132 research outputs found

    Optimal Heliomobile Field Configurations In A Variable-Geometry Test Facility For Central Receiver Solar Systems

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    L'apparato sperimentale per sistemi a torre a geometria variabile costruito presso il CTAER di Tabernas (Almería, Spagna) è una novità nel mondo del solare termodinamico. Attraverso un codice scritto in Matlab si è valutato ed ottimizzato il rendimento ottico di un ridotto campo solare mobile; un'analisi comparativa con un sistema concentratore fisso e la validazione dei risultati ottenuti mediante il software di ray-tracing Tonatiuh evidenziano le caratteristiche della struttura studiataope

    Numerical simulation and design of multi-tower concentrated solar power fields

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    In power tower systems, the heliostat field is one of the essential subsystems in the plant due to its significant contribution to the plant’s overall power losses and total plant investment cost. The design and optimization of the heliostat field is hence an active area of research, with new field improvement processes and configurations being actively investigated. In this paper, a different configuration of a multi-tower field is explored. This involves adding an auxiliary tower to the field of a conventional power tower Concentrated Solar Power (CSP) system. The choice of the position of the auxiliary tower was based on the region in the field which has the least effective reflecting heliostats. The multi-tower configuration was initially applied to a 50MWth conventional field in the case study region of Nigeria. The results from an optimized field show a marked increase in the annual thermal energy output and mean annual efficiency of the field. The biggest improvement in the optical efficiency loss factors be seen from the cosine, which records an improvement of 6.63%. Due to the size of the field, a minimal increment of 3020 MWht in the Levelized Cost of Heat (LCOH) was, however, recorded. In much larger fields, though, a higher number of weaker heliostats were witnessed in the field. The auxiliary tower in the field provides an alternate aim point for the weaker heliostat, thereby considerably cutting down on some optical losses, which in turn gives rise to higher energy output. At 400MWth, the multi-tower field configuration provides a lower LCOH than the single conventional power tower field

    A parallel genetic algorithm for continuous and pattern-free heliostat field optimization

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    The heliostat field of a solar power tower system, considering both its deployment cost and potential energy loss at operation, must be carefully designed. This procedure implies facing a complex continuous, constrained and large-scale optimization problem. Hence, its resolution is generally wrapped by extra distribution patterns or layouts with a reduced set of parameters. Griding the available surface is also an useful strategy. However, those approaches limit the degrees of freedom at optimization. In this context, the authors of this work are working on a new meta-heuristic for heliostat field opti- mization by directly addressing the underlying problem. Attention is also given to the benefits of modern High-Performance Computing (HPC) to allow a wider exploration of the search-space. Thus, a parallel genetic optimizer has been designed for direct heliostat field optimization. It relies on elitism, uniform crossover, static penalization of infeasible solutions and tournament selection

    Hector, a new methodology for continuous and pattern-free heliostat field optimization

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    In the framework of central receiver solar plants, the heliostat field can take up to 50% of the initial investment and cause up to 40% of energy loss. The most popular design strategies are based on: (i) forcing heliostats to follow known distribution patterns and (ii) iterative selection of positions. However, these methods might produce suboptimal solutions. The evolution of computational platforms allows the development of more flexible approaches. In this work, Hector, a new meta-heuristic aimed at facilitating coordinate-based optimization, is presented. First, since East-West symmetry is imposed, one of those regions is ignored and the number of heliostats to be placed is halved. Second, the selected region is split into separate circular sectors around the receiver. Next, at every iteration, a new heliostat is added to the most promising sector. Then, it is optimized by a user-selected algorithm, as an independent problem, in a continuous search-space. This procedure is repeated until all the required heliostats have been deployed. The computed half is finally cloned into the other one. Two versions of this strategy are proposed. Our empirical results show that, for a given optimizer, better fields are obtained with Hector. The second version yields the best fields but requires more runtime

