Gotowa bibliografia na temat „Multi-energy system (LMES)”

SUMMARYThis paper reports an extended state observer (ESO)-based robust dynamic surface control (DSC) method for triaxial MEMS gyroscope applications. An ESO with non-linear gain function is designed to estimate both velocity and disturbance vectors of the gyroscope dynamics via measured position signals. Using the sector-bounded property of the non-linear gain function, the design of an $\mathcal{L}_2$-robust ESO is phrased as a convex optimization problem in terms of linear matrix inequalities (LMIs). Next, by using the estimated velocity and disturbance, a certainty equivalence tracking controller is designed based on DSC. To achieve an improved robustness and to remove static steady-state tracking errors, new non-linear integral error surfaces are incorporated into the DSC. Based on the energy-to-peak ($\mathcal{L}_2$-$\mathcal{L}_\infty$) performance criterion, a finite number of LMIs are derived to obtain the DSC gains. In order to prevent amplification of the measurement noise in the DSC error dynamics, a multi-objective convex optimization problem, which guarantees a prescribed $\mathcal{L}_2$-$\mathcal{L}_\infty$ performance bound, is considered. Finally, the efficacy of the proposed control method is illustrated by detailed software simulations.

Acidiphilium multivorum LMS is an acidophile isolated from industrial bioreactors during the processing of the gold-bearing pyrite-arsenopyrite concentrate at 38–42 °C. Most strains of this species are obligate organoheterotrophs that do not use ferrous iron or reduced sulfur compounds as energy sources. However, the LMS strain was identified as one of the predominant sulfur oxidizers in acidophilic microbial consortia. In addition to efficient growth under strictly heterotrophic conditions, the LMS strain proved to be an active sulfur oxidizer both in the presence or absence of organic compounds. Interestingly, Ac. multivorum LMS was able to succeed more common sulfur oxidizers in microbial populations, which indicated a previously underestimated role of this bacterium in industrial bioleaching operations. In this study, the first draft genome of the sulfur-oxidizing Ac. multivorum was sequenced and annotated. Based on the functional genome characterization, sulfur metabolism pathways were reconstructed. The LMS strain possessed a complicated multi-enzyme system to oxidize elemental sulfur, thiosulfate, sulfide, and sulfite to sulfate as the final product. Altogether, the phenotypic description and genome analysis unraveled a crucial role of Ac. multivorum in some biomining processes and revealed unique strain-specific characteristics, including the ars genes conferring arsenic resistance, which are similar to those of phylogenetically distinct microorganisms.

AbstractAlthough Li‐metal has been revisited as the most attractive anode in building high‐energy‐density batteries owing to its superiority, such as ultimate theoretical capacity and lowest working voltage, notorious Li dendrite growth has plagued its practical uses. Since dendritic Li electroplating is mostly caused by poor Li+ transport and inferior stability of solid‐electrolyte interphase (SEI), an innovative reframing of the electrolyte is crucial to the success of Li‐metal anodes (LMAs). This review presents a new class of electrolytes, nano‐colloidal electrolytes (NCEs), providing a new avenue for next‐generation Li‐metal batteries (LMBs). Without searching for new salts/solvents or their compositional tuning, NCEs exploiting multi‐functional nanoparticles dispersed in liquid electrolytes can promote Li+ transport and reinforce the SEI of liquid electrolytes that are solely used. This review discusses various types of nanoparticles and their key roles in demonstrating excellent suppression of Li dendrite growth and enhancing the cycling stability of LMBs. Unraveling the underlying design principles of NCEs offers practical solutions for stabilizing LMAs, paving the way for developing intelligent battery systems.

