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100 90 80 70 60 50 SM = 3.5 SM = 2.5 SM = 2.0 SM = 1.5 5 10 15 20 h [eq. hours] TES 20 10 0 -10 -20 -30 -40 -50 4 2 0 SM = 3.5 SM = 2.5 SM = 2.0 -2 SM = 1.5 5 10 15 20 h [eq. hours] TES Chapter 6 (a) (b) Figure 6.4: Yearly results for the comparison between reference and optimized solar tower plant operation. The results are shown as a function of the TES system capacity hTES. The symbols refer to the SM values. 6.4a results in terms of harvested revenue Rev, black lines: optimized operation, gray lines: reference operation (these lines correspond to the solid black lines reported in Fig. 6.2a). 6.4b percentage differences among the results shown in Fig. 6.4a; red lines (and red ordinates axis): iso-abscissae comparison (i.e., possible increase in revenue for a given hTES ), black lines (and black ordinates axis): iso-ordinates comparison (i.e., possible decrease of hTES for a given revenue). In order to present a thorough analysis, however, the yearly system performance must be considered. The solution strategy is the same, and the optimal control result has been obtained by separately op- timizing each month of operation, and then by summing the resulting monthly revenues. Since the adopted approach assumes perfect knowledge of the weather forecast within the analysis interval, considering monthly intervals may seem inappropriate. However, as discussed in Ref. [20], expand- ing the forecasting horizon to more than 2 − 3 days has only a minor effect on the yearly revenue, since the storage capacity limitation constrains the amount of energy that the optimizer can shift. The plant yearly revenue as a function of the storage capacity, with and without optimal control and for several SM values, is shown in Fig. 6.4a. Fig. 6.4b sheds some more light on these results. It can be seen that, for any storage capacity, the optimal operation strategy allows for a positive gain in terms of revenue, ranging approximately from 2% up to 5% (see red lines, and red ordinates axis). Notably, a complementary perspective can be considered, i.e., the operating strategies can be compared for equal revenue yields, thus eval- uating the potential reduction in TES system size they allow for, or, in other words, their impact on the system design. Also in this case, the gain achievable thanks to the optimized operation is considerable (see black lines, and black ordinates axis). To put these conclusions in the right perspective, that is, in order to properly discriminate among an increase in the yearly revenue and a decrease of the capital cost, a financial analysis considering the whole plant life-time is necessary. A detailed financial model has been developed to this end, based on the framework implemented in SAM [26]; the adopted methodology is detailed in A.2. All 160 Rev. [M$] ∆h (at=Rev.) [%] TES ∆Rev.(at=h ) [%] TESPDF Image | New Concepts FOR Organic Rankine Cycle Power Systems
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