BC Hydro Wind Data Study Update

Transcription

1 PUBLIC DOCUMENT September 24, 2009 Prepared for: British Columbia Hydro & Power Authority 333 Dunsmuir Street Vancouver, BC V6B 5R3 DNV Global Energy Concepts Inc th Avenue, Suite 900 Seattle, Washington USA Phone: (206) Fax: (206)

2 Approvals Prepared by Jeffrey Gessert September 24, 2009 Date Reviewed by Kevin J. Smith September 24, 2009 Date Version Block Version Release Date Summary of Changes A September 24, 2009 Original DNV Global Energy Concepts Inc. September 24, 2009

3 Table of Contents INTRODUCTION... 2 OVERVIEW OF PROJECT SCOPE... 2 WIND POWER PROJECT DELINEATION... 2 STUDY AREA SELECTION... 2 PROJECT DELINEATION CRITERIA... 3 PROJECT DELINEATION METHODOLOGY... 4 THEORETICAL PROJECTS... 5 PROJECT CAPACITY AND NET CAPACITY FACTOR ESTIMATION... 6 PROJECT CAPACITY ESTIMATION... 6 NET CAPACITY FACTOR ESTIMATION... 7 APPENDIX A OUTLINED PROJECTS AND INSTALLED CAPACITY DNV Global Energy Concepts Inc. September 24, 2009

4 List of Figures Figure 1. Study Areas... 3 Figure 2. Theoretical Projects... 6 List of Tables Table 1. Project Delineation Criteria... 3 Table 2. Turbine Specifications... 7 Table 3. Projects and Installed Capacity... 7 DNV Global Energy Concepts Inc. September 24, 2009

5 Introduction In May 2009, DNV-GEC completed a study for the British Columbia Hydro & Power Authority (BC Hydro), titled BC Hydro Wind Data Study. The objectives of that study were to identify and delineate theoretical wind power projects, and to supply synthesized wind and wind power production data that accurately represented the spatial and temporal characteristics of these projects. This study focused on regions of British Columbia that are likely to experience significant wind energy development in the future. At BC Hydro s request, DNV-GEC has updated the BC Hydro Wind Data Study to provide estimated wind project capacity information for regions outside of the domains used in the original study. The results of this update are presented in this report. Overview of Project Scope The objectives of this study update are to identify potential project areas and their estimated capacity in regions not covered in the BC Hydro Wind Data Study. The areas included in this update cover northern and central British Columbia as well as the former Northwest domain from the original study. Similar to the original study, mean annual wind speed and maximum slopes are the main criteria used in identifying potential project areas. In contrast to the original study, however, distance to transmission is not considered as a criterion. It should be noted that in the original study, distance to transmission did not eliminate any projects, but rather was one of the determining factors to classify a project as either readily available or ambitious. Such classifications are not made in this update. Study Area Selection Wind Power Project Delineation The geographic scope of this study focuses on areas not covered in the original study as well as the Northwest domain outlined in the original study. In that study, only a few small projects in the ambitious category were identified in the Northwest domain. Considering the small quantity of projects in the Northwest domain in relation to the volume of projects delineated within the entire study domain, a collective decision was made to focus on the other domains. The area covered by the Northwest domain is re-assessed for this project. Figure 1 shows the extent of the study areas used in this project. DNV Global Energy Concepts Inc. 2 September 24, 2009

6 Figure 1. Study Areas Project Delineation Criteria To identify potential wind power project areas, the regions not covered in the original wind data study were screened, and theoretical projects were outlined based on pre-determined criteria. These criteria are listed in Table 1. Table 1. Project Delineation Criteria Minimum Long-Term Wind Speed Average Maximum Slope 6.0 m/s Areas with 20% or greater slope excluded. Areas with 10-20% slope avoided when possible. DNV Global Energy Concepts Inc. 3 September 24, 2009

