Relevant bibliographies by topics / Energy modeling and optimization

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Energy modeling and optimization'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 February 2022

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Journal articles on the topic "Energy modeling and optimization"

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Tovar-Facio, Javier, Mariano Martín, and José María Ponce-Ortega. "Sustainable energy transition: modeling and optimization." Current Opinion in Chemical Engineering 31 (March 2021): 100661. http://dx.doi.org/10.1016/j.coche.2020.100661.

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Maleki, Akbar. "Modeling and optimization of energy systems." Journal of Thermal Analysis and Calorimetry 144, no. 5 (April 15, 2021): 1635–38. http://dx.doi.org/10.1007/s10973-021-10782-7.

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Xiao, Dong, Xiao-li Pan, Yong Yuan, Zhi-zhong Mao, and Fu-li Wang. "Modeling and optimization for piercing energy consumption." Journal of Iron and Steel Research International 16, no. 2 (February 2009): 40–44. http://dx.doi.org/10.1016/s1006-706x(09)60025-x.

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Vera, J., and F. Urbina. "Modeling the decentralized optimization of communicative energy." EPL (Europhysics Letters) 131, no. 6 (October 13, 2020): 68002. http://dx.doi.org/10.1209/0295-5075/131/68002.

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Evans, R. J., and P. D. Franzon. "Energy consumption modeling and optimization for SRAM's." IEEE Journal of Solid-State Circuits 30, no. 5 (May 1995): 571–79. http://dx.doi.org/10.1109/4.384170.

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Liu, Pei, Dimitrios I. Gerogiorgis, and Efstratios N. Pistikopoulos. "Modeling and optimization of polygeneration energy systems." Catalysis Today 127, no. 1-4 (September 30, 2007): 347–59. http://dx.doi.org/10.1016/j.cattod.2007.05.024.

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Kusiak, Andrew, Mingyang Li, and Fan Tang. "Modeling and optimization of HVAC energy consumption." Applied Energy 87, no. 10 (October 2010): 3092–102. http://dx.doi.org/10.1016/j.apenergy.2010.04.008.

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Yin, Yonghua. "OPTIMUM ENERGY FOR ENERGY PACKET NETWORKS." Probability in the Engineering and Informational Sciences 31, no. 4 (April 9, 2017): 516–39. http://dx.doi.org/10.1017/s0269964817000067.

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The concept of Energy Packet Network (EPN) proposed by Gelenbe, is a new framework for modeling power grids that takes distributed energy generation such as renewable energy sources into consideration, and which contributes to modeling the smart grid. Based on G-network theory, this paper presents a simplified model of EPN and formulates energy-distribution as an optimization problem. We analyze it theoretically, and detail its optimal solutions. In addition to using existing optimization algorithms, a heuristic algorithm is proposed to solve for EPN optimization. The optimal solutions and efficacy of the algorithm are illustrated with numerical experiments. Further, we present an EPN with disconnections and a similar optimization problem is investigated. Optimal solutions are presented, and numerical results using the analytic optimal solutions, random solutions, a cooperative particle swarm optimizer and a heuristic algorithm illustrate the power of different approaches for solving energy-distribution problems using the EPN formalism.
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Bansal, Manoj. "Optimization Modelling for Renewable Energy Resources based Distribution Generation." Revista Gestão Inovação e Tecnologias 11, no. 3 (June 30, 2021): 1510–19. http://dx.doi.org/10.47059/revistageintec.v11i3.2027.

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Bryan, Lisk, John Collett, and Robert Walters. "Smart Modeling for Water Distribution System Energy Optimization." Proceedings of the Water Environment Federation 2016, no. 10 (January 1, 2016): 3174–81. http://dx.doi.org/10.2175/193864716819707788.

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Dissertations / Theses on the topic "Energy modeling and optimization"

