Dubuque, Iowa has become increasingly renowned for being a so-called poster child

Transcription

1 Background Dubuque, Iowa has become increasingly renowned for being a so-called poster child for sustainability in the Midwest. The re-invented river town along the Mississippi looks to incorporate renewable energy as a way to promote sustainability and resiliency in the community. Since Dubuque s coal-fired power plant, currently owned and operated by Alliant Energy, will go off-line in the next few years, Dubuque must import all of its energy to meet residential, industrial, and commercial demand. In order to achieve its goals of supporting a complete approach to sustainability, promoting economic growth and increased standard of living, and providing reliable, cost-effective energy, Dubuque hopes to integrate renewable energies into the energy portfolio of businesses. This project aims to assess the capacity of renewable energy that can be incorporated into existing and future business operations in Dubuque. Specifically, this project seeks to produce the first ever comprehensive map-study of onsite renewable energy production capacity at the urban scale, incorporating solar, ground source heat pump (GSHP), and wind energy. Several studies have approached urban scale mapping of solar technology, but few studies have examined urban scale geothermal feasibility, and no methodology exists for a community-wide urban scale wind mapping technique. This study improves upon pioneering work in solar capacity mapping, so that it interfaces with other technologies for a holistic understanding of renewable energy capacity mapping. Thesis We pose that Dubuque, Iowa has a wealth of on-site renewable energy capacity at its disposal, across all technologies examined in the study. Based on the findings of the mapping study, the project s next phase will be to create a return on investment model that integrates Page 1

2 return across all types of renewable energy, and investigate several important policy issues related to renewable energy in Dubuque. Renewable energy mapping research will allow Dubuque to continue to promote sustainability. In addition to addressing environmental concerns, incorporating solar energy will provide economic opportunity for businesses in Dubuque to decrease operating costs in order to compete in a challenging global economic environment. It is our hope that the findings of the capacity mapping study, combined with the return on investment template and policy research, will ensure that businesses will stay in Dubuque and provide wages necessary to provide a high-quality and equitable standard of living in the community. Project Scope This project only examines on-site production of renewable energy within the city limits of Dubuque, Iowa. For that reason, technologies have been eliminated. Biomass is eliminated from the scope of this project since not enough land is available to grow a fuel that provides enough energy to offset energy demands of most buildings in Dubuque. Additionally, hydroelectric power is omitted, as dams along the Mississippi are not owned and operated by the City of Dubuque. Last, methane captured from the newly upgraded wastewater treatment plant is not considered, since the City would need to access the grid to transport electricity generated to users. Based on our scope, we only examine the on-site capacity of solar, ground source heat pump, and wind energy within the City of Dubuque. Solar Energy Capacity Mapping Methodology and Findings Developing an accurate solar capacity map for on-site energy production in Dubuque, Iowa was based on the methodology outlined by Leitelt (Leitelt 2010). Leitelt created a solar energy potential map for the city of Chapel Hill, North Carolina using ArcGIS, a geographical information system (GIS) software program. Using the general methodology outlined in this Page 2

3 report and adapting it to Dubuque s needs, an ArcGIS map measuring the incoming solar radiation for rooftops in Dubuque, Iowa was produced. As the project moves forward, this map will be combined with knowledge about the most recent solar panel technology to complete a solar suitability payback analysis for photovoltaic and solar hot water energy. In order to create the solar capacity map, two main data items were collected: Light Detection and Ranging (LiDAR) data and city building footprints. LiDAR data was acquired through the Iowa LiDAR Mapping Project and provides a raster, which is an image file compatible for use with GIS, with elevation data of land, vegetation, and structures. The City of Dubuque provided the building footprint shapefile, a layer used by the ArcGIS software, which was used to clip the final output to rooftops within the city. After attaining National Renewable Energy Laboratory (NREL) Typical Meteorological Year 2 (TMY2) data, solar returns were compared with known solar radiation data, providing for an additional check for accuracy in the data. First, a Digital Surface Model (DSM) was created. A DSM provides first-reflective topographic data of the earth`s surface containing cultural features (buildings, roads, and vegetation) and natural terrain features. In order to create the raster file, the raw LiDAR data was downloaded as several LAS files. 1 These were processed into a multipoint file using the point file information and LAS to multipoint tools within ArcGIS. The multipoint file was then converted to a raster file with sixteen square meter cells and elevation assigned as the value field. Because of the way LiDAR is created, there often exist empty data cells in the raw data. A conditional expression was used to fill these empty cells. 2 This expression uses the values of surrounding cells to calculate the value of empty cells. Unlike the Chapel Hill study, the 1 LAS stands for Log ASCII Standard, which is a format used for LiDar files. 2 Con(IsNull([input]),FocalStatistics([input],NbrRectangle(3,3), Mean ),[input]) Page 3

