ALBANY | BARCELONA | BANGALOREAWS Truepower, LLC | 463 New Karner Road | Albany, New York 12205 | +1-518-213-0044 | awstruepower.com

Poster Title

Researchers’/Presenters’ NamesInstitution/Organization/Company

1 M. Brower, “Development of eastern regional wind resource and wind plant output datasets,” AWS Truewind, LLC, Albany, NY, Tech. Rep. SR-550-46764. Dec. 2009. Available: http://www.nrel. gov/wind/integrationdatasets/pdfs/eastern/2010/aws_truewind_final_ report.pdf.

2 www.NYISO.com

• Assess how LBMP price points at end point buses on a single transmission line can differ inhigh congestion areas

• Assess how the congestion costs component of the LBMP can be used to increase projectrevenue

• Evaluate potential points of interconnection for a given hypothetical wind facility tomaximize potential revenue

• Evaluate potential project areas for a specified point of interconnection

Grid congestion and pricing can either be seen as barriers or opportunities to windintegration. By utilizing current system ratings and historical hourly LBMP pricing,developers can find the best market revenue intensive point of interconnection for theirproposed wind projects.

Hourly production scenarios for hypothetical 300 MW offshore wind facilities in the NewYork Bight area were evaluated, along with NYISO historical hourly LBMP pricing. A BaseCase thermal screening was completed on each potential point of interconnection to verifythe grids ability to accommodate the 300 MW project.

Analysis shows that a significant revenue increase can be realized at substations byunderstanding where the congestion cost contribution to the LBMP is most substantial. Fordevelopers with fixed sites, the increase in congestion cost will require understanding of thepotential offset cost of more transmission. For developers working to identify potentialsites, revenue benefits of greater production must be weighed with cost offsets ofincreased transmission to understand the optimal location for their project.

Full understanding of the value of wind energy based on hourly price points can helpdevelopers understand their true revenue potential and negotiate fair price points in PowerPurchasing Agreements.

Abstract Methods

Grid Congestion and LBMP Pricing: Barrier or Opportunity?Whitney J Wilson – Senior Engineer, AWS Truepower, LLC

Data and Methods

Objectives

MethodsResults

ReferencesConclusions• Defined Project Site analysis: Selection of the point of interconnection basedon the LBMP and congestion contribution equated to approximately $8-10Million in increased annual revenue. This analysis showed the importance ofunderstanding the potential price point implications for substations near thesite.

•Defined Point of Interconnection analysis: Selection of the project locationbased on LBMP pricing and transmission cost trade-off resulted in anapproximately $6 Million increase in annual revenue. This analysis showed theimportance of understanding trade-offs in wind resource and installedtransmission costs and how they can be utilized to increase revenue.

Figure 1: Potential Projects and Transmission System in NY Bight Region

Source: AWS Truepower, LLC

Production Data:• A mesoscale numerical weather prediction model was run at 2-km resolution to

simulate 10-minute wind speeds for 2004-2006 over the eastern United Statesfor the Eastern Wind Integration and Transmission Study (EWITS)1.

• EWITS created multiple 20-MW New York Bight “sites”.• The EWITS 20-MW “sites” were aggregated into larger sites with plant capacities

that were appropriate for local interconnection points (100-500 MW). Resultingsites are at least 5 km from shore, have a maximum water depth of 30 m, and areoutside of the exclusion areas defined for the study. Four of the aggregated siteswere chosen for analysis (9, 10, 16, and 20).

• Hourly time-series production data was created for each of the aggregate sites byusing the AWS Truepower windTrends dataset and Virtual Met Mast – Energy(VMM-E) software. An updated composite offshore power curve was used; thiscurve was created in August 2011 and is comprised of the most up-to-dateturbine technology.

• Losses were applied based on typical offshore losses for New England and NewYork areas. Wake losses were variable with the wind direction and applied as areduction in wind speed. Availability losses are variable with the wind speed torealize the availability correlation with high wind speed events. The electricalloss was applied as a bulk loss after all other losses were completed.

