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Using optimization to design a renewable energy system has become a computationally demanding task as the high temporal fluctuations of demand and supply arise within the considered time series. The aggregation of typical operation periods has become a popular method to reduce effort. These operation periods are modelled independently and cannot interact in most cases. Consequently, seasonal storage is not reproducible. This inability can lead to a significant error, especially for energy systems with a high share of fluctuating renewable energy. The previous paper, “Time series aggregation for energy system design: Modeling seasonal storage”, has developed a seasonal storage model to address this issue. Simultaneously, the paper “Optimal design of multi-energy systems with seasonal storage” has developed a different approach. This paper aims to review these models and extend the first model. The extension is a mathematical reformulation to decrease the number of variables and constraints. Furthermore, it aims to reduce the calculation time while achieving the same results.
In this work the transient simulations of four hybrid solar tower power plant concepts with open-volumetric receiver technology for a location in Barstow-Daggett, USA, are presented. The open-volumetric receiver uses ambient air as heat transfer fluid and the hybridization is realized with a gas turbine. The Rankine cycle is heated by solar-heated air and/or by the gas turbine's flue gases. The plant can be operated in solar-only, hybrid parallel or combined cycle-only mode as well as in any intermediate load levels where the solar portion can vary between 0 to 100%.
The simulated plant is based on the configuration of a solar-hybrid power tower project, which is in planning for a site in Northern Algeria. The meteorological data for Barstow-Daggett was taken from the software meteonorm. The solar power tower simulation tool has been developed in the simulation environment MATLAB/Simulink and is validated.