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Topology optimization for energy problems
Full text linkThe optimal design of energy systems is a challenge due to the large design space and the complexity of the tightly-coupled multi-physics phenomena involved.
Standard design methods consider a reduced design space, which heavily constrains the final geometry, suppressing the emergence of design trends. On the other hand, advanced design methods are often applied to academic examples with reduced physics complexity that seldom provide guidelines for real-world applications. This dissertation offers a systematic framework for the optimal design of energy systems by coupling detailed physical analysis and topology optimization.
Contributions entail both method-related and application-oriented innovations.
The method-related advances stem from the modification of topology optimization approaches in order to make practical improvements to selected energy systems. We develop optimization models that respond to realistic design needs, analysis models that consider full physics complexity and design models that allow dramatic design changes, avoiding convergence to unsatisfactory local minima and retaining analysis stability.
The application-oriented advances comprise the identification of novel optimized geometries that largely outperform industrial solutions. A thorough analysis of these configurations gives insights into the relationship between design and physics, revealing unexplored design trends and suggesting useful guidelines for practitioners.
Three different problems along the energy chain are tackled. The first one concerns thermal storage with latent heat units. The topology of mono-scale and multi-scale conducting structures is optimized using both density-based and level-set descriptions. The system response is predicted through a transient conjugate heat transfer model that accounts for phase change and natural convection. The optimization results yield a large acceleration of charge and discharge dynamics through three-dimensional geometries, specific convective features and optimized assemblies of periodic cellular materials. The second problem regards energy distribution with district heating networks. A fully deterministic robust design model and an adjoint-based control model are proposed, both coupled to a thermal and fluid-dynamic analysis framework constructed using a graph representation of the network. The numerical results demonstrate an increased resilience of the infrastructure thanks to particular connectivity layouts and its rapidity in handling mechanical failures. Finally, energy conversion with proton exchange membrane fuel cells is considered. An analysis model is developed that considers fluid flow, chemical species transport and electrochemistry and accounts for geometry modifications through a density-based description. The optimization results consist of intricate flow field layouts that promote both the efficiency and durability of the cell
A computational approach for the design of high-power performance Proton Exchange Membrane fuel cells.
No full textRobust design of large district heating networks through topology optimization
No full textLarge water distribution networks greatly benefit from topological changes brought by the construction of loops. In fact, besides the reduction of pumping power, adding loops can smooth the overall effects of random malfunctions, making existing networks intrinsically robust. In this paper, we use the tools of topology optimization to generate an optimized looping strategy that minimizes the effect of pipe breakage. The objective is an original robustness index that is formulated as a weighted sum of the minimum supply pressure sensitivities to an infinitesimal valve shutdown. Furthermore, a maximum cost constraint is added to limit investment cost. Predictably, robustness and cost are found to be antagonist objectives: the optimized designs, obtained by systematically relaxing the cost constraint, lay on a smooth Pareto curve that should serve as a reference to both practitioners in the field and decision makers. For the specific network analyzed in this paper, we found that topological modifications can raise the robustness of the system by 29.3 % with an investment limited 200 k€ and decrease the maximum pressure drop by 10.8 %. Above this threshold, we observed no topology modifications of the optimal designs: with a further 800 k€ investment, additional benefits are limited to 2.5 % and 2.3 % in terms of robustness and pressure drop respectively
Heat transfer enhancement in PCM storage tanks through topology optimization of finning material distribution
No full textLatent Heat Thermal Energy Storage provides very high energy density and nearly constant operating temperatures. However, it suffers of very low thermal conductivity that considerably limits the heat transfer rate. The insertion of highly conductive fins looks the most promising option for heat transfer enhancement but raises the fundamental question of how to optimally distribute a limited amount of highly conductive material. In this paper, we show that density-based topology optimization is a very powerful tool to generate optimized devices for heat transfer enhancement in finned shell-and-tube PCM storage tanks. We consider 2D steady-state diffusion with uniform heat generation and we minimize the global heat transfer resistance. The topological designs reduces the maximum overheating of more than 84 % compared to a previous design obtained by parameter shape optimization
Local entropy generation analysis of transient processes - an innovative approach for the design improvement of a Thermal Energy Storage with Integrated Steam Generator
No full textThe application of second-law methodologies for the analysis of unsteady processes, such as TES charging and discharging, is complicated by the fact that the optimization ofthe design involves the search for an optimal time history, i.e. the one that minimizes the global entropy produced during a finite time interval. Most of the works done in the field consists of lumped parameters studies, which do not provide by any mean local information. On the other hand, entropy generation studies through the use of continuum theory have demonstrated to be a very powerful tool. However, a fundamental question arises on which is the most suitable time to stop the operation and analyse the process. In the present work, we aim at bridging this literature gap by proposing a modified local Entropy Generation Analysis (EGA) that well suits the study of unsteady processes. Firstly, the transient performance of a CSP cogeneration plant with a thermocline thermal energy storage (TES) tank and a submerged steam generator are analysed to identify uncommon temporal behaviours of the components. Thereafter, the modified EGA methodology is used to improve the design of the TES-integrated steam generator. Thanks to the introduction of three novel local indicators that record valuable information on the evolution of the system, namely the cumulated local entropy generation, its characteristic time and lifespan, the main criticalities are highlighted and well localized in both time and space and thus the identification of possible design improvements is simplified. The modifications proposed, i.e. the installation of a gate valve and an impeller on the molten salts side of the steam generator, bring an 11.2 % reduction of the irreversibilities generated in the steam generator, a 7.7 % improvements of the thermodynamic performance of the integrated system and a 4.7 % increase of the exergy yield of the entire plant