4 Dubuque study applied the conditional expression four times, which allowed us to fill in most empty cells. The completed DSM layer provides a raster image with elevation data for land vegetation, and structures. The DSM in its entirety for the City of Dubuque is displayed in Figure 1. In Figure 1, darker colors indicate lower elevation, while lighter colors indicate higher elevation. After the DSM layer was created, the ArcGIS Spatial Analyst s Solar Radiation tool helped to derive incoming solar radiation. Analysts changed several inputs from the default settings to better fit the tool to Dubuque s scenario. These input changes included changing the sky size to 512, the time configuration to Multiple Days per Year, the year to 2011, the day and hour interval to one, the zenith and azimuth divisions to sixteen, the diffuse radiation to 0.2, and the transmittivity to 0.7. The project s GIS analysts chose these values since the output aligned with NREL TMY2 data from Waterloo, Iowa, which was the closest city for which reliable data existed (National Renewable Energy Laboratory, 1994). Figure 2 shows area solar radiation return for Dubuque, Iowa. Warmer colors indicate higher incoming solar radiation. After the solar radiation tool produced an output, the solar returns associated with buildings were separated by extracting the solar raster to the City of Dubuque s building footprint shapefile. This removed all unnecessary solar returns from vegetation, roads, and bare terrain. Next the extracted solar raster to point data and the output value was converted from Watt hours per square meter per year (Wh/m 2 /year) to kilowatt hours per square meter per day (kwh/m 2 /day), which is universally more useful. The final output is a point file extracted to buildings within the city with an average incoming solar radiation for each sixteen square meter area within the city, shown in Figure 3. Warmer colors (i.e. red and orange) in the map below Page 4

5 indicate higher incoming solar radiation, while cooler colors (i.e. green and blue) indicate lower solar radiation. Ground Source Heat Pump Suitability Mapping Methodology and Findings Next, the project focused on mapping ground source heat pump (GSHP) energy capacity in Dubuque. Notably, the term geothermal system is not used in this project, since geothermal energy describes a technology that utilizes a hot ground layer that is created by hot springs or volcanic activity, geologic features that Dubuque, Iowa lacks. There are two different types of GSHP systems, open and closed loops. This project only incorporates assessment of sites based upon the feasibility of installing a closed loop system which does not require tapping into an aquifer the way an open loop system does, a more sustainable approach to energy production. Few maps that investigate GSHP feasibility have been created, largely in part because conditions for GSHP feasibility are highly site-specific. However, the State of Vermont is currently using a model with methodology that utilizes publicly-available data kept by the Iowa Department of Natural Resources (DNR) (Vermont Sustainable Jobs Fund, 2011). The process centers on eliminating parcels that can be immediately excluded based on certain criteria. Criteria in this study were established with the assistance of the Iowa DNR based on physical infrastructure and site contamination. Parcels containing hospitals, wastewater treatment facilities, solid waste facilities, mines, underground storage tanks (UST), leaking underground surface tanks (LUST), and cemeteries were eliminated from the assessment map as potential GSHP sites. Additional physical site constraints were incorporated, including frequent flood interval and steep slopes, as to further eliminate unsuitable sites. Frequently flooded parcels, as defined by the Iowa DNR, include those parcels entirely contained in the 50% annual flooding recurrence interval (Iowa Department of Natural Resources). Parcels entirely located on slopes Page 5

