This section describes the third case in the file Sample Parabolic Trough Systems.zsam, "100 MW Baseline - Parameterized Storage." The case demonstrates how to optimize the solar multiple for a parabolic trough system with storage to minimize the system's levelized cost of energy.

For a description of the variables used for this analysis, see the Solar Field page and Thermal Storage page descriptions. If you are not familiar with Solar Advisor's parametric variables, you may want to read Parametric Analysis, which explains how to configure a parametric analysis.

For a parabolic trough system with no storage, the optimal levelized cost of energy typically occurs at a solar multiple of between 1.4 and 1.5. Because a trough system only operates at its design point (solar multiple of one) for a very few hours of the year, over-sizing the system (solar multiple greater than one) allows it to operate closer to the design point for more hours of the year. The system with the oversized solar field produces more electricity, thereby reducing the system's levelized cost of energy. However, there is a trade-off between the increased installation cost of the larger system and the increased electric energy output: As the solar field size increases beyond a certain point, the higher cost outweighs the benefit of the higher output. Adding storage to the system introduces another level of complexity: Systems with storage can increase system output by storing energy from an even larger solar field for use during times when the solar field output is below the design point, but the thermal energy storage system's cost and thermal losses have a negative effect on the levelized cost of energy.

The analysis in this case investigates the levelized cost of energy (LCOE) turning point for systems with different solar field and thermal energy storage sizes.

Note that the storage tank heat loss is an input on the Storage page and that its value depends on the storage tank size and type. Whenever you change the value of the Equivalent Full Load Hours of TES variable on the Thermal Storage page, you should also change the Tank Heat Losses value.

When the solar field is sized above its design point, the analysis should account for any energy that might be dumped during periods when the solar field produces more energy than the power block and storage system can handle. Typically, as long as the amount of dumped energy is less than about 10-15% of the new energy resulting from the oversized system, you can reduce the LCOE by increasing solar field size.

To review the parametric analysis on solar multiple and thermal energy storage:

The Solar Multiple values range from 1 to 3.5 in increments of 0.25.

The Equiv. Full Load Hours of TES values range from 0 to 12 in increments of 3.

The Equiv Full Load Hours of TES and Tank Heat Loss variables are linked, because the tank heat losses depend on the size of the storage tanks. Solar Advisor will only simulate systems using values of each of the two variables that are in the same row. For example, for 0 hours of storage, Solar Advisor will use 0 for the tank heat loss. For 3 hours of storage, the tank heat loss will be 0.62, etc.

Solar Advisor must simulate one system for each combination of values for the two variables. In this case, 10 values for solar multiple × 5 values for hours of storage = 50 simulations.

Solar Advisor displays the Parameterized Storage (LCOE) graph among others on the Results page.

Each line in the graph represents a number of hours of thermal energy storage from the list we saw in the list of parametric values for the Equivalent Full Load Hours of TES variable: 0, 3, 6, 9, and 12 hours of storage. Because the hours of storage variable is linked to the tank heat loss variable, each line also represents a tank heat loss value. We saw those values in the Edit Linked Group window: 0, 0.62, 0.96, 1.23, 1.56.

For the no storage case (the darkest line, zero hours of storage), the lowest levelized cost of energy occurs at a solar multiple of 1.5. For a given storage capacity, as the solar multiple increases, both the area-dependent installation costs electricity output increase. The interaction of these factors causes the levelized cost of energy to decrease as the solar multiple increases from 1, but at some point the cost increase overwhelms the benefit of the increased electric energy output, and the levelized cost of energy begins to increase with the solar multiple.