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Craft, David (David Loren) 1973. "Local energy management through mathematical modeling and optimization." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/28858.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2004.
Includes bibliographical references (p. 217-223).
(cont.) Extensions to the core TOTEM model include a demand charge model, used for making daily optimal control decisions when the electric bill includes a charge based on the monthly maximum power draw. The problem of heating, ventilation, and air conditioning (HVAC) control is treated separately since it strongly violates TOTEM's linearity assumptions. Nonetheless, we describe a solution approach to the HVAC problem which operates in conjunction with TOTEM. We also provide an analysis of storage suitability in stochastic supply and demand networks. The node-based approach lends itself well to a software system that uses a drag- and-drop graphical network creation tool. We present a graphical user interface, the XML data representation, and the communication links to and from optimization software.
We develop an extensive yet tractable framework for analyzing and optimally controlling local energy networks. A local energy network is any set of generation, storage, and end-use devices existing to provide energy fulfillment to a building, a group of jointly operated buildings, or a village power system. The software developed is called TOTEM for Total Energy Management, and provides hourly (or sub-hourly) control over the flows in such energy networks. TOTEM manages multiple energy flows such as electricity, chilled water, heat, and steam together, since such energies are often coupled, particularly for networks containing cogeneration turbines (which produce electricity and steam) and absorption chillers (which use steam for driving refrigeration turbines). Due to the large number of interconnected devices in such networks, the model is kept as a linear mixed integer program, able to be solved rapidly with off-the-shelf mathematical optimization packages. Certain nonlinearities, for example input-output relationships for generators, are handled in this linear framework with piecewise linear approximations. Modeling flexibility is achieved by taking a node-centric approach. Each device in the network is represented as a node, and depending on each node's set membership, proper constraint and objective equations are written. Given the network, TOTEM uses hourly electricity and fuel pricing, weather, and demand projections to determine the optimal operating and scheduling strategy for the day, in both deterministic and stochastic settings. MIT's cogeneration plant is used as a case study, with other examples throughout the thesis demonstrate the use of TOTEM for assessing and controlling renewable resources, storage options, and
by David Craft.
Ph.D.
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Xie, Liguang. "Modeling and Optimization of Rechargeable Sensor Networks." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/52243.

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Over the past fifteen years, advances in Micro-Electro-Mechanical Systems (MEMS) technology have enabled rapid development of wireless sensor networks (WSNs). A WSN consists of a large number of sensor nodes that are typically powered by batteries. Each sensor node collects useful information from its environment, and forwards this data to a base station through wireless communications. Applications of WSNs include environmental monitoring, industrial monitoring, agriculture, smart home monitoring, military surveillance, to name a few. Due to battery constraint at each sensor node, a fundamental challenge for a WSN is its limited operational lifetime -- the amount of time that the network can remain operational before some or all of the sensor nodes run out of battery. To conserve energy and prolong the lifetime of a WSN, there have been active research efforts across all network layers. Although these efforts help conserve energy usage and prolong network lifetime to some extent, energy and lifetime remain fundamental bottlenecks and are the key factors that hinder the wide-scale deployment of WSNs. This dissertation addresses the energy problem of a WSN by exploiting a recent breakthrough in wireless energy transfer (WET) technology. This breakthrough WET technology is based on the so-called magnetic resonant coupling (MRC), which allows electric energy to be transferred from a source coil to a receive coil without any plugs or wires. The advantages of MRC are high energy transfer efficiency even under omni-direction, not requiring line-of-sight (LOS), and being robust against environmental conditions. Inspired by this enabling WET technology, this dissertation focuses on applying MRC to a WSN and on studying how to optimally use this technology to address lifetime problem for a WSN. The goal is to fundamentally remove lifetime bottleneck for a WSN. The main contributions of this dissertation are summarized as follows: 1. Single-node Charging for a Sparse WSN. We first investigate how MRC can be applied to a WSN so as to remove the lifetime performance bottleneck in a WSN, i.e., allowing a WSN to remain operational forever. We consider the scenario of a mobile wireless charging vehicle (WCV) periodically traveling inside the sensor network and charging each sensor node's battery wirelessly. We introduce the concept of renewable energy cycle and offer both necessary and sufficient conditions for a sensor node to maintain its renewable energy cycle. We study an optimization problem, with the objective of maximizing the ratio of the WCV's vacation time over the cycle time. For this problem, we prove that the optimal traveling path for the WCV is the shortest Hamiltonian cycle and uncover a number of important properties. Subsequently, we develop a near-optimal solution by a piecewise linear approximation technique and prove its performance guarantee. This first study shows that network lifetime bottleneck can be fundamentally resolved by WET. 2. Multi-node Charging for a Dense WSN. We next exploit recent advances in MRC that allows multiple sensor nodes to be charged at the same time, and show how MRC with multi-node charging capability can address the scalability problem associated with the single-node charging technology. We consider a WCV that periodically travels inside a WSN and can charge multiple sensor nodes simultaneously. Based on the charging range of the WCV, we propose a cellular structure that partitions the two-dimensional plane into adjacent hexagonal cells. We pursue a formal optimization framework by jointly optimizing the traveling path of the WCV, flow routing among the sensor nodes, and the charging time with each hexagonal cell. By employing discretization and a novel Reformulation-Linearization Technique (RLT), we develop a provably near-optimal solution for any desired level of accuracy. Through numerical results, we demonstrate that our solution can indeed address the scalability problem for WET in a dense WSN. 3. Bundling Mobile Base Station and Wireless Energy Transfer: The Pre-planned Path Case. Our aforementioned work is based on the assumption that the location of base station is fixed and known in the WSN. On the other hand, it has been recognized that a mobile base station (MBS) can offer significant advantages over a fixed one. But employing two separate vehicles, one for WET and one for MBS, could be expensive and hard to manage. So a natural question to ask is: can we bundle WET and MBS on the same vehicle? This is the focus of this study. Here, our goal is to minimize energy consumption of the entire system while ensuring that none of the sensor nodes runs out of energy. To simplify the problem, we assume that the path for the vehicle is given a priori. We develop a mathematical model for this problem. Instead of studying the general problem formulation (called CoP-t), which is time-dependent, we show that it is sufficient to study a special subproblem (called CoP-s), which only involves space-dependent variables. Subsequently, we develop a provable near-optimal solution to CoP-s with the development of several novel techniques including discretizing a continuous path into a finite number of segments and representing each segment with worst-case energy bounds. 4. Bundling Mobile Base Station and Wireless Energy Transfer: The Unconstrained Path Case. Based on our experience for the pre-planned path case, we further study the problem where the traveling path of the WCV (also carrying the MBS) can be unconstrained. That is, we study an optimization problem that jointly optimizes the traveling path, stopping points, charging schedule, and flow routing. For this problem, we propose a two-step solution. First, we study an idealized problem that assumes zero traveling time, and develop a provably near-optimal solution to this idealized problem. In the second step, we show how to develop a practical solution with non-zero traveling time and quantify the performance gap between this solution and the unknown optimal solution to the original problem. This dissertation offers the first systematic investigation on how WET (in particular, the MRC technology) can be exploited to address lifetime bottleneck of a WSN. It lays the foundation of exploring WET for WSNs and other energy-constrained wireless networks. On the mathematical side, we have developed or applied a number of powerful techniques such as piecewise linear approximation, RLT, time-space transformation, discretization, and logical point representation that may be applicable to address a broad class of optimization problems in wireless networks. We expect that this dissertation will open up new research directions on many interesting networking problems that can take advantage of the WET technology.
Ph. D.
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Geidl, Martin. "Integrated modeling and optimization of multi-carrier energy systems /." Zürich : ETH, 2007. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=17141.