7 The minimum annual project-average wind speed threshold for all projects was 6.0 m/s at a hub height of 80 m. Project areas were not outlined on very steep terrain. Slopes greater than 20% were excluded from analysis, and areas with slopes between 10% and 20% were avoided when possible. In addition to the above criteria, all project areas had to meet several other criteria. If a project area was flat in general, but contained isolated areas of steep terrain, the assigned percentage of developable land used for project capacity estimation was decreased. Likewise, if a project area contained lakes or wetlands, the assigned percentage of developable land was decreased. For projects identified on ridgelines, the top of the ridge had to have a slope of less than 20% for a width of approximately 100 m or more, an area generally wide enough to permit wind turbine installation. Projects were not outlined on ridgelines running parallel to the known predominant wind direction, because poor exposure to prevailing wind and turbine locations would result in unacceptable column wind conditions. If the wind direction was unknown in a certain area because no met data had been collected within a reasonable distance, the project ridgeline could be oriented in any direction. Areas within provincial or national parks, and protected areas (such as conservancies and biodiversity areas) were excluded from analysis. Finally, a minimum installed capacity or size of 30 MW was assumed for each identified wind power project. The final set of selected project areas represents those areas that met the pre-determined criteria. Some potential project areas that were ultimately not selected may have met one of the criteria, such as wind speed, but were eliminated because they did not meet the other criteria, such as slope or minimum size. It should be noted that there are inherent limitations in the wind modeling. However, the final set of theoretical projects is considered to be a reasonable representation of the available resource potential. The total identified installed capacity is larger than what is likely to actually be developed. As was the case with the original study, it is the intention of the updated study to produce a large set of theoretical projects that allow for additional screening and sensitivity analyses. Additional limiting factors may be associated with these wind project areas including aesthetics, public opposition, environmental concerns, etc. that could reduce their actual development potential. Consequently, the locations of individual outlined project areas do not indicate the overall feasibility or potential economic viability of a certain area for wind power development. Project Delineation Methodology DNV-GEC identified potential wind power project areas, per the above criteria, by utilizing digital wind speed data and GIS technology. The primary data sets used include: 90-m resolution digital elevation model (DEM) data from GeoBase (a service overseen by the Canadian Council on Geomatics); 1:250,000 spatial resolution topographic data procured from the CanMatrix service of Natural Resources Canada; and a 5-km resolution wind map produced by 3TIER for the province of British Columbia. This wind map contains information of mean simulated wind speed at a height of 80 meters, based on ten years of simulated data (January 1997 through December 2006). The 10-year simulated data set was constructed by blending two separate model runs: 1) a ten-year 15km resolution simulation for the period and 2) a one-year 5km resolution simulation for the year DNV Global Energy Concepts Inc. 4 September 24, 2009

8 GIS modeling was used to determine areas within the study domain that met the pre-determined criteria for wind speed and slope considerations. A more detailed visual analysis was then performed on these areas to delineate the wind power project areas. Depending on topography, projects were either drawn as a line (for steeper areas where turbines would likely be installed on top of a ridge), or an area (for flatter areas, where turbines would likely be installed in an array). A single project could consist of a single line/area or multiple lines/areas, depending on topography. During the project delineation process, each project area was assigned a constructible area percentage that was later used to calculate the project s capacity. If an outlined project area had some undevelopable areas, such as lakes, wetlands, or steep terrain, the constructible area percentage was decreased. If a particularly large area could accommodate a very large project (i.e., 500 MW or more) or two or more smaller projects, it was broken up into several smaller projects when possible. Theoretical Projects The theoretical projects resulting from the above methodology and criteria are shown in Figure 2. The northwestern region is characterized by high mountains. The topography becomes less extreme towards the north-central portion, as plateau features begin to dominate the landscape. A number of projects in this region were identified on or near these plateau features. Elsewhere, the topography either exceeded the maximum allowable slope, or the wind speeds were not sufficient, usually in lower elevations such as river valleys. The only ridgeline projects delineated in this study are located in the eastern portion of this region (north of the original Peace domain). While the southern region is less affected by extreme terrain, the central portion of this region suffers from a lack of sufficient wind speeds. The few projects in this region are located on small plateau features. The eastern portion of the southern region reaches the Rocky Mountains, where the topography is not suitable for large-scale wind project development. DNV Global Energy Concepts Inc. 5 September 24, 2009

9 Figure 2. Theoretical Projects Project Capacity and Net Capacity Factor Estimation Project Capacity Estimation The assumptions made in the original wind data study regarding size and type of wind turbine, turbine density and energy losses were applied in this study to estimate the installed capacity of each identified project. Project delineation in this study resulted in no project areas with average wind speeds greater than 9 m/s, and therefore, only the Class II turbine (Siemens ) was used to estimate installed capacity. The IEC design classifications of this wind turbine are presented in Table 2. It should be noted that the appropriate turbine class for a particular site also depends on other factors such as turbulence intensity and the extent of inclined flow. These factors were not considered in this study. DNV Global Energy Concepts Inc. 6 September 24, 2009