Locational Based Marginal Pricing (LBMP) Data:• LBMP data was acquired from the publicly available NYISO Market and

Operations data2.• 2010 historical Time-weighted/Integrated RT LBMP and Congestion Cost data was

compiled for select buses.• Prices during the daylight savings time transition were assumed to be the

average of the preceding and following hours.

Grid Data:• Transmission levels, location and size of plants, and potential point of

interconnection (POI) substations were determined using the Ventyx EnergyVelocity Suite (August 2011).

• The congestion zone utilized was chosen based on the Limiting Constraints datapublicly available from NYISO.

• The Base Case thermal screening (N-0 contingency) was completed based on theNERC 2010 heavy summer case. Specifics of this screening will not be supplied inadherence with Critical Energy Infrastructure Information (CEII) requirements.

Base Case Thermal Screening:• The power flows were solved using Commonwealth Associate’s Transmission

2000® software.• The hypothetical facility generation was ramped up until either a system violation

occurred, a new system violation occurred, or an existing system violationexceeded 110% of its initial rating.

• Both thermal overload violations and voltage limit violations were assessed.

For areas with merchant market participation, the LBMP will help establish the revenue generatedby the project. These projects can directly benefit from selecting a point of interconnection with thegrid that has high negative marginal congestion costs.

For areas that require Power Purchasing Agreements (PPA), the use of the estimated revenue basedon LBMP and marginal congestion costs can help inform the developer’s PPA negotiation process,thus, helping developers get a fair price point.

Developers must understand the cost trade-offs and risks associated with interconnecting to a moredistant substation. The revenue generated must outweigh the additional cost of transmission andthe additional transmission losses. Another key risk is understanding the potential for reduction incongestion. Transmission improvements and system compensation efforts could reduce themarginal congestion cost contribution to LBMP pricing.

Table 1: Analysis of Revenue, Congestion Contribution, and Submarine Transmission Costs for Each Substation

Whitney J Wilson, Senior Engineer, AWS Truepower, LLC wwilson@awstruepower.com

Table 2: Comparison of Gowanus to Goethals

© Copyright 2011

Base Case Thermal Screening• A base case power flow analysis of the system was preformed, which showed that the

Goethals to Gowanus transmission line had a thermal overload in excess of 100% nominalrating in the 2010 base case. This coincides with the NYISO Limiting Constraint report, whichlists the line as the limiting system constraint due to base case overload multiple times in2010.

• The Goethals and Gowanus 345 kV substations were assessed to determine the availablecapacity for system injection. Both substations will likely allow 150 MW without majorupgrades. Gowanus will likely allow 300 MW without major upgrades. 300 MW of injectionshould be possible at Goethals, but upgrades are likely. For the hypothetical case, and tomaintain a more simplistic comparison, the assumption is made that 300 MW will be allowedat both substations without major upgrades.

• Addition of wind generation into the Gowanus substation showed a reduction in the base caseoverload, primarily due to the added reactive power support of the generation facility.

Calculations:• Revenue was calculated using hourly historical LBMP prices for the studied substations from NYISO

data. The production in MW for each hour was multiplied by the hourly $/MW rate supplied in theLBMP pricing. Annual market revenue was calculated as the summation of the hour price points.

• Congestion impact was determine by using the NYISO LBMP price equation to understand the portionof the revenue that was associated with congestion costs.

LBMP = Marginal Cost of Energy + Marginal Cost of Losses – Marginal Cost of Congestion

• Transmission line costs were calculated based on an assumed cost of US$1 Million per km of 345 kVsubmarine transmission line installed.

Defined Project Site – Which Point of Interconnection (POI)?• A hypothetical defined project site at Site 20 in the map above was chosen to complete an

analysis of which substation should be chosen for interconnection with the NYISO grid.• Goethals and Gowanus are approximately 10 km apart. Based on the base case thermal

screening and the assumptions made for this comparison effort, both substations are capable ofaccommodating the 197 MW from Site 20. Thus, both are feasible interconnection options forSite 20 under the assumptions of this study.

• Both substations were assessed to determine which was the most favorable based on therevenue generated, the contribution of congestion to that revenue, the cost of additionaltransmission (annualized over the 10-year PTC term), and the ratio of the number of hours thatcongestion positively contributed to revenue vs. the number of hours congestion negativelycontributed to revenue.