Au cours des dernières décennies, l'industrie énergétique s'est efforcée d'améliorer l'efficacité de la production d'énergie, de réduire les émissions de gaz à effet de serre liées à la production et à la distribution d'énergie et de mieux intégrer les ressources énergétiques renouvelables. Les systèmes multi-énergies locaux (LMES) constituent une alternative intéressante pour atteindre ces objectifs ambitieux. Fondamentalement, un LMES est un système énergétique décentralisé produisant de l'énergie sous de multiples formes pour satisfaire les besoins énergétiques de clients situés dans son voisinage. Les clients correspondent à un ensemble de bâtiments appartenant, par exemple, à un campus, un complexe hospitalier ou un quartier urbain. Les LMES ont une efficacité de production plus élevée et un coût de maintenance plus faible que les systèmes énergétiques fonctionnant au niveau d'un seul bâtiment. La conception d'un LMES consiste à sélectionner les dispositifs de conversion et de stockage de l'énergie du système. Le LMES obtenu doit être capable de satisfaire à tout moment la demande énergétique fluctuante et de minimiser le coût total de construction et d'opération du système sur sa durée de vie, qui s'étend sur plusieurs décennies. Il existe déjà de nombreux outils numériques pour concevoir des LMES. Cependant, la plupart de ces outils reposent sur des hypothèses et des simplifications importantes. Par exemple, la capacité d'un dispositif de conversion peut prendre des valeurs dans une gamme continue prédéfinie, alors que cette capacité devrait en fait être sélectionnée dans une liste discrète des modèles disponibles produits par les fabricants d'équipements. De plus, ces outils limitent généralement fortement la taille des instances considérées afin de pouvoir proposer des solutions dans un temps de calcul acceptable. Cette thèse de doctorat se concentre sur le problème de la conception optimale d'un LMES impliquant à la fois des dispositifs de conversion et de stockage d'énergie. En termes de modélisation, nous améliorons l'état de l'art dans plusieurs directions. Premièrement, nous choisissons la capacité des dispositifs installés dans une liste de valeurs discrètes prédéfinies. Deuxièmement, nous considérons le fait que la construction d'un LMES est un processus en plusieurs étapes dans lequel les décisions d'investissement sont prises petit à petit pour ajuster le déploiement du système à l'augmentation à long terme de la demande d'énergie. Nous cherchons donc à construire un plan de déploiement en plusieurs phases. Troisièmement, nous incorporons dans la fonction objectif le coût d'opération du système sur sa durée de vie. Pour estimer ce coût précisément, nous construisons des plannings d'opération journaliers aux pas de temps horaires pour un ensemble de jours représentatifs. Ces plannings tiennent compte de plusieurs caractéristiques réalistes compliquées telles que l'efficacité à charge partielle et la charge minimale des dispositifs de conversion. Le problème d'optimisation est formulé comme un très grand programme linéaire à nombres entiers mixtes. Nous développons deux nouveaux algorithmes de décomposition qui exploitent la structure spécifique à deux niveaux du problème. Le premier algorithme étend un algorithme de décomposition hiérarchique précédemment publié, le second est un algorithme de décomposition de Benders généralisé. L'approche de modélisation et de résolution proposée sont appliquées à trois cas d'étude réels situés en Chine. Nos résultats numériques montrent que les algorithmes de décomposition proposés sont plus performants que l'algorithme générique de branch-and-cut intégré à un solveur de programmation mathématique et que l'algorithme original de décomposition hiérarchique pour résoudre le programme linéaire en nombres entiers à l'optimalité. Même si certaines approximations sont effectuées dans la modélisation du problème, les plans de déploiement obtenus sont de très bonne qualité
Over the last decades, the energy industry has been striving to improve the energy production efficiency, to lower the greenhouse gas emissions related to energy production and distribution and to better integrate renewable energy resources. Local multi-energy systems (LMESs) are an interesting alternative to meet these challenging objectives. Basically, an LMES is a decentralized energy system producing energy within multiple forms to satisfy the energy needs of customers located in its vicinity. The customers correspond to a set of buildings belonging e.g. to a university campus, a hospital complex or a city district. LMESs have a higher production efficiency and a lower maintenance cost than traditional individual (i.e., single-building) energy systems. LMESs thus display many practical advantages. However, in order to provide their best potential performance, they should be carefully designed. Designing an LMES essentially consists in selecting the energy conversion and storage devices making up the system. The obtained LMES should be able to satisfy the fluctuating energy demand at all time and to minimize the total construction and operation cost of the system over its lifetime usually spanning several decades. Many off-the-shelf numerical decision-aid tools already exist to assist people in the design of LMESs. However, most of these tools rely on strong assumptions and simplifications. For example, they assume that the capacity of an energy conversion device may take any value within a predefined continuous range, while this capacity should in fact be selected within a discrete list of values corresponding to the available models produced by equipment manufacturers. Moreover, these tools usually strongly limit the size of the considered instances to enable the resolution process to terminate within an acceptable computation time. This PhD thesis focuses on the problem of optimally designing an LMES involving both energy conversion and storage devices. In terms of problem modelling, we improve the current state-of-the art in several directions. First, we allow to choose the capacity of the installed devices within a predefined discrete list of value. Second, we consider the fact that building an LMES is not a one-step but rather a multi-step process in which investment decisions are made little by little to adjust the system layout to the long-term increase of the energy demand. We thus seek to build a multi-phase strategic deployment plan for the LMES. Third, we incorporate in the objective function the operation cost of the system over its lifetime. To estimate this cost as accurately as possible, we build detailed daily operation schedules using hourly time steps for a set of representative days. These schedules take into account several realistic complicating features such as the partial load efficiency and the minimum working load of energy conversion devices. The resulting optimization problem is formulated as a very large mixed-integer linear program. To solve it efficiently, we develop two new decomposition algorithms exploiting the specific bi-level structure of the problem. The first algorithm extends a previously published hierarchical decomposition algorithm, the second one is a generalized Benders' decomposition algorithm. The proposed modelling and solving approach are applied to three real-life case studies located in China. Our numerical results first show that the proposed decomposition algorithms significantly outperform both the generic branch-and-cut algorithm embedded in a mathematical programming solver and the original hierarchical decomposition algorithm at solving the mixed-integer linear program to optimality. Our results also show that, even if some approximations are done in the problem modelling, the obtained deployment plans are of very good quality

