 1 0 3 - 1 1 1 4 • P H 8 0 1 . 5 8 2 . 0 3 5 3

September 19, 2013 3

2013 Interconnection-Wide PlanAnalysis of Flexible Reserves for the

Integration of Variable Generation

By

WECC Staff

Western Electricity Coordinating Council

September 19, 2013


Introduction The integration of variable generation (VG) resources into the Western Interconnection has become an increasingly important topic for transmission system planning and operations. In the 2011 WECC Regional Transmission Expansion Plan, all of the cases analyzed had high levels of VG, which caused significant and unprecedented levels of conventional generation ramping and cycling in the PCM. In response, TEPPC recommended that future transmission planning studies include a comprehensive review of VG integration issues related to transmission expansion planning. Following the 2011 Plan, TEPPC committed to identifying and evaluating the challenges of integrating the VG assumed in the Plan and identifying possible options to address these challenges. In the 2013 Plan, TEPPC took steps toward this objective and laid important groundwork for future VG integration analyses within the context of transmission expansion planning.

Four challenges/options to the integration of VG emerged from the 2011 Plan. This report discusses operating reserves for VG (hereinafter “flexibility reserves”). Cycling costs are included in the 2013 Plan via the cycling cost calculator developed by the National Renewable Energy Laboratory (NREL) and described in detail in the Data and Assumptions report. Balancing Authority consolidation and configuration, and intra-hour scheduling are outside of TEPPC’s scope and were addressed in the WECC Variable Generation Subcommittee’s (VGS) “BA Cooperation Study”.1

The analysis described below represents an initial attempt at characterizing VG integration issues by way of flexibility reserves. The analysis was conducted from a transmission planning standpoint, and should be interpreted in that light. The issues surrounding the integration of VG span the realms of operations, markets and planning. The TEPPC analysis of flexibility reserve requirements is a piece of a much larger, evolving discussion of VG integration.

BackgroundBalancing loads and resources takes place as a basic function of grid operations; variability on the grid must be balanced to ensure reliability. There are two primary sources of variability on the grid: consumer loads and VG resources, (i.e., wind and solar Photovoltaic (PV)). Load variability has long played a part in reliable planning and operation of the electric grid. To a great extent, the grid in the Western Interconnection has been built to address load variability. There is vast experience in the Western Interconnection with analyzing, forecasting and accounting for load variability, which is

1 http://www.wecc.biz/committees/StandingCommittees/JGC/VGS/Shared%20Documents/BA%20Cooperation%20Study/Final%.

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http://www.wecc.biz/committees/StandingCommittees/JGC/VGS/Shared%20Documents/BA%20Cooperation%20Study/Final%25


essential to planners and operators as load patterns continue to change – perhaps dramatically in the future.

Variability associated with VG resources is a relatively new concern that has taken shape in the last decade as a large amount of VG has come on line in a short period of time. As with load, forecasting is valuable tool to address VG variability; however, VG forecasting is in a developmental phase and the data underlying VG forecasts do not have the historical depth that load data does. Ultimately, advances in forecasting notwithstanding, variability remains and will persist into the future because we cannot forecast perfectly.

Conditions with high VG penetration can create stress on system operations as the variability is balanced. While balancing load variability and balancing VG variability are fundamentally the same – load must be equal to generation – the characteristics of VG and the political and regulatory environment surrounding it pose unique challenges in balancing the variability. Ultimately, VG cannot be controlled in the way that traditional resources can be controlled. This is not to say that VG cannot be dispatched under certain circumstances, such as CSP with storage, and VG can be curtailed, but, VG resources cannot be dispatched up and down to balance out the continuous movement of load the way that traditional resources, such as gas-fired and hydro resources, can. In addition, the political and regulatory environment may change the way that balancing is approached. For example, in cases of a generation surplus, curtailment of resources is among the possible solutions; however, tax incentives like production tax credits, make curtailing some VG resources unpalatable. The result may be that traditional resources must be backed down to balance the surplus, a solution that comes with its own costs and potential reliability ramifications.

All of this creates operational uncertainty around VG resources. Uncertainty in grid operations invokes reliability concerns. Added to this, from the planning perspective, is the uncertainty associated with future levels of VG. Current state renewable portfolio standards provide some indication of where the future of VG might be going, and these policies form the basis of the 10-year analysis. But, these kinds of drivers are a product of a fluid political, regulatory, and economic environment, which can change substantially over the long-term and are impossible to predict. Planning uncertainty surrounding the future of VG compounds the operational uncertainty and makes planning a future grid more complex.