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Ari, Seckin. "Intelligent modeling of individual thermal comfort and energy optimization." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2009. http://wwwlib.umi.com/cr/syr/main.

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Yaoumi, Mohamed. "Energy modeling and optimization of protograph-based LDPC codes." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2020. http://www.theses.fr/2020IMTA0224.

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Il existe différents types de codes correcteur d’erreurs (CCE), chacun offrant différents compromis entre la performance et la consommation d’énergie. Nous proposons de traiter ce problème pour les codes LDPC (Low-Density Parity Check). Dans ce travail, nous avons considéré les codes LDPC construits à partir de protographes avec un décodeur Min-Sum quantifié, pour leurs bonnes performances et leur implémentation matérielle efficace. Nous avons utilisé une méthode basée sur l’évolution de densité pour évaluer les performances à longueur finie du décodeur pour un protographe donné. Ensuite, nous avons introduit deux modèles pour estimer la consommation d’énergie du décodeur Min-Sum quantifié. A partir de ces modèles, nous avons développé une méthode d’optimisation afin de sélectionner des protographes qui minimisent la consommation d’énergie du décodeur tout en satisfaisant un critère de performance donné.Dans la seconde partie de la thèse, nous avons considéré un décodeur LDPC bruité, et nous avons supposé que le circuit introduit des défauts dans les unités de mémoire utilisées par le décodeur. Nous avons ensuite mis à jour le modèle d’énergie de la mémoire afin de prendre en compte le bruit dans le décodeur. Par conséquent, nous avons proposé une méthode alternative afin d’optimiser les paramètres du modèle et minimiser la consommation d’énergie du décodeur pour un protographe donné
There are different types of error correction codes (CCE), each of which gives different trade-offs interms of decoding performanceand energy consumption. We propose to deal with this problem for Low-Density Parity Check (LDPC) codes. In this work, we considered LDPC codes constructed from protographs together with a quantized Min-Sum decoder, for their good performance and efficient hardware implementation. We used a method based on Density Evolution to evaluate the finite-length performance of the decoder for a given protograph.Then, we introduced two models to estimate the energy consumption of the quantized Min-Sum decoder. From these models, we developed an optimization method in order to select protographs that minimize the decoder energy consumption while satisfying a given performance criterion. The proposed optimization method was based on a genetic algorithm called differential evolution. In the second part of the thesis, we considered a faulty LDPC decoder, and we assumed that the circuit introduces some faults in the memory units used by the decoder. We then updated the memory energy model so as to take into account the noise in the decoder. Therefore, we proposed an alternate method in order to optimize the model parameters so as to minimize the decoder energy consumption for a given protograph
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Angulo, Ignacio. "Harvester Energy Modelling and Optimization." Thesis, KTH, Maskinkonstruktion (Inst.), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-192131.