    New methods and results in the optimisation of solar power tower plants

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    Renewable energy technology has seen great advances in recent decades, combined with an ever increasing interest in the literature. Solar Power Tower (SPT) plants are a form of Concentrating Solar Power (CSP) technology which continue to be developed around the world, and are formed of subsystems that are open to optimisation. This thesis is concerned with the development of new methods and results in the optimisation of SPT plants, with particular focus on operational optimi- sation. Chapter 1 provides background information on the energy sector, before describing the design and modelling of an SPT plant. Here, the optical theory behind the transfer of incident radiation in the system is developed and the relevant equations presented. In Chapter 2, the cleaning operations of the heliostat eld are optimised for a xed schedule length using Binary Integer Linear Programming (BILP). Problem dimensionality is addressed by a clustering algorithm, before an ini- tial solution is found for the allocation problem. Finally, a novel local search heuristic is presented that treats the so-called route \attractiveness" through the use of a sequential pair-wise optimisation procedure that minimises a weighted attractiveness measure whilst penalising for overall energy loss. Chapters 3-6 investigate the aiming strategy utilised by the heliostat eld when considering a desired ux distribution pro le and operational constraints. In Chapter 3, a BILP model was developed, where a pre-de ned set of aim- ing points on the receiver surface was chosen. The linear objective function was constrained with linear equalities that related to distribution smoothing (to pro- tect receiver components from abnormal ux loads) via the use of penalisation. Chapter 4 extended this model by instead considering continuous variables with no xed grid of aiming points. This led to an optimisation problem with a non- linear, non-convex objective function, with non-linear constraints. In this case, a gradient ascent algorithm was developed, utilising a non-standard step-size selection technique. Chapter 5 further extended the aiming point optimisation topic to consider the dynamic case. In this sense, the aiming strategy across a period of time could be optimised, taking into account SPT plant technologi- cal limitations. Two algorithms were considered, Penalisation and Augmented Lagrangian, where theoretical properties for optimality and solution existence were presented. Finally Chapter 6 considered the efects of inclement weather on the optimisation model presented in Chapter 3. Stochastic processes were in- vestigated to determine optimal aiming strategies at a xed point in time when weather data could not be known for certain. All research presented in this thesis is illustrated using real-world data for an SPT plant, and conclusions and recommendations for future work are presented

    Aiming factor to flatten the flux distribution on cylindrical receivers

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    High incident flux gradients and hot spots lead to extreme thermal stresses that may damage and reduce the lifetime of central receivers. An aiming strategy based on a single parameter, k, named aiming factor, is developed to generate symmetric flux maps about the receiver equator. By means of this k factor, ranging between 3 (generally equivalent to equatorial aiming) and 0 (alternatively aiming to top and bottom borders), the solar flux incident on the receiver and the spillage losses can be controlled. For each sector in a heliostat field, the aiming factor values causing the flattest symmetric flux maps, kflat, are deterministically found with a sweep and mesh shifting procedure. Results for Dunhuang solar power tower plant show that kflat is fairly constant throughout the year, except near sunrise and sunset in east and west sectors, respectively./This work has been supported by the Spanish Ministry of Economy and Competitiveness under the project ENE2015-69486-R (MINECO/FEDER, UE)

    Optimization models in solar power tower plant design. Design of the heliostat field and the tower receivers

