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Fig. 1: CSDS Regions are in the southwestern United States Additionally, there are a variety of exclusions applied to the solar resource if the slope exceeds 1%, average annual radiation is less than 6.75 kWh/m2/day, the area is a major urban or wetland area or a protected federal land. If the remaining resource lands are less than 5 contiguous sq. km, they are excluded. Fig. 2 maps the location of the solar resource that is used within CSDS, and the CSDS regions are shown by the light gray boundaries. Fig. 2: Solar Resource in CSDS1 Linear programs, such as WinDS and CSDS, work by minimizing an objective function. The CSDS objective function is a minimization of all the costs of the U.S. electric sector including: • the present value of the installation cost and anticipated operating and maintenance (O&M) costs of both generation and transmission capacity (conventional and renewable) installed in each period (each period represents 2 years), plus • the cost of using the existing transmission grid as represented in the model, plus • the cost of operating that capacity during the current period (fuel costs) to meet load, plus • the cost of reserve capacity. By minimizing these costs while meeting the system constraints (discussed below), the linear program determines (A) at which level to operate the currently installed capacity and (B) which types of new capacity and amount are the most economical to add in each period for each region in the country. Therefore, the capacity factor for each dispatchable technology in each region is an output of the model, and not exogenously defined. Note that hydropower, wind, and CSP are typically operated as much as possible, due to negligible variable cost. Therefore, these technologies operate at the maximum capacity factor possible, based on the resource class or hydro availability. The cost minimization that occurs within CSDS is subject to more than 70 types of constraints, which result in thousands of equations in the model (due primarily to the large number of regions). These constraints fall into several main categories, including: • Resources: The total amount of CSP installed in each region must be less than the solar resource potentially available – by region and resource class – as estimated by the NREL Resource and GIS teams. • Access to existing transmission lines: The amount of new solar capacity that can be transmitted on existing lines is limited by the transmission capacity available on nearby lines. The GIS portion of CSDS determines which solar resources would be most cost-effective in using existing transmission capacity. • Load constraints: The primary load constraint is that the electric load in each power control area (PCA) – there are 136 power control areas in CSDS for the entire country – must be met in each time slice (of which there are 16) throughout a year. The load and its rate of growth in each North American Electric Reliability Council (NERC) region are derived from the Reference Case of the U.S. Energy Information Agency’s Annual Energy Outlook3. • Reserve margin constraint: There are two types of reserves constraints – planning reserve margin and operating reserve. For CSP, in the current version, the amount of storage is assumed to be adequate to provide capacity equal to nameplate capacity during the peak period. In other words, CSP is assumed to be dispatchable. Of course, the cost inputs reflect the larger cost associated with storage (discussed below). For comparison, capacity value for wind power is handled statistically. In each period, CSDS updates the estimate of the marginal capacity value of the next wind farm built in each region using a detailed statistical approach. The approach takes into account the 2PDF Image | Concentrating Solar Deployment System (CSDS) A New Model for Estimating U.S. Concentrating Solar Power (CSP) Market Potential
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