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The Zone Identification and Technical Analysis work group is responsible for developing: 1) the methodology and criteria that identify those areas in the West with the best and most concentrated renewable energy resources and 2) the technology-specific information that can be used in the model developed through the WREZ process to determine the cost of renewable energy resources from the identified zones.
The ZITA work group developed a series of criteria to refine and identify the highest quality and most concentrated renewable energy resources throughout the Western Interconnection. The goal is to identify Renewable Energy Zones that are large enough and contain sufficient resources to warrant the investment that will be required for large-scale transmission projects. The transmission model being used for this process allows the work group to identify and study approximately 50 REZs. The Technical Committee determined that each state and province within the Interconnection should have at least one REZ identified. Although some of the final REZs may not be part of a regional transmission grid, those resources could address particular needs within a state or be picked up by a regional transmission line from another REZ.
Several steps are being taken by the work group to identify the Qualified Resource Areas and eventually the final REZs, as shown in the diagram below and explained in the text that follows.
The ZITA work group used raw data and maps from the U.S. Department of Energy’s National Renewable Energy Lab as the starting point for its analysis of the wind, solar, geothermal, biomass and hydropower resources within the Western Interconnection. Canadian wind data were obtained from two different sources. British Columbia wind data are from a resource assessment being carried out by BC Hydro, which quantifies the wind resource potential in areas with wind project developer interest across British Columbia. Alberta wind data are from the Alberta Electric System Operator queue and reflect wind projects planned by developers who are requesting access to the transmission grid. The Alberta data are points that approximate the planned locations of these wind projects, but do not identify their precise spatial extent. Canadian discovered conventional geothermal data were obtained from the same dataset from GeothermEx that also quantified US geothermal potential. British Columbia large and small hydropower data were obtained from BC Hydro and the BC Transmission Corporation. Alberta large hydropower data were obtained from Canadian Hydropower Developers and, indirectly, from a contact of TransCanada Energy.
Those base resource maps were then refined into Candidate Study Areas using 1) resource criteria developed by the ZITA work group and 2) initial information from the Environment and Lands work group. These areas were considered economically viable for development.
The raw resources identified in Step 1 resulted in areas that were too immense and large to analyze from a transmission perspective. The Technical Committee provided guidance that the large resource areas should be reduced to reflect only the highest quality resources in each respective state or province. The guidance provided by the Technical Committee ensured the identification of the best resources available for use on a regional scale and to meet more localized needs. The details of the state and province criteria are outlined here. Ultimately, the application of the criteria resulted in the Candidate Study Area maps.
The Qualified Resource Areas were created by factoring in several criteria that are explained in the QRA methodology. These criteria would include areas that could not be developed, such as some military lands, wildnerness areas, urban areas and bodies of water. Click here for a comprehensive list of those lands. The product of this analysis can be seen in two separate documents: the map of Qualified Resource Areas and the accompanying map notes and legend.
Please note: These maps do not include information on wildlife sensitivity. Additionally, some data for "exclude and avoid" areas were not received in time to be incorporated into the QRA maps. The QRAs will be further refined into Renewable Energy Zones once wildlife and complete data for exclude/avoid areas are included. Interested parties will be able to comment in late spring on the revised maps.
These maps can also be viewed in a GIS interface by going to the NREL WREZ GIS portal:
The portal is data intensive, so patience is a virtue when drilling down on these maps.
To determine the cost of a renewable energy resources from a certain area, a set of assumptions were made about the type of technology that would produce the energy, e.g. solar photovoltaic, concentrated solar power or wind. The technology assumptions will be used to calculate the Levelized Cost of Energy. Levelized Cost of Energy is a measure of the total costs of a system (over its expected lifetime) divided by the expected energy output (over its useful lifetime), with appropriate adjustments for time, value of money, etc. This data will be used in a model to develop supply curves that will help quantify the renewable energy resource potential of a specific area. The supply curves indicate how much generating capacity a REZ can reasonably provide, and the cost of each unit of energy from that REZ.
ZITA established default assumptions for each resource based on the most commonly used commercial-scale technology. Using the supply curves, individuals can change these assumptions based on applicable project details.
Once the QRAs are refined with wildlife information, the areas will be assessed for their total megawatt potential. All resources will be evaluated and incorporated into a supply curve calculation. The supply curves will indicate how much capacity each REZ can theoretically generate from all resources and the relative cost of developing them. This information will be incorporated into the transmission model created by the Generation and Transmission Modeling work group to calculate the delivered cost of energy from a respective WREZ to load centers.