Reducing or mitigating the uncertainty associated with VG is necessary. While great strides have been made in reducing the uncertainty of VG (e.g., forecasting tools), where uncertainty cannot be reduced, measures must be taken to ensure that enough capacity is available to keep the system operating reliably. One method is to hold enough capacity in reserve to “cover” the variability. TEPPC refers to this held capacity as “flexibility reserves.” TEPPC’s analysis of “flexibility reserves” is the subject of this

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document. From a planning perspective, levels of flexibility reserves can be used as an indicator of the amount of variability on the grid in a given study scenario.

It is important to note that there are other options being discussed, in development, and available to address variability. Options like demand response, BA consolidation, and market mechanisms are just three examples. TEPPC does not contend that any option, including the holding of flexibility reserves, is more viable, preferable, or appropriate than any other, nor does it intend to suggest or recommend how variability should be addressed in the future.

Methodology and Input AssumptionsThe 10-Year Plan Follow-up Group (2011 Plan) recommended that the 2013 Plan include a comparison of various methods of managing the integration of variable resources. WECC uses an analysis of flexibility reserves to evaluate two methods identified by the Group: 1) increasing the size of the balancing footprint; and 2) scheduling the variability of resources to the receiving area.

To conduct the analysis of flexibility reserves, WECC first needed to improve the quantification of flexibility reserve requirements for VG. WECC worked with NREL to develop a flexibility reserve calculator that was used to determine the amount of flexibility reserves needed to balance the inherent variability of wind and solar generation. Flexibility reserves calculated by the tool are included in the 2013 studies.

WECC then worked with NREL to develop a comparative analysis of flexibility reserve requirements across three future resource assumptions: 1) 2020 Base Case assumptions; 2) 3,000 MW wind added in Wyoming; and 3) 3,000 MW solar added in Arizona. For each of the resource assumptions, flexibility reserves were compared across four scenarios: 1) reserves held in the local BA/load area; 2) held in the local subregion of the Western Interconnection; 3) held in the Southern California Edison (SCE) BA/load area; and 4) held in the CA_South subregion. Table 1 summarizes the 10 scenarios analyzed.

Table 1: Summary of Scenarios AnalyzedBA/Load Area Level Subregional Level

Base Case

2020 Base Case (2020 PC1)Flex Reserves for all

BA/load areasFlex Reserves for all portion of the Western

Interconnection

Wind WY

3,000 MW wind in WY (2022 PC20)Flex reserves for all wind

located in PACE_WYFlex Reserves for all wind located in Basin

portion of the Western Interconnection

Wind CA

3,000 MW wind dynamically transferred from WY to CAFlex reserves for all wind

located in SCEFlex Reserves for all wind in CA_South portion

of the Western Interconnection3,000 MW solar in AZ (2022 PC21)

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Solar AZ

Flex reserves for all solar located in APS

Flex Reserves for all solar located in AZNMNV portion of the Western Interconnection

Solar CA

3,000 MW solar dynamically transferred from AZ to CAFlex reserves for all solar in

SCEFlex Reserves for all solar in CA_South portion

of the Western Interconnection

The scenarios are based on the Western Wind and Solar Integration Study-2 “TEPPC” scenario (TEPPC 2020 PC1) with synchronized 2006 data for load, wind and solar PV.2 The 3,000 MW of additional wind in Wyoming were randomly selected from the High Wind scenario. Similarly, the 3,000 MW of solar PV in Arizona were selected from the High Solar scenario. For the California scenarios, it was assumed that the added wind and solar were dynamically transferred into California, rather than selected from resources in California.

The table in Figure 1shows the TEPPC BA/load areas included in each of the regions analyzed. The map shows the TEPPC regions as well as the three BAs used in the flexibility reserves work.

Figure 1: TEPPC BA/load areas included in regional analysis

The regulation reserves were calculated using the following components:

Load: 1 percent of load

Wind: Coverage of 10-minutes un-forecasted events with 95 percent confidence

PV: Coverage of 10-minutes un-forecasted events with 95 percent confidence

2 The Western Wind and Solar Integration Study website contains information on the study and links to study documents; it is available at http://www.nrel.gov/electricity/transmission/western_wind.html.