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    Falta palabras clavesEl diseño de plantas solares con tecnología de torre (utilizaremos las siglas en inglés SPT) comenzó a ser estudiado en los años 70 y sigue siendo hoy en día un área de investigación muy activa. En esta tesis doctoral se estudia el diseño óptimo de la planta solar bajo distintos aspectos, enfocándose en el diseño del sistema torre-receptor y del campo de heliostatos. El primer capítulo presenta una idea general sobre SPT, describiendo los componentes que intervienen en el problema y detallando el modelado matemático utilizado a lo largo de este documento. Un algoritmo para resolver el problema de base se propone en el Capítulo 2. Se trata de un algoritmo, basado en la heurística voraz, que introduce un enfoque innovador al resolver el problema de la localización de heliostatos sin pre-establecer ningún patrón geométrico. Este algoritmo se extiende en el Capítulo 3 para resolver el diseño del campo solar con heliostatos en bloques llamados “pod” (estructuras triangulares que albergan varios heliostatos). Los capítulos 4 y 5 versan sobre los procedimientos heurísticos adaptados para dar solución a nuevos problemas que surgen en este tipo de tecnologías: diseño de sistemas con receptores múltiples y diseño de campos multi-talla. Ambos son problemas desafiantes debido a su alto grado de complejidad. El algoritmo heurístico presentado en el Capítulo 2 ha sido modificado y combinado con distintos procedimientos de optimización para facilitar una solución, que aunque no óptima, sea competitiva y pueda ser considerada como una buena solución. A lo largo de todos los capítulos, los resultados han sido comparados con los resultados disponibles en la literatura. Esto ha permitido validar los algoritmos propuestos. Las conclusiones generales y algunos comentarios sobre trabajos futuros se comentan en el último capítulo.The design of solar power tower (SPT) plants started to be studied in 1970s and is still being an active field of research nowadays. In this dissertation, the optimal design of an SPT plant under different considerations is addressed, focusing on the tower-receiver and heliostat field design. The first chapter provides the general ideas on SPT plants, with a description of the components involved in the problem and a presentation of the mathematical modelling used in this document. An algorithm to solve the basic problem is proposed in Chapter 2. It is a greedy-based heuristic algorithm, which introduces an innovative approach solving the heliostat location problem without fixing geometrical patterns. This algorithm is extended in Chapter 3 to address the solar field design with heliostat pod systems (triangular structures having several heliostats on it). Chapters 4 and 5 concern heuristic procedures adapted to the solution of innovative problems arising in this technology: multiple receivers system design and multi-size-heliostat field design. Both are challenging problems due to their high complexity. The heuristic algorithm in Chapter 2 has been modified and combined with different optimization procedures in order to furnish a solution which, although not optimal, is competitive and can be considered as a good solution. Along all the chapters, the results have been compared to the state-ofthe- art results, when available. This has allowed to validate the proposed algorithms. The general conclusions and some comments on further work are commented in the last chapter

    Proceedings of the XIII Global Optimization Workshop: GOW'16

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    [Excerpt] Preface: Past Global Optimization Workshop shave been held in Sopron (1985 and 1990), Szeged (WGO, 1995), Florence (GO’99, 1999), Hanmer Springs (Let’s GO, 2001), Santorini (Frontiers in GO, 2003), San José (Go’05, 2005), Mykonos (AGO’07, 2007), Skukuza (SAGO’08, 2008), Toulouse (TOGO’10, 2010), Natal (NAGO’12, 2012) and Málaga (MAGO’14, 2014) with the aim of stimulating discussion between senior and junior researchers on the topic of Global Optimization. In 2016, the XIII Global Optimization Workshop (GOW’16) takes place in Braga and is organized by three researchers from the University of Minho. Two of them belong to the Systems Engineering and Operational Research Group from the Algoritmi Research Centre and the other to the Statistics, Applied Probability and Operational Research Group from the Centre of Mathematics. The event received more than 50 submissions from 15 countries from Europe, South America and North America. We want to express our gratitude to the invited speaker Panos Pardalos for accepting the invitation and sharing his expertise, helping us to meet the workshop objectives. GOW’16 would not have been possible without the valuable contribution from the authors and the International Scientific Committee members. We thank you all. This proceedings book intends to present an overview of the topics that will be addressed in the workshop with the goal of contributing to interesting and fruitful discussions between the authors and participants. After the event, high quality papers can be submitted to a special issue of the Journal of Global Optimization dedicated to the workshop. [...
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