The value calculated in Section 5.2 only addresses the variable operational value. Both CSP and PV have the ability to provide system capacity and replace new generation. However, the actual capacity value of solar tech­nologies depends on their coincidence with demand patterns and how this coincidence changes as a function of penetration.

At low penetration, the capacity credit (equal to the fraction of capac­ity that is available during periods of high net demand) of PV and CSP without TES is relatively high. Figure 17 shows the simulated solar out­put during three peak demand days in the low RE system, including the system annual peak on July 27 showing high correlation. As a result, each megawatt of PV or CSP without TES reduces the net demand by a signifi­cant amount and eliminates the need for conventional generation.

As the penetration of PV or CSP without storage increases, the ca­pacity credit drops significantly. Solar energy shifts the peak to later in the day, to periods where solar output is low or zero. In Figure 17, the annual peak demand occurred in the hour ending at 2 p. m. on July 27.





FIGURE 18: Correlation of demand and solar generation on a З-day period starting July 17 (high RE case)


Подпись: The Value of Concentrating Solar Power with Thermal Energy Storage

(Other peak demand hours are typically an hour or two later.) However, in the high RE case, where solar provides 8% of total demand, the net demand has been shifted to later in the day where solar is no longer highly correlated with load. Figure 18 shows an example of a new period of high peak demand in the high RE case where the net load peaks in the hour ending at 7 p. m. on the first and third day. On these 3 days beginning on July 17, there is still strong solar output, but PV and CSP without storage no longer provide significant amounts of net demand reduction. CSP with storage shifts generation to later in the day and provides a net demand re­duction equal to the plant’s rated capacity, resulting in a capacity credit of close to 100%. This is shown in detail in Figure 19, which enlarges the net load on July 17 and shows the net demand after removing the generation from the three different solar technologies.

Estimation of the monetary value of system capacity begins with an esti­mate of each plant’s capacity credit. There are a number of methods used to estimate the capacity credit of VG sources. We used the simple capacity factor approximation technique, which has been shown to be a reasonable approxi­mation for more computationally complex methods (Madaeni et al. 2012).


Based on 2006 load and solar patterns, in the low RE case, where PV provides about 1% of total demand, each 100 MW (AC rating) of PV or CSP without storage provides about 70-75 MW of system capacity value before taking into account forced outages. This is comparable to a previ­ous estimate of PV in Colorado (Xcel 2009). Adding TES to CSP increases the capacity value substantially.

Table 8 summarizes the capacity value estimates from this analysis. The first row in Table 8 is the capacity credit in terms of fraction of rated capacity. This value assumes an equal outage rate for maintenance across technologies. The second row translates this into an annualized value per installed kilowatt of the corresponding technology by multiplying the ca­pacity credit by the low and high estimated annual value of a reference generator with 100% availability. The low value of the reference genera­tor is $77/kW, based on the estimated annualized cost of a combustion turbine, while the high value is $147/kW, based on the annualized cost of combined cycle generator.

Row 3 of Table 8 translates this value per installed kilowatt into a value per unit of generation. This is calculated by multiplying the value per unit of capacity by the total capacity (to get the total annual value of the in­stalled generator), then dividing this value by the total energy production. This introduces some unusual and somewhat counterintuitive outcomes, resulting largely from the impact of solar multiple and the use of TES, as demonstrated previously by Mills and Wiser (2012). A CSP plant with storage and a PV plant providing equal amounts of energy on an annual basis will have a different installed capacity. In the test system, 300 MW of CSP with a solar multiple of 2.0 and 6 hours of storage provides the same amount of energy as 577 MW of PV capacity. In the low penetra­tion case, CSP provides 294 MW of system capacity at a capacity credit of 98%, while PV at a 70% capacity value provides 404 MW. This means the aggregated PV plant has a higher overall capacity value than the CSP plant, and because both plants produce the same amount of energy, PV produces a higher value of capacity on a per unit of energy basis. This effect disappears in the high RE case where the capacity value of PV and CSP without storage is very low. This issue is illustrated conceptually in Figure 20, where the output of PV and CSP is shown for a single day (July 17). It shows that at the peak hour, a CSP plant without storage has a high­er capacity value than the CSP plant with storage. It also shows that this benefit on this particular day is at the very edge of production and again demonstrates the dramatic drop in capacity value of PV and CSP without storage at fairly low penetration.

TABLE 8: Capacity Value

Low RE Scenario

High RE Scenario







CSP (no











Capacity Credit (%)









Capacity Value












Capacity Value









(Low/High) ($/ MWh)






In the high RE scenario, CSP with storage is able to generate at nearly full output during remaining high demand periods in the summer. How­ever, it experiences a reduction in overall capacity value due primarily to limited energy availability during a few hours of relatively high demand in the winter.