The energy transition taking place in various parts of the world will have many effects on the current energy systems as an increasing amount of intermittent power supply gets installed every year. In Sweden, just as many other countries, this will cause both challenges and opportunities for today´s energy producers. Challenges that may arise along with an increasingly fluctuating electricity production include both power deficits at certain times and regions but also hours of over-production which can cause electricity prices to drop significantly. Such challenges will have to be met by both dispatchable power generation and dynamic consumption. Conversely, actors prepared to adapt to the new climate by implementing new technologies or innovative business models could benefit from the transition towards a fully renewable energy system.  This thesis evaluates the techno-economic potential of green hydrogen production at a combined heat and power plant with the objective to provide decision support to a district heat and electricity producer in Sweden. It was in the company’s interest to investigate how hydrogen production could help reduce the production cost of district heat as well as contribute to the reduction of greenhouse gases.  In the project, two separate business models: Power-to-gas and Power-to-power were evaluated on the basis of technical and economic performance and environmental impact. To do this, a mathematical model of the CHP plant and the hydrogen systems was developed in Python which optimizes the operation based on costs. The business models were then simulated for two different years with each year representing a distinctly different electricity market situation.  The main conclusions of the study show that Power-to-gas could already be profitable at a hydrogen retail price of 40 SEK per kg, which is the projected retail price for the transportation sector. The demand today is however limited but is expected to grow fast in the near future, especially within heavy transportation. Another limiting factor for hydrogen production showed to be the availability of storage space, as hydrogen gas even at pressures up to 200 bar require large volumes.  Power-to-power for frequency regulation was found to not be economically justifiable as the revenue for providing grid services could not outweigh the high investment costs for any of the simulated years. This resulted in a high levelized cost of energy at over 3000 SEK per MWh which was mostly due to the low capacity factor of the power-to-power system.  Finally, green hydrogen has the potential of replacing fossil fuels in sectors that is difficult to reach with electricity, for example long-haul road transport or the shipping industry. Therefore, green hydrogen production in large scale could help decarbonize many of society’s fossil-heavy segments. By also serving as a grid-balancer, hydrogen production in a power-to-gas process has the potential of becoming an important part of a renewable energy system. / Energiomställningen som äger rum i olika delar av världen kommer att ha många effekter på de nuvarande energisystemen eftersom en ökande mängd väderberoende kraftproduktion installeras varje år. I Sverige, precis som många andra länder, kommer detta att medföra både utmaningar och möjligheter för dagens energiproducenter. Utmaningar som kan uppstå tillsammans med en alltmer fluktuerande elproduktion inkluderar både kraftunderskott vid vissa tider och regioner men också timmar av överproduktion som kan få elpriserna att sjunka avsevärt. Sådana utmaningar måste mötas av både planerbar kraftproduktion och dynamisk konsumtion. Omvänt kan aktörer som är beredda att anpassa sig till det nya klimatet genom att implementera ny teknik eller innovativa affärsmodeller dra nytta av övergången till ett helt förnybart energisystem.  Denna rapport utvärderar den tekno-ekonomiska potentialen för produktion av grön vätgas vid ett kraftvärmeverk med målet att ge beslutsstöd till en fjärrvärme- och elproducent i Sverige. Det var i företagets intresse att undersöka hur vätgasproduktion kan bidra till att sänka produktionskostnaden för fjärrvärme samt bidra till att minska växthusgaser.  I projektet utvärderades två separata affärsmodeller: Power-to-gas och Power-to-power baserat på teknisk och ekonomisk prestanda samt miljöpåverkan. För att kunna göra detta utvecklades en matematisk modell i Python av kraftvärmeverket och vätgassystemen som optimerar driften baserat på kostnader. Affärsmodellerna simulerades sedan för två olika års elpriser för att undersöka modellens prestanda i olika typer av elmarknader.  De viktigaste slutsatserna i studien visar att Power-to-gas redan kan vara lönsamt till ett vätgaspris på 40 SEK per kg, vilket är det förväntade marknadspriset på grön vätgas for transportsektorn. Efterfrågan är idag begränsad men förväntas växa snabbt inom en snar framtid, särskilt inom tung transport. En annan begränsande faktor för vätgasproduktion visade sig vara tillgången på lagringsutrymme, eftersom vätgas även vid tryck upp till 200 bar kräver stora volymer.  Power-to-power för frekvensreglering visade sig inte vara ekonomiskt försvarbart, eftersom intäkterna för att tillhandahålla nättjänster inte kunde uppväga de höga investeringskostnaderna under några av de simulerade åren. Detta resulterade i en hög LCOE på över 3000 SEK per MWh, vilket främst berodde på Power-to-power-systemets låga utnyttjandegrad.  Slutligen kan det sägas att grön vätgas har stor potential att ersätta fossila bränslen i sektorer som är svåra att elektrifiera, exempelvis tunga vägtransporter eller sjöfart. Därför kan storskalig grön vätgasproduktion hjälpa till att dekarbonisera många av samhällets fossiltunga segment. Genom att dessutom fungera som balansering har väteproduktion i en Power-to-gas-process potential att bli en viktig del av ett system med stor andel förnybar energi.

