PLAS is a cloud-based software used for planning and scheduling fleets of vehicles for material transport. PLAS consists of two components; the Logistic Flow Solver (LFS) and the Material Transport Scheduler (MTS). Based on transportation requests, the LFS generates a set of logistic flows. The MTS then transforms the logistic flows into tasks that are assigned to the vehicles. The LFS is implemented with Mixed Integer Linear Programming (MILP). Currently, the LFS and the MTS are decoupled from each other and there is information that is not considered in the LFS. Thus, the choice of logistic flows generated with the current formulation may negatively impact the final transport plan. The objective of this thesis is to investigate how the generation of logistic flows can be improved. Two alternative mathematical models for the LFS were developed using MILP formulation. Compared to the current model, more information is taken into account in the two new models. Three different objective functions were considered. Scheduling of the vehicles were modelled as pickup and delivery problems, where pickup and delivery pairs correspond to the generated logistic flows. The models were implemented using Google OR-Tools, an open-source software suite for optimization. The different mathematical formulations were evaluated based on their performance for test problems with different fleet compositions. The results show that problem characteristics influence the performance of the models and that there is no model that gives the best result for every type of problem. Therefore, it is necessary to analyse problem characteristics in order to choose a suitable model for generation of logistic flows. / PLAS är en molnbaserad mjukvara som används för planering och schemaläggning av fordonsflottor för materialtransport. PLAS består av två komponenter; Logistic Flow Solver (LFS) and Material Transport Scheduler (MTS). Baserat på transportbehov genererar LFS ett antal logistikflöden. MTS omvandlar sedan logistikflödena till uppdrag som är tilldelade till fordonen. LFS är implementerad med blandad heltalsprogrammering. För närvarande är LFS och MTS frikopplade från varandra och det finns information som inte tas hänsyn till i LFS. Därför kan valet av logistikflöden genererade med den nuvarande formuleringen negativt påverka den slutliga transportplanen. Målet med detta examensarbete är att undersöka hur genereringen av logistikflöden kan förbättras. Två alternativa matematiska modeller utvecklades med MILP-formulering. Jämfört med den nuvarande modellen, tar de två nya modellerna hänsyn till mer information. Tre olika målfunktioner beaktades. Modellerna implementerades med Google OR-Tools, en öppen programvara för optimering. De matematiska formuleringarna utvärderades baserat på deras prestation på testproblem med olika kompositioner av fordonsflottor. Resultaten visar att problemegenskaper påverkar modellernas prestationer och att det inte finns någon modell som ger bäst resultat för varje problemtyp. Därför är det nödvändigt att analysera problemegenskaper för att kunna välja en lämplig modell för generering av logistikflöden.

京都大学 / 新制・課程博士 / 博士(情報学) / 甲第24938号 / 情博第849号 / 新制||情||142(附属図書館) / 京都大学大学院情報学研究科数理工学専攻 / (主査)准教授 原口 和也, 教授 山下 信雄, 教授 阿久津 達也 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

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For manufacturing companies, the supply chain operations can be very large. Both supplies and delivery to the end customer need to be strategically planned and executed. Inthis thesis, we have looked closer at one of the largest heavy vehicle brands in the world,Scania, and zoomed into a certain part of their supply chain. All parts that are in atruck have their origin, and from this origin, the parts are sent over and over again tothe production facilities of Scania as trucks and buses are being produced. To make surethat the flow of parts to the production units is as efficient as possible, Scania providesits own packaging to the suppliers, and that is what this thesis analyses.We investigate how Scania can make sure that their empty packaging is delivered to thesuppliers in the most cost and CO2 efficient way possible. We begin by describing thecurrent state of the packaging logistics network and what the transport flows look liketoday. From here, we describe the circumstances that are important for the supply chainoperations. Further on we describe theory related to the subject, such as various locationmodels, graphs, networks, and sustainability-related topics among other things. Withhelp from the presented theory and by data preprocessing, we are able to translate theproblem into a mixed integer linear program which tries to minimise the total transportation costs related to the distribution network of packaging. We present our findings anddiscuss the relevance of the results obtained. Finally, we give our recommendations andprovide suggestions for further studies within the area.