• As seen in Table 1 and Table 2, Gowanus out performs Goethals from both a revenue andtransmission cost stand point. Gowanus, on average, makes approximately $12/MWh more thanGoethals and approximately $11.75/MWh of that difference is a direct contribution of marginalcongestion costs. Had the distance to transmission been reversed, the 10-year PTC term costtrade off would have reduced the annual revenue benefit to approximately $8 Million.

Site 20 - 197 MW Goethals GowanusTotal Net Production (MWh) 621884.55 621884.55Estimated Net CF (%) 36.04% 36.04%Average LBMP ($/MWh) 53.26 65.34Average Congestion Price ($/MWh) -7.73 -19.46Number of Hours w/ Favorable Congestion 2224 3573Number of Hours w/ Unfavorable Congestion 205 27Ratio (Favorable : Unfavorable) 10.8:1 132.3:1Estimated Annual Revenue $34,855,766.72 $43,966,306.96 Estimated Revenue Due to Congestion Price $6,250,346.32 $15,145,840.34 Distance to Bus (km) 37.83 28.26Transmission Rating (kV) 345 345Assumed Cost of 345 kV - AC Submarine Line ($/km) $1,000,000 $1,000,000 Estimated Cost of Submarine AC Transmission $37,830,000.00 $28,260,000.00

Gowanus Compared to Goethals

Difference in Average LBMP ($/MWh) 12.07

Difference in Average Congestion Contribution ($/MWh) 11.73

Difference in Revenue $9,110,540.24

Difference in Transmission Cost ($9,570,000.00)

Difference in Transmission (Annualized Over 10-Year PTC Term) ($957,000.00)

Net Difference (Revenue/Transmission Cost Trade-off) $10,067,540.24

Defined Point of Interconnection – Which Project Site is Best?• Analysis of average LBMP pricing and substantial contribution of congestion has selected the Gowanus

substation as our primary POI consideration.• All 4 potential wind facility sites were assumed to have an installed capacity of 300 MW for direct comparison.

Assuming that Site 20 is our primary site location, Sites 9, 10, and 16 were analyzed to see if another potentialproject location could return more net revenue with transmission cost trade-off.

• As seen in Table 3 and Table 4, Site 20 has the lowest production and overall revenue. Although Site 9 has thehighest estimated production, capacity factor, and revenue, the cost trade-off of the additional transmission linemakes Site 10 the best potential site.

• It should be noted that considerations, such as depth of water, have not been made in this study and couldmake the weighting between Site 9 and Site 10 more comparable. An enhanced site screening analysis wouldbe completed to consider these additional factors.

All Project Sites are 300 MW Installed Capacity Site 16 Site 20 Site 10 Site 9Total Net Production (MWh) 1017136.87 947032.40 1051334.78 1056158.26Estimated Net CF (%) 38.70% 36.04% 40.01% 40.19%Average LMBP ($/MWh) 65.34Average Congestion Price ($/MWh) -19.46Estimated Annual Revenue $73,041,178.60 $66,953,776.16 $75,149,841.31 $75,721,127.29Estimated Revenue Due to Congestion Price $25,769,542.45 $23,064,736.62 $26,404,405.63 $26,789,500.88Distance to Bus (km) 44.31 28.26 50.65 64.47Assumed Cost of 345 kV AC Submarine Line ($/km) $1,000,000 $1,000,000 $1,000,000 $1,000,000Estimated Cost of Submarine AC Transmission $44,310,000.00 $28,260,000.00 $50,650,000.00 $64,470,000.00

Table 3: Analysis of Revenue, Congestion Contribution, and Submarine Transmission Costs for Each Potential Project Site

Comparison of Site 20 with Alternate Sites Site 16 Site 10 Site 9Difference in Estimated Revenue $6,087,402.44 $8,196,065.15 $8,767,351.12Difference in Estimated Transmission Cost (Annualized Over 10-Year PTC Term) $1,605,000.00 $2,239,000.00 $3,621,000.00Net Difference in Revenue $4,482,402.44 $5,957,065.15 $5,146,351.12

Table 4: Comparison of Primary Site (Site 20) with Alternate Options (Site 16, Site 10, and Site 9)