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CA_NORTH

CA_SOUTHAZNMNV

RMPPBasin

Northwest

Alberta

British Columbia

Basin AZNMNV CA_SouthFar East APS IIDMagic Valley NEVP LDWPPACE ID PNM SCEPACE UT SRP SDGEPACE WY TEPSPP WALCTreasure Valley

http://www.nrel.gov/electricity/transmission/western_wind.html


Assuming independence between the three components, the total reserves were added geometrically, so reserves equal:

ඥ(1% 𝑙𝑜𝑎𝑑)2 + (𝑊𝑖𝑛𝑑 𝑟𝑞𝑡)2 + (𝑃𝑉 𝑟𝑞𝑡)2

The load component was reported so the incremental effect of wind and PV could be calculated.

Key Observations Flexibility reserve requirements were smaller when integrating variable resources

at the regional level versus the BA/load area level; however, there are instances where the reduction is not significant.

Scheduling the variability of added resources in the SCE load area and CA South region reduced the incremental flexibility reserve requirement; however, the reductions varied in magnitude and significance. Scheduling the variability of Wyoming wind into California resulted in significant reductions, while only nominal reductions resulted from moving the Arizona solar.

Load is a determinative factor in comparing the impacts of different methods of managing variability.

Small vs. LargeIn the follow-up discussion to the 2011 Plan, concern was raised that it may be more difficult and/or more expensive to integrate large amounts of variable resources in the relatively small BAs in the Western Interconnection, as opposed to larger areas – in the case of this study, the TEPPC regions. The TEPPC analysis of flexibility reserve requirements supports the widely-accepted concept that integrating VG over a larger area requires fewer flexibility reserves. However, the results should not be taken to support an overarching conclusion that in all cases there is a significant benefit to balancing resources in a region, as opposed to a BA/load area. In this analysis, the level of benefits depends largely on the differences between the BA/Load area and the region, in other words, if the two cover virtually the same area and load, the benefit will likely be much smaller than if the BA/Load area is vastly different from the region.

Another factor that affects the benefits of integrating over larger areas is the diversity of the variable resources. As the diversity of resources within a footprint increases, the aggregated variability within that footprint decreases. This analysis did not evaluate the effect of changes in the diversity of variable resources, an improvement that can be made in the next study cycle as part of a more robust integration analysis. This analysis may identify changes to flexibility reserves that implicate this relationship, however, more analysis is necessary to determine the extent to which the increased diversity affects the results in the specific cases presented here.

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Figure 2 shows the annual average flexibility reserve requirements in 2020 for each of the scenarios studied. To avoid a skewed average in the case of solar, the average was calculated only for the times during which there was solar generation (i.e., daylight hours). The whiskers in the figure represent the annual maximum and minimum flexibility reserve requirements. The flexibility reserve requirements are smaller in each region than in its corresponding BA/load area.

Figure 2: Average Annual Flexibility Reserve Requirements

PA

CE

_WY

Bas

in

SC

E

CA

_So

AP

S

AZN

MN

V

SC

E

CA

_So

Wind Solar

0

10

20

30

40

50

60

70

80

90

Base Case + 3,000 MW

Rese

rve

Requ

irem

ents

(MW

)

A comparison of the increase from the 2020 Base Case to the +3,000 MW case (Figure 3) shows that the number of incremental reserves is also greater in the BA/load area than in the region, except in the case of PACE_WY and Basin. In that case, there is actually a larger percent increase in flexibility reserve requirements in the Basin region than in PACE_WY. This seems counterintuitive given the assumption that spreading variability across a larger footprint decreases the overall variability and reduces the flexibility reserve requirement. A possible explanation is that because the Basin footprint is relatively diverse, and thus has a relatively small flexibility reserve requirement to start with, the addition of the 3,000 MW of wind makes a larger impact than in the smaller and more variable PACE_WY footprint. It is important to recognize that the overall number of flexibility reserves in the Basin region is smaller than in PACE_WY.

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Figure 3: MW and Percent Change in Flex Reserve Requirements from Base Case to +3,000 MW Case

PACE_WY Basin SCE CA_So APS AZNMNV SCE CA_SoWind Solar

0

10

20

30

40

50

60

241% 262% 43% 31% 144% 52% 43% 36%

MW

The impact of the incremental flexibility reserves can be further understood by looking at the additional flexibility reserves as a percentage of load, as seen in Figure 4. The impact of the additional flexibility reserves is smaller in the regions. This is due in part to the larger loads in the regions. In addition, the variability of resources tends to be less severe as resource diversity works to smooth the variability. For example, the difference between the PACE_WY and Basin base case reserve numbers indicates that even before the variability is added, Basin requires fewer reserves. When the wind is added, the impact on Basin from the additional reserves is lower in terms of how it compares to load than in PACE_WY. This indicates that Basin is better able to absorb the variability of the new resources than PACE_WY. While the same observation holds true in the wind in California and solar cases, the relative impact in the California cases is much smaller. In some circumstances, while the larger balancing footprint does reduce the flexibility reserve requirement, the magnitude of the reduction as a portion of load is negligible.