6 with greater than fourteen percent slope were also eliminated. However, parcels that are partially comprised of an area with a steep slope or frequent flooding were considered potential sites, if they met other criteria. Last, based on soil conditions, parcels containing high clay or sand content were also omitted. Soils with high clay content do not percolate well and may result in standing water. Soils that have a high sand content percolate too well and dry out quickly. According to the Vermont study, neither is desirable for siting a GSHP system. Again, parcels that were not entirely comprised of clay or sandy soils were still considered as potential sites if they met other criteria (Renewable Energy Atlas of Vermont). Figure 4 displays the sites in Dubuque deemed suitable for GSHP in light green, based on the criteria determined in this project s methodology. GSHP systems are highly dependent upon the site-specific ground conditions. Other conditions that might affect whether or not a particular system is feasible are the desired configuration of the system and the building-to-parcel ratio. Two main types of system configurations exist: horizontal loop systems and vertical loop systems. A horizontal loop system requires a large surface area; a vertical loop system requires only a small amount of ground surface area. It should be noted that determining which system configuration, horizontal or vertical loop system, should be chosen is beyond on the scope of this project. As with any of the technologies examined in this project, consulting an experienced professional is a necessary final step before installing a system. Wind Energy Capacity Mapping Methodology and Findings Creating a wind energy capacity map was relatively more challenging than either the solar or GSHP mapping stages. Obtaining wind speed data for the Dubuque area perhaps has been the most difficult aspect of the mapping portion of this project. In addition, very few, if any Page 6

7 other wind studies, exist that include methodology or data sources that could be extrapolated to fit the needs of this project. The divergence with existing literature helps to set this project apart, since few studies analyze data at the urban scale. Furthermore, studies that focus on smaller scale energy production neither discuss potential wind energy at a given site, nor include information on how to map potential capacity on community level. Most studies, whether urban or utility scale, also mentioned that the best method to determine suitability would be to install an anemometer on-site for a period of six months to one year in order to obtain accurate wind power curve data. Nonetheless, these studies did provide some base information on the benefits of wind power as well as the problems associated with harnessing wind to produce energy. The focus became placed on identifying wind speed data sources and obtaining data, preferably in the ArcGIS shapefile format. Project analysts contacted agencies such as the Iowa Energy Center, Iowa Farm Bureau, and the Iowa Wind Energy Association for assistance in finding urban scale wind speed data for Dubuque. Unfortunately, these agencies were not able to provide such data. However, the interaction alone proved very valuable in referring to different organizations which could potentially assist, giving the opportunity to increase the visibility of the project. In October, a dataset containing anemometer readings from twelve locations throughout the City of Dubuque was obtained. This dataset included information such as anemometer model, wind speed, temperature, and time. Quality assurance was performed in November. Readings from some anemometers were problematic, as not all locations collected data at the same time period and at the same interval. For instance, readings taken at the Dubuque Airport were collected daily from April, 2010 to November, The City Hall Annex data, on the other hand, was collected at five-minute intervals from August, 2006 to March, Page 7

8 Furthermore, it was found that some locations had errant data. For example, observations from the Roshek Building anemometer did not include temperature readings for certain days in August and December, Also, the Mississippi River Lock and Dam anemometer shows negative wind speed throughout Hence, it is imperative all readings such as those listed above were removed so they do not cause conflicts with the wind mapping software. One final item needed was the elevation of the anemometer, if available, because the variability in wind speed at different altitudes could affect the final results. Additionally, anemometer elevation was important to determine an accurate prediction of power output at a specific height of the installed turbine technology. The final step in wind mapping was to determine how to map the energy capacity within Dubuque based on our wind speed data. Many wind energy studies were examined in hopes of finding best methodology for mapping wind resources in our project. Few, if any, of these studies offered a model that could be applied to this project as much of the data and methods used in these studies were tailored for the needs of utility-scale projects. The methods used in this project need to account for the turbulent and unpredictable wind patterns in the urban environment. This particular element of mapping wind capacity at the urban scale is much more feasible now that the City of Dubuque provided anemometer readings from multiple locations within the city limits. To map wind capacity, an open source software program called OpenWind was used. This program was developed as an aid for the design, optimization, and assessment of wind power projects and uses an ArcGIS interface to model wind speed in an area based on known wind speed, elevation, vegetation and structure height, and surface roughness data (AWS Truepower, LLC, 2010). Figure 5 contains a test run for a small area of the city using elevation Page 8