10 Table 2. Turbine Specifications Design Classification IEC Class II Turbine model Siemens 2.3 Nameplate capacity 2.3 MW Rotor diameter 93 m Turbine density was assumed to be 2.3 turbines per square kilometer for area projects, and 2.7 turbines per kilometer for ridgeline projects. A standard energy loss factor of 18.5% was assumed to account for system energy losses incurred within the project. This loss factor does not include transmission system outages or curtailment losses. The power curve for the Siemens turbine was obtained from the manufacturer for standard atmosphere (1.225 kg/m 3 air density). An air density of kg/m 3 was assumed for projects along the coast while all inland projects were assumed to have an air density of kg/m 3. The power curves for the kg/m 3 air density were created by DNV-GEC by interpolation from the standard atmosphere power curve, per IEC standard Turbine density assumptions were applied to each outlined project area, based on whether it was delineated as an area or a ridgeline. Local factors such as topography, rivers, and wetlands have an impact on the estimated installed capacity numbers. These factors were considered in defining the percentage of constructable area for each array-type area project. After the percentage of constructable area was taken into account, the area of each delineated array-type area project was multiplied by a per-square-kilometer turbine density assumption. For ridgelines, 100% constructability was assumed, and the length of each ridgeline was multiplied by a per kilometer turbine density assumption. The final number of outlined projects and installed capacities are shown in Table 3. A complete table of all identified projects and their individual estimated installed capacities is available in Appendix A. Table 3. Projects and Installed Capacity Category Number of Projects Total Installed Capacity (MW) Total Net Capacity Factor Estimation In calculating the net capacity factors for each project, the wind speed map was first reclassified into wind speed bins, with each bin containing areas with wind speeds ± 0.25 m/s surrounding the center of each bin. For instance, the wind speed bin for 7.25 m/s would include all areas with speeds from 7 m/s to 7.5 m/s. Using GIS and the assumptions noted above regarding turbine density, the number of turbines contained in each average wind speed bin was calculated. Due to the lack of time series data, a Weibull Distribution with a standard North American shape factor of 2.0 was used to create the frequency distribution for each average wind speed bin. Along with the assumptions discussed above regarding air density and losses, the wind speeds were input into the appropriate Siemens power curve to estimate the energy production output. Net capacity factor numbers were then calculated for each section of each project, and a weighted net capacity factor was then determined for each project based on the length and area of each project section relative to the whole. DNV Global Energy Concepts Inc. 7 September 24, 2009

11 The estimated net capacity factors, shown in Appendix A for each project, range from 0.20 to 0.32 for area projects, and from 0.15 to 0.30 for ridgeline projects. The range in net capacity factors for area projects is similar to that found in the original wind data study. However, the capacity factors for ridgeline projects are somewhat lower than those in the original study where ridgeline capacity factors ranged from 0.20 to A comparison between the two wind maps has not been made, and hence it is not possible to know if the lower capacity factors are due to projects being identified in areas less favorable for wind development, or if the lower capacity factors are due to the coarser wind map used in this follow-up study. The original study utilized wind maps with a grid resolution of 2 km (i.e., each grid point covers a 2 km by 2 km area), while the present study uses a 5-km resolution wind map (i.e., each grid point covers a 5 km by 5 km area). As a result, wind speed values for narrow ridge top areas may not match measured wind speed values due to the coarseness of the map. The lower resolution inherently prevents the wind speed map from completely discerning ridgeline features, possibly resulting in an underestimation of the capacity factors as well as installed capacity for certain projects found along ridgelines. DNV Global Energy Concepts Inc. 8 September 24, 2009

12 Appendix A Outlined Projects and Installed Capacity Project Name Table A-1. Theoretical Project Summary Ridgelines Capacity (MW) Number of Turbines Net Project Capacity Factor at 80 meters Distance to Transmission (km) BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC DNV Global Energy Concepts Inc. A-1 September 24, 2009

13 Project Name Table A-2. Theoretical Project Summary Areas Capacity (MW) Number of Turbines Net Project Capacity Factor at 80 meters Distance to Transmission (km) BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC DNV Global Energy Concepts Inc. A-2 September 24, 2009