Multi-scale concurrent material and structure design of a metal matrix for heat transfer enhancement in phase change materials
No full textDesigning thermal energy storage units with high energy and power density is a key objective for accommodating more renewable generation. The low thermal conductivity of phase change materials (PCMs) demands for finely tailored metal matrixes or foams to increase the amount of energy that can be stored/retrieved in a given amount of time. Previous design studies have explored a limited design space and never analyzed nor optimized the micro-structural topology of the matrix. This paper proposes for the first time a multi-scale design optimization of the PCM-metal composite and the metal matrix layout. The material constitutive law of the heat transfer structure at the macro-scale is governed by the layout of a representative volume element at the micro-scale, where a universal material layout is considered. The phase change problem is solved through a fixed-grid finite element method based on the enthalpy-porosity model, which accounts for natural convection in the liquid at the macro-scale. Topology optimization at both scales is formulated according to a density based approach. The optimization results indicate that: (i) the topology of the micro structure strongly influences the device performance and the macro structure layout; (ii) the multi-scale design approach yields remarkable improvements compared to a standard mono-scale approach; (iii) the optimized micro-structural layout is slightly sensitive to changes in the operating conditions
CFD-based reduced model for the simulation of thermocline thermal energy storage systems
Full text linkThermocline thermal storages are widely used in energy systems. Computational Fluid Dynamic (CFD) can be used for an accurate simulation of the physical phenomenon but its implementation in system-level annual simulations is hardly possible because of the huge computational time required. The present paper proposes a novel approach for the utilization of CFD simulation results in system-level annual simulations and optimizations. An analytical function able to represent the dimensionless vertical temperature profile inside the tank is parameterized statistically using the results of multiple simulations of a CFD model, which have been previously validated with experimental data. The reduced model obtained is then compared to other CFD simulations under highly variable conditions, showing a satisfactory degree of agreement (the mean absolute error and the error standard deviation are calculated to be 1.52 K and 1.93 K respectively). Furthermore, it is demonstrated that this approach can be conveniently adopted for the modeling of a wide range of systems with a single tank thermal energy storage, from Concentrated Solar Power to District Heating
Techno-economic optimization of Concentrated Solar Power plants with thermocline thermal energy storage and integrated steam generator
No full textThe utilization of molten salts as the Heat Transfer Fluid (HTF) in Concentrated Solar Power (CSP) allows to increase the maximum operational temperature of parabolic trough power plants, with a substantial gain in the power cycle efficiency. ENEA has recently tested a way to further ameliorate this concept by introducing a single-tank configuration of the storage system with an integrated steam generator, which can dramatically reduce the total investment cost and simplify the power plant layout. In this paper we propose to couple this system to a waste-heat recovery unit for the cogeneration of power, heating and cooling, which has the potential to extend the range of applications of CSP plants to small-size systems and to regions with a moderate solar resource. In this paper, a techno-economic analysis is implemented to investigate the feasibility of this innovative technological pathway, to determine the optimal design of a representative 1 MWe plant located in Rome and to analyze its performances.Results reveal that the heat market brings a 28 % reduction of the Levelized Electricity Cost, allowing to reach the competitive value of 230.25
Centralized control of district heating networks during failure events using discrete adjoint sensitivities
Full text linkReal-time control of district heating networks in the case of failures requires for accurate and fast strategies able to guarantee thermal comfort to all connected users. In this paper, we demonstrate a control framework that responds to these essential requirements. We minimize a global measure of discomfort based on a smooth maximum approximation. The optimization problem is solved through a gradient-based algorithm that can be naturally integrated with distributed meter readings leading to high accuracy of both forward and sensitivity analysis. Objective function gradients are computed by a discrete adjoint method, which is fast and nearly insensitive to the dimensionality of the optimization problem. The proposed framework is tested with numerical experiments on a reference medium-size distribution network in Turin. Results show that the thermal comfort of most critical users increases quickly, yielding to a nearly homogeneous discomfort distribution at the end of the optimization process. Studying the effect of the inlet pressure head on the optimized system performance reveals that a centralized operation results in increased robustness of the network and allows reducing backup pumping equipment. Furthermore, applying the proposed framework at the distribution network level yields remarkable benefits also in case of failures in the main transportation network
Discrete Adjoint Sensitivities for the Real-Time Optimal Control of Large District Heating Networks During Failure Events
No full textIn this paper, we propose an innovative approach for the real-time optimal control of district heating networks during anomalous conditions. We aim at minimizing the maximum thermal discomfort of the connected users after a pipe breakage by an integrated and centralized management of the user control-valves. Our control strategy uses a gradient-based optimizer driven by discrete adjoint sensitivities, which makes it fast and nearly insensitive to the problem dimensions. We tested the proposed approach by simulating a set of different malfunctions in the Turin District heating network and by analyzing the building temperature field during the optimizer convergence history. Compared to the control strategy in use today, we observe that our approach flattens the temperature field and eliminates discomfort peaks, bringing a considerable increase of the minimum user temperature which ranges from a minimum of 1.8 °C to a maximum of 15.4 °C. Furthermore, our optimization strategy allows for superior results to what is achievable conventionally with an 85 % increase of the pumping head, making back-up pumping devices a non-necessary investment
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