The United States is facing a rising average age of principal farm operators and a decline in number of beginning farmers. With numerous barriers and challenges resulting in many farm failures, a majority of beginning farmers are relying on off-farm income to support their households. Decision-making and farm business planning are difficult skills to develop and improve, and the ability to develop a plan to balance on- and off-farm labor could allow farmers to make more profitable decisions. In this study, a General Algebraic Modeling System (GAMS) is used to develop a labor management planning framework for use by Virginia's beginning vegetable farmers or service providers, such as extension agents, with the goal of improving total (on- and off-farm) profitability and farm viability. Study findings suggest that a willingness to work of 12 hours per day, 365 days per year and hired labor costs of $9.30 per hour, which is the national average for agricultural workers encourage a farmer to maintain an off-farm job, while a relatively lower off-farm wage or salary may encourage a farmer to work on the farm only. Lastly, higher hired labor costs may encourage a farmer to pursue his or her most profitable work opportunity, be it on- or off-farm, without hiring labor to maintain the farm. The model developed in this study may be used to plan multiple years of farm management to include anticipated changes in off-farm employment opportunities, land availability, product mix, and access to farm labor. The author suggests that beginning farmers who use this planning tool are able to make more informed decisions related to allocation of labor time and resources, resulting in lower failure rates for beginning farmers in Virginia. A user-friendly interface may be developed based on the study framework, to strengthen the results and increase the practicality of the tool. / Master of Science

The rapid escalation in plug-in electric vehicles (PEVs) and their uncoordinated charging patterns pose several challenges in distribution system operation. Some of the undesirable effects include overloading of transformers, rapid voltage fluctuations, and over/under voltages. While this compromises the consumer power quality, it also puts on extra stress on the local voltage control devices. These challenges demand a well-coordinated and power network-aware charging approach for PEVs in a community. This paper formulates a realtime electric vehicle charging scheduling problem as a mixed-integer linear program (MILP). The problem is to be solved by an aggregator that provides charging services in a residential community. The proposed formulation maximizes the profit of the aggregator, enhancing the utilization of available infrastructure. With prior knowledge of load demand and hourly electricity prices, the algorithm uses a moving time horizon optimization approach, allowing an unknown number of arriving vehicles. In this realistic setting, the proposed framework ensures that power system constraints are satisfied and guarantees the desired PEV charging level within the stipulated time. Numerical tests on an IEEE 13-node feeder system demonstrate the computational and performance superiority of the proposed MILP technique. / M.S. / There is an enhanced rate of global warming due to emissions and increased usage of fossil fuels in the transportation sector. As a feasible solution, electrification of transportation has become a necessary step towards an environment-friendly future. The escalation in plug-in electric vehicles (PEVs) has increased the impact on loading and voltage fluctuations in the distribution grid due to uncoordinated charging. This puts on extra stress on the grid system and compromises the system performance. As a measure to control the vehicle charging in a residential setup, a real-time optimal charging scheduling algorithm is developed which is implemented at the neighborhood level. To increase the charging performance with the limited available resources, an aggregator is introduced. The charging profit is maximized as the PEV charging problem is solved optimally by the aggregator. This facilitates the reduction in night-time grid congestion and maximization of number of PEVs getting charged with limited dependency on communication to avoid long delays in charging control. The proposed technique guarantees the complete charging of the selected PEVs in the stipulated time while considering the power grid operational constraints. It also reduces the impact of peak load demand by flattening the base load demand curve. To demonstrate the efficiency of the proposed mixed integer linear programming optimization algorithm, numerical tests for an IEEE 13 node feeder are performed. The results are discussed to give an outlook on the balance between system and user requirements by meeting the demand of the PEV users.

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