TY - CHAP A1 - Hoffschmidt, Bernhard A1 - Alexopoulos, Spiros A1 - Göttsche, Joachim A1 - Sauerborn, Markus A1 - Kaufhold, O. T1 - High Concentration Solar Collectors T2 - Comprehensive Renewable Energy (Second Edition) / Volume 3: Solar Thermal Systems: Components and Applications N2 - Solar thermal concentrated power is an emerging technology that provides clean electricity for the growing energy market. To the solar thermal concentrated power plant systems belong the parabolic trough, the Fresnel collector, the solar dish, and the central receiver system. For high-concentration solar collector systems, optical and thermal analysis is essential. There exist a number of measurement techniques and systems for the optical and thermal characterization of the efficiency of solar thermal concentrated systems. For each system, structure, components, and specific characteristics types are described. The chapter presents additionally an outline for the calculation of system performance and operation and maintenance topics. One main focus is set to the models of components and their construction details as well as different types on the market. In the later part of this article, different criteria for the choice of technology are analyzed in detail. KW - Central receiver system KW - Concentrated solar collector KW - Solar dish KW - Solar concentration Y1 - 2022 SN - 978-0-12-819734-9 U6 - http://dx.doi.org/10.1016/B978-0-12-819727-1.00058-3 SP - 198 EP - 245 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Blanke, Tobias A1 - Schmidt, Katharina S. A1 - Göttsche, Joachim A1 - Döring, Bernd A1 - Frisch, Jérôme A1 - van Treeck, Christoph ED - Weidlich, Anke ED - Neumann, Dirk ED - Gust, Gunther ED - Staudt, Philipp ED - Schäfer, Mirko T1 - Time series aggregation for energy system design: review and extension of modelling seasonal storages T2 - Energy Informatics N2 - 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. KW - Energy system KW - Renewable energy KW - Mixed integer linear programming (MILP) KW - Typical periods KW - Time-series aggregation Y1 - 2022 U6 - http://dx.doi.org/10.1186/s42162-022-00208-5 SN - 2520-8942 N1 - Proceedings of the 11th DACH+ Conference on Energy Informatics, 15-16 September 2022, Freiburg, Germany. VL - 5 IS - 1, Article number: 17 SP - 1 EP - 14 PB - Springer Nature ER -