This study derives the levelized cost of heat (LCOH) for exemplary post-fossil district heating (DH) scenarios. The DH system of Leipzig in 2040 under the assumption of a completely climate-neutral heat supply is considered. Accordingly, four generation scenarios (GS) are proposed based on different energy carriers that are characterized as follows: (1) natural gas with carbon capture and storage, (2) hydrogen, (3) diversified mix of biomass, waste heat and solar, and (4) electricity. In addition, the scenarios’ robustness toward commodity prices is investigated using a sensitivity analysis. A modeling environment was used to optimize the hourly economic dispatch. Based on this, levelized costs are determined. For the reference case, the LCOH of the GS 1 and 2 exceeds the LCOH of GS 3 and 4. Furthermore, the results indicate that relying on singular energy carriers as opposed to diversified generation portfolios leads to less robust LCOH regarding price sensitivities.

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The evolution and deployment of fifth-generation (5G) and beyond (B5G) infrastructure will require a tremendous effort to specify the design, standards, and manufacturing. 5G is vital to modern technological evolution, including industry 4.0, automotive, entertainment, and health care. The ambitious and challenging 5G project is classified into three categories, which provide an essential supporting platform for applications associated with: Enhanced mobile broadband (eMBB) Ultra-reliable low-latency communication (URLLC) Massive machine-type communication (mMTC) The demand for URLLC grows, particularly for applications like autonomous guided vehicles (AGVs), unmanned aerial vehicles (UAVs), and factory automation, and has a strict requirement of low latency of 1 ms and high reliability of 99.999%. To meet the needs of communication-sensitive and computation-intensive applications with different quality-of-service (QoS) requirements, this evolution focuses on ultra-dense edge networks with multi-access edge computing (MEC) facilities. MEC emerges as a solution, placing resourceful servers closer to users. However, the dynamic nature of processing and interaction patterns necessitates effective network control, which is challenging due to stringent requirements on both communication and computation. In this context, we introduce a novel approach to optimally manage task offloading, considering the intricacies of heterogeneous computing and communication services. Unlike existing methods, our methodology incorporates the number of admitted service migrations and QoS upper and lower bounds as binding constraints. The comprehensive model encompasses agent positions, MEC servers, QoS requirements, edge network communication, and server computing capabilities. Formulated as a mixed-integer linear program (MILP), it provides an optimal schedule for service migrations and bandwidth allocation, addressing the challenges posed by computation-intensive and communication-sensitive applications. Moreover, tailoring to an indoor robotics environment, we explore optimization-based approaches seeking an optimal system-level architecture while considering QoS guarantees. Optimization tools, e.g., ARCHEX, prove their ability to capture cyber-physical systems (CPS) requirements and generate correct-by-construction architectural solutions. We propose an extension in ARCHEX by incorporating dynamic properties, i.e., robot trajectories, time dimension, application-specific QoS constraints, and finally, integrating the optimization tool with a discrete-event network simulator (OMNeT++). This extension automates the generation of configuration files and facilitates result analysis, ensuring a comprehensive evaluation. This part of the work focuses on the dynamism of robots, server-to-service mapping, and the integration of automated simulation. The proposed extension is validated by optimizing and analyzing various indoor robotics scenarios, emphasizing critical performance parameters such as overall throughput and end-to-end delay (E2E). This integrated approach addresses the complex interplay of computation and communication resources, providing a solution for dynamic mobility, traffic, and application patterns in edge server environments.

Portfolio optimization is a crucial practice in finance aimed at maximizing the return while minimizing the risk through strategic asset allocation. This paper explores two distinct approaches to modeling robust portfolio optimization, comparing their efficacy in balancing the return and the risk. The first approach focuses on diversifying the portfolio by varying the number of stocks and sector allocation, while the second approach emphasizes minimizing risk by selecting stocks with low correlation. Theoretical foundations and mathematical formulations underpinning these approaches are discussed, incorporating concepts from Modern Portfolio Theory and Mixed Integer Linear Programming. Practical implementation involves data collection from Yahoo Finance API and computational analysis using Python and the optimization tool Gurobi. The results of these methodologies are evaluated, considering factors such as budget constraints, maximum and minimum investment limits, binary constraints, and correlation thresholds. The study concludes by discussing the implications of these findings and their relevance in contemporary financial decision-making processes.