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Denna rapport är resultatet av ett examensarbete på Kungliga Tekniska Högskolan i samarbete med Skogforsk. Syftet är att analysera den trädkapningsprocessen hos en skördare, optimera dess energiförbrukning och föreslå modifieringar av systemet. En analys av skördarhuvudets energiförbrukning genomfördes baserat på testdata från Skogforsk. Denna undersökning gav en inblick i prestandan hos hydraulmotorn Parker F11-19 vid kapnng av träd med varierande diameter, samt en kvantifiering av mängden energi som används av skördarhuvudets olika komponenter. Hydrauliska och mekaniska modeller av skördarhuvudet skapades med hjälp av simuleringsverktygen Hopsan och Simulink. Dessa modeller användes för att verifiera optimeringsförslagen. Resultatet av denna studie är fyra optimeringslösningar för ett skördarhuvud. Det första förslaget är att använda en ackumulator för kinetisk energiåtervinning i matningsrullarna, vilket kommer att bidra med en minskning av energiförbrukningen med 6.85%. Det andra förslaget är att optimera sågcylinderns position, vilket kommer leda till en reduktion med 0%, dvs aktuell position bedöms vara optimal. Det tredje förslaget är förändring av kvistknivarnas utformning, vilket minskar energiförbrukningen med 2.72%. Det fjärde förslaget är att använda en alternativ motor som kräver mindre energi, vilket bidrar till en markant minskning av energiförbrukningen med 28.4%. Totalt kommer de föreslagna förändringarna att resultera i en reduktion av energiförbrukningen med 37.9%. Resultatet är teoretiskt och ytterligare fält- och riggprov är nödvändiga för att validera resultaten.
This report is the result of the Master of Science thesis project developed for KTH Royal Institute of Technology in collaboration with the Forestry Research Institute of Sweden (Skogforsk) for the Forestry Master Thesis School 2016. The purpose is to analyze the tree cutting process of a harvester machine, optimize the energy consumption and propose modifications to the system of components if applicable. A study on the energy usage of a harvester head was performed based on test data gathered by Skogforsk, providing insight about the performance of the hydraulic motor Parker F11-19 when cutting different tree diameters and quantifying the amount of energy used on each part of the harvester head. Hydraulic and mechanical models of the head were built using Hopsan and Simulink, respectively. These models were used for the verification of the optimizations proposed. The results from this research study are four optimization solutions for a harvester head. The first suggestion is to use an accumulator for kinetic energy recovery in the feeding rollers, which will contribute with a reduction in energy consumption of 6.85%. The second suggestion is to optimize the saw’s cylinder position, which did not provide any improvements. The third suggestion is a redesign of the delimbing knives, which will reduce the energy consumption with 2.72%. And the final suggestion is to use an alternative motor that requires less power, which will result in a significant decrease of energy consumption by 28.4%. In total, the changes suggested will result in a reduction of the energy consumption by 37.9%. The results are theoretical and further testing in practice is needed in order to assess the veracity of the results.
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Calle, Laguna Alvaro Jesus. "Isolated Traffic Signal Optimization Considering Delay, Energy, and Environmental Impacts." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/74238.

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Traffic signal cycle lengths are traditionally optimized to minimize vehicle delay at intersections using the Webster formulation. This thesis includes two studies that develop new formulations to compute the optimum cycle length of isolated intersections, considering measures of effectiveness such as vehicle delay, fuel consumption and tailpipe emissions. Additionally, both studies validate the Webster model against simulated data. The microscopic simulation software, INTEGRATION, was used to simulate two-phase and four-phase isolated intersections over a range of cycle lengths, traffic demand levels, and signal timing lost times. Intersection delay, fuel consumption levels, and emissions of hydrocarbon (HC), carbon monoxide (CO), oxides of nitrogen (NOx), and carbon dioxide (CO2) were derived from the simulation software. The cycle lengths that minimized the various measures of effectiveness were then used to develop the proposed formulations. The first research effort entailed recalibrating the Webster model to the simulated data to develop a new delay, fuel consumption, and emissions formulation. However, an additional intercept was incorporated to the new formulations to enhance the Webster model. The second research effort entailed updating the proposed model against four study intersections. To account for the stochastic and random nature of traffic, the simulations were then run with twenty random seeds per scenario. Both efforts noted its estimated cycle lengths to minimize fuel consumption and emissions were longer than cycle lengths optimized for vehicle delay only. Secondly, the simulation results manifested an overestimation in optimum cycle lengths derived from the Webster model for high vehicle demands.
Master of Science
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Mergulhao, Vasco. "Innovation and Optimization of Energy Systems in the Temporary Entertainment Events Industry : Modeling & Optimization of temporary energy systems." Thesis, KTH, Kraft- och värmeteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-263612.

