Literatura científica selecionada sobre o tema "Multi-energy system (LMES)"
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Artigos de revistas sobre o assunto "Multi-energy system (LMES)"
Hosseini-Pishrobat, Mehran, e Jafar Keighobadi. "Extended state observer-based robust non-linear integral dynamic surface control for triaxial MEMS gyroscope". Robotica 37, n.º 3 (9 de novembro de 2018): 481–501. http://dx.doi.org/10.1017/s0263574718001133.
Texto completo da fontePanyushkina, Anna, Aleksandr Bulaev e Aleksandr V. Belyi. "Unraveling the Central Role of Sulfur-Oxidizing Acidiphilium multivorum LMS in Industrial Bioprocessing of Gold-Bearing Sulfide Concentrates". Microorganisms 9, n.º 5 (1 de maio de 2021): 984. http://dx.doi.org/10.3390/microorganisms9050984.
Texto completo da fonteLim, Minhong, Jiyeon Seo, Bokyung Choi, Beomjun Kim, Jiwon Lee, Sanghyun Park e Hongkyung Lee. "Intelligent Nano‐Colloidal Electrolytes for Stabilizing Lithium Metal Anodes: A Review". ChemElectroChem, 26 de janeiro de 2024. http://dx.doi.org/10.1002/celc.202300621.
Texto completo da fonteTeses / dissertações sobre o assunto "Multi-energy system (LMES)"
Liu, Bingqian. "Optimal design of local multi-energy systems : mixed-integer linear programming models and bi-level decomposition approaches". Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG046.
Texto completo da fonteOver 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
Trabalhos de conferências sobre o assunto "Multi-energy system (LMES)"
Vahdati, Nader, e Somayeh Heidari. "Development of an Electromagnetic Active Engine Mount". In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-53511.
Texto completo da fonte