通常已建立的指數基金，經過一段時間後其追蹤指數的效能已經無法滿足初期建購時的要求，此時管理者便面臨指數基金投資組合的調整問題。本論文融合建構指數基金的方法及最小化交易成本的概念，提出一個新的混合整數線性規劃模型以調整指數基金投資組合。模型亦考慮實務中交易成本、最小交易單位及批量、固定交易費用比率、以及資產總類數等限制。因此，模型包含整數變數及二元變數，求解也較為困難許多。本論文以啟發式演算法增進求解的效率，並以台灣50指數的相關資料做為實證研究的對象。 / The efficiency of index-tracking in index fund, which has been built, has usually been incapable to meet the needs after a period of time. In this moment, the managers have to face with the problems of the adjusting for index fund portfolio. In this paper, we integrate the methods of constructing index fund and the concepts of minimum transaction cost with it, and propose a new mixed integer linear program model to adjust the index fund portfolio. Moreover, the model also considers some limitations, such as the transaction costs, minimum transaction units and lots, fixed proportional transaction rates, and cardinality constraint in practical operating. For this reason, a set of integer variables and binary variables are introduced. However, they increase the computational complexity in model solution. Due to the difficulty of the MILP problem, a heuristic algorithm has been developed for the solution. The computational results are presented by applying the model to the Taiwan 50 index.

Modern traffic signal control systems have not changed significantly in the past 40-50 years. The most widely applied traffic signal control systems are still time-of-day, coordinated-actuated system, since many existing advanced adaptive signal control systems are too complicated and fathomless for most of people. Recent advances in communications standards and technologies provide the basis for significant improvements in traffic signal control capabilities. In the United States, the IntelliDriveSM program (originally called Vehicle Infrastructure Integration - VII) has identified 5.9GHz Digital Short Range Communications (DSRC) as the primary communications mode for vehicle-to-vehicle (v2v) and vehicle-to-infrastructure (v2i) safety based applications, denoted as v2x. The ability for vehicles and the infrastructure to communication information is a significant advance over the current system capability of point presence and passage detection that is used in traffic control systems. Given enriched data from IntelliDriveSM, the problem of traffic control can be solved in an innovative data-driven and mathematical way to produce robust and optimal outputs.In this doctoral research, three different problems within a v2x environment- "enhanced pseudo-lane-level vehicle positioning", "robust coordinated-actuated multiple priority control", and "multimodal platoon-based arterial traffic signal control", are addressed with statistical techniques and mathematical programming.First, a pseudo-lane-level GPS positioning system is proposed based on an IntelliDriveSM v2x environment. GPS errors can be categorized into common-mode errors and noncommon-mode errors, where common-mode errors can be mitigated by differential GPS (DGPS) but noncommon-mode cannot. Common-mode GPS errors are cancelled using differential corrections broadcast from the road-side equipment (RSE). With v2i communication, a high fidelity roadway layout map (called MAP in the SAE J2735 standard) and satellite pseudo-range corrections are broadcast by the RSE. To enhance and correct lane level positioning of a vehicle, a statistical process control approach is used to detect significant vehicle driving events such as turning at an intersection or lane-changing. Whenever a turn event is detected, a mathematical program is solved to estimate and update the GPS noncommon-mode errors. Overall the GPS errors are reduced by corrections to both common-mode and noncommon-mode errors.Second, an analytical mathematical model, a mixed-integer linear program (MILP), is developed to provide robust real-time multiple priority control, assuming penetration of IntelliDriveSM is limited to emergency vehicles and transit vehicles. This is believed to be the first mathematical formulation which accommodates advanced features of modern traffic controllers, such as green extension and vehicle actuations, to provide flexibility in implementation of optimal signal plans. Signal coordination between adjacent signals is addressed by virtual coordination requests which behave significantly different than the current coordination control in a coordinated-actuated controller. The proposed new coordination method can handle both priority and coordination together to reduce and balance delays for buses and automobiles with real-time optimized solutions.The robust multiple priority control problem was simplified as a polynomial cut problem with some reasonable assumptions and applied on a real-world intersection at Southern Ave. & 67 Ave. in Phoenix, AZ on February 22, 2010 and March 10, 2010. The roadside equipment (RSE) was installed in the traffic signal control cabinet and connected with a live traffic signal controller via Ethernet. With the support of Maricopa County's Regional Emergency Action Coordinating (REACT) team, three REACT vehicles were equipped with onboard equipments (OBE). Different priority scenarios were tested including concurrent requests, conflicting requests, and mixed requests. The experiments showed that the traffic controller was able to perform desirably under each scenario.Finally, a unified platoon-based mathematical formulation called PAMSCOD is presented to perform online arterial (network) traffic signal control while considering multiple travel modes in the IntelliDriveSM environment with high market penetration, including passenger vehicles. First, a hierarchical platoon recognition algorithm is proposed to identify platoons in real-time. This algorithm can output the number of platoons approaching each intersection. Second, a mixed-integer linear program (MILP) is solved to determine the future optimal signal plans based on the real-time platoon data (and the platoon request for service) and current traffic controller status. Deviating from the traditional common network cycle length, PAMSCOD aims to provide multi-modal dynamical progression (MDP) on the arterial based on the real-time platoon information. The integer feasible solution region is enhanced in order to reduce the solution times by assuming a first-come, first-serve discipline for the platoon requests on the same approach. Microscopic online simulation in VISSIM shows that PAMSCOD can easily handle two traffic modes including buses and automobiles jointly and significantly reduce delays for both modes, compared with SYNCHRO optimized plans.