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An unprecedented view into the nature of energy systems in the Temporary Entertainment Events Industry (TEEI) is developed. A characterization of the context of the latter and its energy systems state-of-the-art is performed. Allowing for the main development of the present study, the modeling of temporary energy systems in the TEEI, ultimately delivering a tool for the assessment of the performance of these systems at a level of analytical detail previously inexistent in the industry. In the absence of previews literature on the topic, state-of-the-art modeling techniques have been reviewed from the field of small-scale polygeneration system to develop a customized approach for the modeling of temporary energy systems. An Integrated Design, Synthesis and Operation Optimization (IDSOO) approach has been adapted in a Mixed Integer Linear Programing (MILP) model and contextualized for the TEEI. Additionally, a customized approach has been developed for the treatment and compression of the original energy demand curves in a separate optimization algorithm defined in respect to the constraints and priorities of the given context. The model has been developed to cater to the evaluation of the targets set by the Festival Vision 2025 pledge. Which is then applied in a case study event set in the United Kingdom (UK), with over 50 000 visitors over a period of 4 days. In addition to the evaluation of the pledge’s targets, two additional scenarios are created to better explore to full potential of the methodology presently developed. Namely, first an integrated system approach and its benefits has been evaluated to counterpose the established practice of isolating the event’s energy sub-systems. Secondly, the effects of the prevailing energy demand uncertainty in TEEI and its typical preference of overgenerous systems’ designs are analyzed in a hypothetical, yet representative, scenario. Finally, given the pioneering nature of the developed study, a listing has been made with the argued most relevant future study topics that were found to offer the highest benefits to the TEEI. In conclusion, it has been found that there seems to be more potential than previously thought for the improvement of the performance of the TEEI’s current energy systems. It is shown that even when optimized, isolated generator-based systems in some cases will inevitably incur into undesired operational conditions, thus demonstrating the limits of the current practices and technology selection. Nevertheless, it was found that, at least for the given case study, the Festival Vision 2025 medium term targets are achievable even when resorting solely to the optimization of the current diesel-based systems. Reinstating the need for better energy systems planning and designs. Ultimately, it was concluded that the developed model fulfills the objective of representing the TEEIs energy systems to a level of detail unprecedented and that it, or similar tools, could be used to quantify and substantiate the implications of the industry’s environmental goals for its energy systems.
En ny syn på energisystem för tillfällig underhållning (TEEI) är under utveckling. En karaktärisering av sammanhanget för det senare och dess energisystem har varit fokus i denna studie. Utgående från utvecklingen av den aktuella studien, modellering av tillfälliga energisystem i TEEI, levereras ett verktyg för bedömning av prestandan hos dessa system på en nivå av analytisk detaljering som tidigare inte fanns i branschen. I avsaknad av tidigare litteratur om ämnet har state-of-the-art modelleringstekniker från området för småskaligt polygenerationssystem använts för att utveckla ett anpassat tillvägagångssätt för modellering av tillfälliga energisystem. En integrerad strategi för design, syntes och driftoptimering (IDSOO) har anpassats i en MILPmodell (Mixed Integer Linear Programing) och kontextualiserats för TEEI. Dessutom har ett anpassat tillvägagångssätt utvecklats för behandling och komprimering av mätningar av faktiska energibehov i en separat optimeringsalgoritm definierad med avseende på begränsningarna och prioriteringarna i det givna sammanhanget. Modellen har utvecklats för att tillgodose utvärderingen av de mål som fastställts av Festival Vision 2025- pantsättningen. Som sedan tillämpas i en fallstudiehändelse i Storbritannien (Storbritannien), med över 50 000 besökare under en period av fyra dagar. Förutom utvärderingen av de uppsatta målen skapas ytterligare två scenarier för att bättre utforska till den fulla potentialen för den för närvarande utvecklade metodiken. Först har en integrerad systemansats och dess fördelar utvärderats för att motverka den etablerade praxisen att isolera evenemangets energi-delsystem. För det andra analyseras effekterna av den rådande osäkerheten om energibehov i TEEI och dess typiska preferens för systemdesign med alltör generösa säkerhetsmarginaler i ett hypotetiskt men ändå representativt scenario. Slutligen, med tanke på studiens banbrytande karaktär, har en lista gjorts med de mest relevanta framtida studieämnen som visat sig ge de främsta fördelarna för TEEI. Sammanfattningsvis har det visat sig att det verkar finnas mer potential än man tidigare trott för förbättring av prestandan i TEEI: s nuvarande energisystem. Det visas att även när optimerade och isolerade generatorbaserade system i vissa fall oundvikligen kommer att drabbas av oönskade driftsförhållanden och därmed demonstreras gränserna för den nuvarande praxisen och teknikvalet. Trots det konstaterades att, åtminstone för den givna fallstudien, Festival Vision 2025 målsättningarna på medellång sikt kan uppnås även om man endast använder sig av optimeringen av de nuvarande dieselbaserade systemen, vilket återinför behovet av bättre planering och design av energisystem. I slutändan drogs slutsatsen att den utvecklade modellen uppfyller målet att representera TEEI: s energisystem till en ny detaljnivå och att den, eller liknande verktyg, skulle kunna användas för att kvantifiera och underbygga konsekvenserna av branschens miljömål för dess energisystem.
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DeLuca, Christopher. "Numerical Modeling and Optimization of Mechanically Active Electrochemical Systems." Thesis, University of Colorado at Boulder, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3592275.