Due to the increase in electrical demand and renewable penetration, electrical utilities need to improve and optimize the grid infrastructure. Fundamental components in this grid infrastructure are transformers, which are designed conservatively on the base of a static rated power. However, load and weather change continuously and hence, transformers are not used in the most efficient way. For this reason a new technology has been developed: Dynamic transformer rating (DTR). By applying DTR, it is possible to load transformers above the nameplate rating without affecting their life time expectancy. This project goes one step further and uses DTR for the short term and long term wind farm planning. The optimal wind farm is designed by applying DTR to the power transformer of the farm. The optimization is carried out using a Mixed-Integer Linear Programming (MILP) model. In respect of the transformer thermal analysis, the linearized top oil model of IEEE Clause 7 is selected. The model is executed for 4 different types of power transformers: 63 MVA, 100 MVA, 200 MVA and 400 MVA. As result, it is obtained that the net present value for the investment and the capacity of the wind farm increase linearly with respect to the size of the transformer. Then, a sensitivity analysis is carried out by modifying the wind speed, the electricity price, the lifetime of the transformer and the selected weather data. From this sensitivity analysis, it is possible to conclude that wind resources and electricity price are key parameters for the feasibility of the wind farm. / På grund av ökningen av efterfrågan av elektricitet och förnybara energin, elförsörgingsföretag måste förbättras och elnätets infrastruktur måste optimeras. Grundläggande komponenter i elnätet är transformatorer, som är designade konservativt efter en statisk märkeffekt. Laster och vädret ändras dock kontinuerligt, detta betyder att transformatorer inte används på de mest effektiva sätten. Av denna anledning har en ny teknik utvecklats: Dynamisk lastbarhet hos transformatorer (DTR). Genom att applicera DTR, gör det möjligt att belasta en transformator högre än märkdata utan att påverka den förväntade livslängden. Detta projekt går ett steg längre och använder DTR för kort och lång sikts vindkraftparkplaneringar. Den optimala vindkraftparken är designad genom att använda DLT på krafttransformatorn för vindkraftsparken. Optimeringen utförst med hjälp av Mixed-Integer Linear programming (MILP) modell. Gällande transformatorns termiska analys, så valdes den linjäriserade toppoljemodellen av IEEE Clause 7. Modellen var utförd för fyra olika krafttransformatorer: 63 MVA, 100 MVA, 200 MVA och 400 MVA. Resultatet blev att nettonuvärdet för investeringen och kapaciteten av vindkraftsparken ökade linjärt med avseende på storleken på transformatorn. En känslighetsanalys var utförd genom att ändra vindhastigheten, elpriset, livstiden av transformatorn och de valda väderdata. Från känslighetsanalysen så var det möjligt att dra slutsatsen att vindresurser och elpriset är nyckelparametrar för vindkraftsparkens genomförbarhet.

Approved for public release, distribution is unlimited / Tomahawk cruise missiles (TCM) cost over one million dollars and are in short supply. U.S. Navy ships require TCM and other conventional ammunition be loaded in appropriate amounts prior to deploying to sea. A typical deployment lasts for six months and, when completed, any remaining ammunition must be unloaded and made ready for other deploying ships. For ships under Commander, Naval Surface Force U.S. Pacific Fleet (SURFPAC), about 3,500 tons of ammunition must be loaded and unloaded annually; this currently costs 14 million dollars for just pilots, tugboats and fuel. This thesis formulates and solves an integer linear program, Surface Navy Scheduler (SNSKED), to prescribe an ammunition load and unload schedule for San Diego homeported ships. SNSKED seeks a schedule with minimized costs subject to constraints on ships availability, port capabilities and support assets. We test SNSKED on a realistic quarterly scenario consisting of 19 combatant ships, three weapons stations, two ammunition ships, five mission types, two ammunition types, and three ways of loading ammunition. SNSKED provides optimal schedules that reduce costs by over 16 percent. We also use SNSKED to evaluate different operational policies, ammunition port utilization, and ammunition loading times. / Lieutenant Commander, United States Navy

Autonomous coordination among multiple aerial vehicles to ensure a collision free airspace is a critical aspect of today’s airspace. With the rise of Unmanned Aerial Vehicles (UAVs) in the military and commercial sectors, obstacle avoidance in a densely populated airspace is necessary. This thesis investigates finding optimal or near-optimal trajectories in real-time for aircraft in complex airspaces containing a large number of obstacles. The solution for the trajectories is described as a linear program subject to mixed integer constraints, known as a Mixed Integer Linear Program (MILP). The resulting MILP problem is solved in real time using a well-known, public domain MILP solver. In addition, an Exhaustive, Breadth-First Search algorithm was implemented and is used for comparison in terms of execution time and flight path optimality. The Exhaustive Search algorithm is comprised of a multi-branch tree structure that iterates through all possible flight paths from source to target. The MILP solution was implemented in both PC based and embedded system environments. The embedded system environment was implemented on an onboard processor to develop trajectories for each individual aircraft in real time.