9 data obtained from the Iowa Department of Natural Resources (DNR), vegetation height and roughness created from LiDAR data, and surface roughness data obtained from the 2006 National Land Cover Database (Iowa Geological and Water Survey; Xian and Fry, 2009). The wind rose for the City Hall Annex data is visible on eastern side of Dubuque. This wind rose shows that observations at the City Hall Annex indicate that winds out of the north and northwest were most common. Known wind speed data from an anemometer placed at Dubuque s City Hall Annex was used. The output of the model was converted to a raster image which can be imported into and analyzed in ArcGIS, shown in Figure 6. After finishing the quality checks on the OpenWind data for all of the anemometer locations throughout the City of Dubuque, necessary parameters will be adjusted in order to run the model over the entire city. Furthermore, observations from other Dubuque locations can be processed in order to provide additional quality checks, thus, improving the accuracy of the results. Conclusions Performing a comprehensive renewable energy mapping study is the first step at identifying the degrees to which renewable energy can meet the energy needs of Dubuque s business community. From the findings of the on-site capacity mapping, By better understanding on-site capacity of solar, ground source heat pump, and wind energy, an accurate return on investment model can be created that maximized return across all three energy technologies. This project proves that communities, like Dubuque, can implement a holistic approach to examining renewable energy capacity of multiple forms of renewable energy at the urban scale. Page 9

10 Figure 1 (Below): Digital Surface Model (DSM) of Dubuque, Iowa Figure 2 (Below): Area Solar Radiation Return for Dubuque, Iowa High: Low: Figure 3 (Left): Solar Radiation Point File, Return for a Portion of Downtown Dubuque, Iowa Page 10

11 Figure 4 (Below): Ground Source Heat Pump Suitability Map for Dubuque, Iowa Figure 5 (Below): OpenWind Software Tool Run with City Annex Data Figure 6 (Left): Average Wind Speeds Calculated with ArcGIS Software based on OpenWind Output for Selected Part of Dubuque, Iowa Page 11

12 References AWS Truepower, LLC,. "OpenWind User Manual.". AWS True Wind, LLC., 08/2010. Web. 3 Feb < Iowa Department of Natural Resources. "Natural Resources Geographic Information Systemsm Library. Natural Resources Geographic Information Systems Library. GIS Section, Iowa Geological and Water Survey. Web. 3 Feb < Iowa Geological and Water Survey. Three Meter Digital Elevation Model of Dubuque County Iowa, Natural Resources Geographic Information Systems Library. GIS Section, Iowa Geological and Water Survey. Web, 20 Oct 2011, <ftp://ftp.igsb.uiowa.edu/gis_library/counties/dubuque/dem_3m_i_31.zip/>. Leitelt, Lyle Robert, Developing a Solar Energy Potential Map for Chapel Hill, NC. University of North Carolina Department of City and Regional Planning. Web, 1 Sept 2011, < tps://cdr.lib.unc.edu/indexablecontent?id=uuid:6e5c0eac-e b038- d7e9c3e4da41&ds=data_file&dl=true/>. National Renewable Energy Lab. "Solar Radiation Data Manual for Flat-Plate and Concentrating Collectors: Iowa Data Tables. 05/1994. Web. 3 Feb < Vermont Sustainable Jobs Fund. "Renewable Energy Atlas of Vermont." Web. 3 Feb < Xian, G, Homer, C, and Fry, J Updating the 2001 National Land Cover Database Land Cover Classification to 2006 by Using Landsat Imagery Change Detection Methods. Remote Sensing of Environment, Vol. 113, No. 6. pp Page 12