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This work is primarily motivated by the hope that Silicon (Si) can be utilized in Lithium (Li) ion batteries to enable an order of magnitude capacity increase if Li-Si systems can be better understood. In order to create a valuable tool that could be used to study a wide range of problem, pertinent physical models were implemented in an extended finite element method (XFEM) framework written in c++. One of the major contribution of this work goes to the battery modeling community, by generalizing several existing electrochemical-mechanical models which use a small deformation approximations so they can accommodate finite deformation. A general theory which can be used to guide the development of new finite element models is presented in detail. This work also contributes new finite element modeling tools with novel predictive capabilities to the battery modeling community, which will hopefully facilitate the design and optimization of next generation battery micro-structures. Studies within demonstrate that small deformation approximation models can produce incorrect predictions about the behavior of Li-Si systems, supporting the case for using finite deformation models. The developed tools are used to demonstrate that arbitrary geometries can easily be simulated on a the same fixed grid, facilitating automated geometry studies including parameter sweeping and topology optimization.

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Bao, Wenlei. "Compiler Techniques for Transformation Verification, Energy Efficiency and Cache Modeling." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1524073563586939.

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Books on the topic "Energy modeling and optimization"

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Wei, Wei, and Jianhui Wang. Modeling and Optimization of Interdependent Energy Infrastructures. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-25958-7.

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Şahin, Arzu Şencan. Modeling and optimization of renewable energy systems. Rijeka: InTech, 2012.

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Knopf, F. Carl. Modeling, Analysis and Optimization of Process and Energy Systems. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118121160.

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Athienitis, Andreas, and William O'Brien, eds. Modeling, Design, and Optimization of Net-Zero Energy Buildings. Berlin, Germany: Wilhelm Ernst & Sohn, 2015. http://dx.doi.org/10.1002/9783433604625.

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Modeling, analysis, and optimization of process and energy systems. Hoboken, N.J: Wiley, 2012.

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Spreemann, Dirk. Electromagnetic Vibration Energy Harvesting Devices: Architectures, Design, Modeling and Optimization. Dordrecht: Springer Netherlands, 2012.

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Guzzella, Lino. Vehicle Propulsion Systems: Introduction to Modeling and Optimization. 3rd ed. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Optimization modeling with spreadsheets. 2nd ed. Hoboken, NJ: Wiley, 2011.

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Yao, David D., Xun Yu Zhou, and Hanqin Zhang. Stochastic Modeling and Optimization. New York, NY: Springer New York, 2003. http://dx.doi.org/10.1007/978-0-387-21757-4.

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Pötzsche, Christian, Clemens Heuberger, Barbara Kaltenbacher, and Franz Rendl, eds. System Modeling and Optimization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-45504-3.

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Book chapters on the topic "Energy modeling and optimization"

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Sanz, Abel, Ana Susmozas, Jens Peters, and Javier Dufour. "Biorefinery Modeling and Optimization." In Lecture Notes in Energy, 123–60. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-48288-0_6.

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Gabriel, Steven A., Antonio J. Conejo, J. David Fuller, Benjamin F. Hobbs, and Carlos Ruiz. "Optimization Problems Constrained by Complementarity and Other Optimization Problems." In Complementarity Modeling in Energy Markets, 221–62. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-6123-5_6.

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Soroudi, Alireza. "Energy System Integration." In Power System Optimization Modeling in GAMS, 265–92. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62350-4_10.

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Soroudi, Alireza. "Energy Storage Systems." In Power System Optimization Modeling in GAMS, 175–201. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62350-4_7.

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Liao, Wenhe, Hao Liu, and Tao Li. "Energy Optimization Method and Subdivision Surfaces." In Subdivision Surface Modeling Technology, 167–95. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3515-9_6.

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Nwulu, Nnamdi, and Saheed Lekan Gbadamosi. "Mathematical Optimization Modeling and Solution Approaches." In Green Energy and Technology, 37–61. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-00395-1_3.

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Mahoney, Daniel. "Valuation, Portfolios, and Optimization." In Modeling and Valuation of Energy Structures, 48–117. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/9781137560155_3.

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Sai Kaushik, A., and Satya Sekhar Bhogilla. "Solar-Driven Potassium Formate Liquid Desiccant Dehumidification System with Thermal Energy Storage." In Modeling, Simulation and Optimization, 737–50. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9829-6_58.

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Rajput, Isha, Jyoti Verma, and Hemant Ahuja. "Controller Design for Dynamic Stability and Performance Enhancement of Renewable Energy Systems." In Modeling, Simulation and Optimization, 657–69. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9829-6_52.

