Integrating ecological data into long-term energy planning is critical to meet both California’s long term energy and conservation goals. To demonstrate that meeting both goals is not only possible, but also cost-effective, in 2015 The Nature Conservancy, in partnership with Energy and Environmental Economics, Inc. (E3), and Grace Wu (UC Berkeley), completed a state-wide assessment of the potential trade-offs associated with renewable energy build-out. The analysis evaluated the land and water use implications and cost of a range of potential renewable energy scenarios for meeting climate goals by 2030.

When TNC initiated this assessment, California energy agencies were using the output from the California Renewable Energy Portfolio Calculator v6.0 (RPS Calculator) to inform transmission and long-term procurement planning decisions. The calculator incorporates data on transmission availability, renewable energy resource potential and other factors. The agencies use the output to design a portfolio of future renewable energy projects (for multiple technologies) that meets a projected renewable energy generation scenarios at the lowest cost. However, the RPS Calculator does not account for the many areas where renewable energy development may generate conflict due to impacts on conservation values. The model and analysis presented in the 2015 assessment incorporates ecological information into the RPS Calculator using the Optimal Renewable Energy Build-out (ORB) model. The Executive Summary provides an overview of the assessment, key findings and policy recommendations from The Nature Conservancy.

How to Explore the ORB Model Results

In the Spring of 2018, The Nature Conservancy partnered with Conservation Biology Institute to develop an online viewer for users to explore the ORB model results. The data are reported at the level of Super Competitive Renewable Energy Zones (SuperCREZ, shown in map to left). SuperCREZs are roughly county-scale energy planning units for which renewable resource potential, transmission capacity and renewable energy project costs have been estimated. The renewable energy resources considered in this study are: solar photovoltaic (PV), concentrating solar power (CSP), wind and geothermal. The 2030 renewable energy generation scenarios considered in the assessment are: 33% in-state generation, 50% in-state generation, or 50% west-wide generation. In this viewer, we consider the results for only 33% or 50% in-state generation due to the fact that evaluation of environmental impacts west-wide was outside the scope of this study.

The ORB model uses four levels of increasingly restrictive environmental exclusion. The land categorizations and datasets draw primarily on previous renewable energy planning studies, including the WECC Transmission Expansion Plan, the Western Renewable Energy Zones (WREZ) project and the Renewable Energy Transmission Initiative (RETI), along with important additional data inputs from The Nature Conservancy. The full list of data sources appears in Table A-2 in the full assessment. In cases where environmental exclusions precluded meeting the RPS Calculator's minimum resource potential estimates for a SuperCREZ, we "relaxed" the environmental exclusions for that SuperCREZ to be less restrictive.

The ORB model results data that can be explored are: 1) Renewable energy resource potential associated with different levels of environmental exclusions; and, 2) Renewable energy resources selected for a portfolio to meet 33% or 50% in-state generation scenarios for 2030.

There are two ways to access the information: 1) Spatial visualization through the ORB Study Quickstart Map; 2) SuperCREZ Summary Card showing the suite of data in a simple infographic format (for 28 SuperCREZs).

Data to explore in the ORB Study Quickstart Map:

• Existing and commercial renewable energy projects by SuperCREZ with point location of existing and commercial renewable energy projects. Existing projects are those that have come online and are currently generating electricity. Commercial projects are those that are still in development but have a Power Purchase Agreement with an electricity buyer.
• Resource potential by SuperCREZ for wind, solar PV, CSP and geothermal.
• Selected resources by SuperCREZ under the 33% in-state generation scenario for wind, solar PV, CSP and geothermal.
• Selected resources by SuperCREZ under the 50% in-state generation scenario for wind, solar PV, and CSP.
• Supporting datasets: County boundaries, SuperCREZ boundaries, transmission lines and current land use.

To visualize the datasets check on/off the layers you are interested in. You can use the swiping tool to explore overlapping layers. For example, if you are interested in how land cover is related to resource potential, you can turn on both of these layers and use the swiper tool to go back and forth between them.

SuperCREZ Summary Card

The ORB results include a complex set of data that has been summarized by individual SuperCREZ. A simple “summary card” for 28 of the 61 SuperCREZs showing the results by the four technologies was created to provide a snapshot of the data. This summary card is accessed through the SuperCREZ with ORB Model Results and Summary Card dataset, which is also included in the Quickstart Map. Users can select a SuperCREZ unit using the “i” identify tool in the Data Basin mapping application. A pop-up with detailed breakdown of the resource potential by technology and by environmental exclusion category will appear (see image at left).

For the 28 SuperCREZs that have resources selected for one or more technology, this pop-up also includes a hyperlink to a summary card. The summary card is a printable summary of the ORB model results for renewable energy resources selected to meet two renewable energy build-out scenarios (33% and 50% in-state generation) at two levels of environmental exclusion category (Category 2 & 3). In addition, the summary card summarizes the environmental impact and water use for the build-out scenarios. For the 13 SuperCREZs that had only one technology for one Category to meet one RPS scenario, no summary card was generated due to insufficient results data to display.

Water use estimates rely on the literature compilation of technology-specific water consumption values (see Table 2 in the report). Using the median value (gallons MWh-1) and the annual MWh generated per technology, we estimated annual water consumption values in gallons/year and categorized those values into very high, high, medium, low and very low water usage.

Environmental impact score refers to the level of environmental impact that the selected resources will have. The scoring is based on the assumption that sighting in areas with less legally stringent conservation values will be lower impact than if development occurred on land areas with more stringent values. Environmental impact scores range from 3 (highest impact) to 0 (least impact). In the dashboard, these values were categorized into high (values between 2-3), medium (values between 1-2) and low (values between 0-1) environmental impact.

The combinations of environmental protection categories and build-out scenarios are presented as a plausible range of future scenarios for renewable energy development in California. The scenarios are meant to illustrate the magnitude of trade-offs between the development of renewable energy capacity, environmental impacts and costs given a range of inputs and assumptions. The data are not intended to inform facility siting decisions, and all renewable energy projects should complete site-level environmental assessments to ensure impacts are avoided and minimized.