No description available.

Este trabalho trata de um problema de programação da produção em fundições de pequeno porte, que consiste em programar as ligas que devem ser produzidas em cada período do planejamento e como tais ligas devem ser usadas para a produção de itens sob encomenda, de modo que atrasos e custos operacionais sejam minimizados. Devido à certa incerteza nos dados do problema, a estratégia de horizonte rolante foi empregada. Este problema é representado por um modelo matemático de programação linear inteira mista. Neste trabalho foi desenvolvida uma heurística do tipo residual para obter uma boa solução inteira factível do problema, partindo da solução contínua encontrada pelos métodos relaxe-e-fixe e busca local / This work addresses a planning production problem that arises in small market-driven foundries, which consists of programming a number of alloys that have to be produced in each period of the planning horizon and how these alloys should be used to producing ordered items, in such way that delays and operational costs are minimized. Due to uncertainties in the problem data, the strategy of rolling horizon was used. This problem is modeled as a mixed integer linear programe. In this work we developed a residual typed heuristic in order to obtain a good feasible integer solution of the problem, which are built from the continuous solution found by relax-and-fix and local search methods. Keywords: Lot-sizing problems, mixed integer linear programming, production planning in foundries

A localização de fábricas, fornecedores e/ou CDs é um problema de grande complexidade, principalmente em empresas com operações internacionais. Na literatura mundial são poucos os modelos desenvolvidos que tratam da localização de instalações em escala global. Este trabalho propõe um modelo de Programação Linear Inteira Mista que soluciona o problema minimizando os custos logísticos (custos fixos, custos de transferência, custos de distribuição, impostos não recuperáveis, estoques, take-or-pay, matéria-prima e custos de agregação de valor e transbordo) levando em consideração vários elos da cadeia de suprimentos. Como principais contribuições do modelo citam-se a inclusão de benefícios fiscais em transações internacionais, tais como o drawback, o cálculo pioneiro para custo no carregamento dos estoques e o tratamento dado aos custos tipo take-or-pay. São sugeridas adaptações do modelo para utilização em quaisquer segmentos de indústria. O modelo foi aplicado com sucesso em um caso real de uma indústria do segmento químico. / The location of factories, suppliers and distribution centers has always been a problem of great complexity, mainly for companies with global operations. In the literature, there are a few models developed for facilities location in a global scale. This work proposes a Mixed Integer Linear Programming model that solves the problem minimizing the total logistic cost (fixed, transfer and distribution costs, non recoverable duties, carrying, take-or-pay, raw material, added value and handling costs) taking into consideration several echelons in the supply chain network. The main contributions of the proposed model are the considerations regarding fiscal benefits in international trade such as drawback, the pioneer carrying cost calculation and the treatment given to the take-or-pay costs. Some adaptations of the model have been suggested for use in any type of industry. The model was successfully applied in a real case of a chemical industry.

<p>U disertaciji je predstavljen pristup zasnovan na algoritmu mešovitog celobrojnog linearnog programiranja (MILP) za određivanje optimalnog broja, tipa i lokacije uređaja za automatizaciju distributivne mreže. Ugradnja različitih tipova nove opreme (daljinski kontrolisani reklozeri, sekcioneri i indikatori prolaska struje kvara) kao i relokacija postojeće opreme su istovremeno razmatrani. Prilikom određivanja optimalnog scenarija za automatizaciju, predloženi pristup uvažava troškove ispada potrošača/proizvođača usled trenutnih, kratkotrajnih i dugotrajnih ispada, najčešće korišćene pokazatelje pouzdanosti (SAIFI, SAIDI, MAIFI, i ASIDI) kao i troškove distributivnog preduzeća, asocirane uređajima za automatizaciju i ekipama koje su uključene u proces rešavanja prekida napajanja.<br />Dakle, osnovni cilj ove disertacije je, da se napravi model zasnovan na mešovitom celobrojnom linearnom programiranju koji će omogućiti određivanje najboljeg scenarija za automatizaciju distributivne mreže u slučajevima kada se ocena kvaliteta isporuke definiše preko pokazatelja pouzdanosti, preko troškova usled prekida napajanja ili kombinacijom ova dva pokazatelja.</p> / <p>The dissertation presents a mixed integer linear programming (MILP) based approach for determining the optimal number, type and location of automation devices to be installed in the network by considering different types of devices simultaneously (remotely controlled circuit breakers/reclosers, sectionalizing switches, remotely supervised fault passage indicators). Simultaneously, it determines the new (optimal) locations of the automation devices that already exist in the network. In determining the most effective network automation scenario, the proposed approach takes into account the outage cost of consumers/producers due to momentary, short-term, and long-term interruptions, the commonly used network reliability indices (SAIFI, SAIDI, MAIFI, and ASIDI) as well as the cost of automation devices and the cost of crews. It provides the best network automation scenario in distribution systems if the network reliability indices are used for measuring the distribution system reliability, if cost of interruptions is defined to all consumers/producers, and if both approaches (criteria) are used.</p>