Approved for public release; distribution is unlimited / To ensure sufficient capacity to handle unexpected demands for electric power, decision makers often over-estimate expeditionary power requirements. Therefore, we often use limited resources inefficiently by purchasing more generators and investing in more renewable energy sources than needed to run power systems on the battlefield. Improvement of the efficiency of expeditionary power units requires better managing of load requirements on the power grids and, where possible, shifting those loads to a more economical time of day. We analyze the performance of a previously developed optimization model for scheduling time-shiftable electrical loads in an expeditionary power grids model in two experiments. One experiment uses model data similar to the original baseline data, in which expected demand and expected renewable production remain constant throughout the day. The second experiment introduces unscheduled demand and realistic fluctuations in the power production and the demand distributions data that more closely reflect actual data. Our major findings show energy grid power production composition affects which uncertain factor(s) influence fuel con-sumption, and uncertainty in the energy grid system does not always increase fuel consumption by a large amount. We also discover that the generators running the most do not always have the best load factor on the grid, even when optimally scheduled. / Lieutenant Commander, United States Navy

[pt] No Brasil, as três principais fontes renováveis de energia elétrica são eólica, pequenas centrais hidrelétricas (PCHs) e biomassa. A comercialização da energia proveniente dessas fontes ocorre majoritariamente no ambiente de contratação regulada (ACR), através de leilões, em detrimento do ambiente de contratação livre (ACL). Isso devido ao fato de seus recursos naturais serem sazonais, estabelecendo o risco de preço-quantidade no ACL, em que o excesso ou déficit de energia gerada em relação à quantidade contratada é liquidado ao preço de liquidação de diferenças (PLD), uma variável sistêmica e altamente volátil. Contudo, a complementaridade dessas fontes permite reduzir esses riscos quando a energia é comercializada de forma conjunta, através de um fundo de energia que gera aumento do valor do portfólio com relação à comercialização individual. Esta dissertação utiliza a teoria de jogos cooperativos para analisar formas de repartir o benefício gerado, através da alocação de quotas financeiras. O conjunto de soluções onde o resultado individual das fontes no fundo é maior do que o resultado individual em qualquer subcoalisão define o núcleo do jogo. Assim, a complexidade de encontrar uma solução dentro do núcleo depende do número de subcoalizões, que cresce exponencialmente com o número de jogadores. Nesse contexto, este trabalho se propôs a apresentar: (i) um modelo de portfólio que incentiva a participação de fontes renováveis no ACL; (ii) um modelo de programação linear que busca o núcleo do jogo; (iii) uma metodologia eficiente baseada em decomposição de Benders, capaz de suprimir a questão da explosão combinatória do problema. / [en] In Brazil, the three main sources of renewable energy are wind, small run-of-river hidros (SH) and biomass. The energy sale of such sources occurs mainly in the Regulated Trading Environment (RTE), through auctions, with shy occurrences in the Free Trading Environment (FTE). This is due to the fact that their natural resources are seasonal, establishing the so-called price-quantity risk in the FTE, as the surplus or deficit of energy generated relative to the contracted amount is settled at the market’s spot price, a systemic and highly volatile variable. However, the complementary nature of these sources allows risk reduction if their energy are trade jointly, through an energy hedge pool that increases the value of the portfolio in comparison to individual strategies. This work makes use of cooperative games theory to analyze ways of sharing the generated benefit, through financial quotas allocation. The set of solutions where the individual sources results in the pool are greater than its results at any possible subcoalition defines the core of the game. Thus, the challenge of finding a solution inside the core depends on the number of subcoalitions, which grows exponentially with the number of players. In this context, this work proposes to present: (i) a model of portfolio that encourages the penetration of renewable sources in the FTE; (ii) a linear programming model that pursuits the game’s core; (iii) an efficient methodology based on Benders decomposition that is capable of suppress the problem of combinatorial explosion, typical of cooperative games with many players.