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Figure 4: Average Reserve Requirements as a Percent of Load

PA

CE

_WY

Bas

in

SC

E

CA

_So

AP

S

AZN

MN

V

SC

E

CA

_So

Wind Solar

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

Base Case + 3,000 MWRe

serv

e Re

quire

men

t as

% o

f Loa

d

The discussion of footprint size is particularly timely as work is currently underway to develop a new TEPPC topology for the next study cycle. The TEPPC topology will be changed from eight regions to approximately 24 BA pools. The topology change will also result in changes to the flexibility reserve requirement assumptions in the next planning cycle.

Shifting the BurdenScheduling the variability of variable resources into the receiving BA is the second method evaluated in this analysis. One way that this may be accomplished is through dynamic transfers from one BA/load area or region to another. This analysis assumed dynamic transfers as the generic method of “moving” the added resources from one area to another; it did not include any analysis of the costs, benefits, limitations or feasibility of dynamic transfers.

Figure 4 shows the extreme difference between balancing 3,000 MW of wind in the PacifiCorp East - Wyoming (PACE_WY) BA Area versus the SCE load area. Not only are fewer flexibility reserves needed in the SCE (Figure 3), but in the SCE the ratio of incremental flexibility reserves to load is much smaller. This is more so the case when the wind is scheduled into the CA South region. However, scheduling the variability into the receiving region does not seem to have significant impact in all cases. For example, the ratio of flexibility reserve to load for the +3,000 MW Solar case is 1.23 percent in the AZNMNV region and 1.25 percent in the CA South region. The benefits of transferring the burden of holding flexibility reserves appears to have less impact when scheduling

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the variability of the solar to California. Other factors, such as cost of flexibility reserves, have not been considered in this analysis. It appears from this limited analysis that the benefits of shifting the burden of holding the flexibility reserves to the receiving BA/load area or region depends on the specific areas involved and on additional factors, including load.

Load MattersWhether the discussion is about small versus large balancing footprints or about shifting the responsibility for holding flexibility reserves, load is a key consideration. For example, the benefits of balancing 3,000 MW of solar in the CA South region versus the SCE load area are not significant. The average load in the SCE is 13,082 MW, while in CA South the average load is 19,606 MW. Compare this to PACE WY, which has an average load of 1,563 MW, to the Basin region which has an average load of 5,534 MW. In the Wyoming case, the regional load is over three times as large as that of the BA/load area. In the California case, the regional load is only about fifty percent larger. Table 2 shows the load values for the BA/load areas and regions in this analysis.

Table 2: Annual Load for Regions and BA/Load AreasTotal

(MWh)Average

(MW)Minimum

(MW)Maximum

(MW)

Reg

ion Basin 583,342,521 5,534 4,089 8,187

AZNMNV 1,634,879,235 15,510 9,998 29,554

CA_South 2,066,614,272 19,606 13,052 36,030

BA

/Loa

d A

rea

PACE_WY 164,783,869 1,563 1,144 1,868

APS 414,216,339 3,930 1,916 8,789

SCE 1,378,901,731 13,082 8,315 24,177

Figure 5 gives another example of the impact of load on flexibility reserves. Figure 5 compares the fluctuation in flexibility reserve requirements for solar in Arizona Public Service Company (APS) and wind in PACE WY. APS average load is over three times that of PACE WY. The magnitude of the APS daily average more closely follows the 2020 Base Case daily average, whereas the magnitude of the PACE WY daily average is much more extreme as the PACE WY load is less able to absorb the variability.

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Figure 5: Comparison of Flexibility Reserve Requirements Daily Average and Max (MW)

Load also affects the benefits of scheduling variability into the load area. From Figure 5, there appear to be significant benefits from scheduling the variability of Wyoming wind into California; however, the benefits of scheduling the solar variability from Arizona into California are not as significant and may be overcome by costs to carry out this method of managing VG integration.

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