Abstract
This study employs the dynamic programming (DP) optimization approach to maximize the daily revenue of a concentrating solar power plant (CSP) equipped with a thermal energy storage system (TES). DP guarantees the optimal solution and is easy from the computer coding point of view; therefore, it can be of great importance. Two real-life case studies are considered. The first case has a simple thermal model and is mainly chosen in order to verify the present optimization program. In this case, the present work achieves 1.3% (or US$480 /day) higher daily revenue in comparison with the literature. However, the simple thermal model of the first case study cannot appropriately simulate the actual operation of a CSP. Therefore, the optimization was applied to another case with a more detailed thermal model. The findings indicate that in order to maximize revenue, the charging and discharging of the TES should be managed such that the power block works under base load conditions (whenever it is active) and during periods of high electricity prices, regardless of the level of the daily solar radiation pattern. Furthermore, quantitative investigations show the substantial influence of the TES system on the daily revenue, especially for the case of low solar radiation pattern.
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