Este trabalho apresenta um modelo linearizado para ser utilizado em problemas de planejamento da expansão de sistemas de distribuição de energia elétrica (SDEE) com geração distribuída (GD), em um horizonte de curto prazo. O ponto de operação em regime permanente é calculado através de um modelo linearizado da rede, sendo as cargas e geradores representados por injeções constantes de corrente, o que torna possível calcular as correntes nos ramos e as tensões nas barras através de expressões lineares. As alternativas de expansão consideradas são: (i) alocação de bancos de capacitores; (ii) alocação de reguladores de tensão; e (iii) recondutoramento. Ainda, o modelo considera a possibilidade de seleção do tap dos transformadores de distribuição como alternativa para a redução das violações de tensão. A flexibilidade do modelo permite obter soluções considerando a contribuição das GDs no controle de tensão e potência reativa sem a necessidade de especificar uma tensão para a barra da subestação. O modelo de otimização proposto para a solução destes problemas utiliza uma função objetivo linear, além de restrições lineares e variáveis contínuas e binárias. Dessa forma, o modelo de otimização pode ser representado como um problema de programação linear inteira mista (PLIM) A função objetivo considera a minimização dos custos de investimento (aquisição, instalação e remoção de equipamentos e aquisição de condutores) e dos custos de operação, que correspondem aos custos anuais de manutenção somados aos custos das perdas de energia e das violações dos limites de tensão. A variação da carga é representada através de curvas de duração, sendo que os custos das perdas e das violações são ponderados pela duração de cada nível de carregamento. Utilizando uma abordagem de PLIM, sabe-se que existem condições suficientes que garantem a otimalidade de uma dada solução factível, além de permitir que a solução seja obtida através de métodos de otimização clássica. O modelo proposto foi implementado na linguagem de programação OPL e resolvido utilizando o solver comercial CPLEX. O modelo foi validado através da comparação dos resultados obtidos para cinco sistemas de distribuição com os resultados obtidos utilizando um fluxo de carga convencional. Os casos analisados e os resultados obtidos demonstram a precisão do modelo proposto e seu potencial de aplicação. / This work presents a linearized model to be used in short-term expansion planning problems of power distribution systems (PDS) with distributed generation (DG). The steady state operation point is calculated through a linearized model of the network, being the loads and generators modeled as constant current injections, which makes it possible to calculate the branch currents and bus voltages through linear expressions. The alternatives considered for expansion are: (i) capacitor banks placement; (ii) voltage regulators placement; and (iii) reconductoring. Furthermore, the model considers the possibility of adjusting the taps of the distribution transformers as an alternative to reduce voltage violations. The flexibility of the model enables solutions that includes the contribution of DGs in the control of voltage and reactive power without the need to specify the substation voltage. The optimization model proposed to solve these problems uses a linear objective function, along with linear constraints, binary and continuous variables. Thus, the optimization model can be represented as a mixed integer linear programming problem (MILP) The objective function considers the minimization of the investment costs (acquisition, installation and removal of equipment and acquisition of conductors) and the operation costs, which corresponds to the annual maintenance cost plus the costs related to energy losses and violation of voltage limits. The load variation is represented by discrete load duration curves and the costs of losses and voltage violations are weighted by the duration of each load level. Using a MILP approach, it is known that there are sufficient conditions that guarantee the optimality of a given feasible solution, besides allowing the solution to be obtained by classical optimization methods. The proposed model was written in the programming language OPL and solved by the commercial solver CPLEX. The model was validated through the comparison of the results obtained for five distribution systems with the results obtained through conventional load flow. The analyzed cases and the obtained results show the accuracy of the proposed model and its potential for application.

A presente pesquisa considera o problema de programação de uma frota de embarcações de lançamentos de dutos, conhecidas como Pipe Layer Support Vessel (PLSVs), as quais fazem parte da frota de apoio marítimo de uma operação offshore. As embarcações do tipo PLSVs são responsáveis pelas tarefas de lançamento de dutos submarinos, que escoam a produção dos poços de petróleo, e pela interligação destes dutos à infraestrutura submarina. A programação da frota deve atender uma demanda de serviço conhecida, em um horizonte de médio prazo, respeitando restrições operacionais, visando minimizar o atraso ponderado total das tarefas ou evitar que existam atrasos. Foi desenvolvido um método para estimar o valor da solução ótima do problema, baseado na técnica de relaxação Lagrangiana, e um conjunto de heurísticas para gerar soluções viáveis para o problema. / This research considers the problem of scheduling a fleet of specialized vessels used for launching pipes and connecting them to the subsea infrastructure, in an offshore oil production environment. The Pipe Layer Support Vessels (PLSV) must be scheduled such that the demand is fully attended within the planning horizon, observing other operational constraints, with the purpose of minimizing the total weighted tardiness. The solution method is based on constructive and local search heuristics. Bounds on the optimal solution were derived by a Lagrangean relaxation algorithm.