Engine mounts need to satisfy three design requirements: (1) firmly support engine weight, (2) isolate structure from the engine’s noise and vibration, and (3) control engine motion when large shocks or engine resonances are present. In addition to these three criteria, which are common for designing all types of engine mounts (passive, semi-active, and active), two more design requirements need to be satisfied for active engine mounts. First, they should be designed such that if there is any malfunction with the actuator, the controller, or the sensors, the active engine mount should still safely operate as a passive mount. Second, the power consumption, the size and weight of the required actuator and its controller should be kept as low as possible. The current paper aims to present an active hydraulic (or fluid) engine mount design by using an electromagnetic actuator and capacitive circuit such that it is able to act as a passive mount, semi-active mount, and an active mount. In addition, the presented design has the capability to be converted to a damper as and when needed. The multi-functional capability of the proposed engine mount design (passive, semi-active, active, and damper) distinguishes the current design from the previously designed active engine mounting systems, and this multi-functional capability is explained in the paper. The proposed design consists of a conventional passive hydraulic (fluid) mount, an electromagnetic actuator (voice coil) and a capacitive circuit. The voice coil is placed in the lower chamber of the passive hydraulic mount and it can change the volumetric stiffness of the bottom chamber actively such that the engine mount has low dynamic stiffness in a wide range of frequencies. The capacitive circuit is paralleled with the voice coil and in situations when large shock inputs are present; it adds capacitance to the electromagnetic circuit and changes the characteristics of the mount from an isolator to a damper. Since the active engine mount design of this paper involves several energy domains, bond graph modeling technique is used for mathematical modeling. MATLAB simulation results are shown for an automotive application and the performance of the proposed active engine mount design is evaluated as an isolator and as a damper. Finally, an adaptive controller, based on Filtered-X LMS algorithm, is proposed and its performance is investigated. The proposed design can eliminate transmitted force from the engine to the structure in a frequency range of 15 Hz to 125 Hz.