<p>Energy management has become a major concern in the past two decades with the increasing energy prices, overutilization of natural resources and increased carbon emissions. According to the department of Energy the industrial sector solely consumes 22.4% of the energy produced in the country [1]. This calls for an urgent need for the industries to design and implement energy efficient practices by analyzing the energy consumption, electricity data and making use of energy efficient equipment. Although, utility companies are providing incentives to consumer participating in Demand Response programs, there isn’t an active implementation of energy management principles from the consumer’s side. Technological advancements in controls, automation, optimization and big data can be harnessed to achieve this which in other words is referred to as “Smart Manufacturing”. In this research energy management techniques have been designed for two SEU (Significant Energy Use) equipment HVAC systems, Compressors and load shifting in manufacturing environments using control and optimization.</p> <p>The addressed energy management techniques associated with each of the SEUs are very generic in nature which make them applicable for most of the industries. Firstly, the loads or the energy consuming equipment has been categorized into flexible and non-flexible loads based on their priority level and flexibility in running schedule. For the flexible loads, an optimal load scheduler has been modelled using Mixed Integer Linear Programming (MILP) method that find carries out load shifting by using the predicted demand of the rest of the plant and scheduling the loads during the low demand periods. The cases of interruptible loads and non-interruptible have been solved to demonstrate load shifting. This essentially resulted in lowering the peak demand and hence cost savings for both “Time-of-Use” and Demand based price schemes. </p> <p>The compressor load sharing problem was next considered for optimal distribution of loads among VFD equipped compressors running in parallel to meet the demand. The model is based on MILP problem and case studies was carried out for heavy duty (>10HP) and light duty compressors (<=10HP). Using the compressor scheduler, there was about 16% energy and cost saving for the light duty compressors and 14.6% for the heavy duty compressors</p> <p>HVAC systems being one of the major energy consumer in manufacturing industries was modelled using the generic lumped parameter method. An Electroplating facility named Electro-Spec was modelled in Simulink and was validated using the real data that was collected from the facility. The Mean Absolute Error (MAE) was about 0.39 for the model which is suitable for implementing controllers for the purpose of energy management. MATLAB and Simulink were used to design and implement the state-of-the-art Model Predictive Control for the purpose of energy efficient control. The MPC was chosen due to its ability to easily handle Multi Input Multi Output Systems, system constraints and its optimal nature. The MPC resulted in a temperature response with a rise time of 10 minutes and a steady state error of less than 0.001. Also from the input response, it was observed that the MPC provided just enough input for the temperature to stay at the set point and as a result led to about 27.6% energy and cost savings. Thus this research has a potential of energy and cost savings and can be readily applied to most of the manufacturing industries that use HVAC, Compressors and machines as their primary energy consumer.</p><br>

In this research, a decision support model for coordinating sustainable product and supply chain design decisions is developed using a multi-stage hierarchical approach. The model evaluates alternate product designs and their corresponding supply chain configurations to identify the best product design and the corresponding supply chain configuration that maximizes the economic, environmental and societal benefits. The model considers a total life-cycle approach and incorporates closed-loop flow among multiple product lifecycles. In the first stage, a mixed integer linear programming model is developed to select for each product design an optimal supply chain configuration that maximizes the profit. In the subsequent stages, the economic, environmental and societal multiple life-cycle analysis models are developed which assess the economic, environment and the societal performance of each product design and its optimal supply chain configuration to identify the best product design with highest sustainability benefits. The decision support model is applied for an example problem to illustrate the procedure for identifying the best sustainable design. Later, the model is applied for a real-time refrigerator case to identify the best refrigerator design that maximizes economic, environmental and societal benefits. Further, sensitivity analysis is performed on the optimization model to study the closed-loop supply chain behavior under various situations. The results indicated that both product and supply chain design criteria significantly influence the performance of the supply chain. The results provided insights into closed-loop supply chain models and their behavior under various situations. Decision support models such as above can help a company identify the best designs that bring highest sustainability benefits, can provide a manager with holistic view and the impact of their design decisions on the supply chain performance and also provide areas for improvement.