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Ziębik, Andrzej, and Krzysztof Hoinka. "Mathematical Modeling and Optimization of Energy Systems." In Green Energy and Technology, 29–58. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4381-9_3.

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Conference papers on the topic "Energy modeling and optimization"

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Saadon, Salem, and Othman Sidek. "Ambient vibration-based MEMS piezoelectric energy harvester for green energy source." In 2011 Fourth International Conference on Modeling, Simulation and Applied Optimization (ICMSAO). IEEE, 2011. http://dx.doi.org/10.1109/icmsao.2011.5775554.

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Komali, Ramakant S., and Allen B. MacKenzie. "Impact of Selfish Packet Forwarding on Energy-Efficient Topology Control." In 6th International ICST Symposium on Modeling and Optimization. IEEE, 2008. http://dx.doi.org/10.4108/icst.wiopt2008.3160.

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Pedersen, Morten V., Gian Paolo Perrucci, Frank H. P. Fitzek, and Torben Larsen. "Energy and Link Measurements for Mobile Phones using IEEE802.11b/g." In 6th International ICST Symposium on Modeling and Optimization. IEEE, 2008. http://dx.doi.org/10.4108/icst.wiopt2008.3262.

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Qian, Yulin, Yang Zhang, Yuanhe Tang, and Pengfei Ye. "Mathematical modeling and control optimization for energy internet." In 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2017. http://dx.doi.org/10.1109/ei2.2017.8245325.

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Shuman, David, and Mingyan Liu. "Energy-Efficient Transmission Scheduling for Wireless Media Streaming with Strict Underflow Constraints." In 6th International ICST Symposium on Modeling and Optimization. IEEE, 2008. http://dx.doi.org/10.4108/icst.wiopt2008.3198.

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Rana, Bhumika K., Sudhir P. Dabke, Swapan Paruya, Samarjit Kar, and Suchismita Roy. "Molecular Model and Helmholtz Energy Contribution for Association Effects in SAFT." In INTERNATIONAL CONFERENCE ON MODELING, OPTIMIZATION, AND COMPUTING (ICMOS 20110). AIP, 2010. http://dx.doi.org/10.1063/1.3516295.

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Biswas, Aritra, B. L. Deekshatulu, Shibendu Shekhar Roy, Swapan Paruya, Samarjit Kar, and Suchismita Roy. "Energy Optimal Trajectory Planning of a Robotic Manipulator Using Genetic Algorithm." In INTERNATIONAL CONFERENCE ON MODELING, OPTIMIZATION, AND COMPUTING (ICMOS 20110). AIP, 2010. http://dx.doi.org/10.1063/1.3516354.

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Sarkar, Sabuj, and Mostafizur Rahman. "Power-Energy Optimization of Solar Photovoltaic Device Modeling." In 2018 IEEE Electron Devices Kolkata Conference (EDKCON). IEEE, 2018. http://dx.doi.org/10.1109/edkcon.2018.8770431.

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Dietmair, Anton, and Alexander Verl. "Energy consumption modeling and optimization for production machines." In 2008 IEEE International Conference on Sustainable Energy Technologies (ICSET). IEEE, 2008. http://dx.doi.org/10.1109/icset.2008.4747073.

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Kolekar, Nitin, Suchi Subhra Mukherji, and Arindam Banerjee. "Numerical Modeling and Optimization of Hydrokinetic Turbine." In ASME 2011 5th International Conference on Energy Sustainability. ASMEDC, 2011. http://dx.doi.org/10.1115/es2011-54252.

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Hydrokinetic turbines, unlike conventional hydraulic turbines are zero head energy conversion devices which utilize the kinetic energy of flowing water for power generation. The basic operational principle of the horizontal axis hydrokinetic turbine (HAHkT) is same as the wind turbine, the only difference being change in working media: water instead of air. This paper discusses the hydrodynamic design of HAHkT via numerical modeling. Presently these turbines suffer from low coefficient of performance (Cp) which is governed by several design variables such as tip-speed ratio, chord distribution, solidity and number of blades. The numerical modeling is performed for both constant and varying chord geometries using commercially available computational fluid dynamics software (CFX/FLUENT) to understand the effect of each of the design variable on turbine performance. Since the flow Reynolds number is large (≥ 105), both one- and two-equation turbulence models are applied to solve Reynolds Averaged Navier Stokes equations. In addition, a three dimensional analysis of HAHkT is performed to give a better insight into the effect of tip vortices and flow separation phenomenon on turbine performance; the results are then compared with Blade Element Momentum (BEM) theory analysis. In addition, a procedure for a multivariate optimization scheme is discussed that aims at maximizing Cp for a constant flow velocity while maintaining optimum values of critical design variables listed above. Finally, the effect of variation of angle of attack on the flow around a hydrofoil is investigate using both static and transient analysis, the transient analysis being performed by subjecting the airfoil to periodic oscillations.
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Reports on the topic "Energy modeling and optimization"

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Pulay, Peter, and Jon Baker. Efficient Modeling of Large Molecules: Geometry Optimization Dynamics and Correlation Energy. Fort Belvoir, VA: Defense Technical Information Center, April 2003. http://dx.doi.org/10.21236/ada416248.

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Zuo, Wangda, Michael Wetter, James VanGilder, Xu Han, Yangyang Fu, Cary Faulkner, Jianjun Hu, Wei Tian, and Michael Condor. Improving Data Center Energy Efficiency Through End-to-End Cooling Modeling and Optimization. Office of Scientific and Technical Information (OSTI), April 2021. http://dx.doi.org/10.2172/1773506.

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Baker, Justin S., George Van Houtven, Yongxia Cai, Fekadu Moreda, Chris Wade, Candise Henry, Jennifer Hoponick Redmon, and A. J. Kondash. A Hydro-Economic Methodology for the Food-Energy-Water Nexus: Valuation and Optimization of Water Resources. RTI Press, May 2021. http://dx.doi.org/10.3768/rtipress.2021.mr.0044.2105.

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Growing global water stress caused by the combined effects of growing populations, increasing economic development, and climate change elevates the importance of managing and allocating water resources in ways that are economically efficient and that account for interdependencies between food production, energy generation, and water networks—often referred to as the “food-energy-water (FEW) nexus.” To support these objectives, this report outlines a replicable hydro-economic methodology for assessing the value of water resources in alternative uses across the FEW nexus–including for agriculture, energy production, and human consumption—and maximizing the benefits of these resources through optimization analysis. The report’s goal is to define the core elements of an integrated systems-based modeling approach that is generalizable, flexible, and geographically portable for a range of FEW nexus applications. The report includes a detailed conceptual framework for assessing the economic value of water across the FEW nexus and a modeling framework that explicitly represents the connections and feedbacks between hydrologic systems (e.g., river and stream networks) and economic systems (e.g., food and energy production). The modeling components are described with examples from existing studies and applications. The report concludes with a discussion of current limitations and potential extensions of the hydro-economic methodology.
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Howard, Heidi, Chad Helmle, Raina Dwivedi, and Daniel Gambill. Stormwater Management and Optimization Toolbox. Engineer Research and Development Center (U.S.), January 2021. http://dx.doi.org/10.21079/11681/39480.

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As stormwater regulations for hydrologic and water quality control become increasingly stringent, Department of Defense (DoD) facilities are faced with the daunting task of complying with multiple laws and regulations. This often requires facilities to plan, design, and implement structural best management practices (BMPs) to capture, filter, and/or infiltrate runoff—requirements that can be complicated, contradictory, and difficult to plan. This project demonstrated the Stormwater Management Optimization Toolbox (SMOT), a spreadsheet-based tool that effectively analyzes and plans for compliance to the Energy Independence and Security Act (EISA) of 2007 pre-hydrologic conditions through BMP implementation, resulting in potential cost savings by reducing BMP sizes while simultaneously achieving compliance with multiple objectives. SMOT identifies the most cost-effective modeling method based on an installation’s local conditions (soils, rainfall patterns, drainage network, and regulatory requirements). The work first demonstrated that the Model Selection Tool (MST) recommendation accurately results in the minimum BMP cost for 45 facilities of widely varying climatic and regional conditions, and then demonstrated SMOT at two facilities.
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Brigantic, Robert T., Anthony F. Papatyi, and Casey J. Perkins. Comprehensive Energy Assessment: EE and RE Project Optimization Modeling for United States Pacific Command (USPACOM) American Recovery and Reinvestment Act (ARRA) FEMP Technical Assistance. Office of Scientific and Technical Information (OSTI), September 2010. http://dx.doi.org/10.2172/1000152.

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Morton, David P., Richard E. Rosenthal, and Lim T. Weng. Optimization Modeling for Airlift Mobility. Fort Belvoir, VA: Defense Technical Information Center, September 1995. http://dx.doi.org/10.21236/ada299818.

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Luccio A. U., R. Gupta, W. W. MacKay, and T. Roser. Cold AGS Snake Optimization by Modeling. Office of Scientific and Technical Information (OSTI), December 2003. http://dx.doi.org/10.2172/1061721.

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Peles, S. Open source Modeling and optimization tools for Planning. Office of Scientific and Technical Information (OSTI), February 2017. http://dx.doi.org/10.2172/1343841.

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Eskow, Elizabeth, and Robert B. Schnabel. Mathematical Modeling of a Parallel Global Optimization Algorithm. Fort Belvoir, VA: Defense Technical Information Center, April 1988. http://dx.doi.org/10.21236/ada446514.

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Beaman, Joseph J. Computer Modeling and Optimization of OBOGS with Contaminants. Fort Belvoir, VA: Defense Technical Information Center, October 1986. http://dx.doi.org/10.21236/ada178038.

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